Standard Operating Procedures for Clinical Trials of the Central European Society for Anticancer Drug Research (Cesar-Ewiv (Supplement Issue: Onkologie 2003, 6)

Supplement 6, Vol. 26, October 2003 Standard Operating Procedures for Clinical Trials of the CESAR Central European So...

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Supplement 6, Vol. 26, October 2003

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

G. Gastl (Chairman of SOP Committee), Innsbruck W. Berdel, Mu¨nster L. Edler, Heidelberg U. Jaehde, Bonn R. Port, Heidelberg K. Mross, Freiburg i.Br. M. Scheulen, Essen H. Sindermann, Frankfurt/M. C. Dittrich (President of CESAR), Wien

Basel Freiburg Paris London New York Bangalore Bangkok Singapore Tokyo Sydney

Contents

VI Inventories

36

VII Authors VIII Glossary IX Preface 1

SOP 01: Clinical Investigations in CESAR Background and Principles Becoming a Member of a the WorkingGroup(s) of CESAR References Appendix

5

38

SOP 03: Preparation and Structure of Trial Protocols Background/Objectives Structure of a Trial Protocol Standard Format of Individual Protocol Elements References Appendix

15

23

41

43

SOP 5: Patient Information and Informed Consent

SOP 6: Selecting the Participating Centers and Activation of a Trial Background Selection of Suitable Trial Centers Competing Studies Exclusion from an Ongoing Study Study Activation

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SOP 9: Statistical Design and Analysis Background Statistical Issues of the Trial Protocol Statistical Study Design Patient Registration and Control of the Study Statistical Analysis Biometric Report/Statistical Report Documentation and Archiving of Study Data References

Background Elements of Information to Patients Model Texts References Appendix

34

SOP 8: Reporting of Adverse Events Definitions Documentation Immediate Reporting of Serious or Unexpected Adverse Events Classification/Grading Evaluation of a Relationship References

SOP 4: Data Collection Forms (Case Report Forms) Background Logistic Considerations General Remarks on Case Report Form Handling References Appendix

SOP 7a: Monitoring of a Trial under CESAR Responsibility Background General Considerations and Procedures Activities before a Trial Initiation Visit Activities during a Trial Initiation Visit Activities Following a Trial Initiation Visit Activities before a Monitoring Visit Activities during a Monitoring Visit Activities Following a Monitoring Visit Activities before a Closeout Visit Activities during a Closeout Visit Activities Following a Closeout Visit

SOP 02: Evaluation and Selection of a Clinical Trial Proposal for CESAR Background/Objectives Membership of the Project Review Committee (PRC) Tasks of the Project Review Committee Evaluation Process Appendix

11

SOP 7: Data Flow, Monitoring, and Archiving Background Patient Registration CRF Submission Paths Notes Regarding Data Submission Paths Trial Documentation Site Visit Report Archiving of Essential Documents References

48

SOP 10: Study Report and Publication Study Report Responsibility for Publication Authorship for Publications Time Schedule Publication of Data from an Ongoing Study Publication of Data from Single Institutions Press Release and Information to the Public

Contents

50

SOP 11: Quality Assurance

56

Background/Objectives Quality Assurance by the Sponsor/Inspection by Relevant Authorities System Audits of CESAR Study Evaluation Meetings/Response Evaluation Meetings

52

SOP 12: Validation of Bioanalytical Methods Background and Objectives Types of Method Validation Validation Parameters Validation Report Routine Drug Analysis Special Considerations for Immunoassays Documentation and Archiving of Analytical Data References

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SOP 13: Pharmacokinetic Data Analysis Background and Objectives Relevant Pharmacokinetic Parameters Study Considerations Data Handling Noncompartmental Data Analysis Compartmental Data Analysis Physiologically-based Pharmacokinetic Models (PBPK Models) PK/PD Modeling Population Pharmacokinetic Data Analysis Pharmacokinetic Report References

60

SOP 14: Population Pharmacokinetic Analysis Background an Objectives Study Design and Execution Data Acquisition and Handling Graphical Analysis Basic Model Explanatory Model Goodness of Fit Summary References

V

Inventories

Inventory of Current Standard Operating Procedures (SOPs) SOP no.

SOP titlea

Current versionb

01

Clinical Investigations in CESAR

01: 28.06.2001

02

Evaluation and Selection of a Clinical Trial Proposal for CESAR

01: 28.06.2001

03

Preparation and Structure of Trial Protocols

01: 28.06.2001

04

Data Collection Forms (Case Report Forms)

01: 28.06.2001

05

Patient Information and Informed Consent

01: 28.06.2001

06

Selecting the Participating Centers and Activation of a Trial

01: 28.06.2001

07

Data Flow, Monitoring, and Archiving

01: 28.06.2001

07a

Monitoring of a Trial under CESAR Responsibility

01: 28.06.2003

08

Reporting of Adverse Events

01: 28.06.2001

09

Statistical Design and Analysis

01: 28.06.2001

10

Study Report and Publication

01: 28.06.2001

11

Quality Assurance

01: 28.06.2001

12

Validation of Bioanalytical Methods

01: 15.11.2002

13

Pharmacokinetic Data Analysis

01: 15.11.2002

14

Population Pharmacokinetic Analysis

01: 20.06.2003

a b

Primary authorship for individual SOPs: L. Edler SOP 10; U. Jaehde SOP 12, 13; R. Port SOP 14; H. Sindermann SOP 1–9, 11. Valid SOP version as per date of this publication; the homepage of CESAR (www.cesar-ewiv.org) should be consulted to verify the version status.

Inventory of SOP attachments SOP no.

Attachment title

Current version

01

Investigator’s Declaration

28.06.2001

Declaration on the Investigator’s Institution

28.06.2001

Validated Laboratory Normal Ranges

28.06.2001

Checklist 2a: Project Evaluation by the Project Review Committee (PRC)

28.06.2001

Checklist 2b: Vote on Project/Trial Protocol by PRC Members

28.06.2001

Flow of Information during Protocol Review

14.11.2002

Template for the Cover Page of a Clinical Trial Protocol

28.06.2001

Template for the Synopsis of a Clinical Trial Protocol

28.06.2001

Phase I/II Data Collection Forms/Case Reports Forms CTC Criteria; Version 2.0*

30.04.1999

Current Symptoms/Adverse Event Checklist

28.06.2001

Model Patient Information/Informed Consent

28.06.2001

Template for Patient Information/Informed Consent translated from template of the NCI

28.06.2001

02

03

04

05

28.06.2001

* For guidance on the use of the criteria and notification of recent changes see http://ctep.info.nih.gov/CTC3/NoM.htm.

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Authors

Standard Operating Procedures (SOP) Committee of CESAR

Univ.-Prof. Dr. Gu¨nther Gastl (Chairman of SOP Committee) Abteilung fu¨r Ha¨matologie und Onkologie Universita¨ts-Klinik fu¨r Innere Medizin Universita¨t Innsbruck Anichstraße 35 A-6020 Innsbruck Tel. +43 512 50440-03, Fax -06 E-mail [email protected] Prof. Dr. Wolfgang Berdel Medizinische Klinik A Universita¨tsklinikum Mu¨nster Albert Schweitzer-Straße 33 D-48149 Mu¨nster Univ.-Prof. Dr. Christian Dittrich (President of CESAR)

Prof. Dr. Ulrich Jaehde Pharmazeutisches Institut Universita¨t Bonn An der Immenburg 4 D-53121 Bonn Dr. Ru¨diger Port Abt. D-0200 Deutsches Krebsforschungszentrum Postfach 101949 D-69009 Heidelberg PD Dr. Klaus Mross Klinik fu¨r Tumorbiologie Albert-Ludwigs-Universita¨t Freiburg Breisacherstraße 117 D-79106 Freiburg

3. Medizinische Abteilung mit Onkologie Ludwig Boltzmann-Institut fu¨r Angewandte Krebsforschung (LBI-ACR VIEnna) Kaiser Franz Josef-Spital Kundratstraße 3 A-1100 Wien

Prof. Dr. Max Ernst Scheulen

Dr. Lutz Edler

Dr. Herbert Sindermann

Biostatistik R0700 Deutsches Krebsforschungszentrum Im Neuenheimer Feld 280 D-69120 Heidelberg

Medical Research and Development Zentaris GmbH Weismu¨llerstraße 45 D-60314 Frankfurt

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Tumorforschung Innere Universita¨ts-Klinik und Poliklinik Universita¨tsklinikum Essen Hufelandstraße 55 D-45122 Essen

VII

Glossary

ADR Adverse Drug Reaction AE Adverse Event AIC Akaike Information Criterion AMG Arzneimittelgesetz (German Drug Law) ASCII American Standard Code for Information Interchange AUC Area under the plasma concentration-time curve AUMC Area under the first moment curve Basic model A population model that describes all interindividual variability as random (synonym: descriptive model) BC Biometric Center of CESAR CE Capillary electrophoresis CESAR CESAR – Central European Society for Anticancer Drug Research – EWIV CI Coordinating Investigator (the only investigator determined by CESAR to guide a specific study on behalf of the society) CE Capillary electrophoresis CL Total clearance Cmax Maximum concentration Cmin Minimum concentration after repeated dosing cov Covariance Covariate Observable or measurable patient feature like sex, height, smoking habit CRA Clinical Research Associate CrCL Creatinine clearance CRF Case Report Form Css Plasma concentration at steady state CTC Common Toxicity Criteria (NCI) CV Coefficient of variation Descriptive model Synonym for: basic model DLT Dose Limiting Toxicity EC Ethics Committee ELS Extended least squares EMEA European Medicines Evaluation Agency EWIV Eingetragener Wirtschaftsinteressenverband (European Economic Interest Grouping; EEIG) Explanatory model A population model that explains interindividual variability partly by differences in covariates like sex, height etc.; contains shift parameters while a basic model does not F Bioavailability; the fraction of a drug dose which, after extravascular administration, reaches the systemic circulation fe Fraction of dose excreted unchanged in urine fu Fraction of unbound drug in plasma GC Gas chromatography GCP Good Clinical Practice HPLC High-performance liquid chromatography ICH International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use ICH-GCP EMEA. Note for Guidance on Good Clinical Practice (CPMP/ICH/135/95) IRB Institutional Review Board ka Absorption rate constant kM Michaelis-Menten constant LLOQ Lower limit of quantification

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lz MTD NCA NCI OLS PBPK PD PGDE PI PK Population

Terminal elimination rate constant Maximum Tolerated Dose Noncompartmental analysis National Cancer Institute Ordinary least squares Physiologically-based pharmacokinetics Pharmacodynamics Pharmacokinetically-guided dose escalation Principal Investigator Pharmacokinetics mean The value of a kinetic parameter that would be expected if there were no interindividual variability (synonym: ‘typical value’, TV) Population parameters Population means, shift parameters, interindividual variances (w2 ), residual variance(s) (s2 ) PRC Project Review Committee QUAC Quality Assurance Committee QUC Quality control RECIST Response Evaluation Criteria in Solid Tumors SAE Serious Adverse Event SC Schwarz Criterion SD Standard deviation Shift parameter A population parameter that describes a fixed dependence of one of the kinetic parameters (CL, V etc.) on a covariate; examples: a fixed reduction of clearance in females, or a fixed proportionality between drug clearance and individual creatinine clearance SOP Standard Operating Procedures Structural model That part of a population model which is adopted before considering variability; it is assumed to hold for all individuals; examples: a linear one-compartment model with first-order absorption, a linear two-compartment model with zero-order input STS Standard two-stage approach t1/2 Z Terminal half-life tmax Time of maximum concentration Typical value Synonym for: population mean V Volume of distribution vmax Maximum velocity of a Michaelis-Menten process Vss Volume of distribution at steady-state VZ Volume of distribution during the terminal phase WHO World Health Organization WLS Weighted least squares e Residual random deviation from the individual prediction of response (e is not a population parameter because it varies between observations while its variance is s2 ) h Individual random deviation from the population mean of a kinetic parameter, or from the individual prediction of this parameter as derived from the population mean and individual covariates (h varies between individuals while its variance is w2 ) s2 Residual random variance (variance of e) w2 Interindividual random variance (variance of) that is associated with one of the kinetic parameters)

Preface

The CESAR Central European Society for Anticancer Drug Research – EWIV (CESAR) is a society of scientists in basic research, preclinical oncology, and applied cancer research, sharing as common central mission the development of new antitumoral agents, therapies, and/or therapeutic strategies. Among these areas tumor biology, molecular biology, chemistry, pharmacology, toxicology, clinical pharmacology, biometry, and clinical oncology have to be mentioned in detail. This international society is recruiting its members mainly from the Central European area and is focusing its activities in a common effort of developing new antitumoral substances in Europe. The CESAR is attempting to reflect and represent specifically the geopolitical as well as the sociocultural peculiarities of the Central European region. The CESAR is composed of Central European research associations. The goals of these groups are identical to those of the CESAR. In particular, the CESAR claims to specifically represent Central Europe within a global ‘Early Drug Development Network’ of Europe. The simplest description of this situation is using the metaphor of a natural ligand (instead of the CESAR) binding with the so far free receptor for new drug development (in Central Europe). The goal of the CESAR is the development of new antitumoral agents and the clinical testing of new agents and/or antitumoral principles with regard to their effectivity and safety in patients with malignant diseases. The testing or development of new antitumoral substances has to be based on the scientifically most adequate method, including the pharmacologic expertise and the actual valid state of the art procedures with respect to science, ethics and law. In particular Good Manufacturing Practice (GMP), Good Laboratory Practice (GLP) and Good Clinical Practice (GCP) according to the International Conference on Harmonisation (ICH) have to be considered.

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The CESAR has established a permanent committee designated for the task of working out Standard Operating Procedures (SOPs) for the clinical working groups of the society, notably the working groups CESAR Phase-I, CESAR Phase-II and CESAR Phase-III, but also the Working Group on Pharmacology in Oncology and Hematology (CESAR-APOH). The SOP Committee (SOPC) has undertaken every effort in combining enthusiasm, meticulosity and the wish to produce a useful compendium for clinical researchers in the sense of a codex of how to behave adequately and correctly while performing clinical trials. Thus, the SOPs have been accepted by the CESAR as internal regulation that all members of the CESAR confess to submit to. Some parts of the SOPs have to be considered as classical parts of such regulation, but representing a very new status including all available and internationally accepted regulations. Especially the ‘SOP 12: Validation of Bioanalytical Methods’, ‘SOP 13: Pharmacokinetic Data Analysis’ and ‘SOP 14: Population Pharmacokinetic Analysis’ represent some rare examples of harmonization in this area which has become of utmost importance to all investigators in the field of new drug development. We would like to thank all members of the SOPC for their dedication to the creation of these SOPs. In particular we would like to mention the expertise and workload of Dr. Herbert Sindermann. Moreover, we are grateful to Dr. Ru¨diger Port and the CESAR-APOH for writing SOPs 12–14. We wish all clinical investigators in the field of new drug development in oncology that they will find useful information for their daily professional life in this compendium. G. Gastl, Chairman Standard Operating Procedures Committee of CESAR C. Dittrich, President of CESAR

IX

Onkologie 2003; 26 (suppl 6): 1–4

Version 01 Approval: June 28, 2001 Implementation: June 29, 2001

SOP 01: Clinical Investigations in CESAR

Background and Principles

CESAR Central European Society for Anticancer Drug Research – EWIV (CESAR) is an association of scientists in the area of basic sciences, preclinical oncology and clinical oncology (see also I. Preamble of the Bylaws of CESAR). CESAR is organized in specific working groups dealing with drug development and preclinical pharmacology, Phase I, phase II, and phase III study performance and clinical pharmacology thereby contributing to reach the above defined goals. Aim of the preclinical and clinical oncologic scientists is to conduct clinical trials in medical oncology, either on behalf of the study group itself or on behalf of external sponsors, like pharmaceutical companies. Such trials have to comply with current guidelines on Good Clinical Practice (GCP) to ensure the acceptability of the data to the scientific community and to drug regulatory authorities. The Note for Guidance on GCP that has been issued by ICH (International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use) is applicable to clinical trials commencing after January 17, 1997 [1]. Because of convenience, these GCP guidelines are referred to as ‘ICH-GCP’ within this SOP series. The SOPs of CESAR define or address exclusively requirements for clinical activities but do not apply basic scientific and preclinical activities, that are covered by CESAR-AWO regulations. According to ICH-GCP, the sponsor of a clinical trial has to verify the suitability of each participating investigator and institution [1; section 5.6.1]. It is the aim of CESAR to shorten the lead time for the initiation of a particular clinical trial by applying and documenting appropriate procedures before granting a group membership. The selection criteria for becoming a member in a clinical working group (phase I, phase II, phase III) cover both the medical qualification and experience of the medical oncologist as well as the organization and equipment of the institution to which he/she is affiliated.

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A cumulative data base on the number of patients with key indications that working group members have treated will support the identification of institutions with adequate recruitment rates for a new clinical trial.

Becoming a Member of a (the) Working Group(s) of CESAR

Acceptance for membership in the working group(s) of CESAR will be based on both the scientific qualification of an applicant and on the fulfillment of the technical and organizational prerequisites for performing phase I or phase II trials at the applicant’s institution. Thus, membership will neither be sustained automatically if a member changes his/her institutional affiliation nor be transferred to a successor at the institution he/she is leaving. Selection Criteria for Becoming a Clinical Investigator of CESAR It is the aim of CESAR to ensure that each clinical investigator of each CESAR working group fulfills the basic requirements for being an investigator according to ICHGCP. Compliance with study-specific eligibility criteria will be required to participate in a particular study of CESAR. – Coordinating Investigator (CI)/Principal Investigator (PI) Licensed as physician with at least 2 years of experience in clinical trials (as evidenced by a current curriculum vitae including scientific training and list of publications) (see Attachment 1 for corresponding declaration). CI is the only investigator determined by CESAR to guide a specific study on behalf of the society. He will be identified by the chairman of the respective working group. PI is each investigator responsible for one center regarding the participation in a specific study on behalf of CESAR who reports to the CI with regard to a distinct study.

– Investigator Long-term affiliation to the corresponding institution (affiliation to an institution by a short-term contract, e.g., for less than 2 years, will not be acceptable for a CI/PI of CESAR, as maintenance of an adequate infrastructure for clinical trials meeting the standards of CESAR may not be assured under such circumstances). Commitment to participate in quality assurance measures as required by ICH-GCP. – Organizational Prerequisites at the Study Center (see Attachment 2) Identification and documented composition of the relevant local Ethics Committee (policy regarding votes from an outside CI must be known). Adequate staff: experienced medical and nursing staff for the management of study patients, adequately trained and experienced medical doctor who will be in charge of the study during transient absence of the Full Member (principal investigator), documentation (as clinical trial protocols and case record forms (CRFs) are often written in English and CRF entries may be required in English, persons assigned the responsibility for documentation should be adequately skilled in English), drug accountability (storage, distribution and return of trial medication). Facilities required for trials, such as: local access to imaging techniques that are commonly required to measure target lesions (e.g. radiography, CT scan, MRI), access to hospital beds for inpatient observation, direct access to an intensive care unit/resuscitation equipment (depending on type of study), quality assurance of diagnostic procedures (e.g. by participation in quality assurance programs) (see Attachment 3 regarding clinical laboratory), access to a clinical pharmacological laboratory for test drug or metabolite assays (depending on the analytes to be detected, the cooperation with an external institution may be necessary; for such cases adequate freezer capacity and access to dry ice for shipment of biological specimens must be available). Adequate facilities for storage of study materials such as study files and trial medication in a secure, limited access area. Adequate facilities for later archiving of the ‘essential documents’ (ICH-GCP) after completion of the study (see SOP 11). Equipment for electronic messages and information transfer.

2

Onkologie 2003; 26 (suppl 6): 1–4

– Availability of patients who may be eligible for clinical trials The type of patients that an investigator’s institution commonly sees is a critical issue in assessing the suitability of that investigator and institution for participating in a particular clinical trial. Therefore, an applicant for a membership in one or several working groups of CESAR is expected to present an overview of the kind of patients that have been treated in the applicant’s institution during the last year (see attachment ‘Declaration on the Investigator’s Institution’). The focus should be on the number of patients who would meet common selection criteria for phase I or phase II trials and on how many patients actually entered clinical trials. Such information will serve as a basis for reliably estimating accrual rates for trials of the working groups. After nomination as a member of a working group, the Declarations may be used to assess an individual study center’s suitability to participate in a particular trial project (for details see SOP 6). For this reason, all members of the working group have to update this checklist at regular intervals and submit notes on relevant changes at their institution. The checklist can serve to facilitate the decisionmaking process when selecting the most suitable institutions for trials involving a limited number of centers. A participating center can be excluded from an ongoing study or from the working group in case of considerable overestimation of its own capacities or severe deficiencies in study documentation (for details see Sections 1.2.6 and 1.2.7). The above checklist is supplemented by an annual report of the Data Center on the working group at the biometry of CESAR at the Deutsches Krebsforschungszentrum (German Cancer Research Center) on each trial center’s performance level during the preceding year: Patient accrual by indications Protocol violations Patients lost to follow-up Delays in the submission of data collection forms.

References 1 ICH-GCP: EMEA. Note for Guidance on Good Clinical Practice (CPMP/ICH/135/95).

Appendices

Attachment 1: Investigator’s Declaration Attachment 2: Declaration on the Investigator’s Institution Attachment 3: Validated Laboratory Normal Ranges

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

SOP 01: Clinical Investigations in CESAR

Onkologie 2003; 26 (suppl 6): 1–4

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Onkologie 2003; 26 (suppl 6): 5–10

Version 01 Approval: June 28, 2001 Implementation: June 29, 2001

SOP 02: Evaluation and Selection of a Clinical Trial Proposal for CESAR

Background and Principles

SOP 2 defines the composition and procedures of the Project Review Committee (PRC) of CESAR. The PRC works independently of the time schedule of working group meetings, and its task is to ensure a rapid and objective evaluation of trial projects proposed to CESAR via its working groups and the prompt activation of approved studies. The PRC’s decision must take into consideration the interests of CESAR to have adequate information on the investigational drug and the proposed project while at the same time maintaining the strictest secrecy of confidential information provided by a sponsor.

Membership of the Project Review Committee

The membership of the PRC consists of the chairpersons and/or co-chairpersons of the working groups CESARPhase I, CESAR-Phase II, and CESAR-Phase III and of statistician. For a given project, e.g. a phase II study, the chairperson and co-chairperson of the respective working group will finally decide who will act as ‘Working Group Representative of the PRC’ for that project.

Eligibility Criteria for Membership in the Protocol Review Committee of CESAR

To be eligible for being elected as a member of the PRC in CESAR, the candidate must fulfill the following criteria: – Holding an academic degree (MD, PhD); – Proper knowledge of GCP guidelines, statistical methodology and ethical regulations (e.g. Helsinki declaration); – Documented major involvement in the development of protocols for clinical phase I, phase II and/or phase III studies according to GCP guidelines; – Experience as clinical investigator or co-investigator in monocenter and multicenter clinical trials and first-,

# 2003 S. Karger GmbH, Freiburg Fax +49 761 4 52 07 14 E-mail [email protected] www.karger.com

Accessible online at: www.karger.com/onk

senior- or co-authorship of more than three publications in peer-reviewed journals reporting results from such clinical studies; – Disclosure of financial interests in non-academic organizations and/or private companies.

Tasks of the Project Review Committee

The PRC evaluates proposed trial projects on the basis of a standardized checklist (see Attachment 1). The PRC’s decision will in particular be based on the following criteria: – Adequate pharmaceutical, pharmacological, and toxicological characterization of the investigational product, – The proposed design and draft of the trial protocol submitted by the sponsor (including information to be given to the patients), – The risk/benefit assessment regarding the use of the investigational product, – Compatibility of the trial with the global objectives of CESAR, – Feasibility of the trial for the institutions represented in CESAR or its working groups, – Scientific priority of the trial project (novel investigational product / adequate trial design). Upon approval of a proposed trial, the PRC in consultation with the members of the corresponding working group will coordinate the finalization of the study documentation. The identification of the institutions to participate in the study will finally be performed by the chairperson(s) of the respective working group(s).

Evaluation Process

Offers by Sponsors A sponsor who suggests a study project has to submit the relevant documentation in sufficient number of x copies to

the Chair of the relevant working group (5 sets of copies for the PRC, one set for the Coordinating Investigator (CI) to be nominated for the project). Checklist 2a (see Attachment 1), to be completed by the sponsor, serves to facilitate and speed up the formal evaluation process of the proposed study. Evaluation by the PRC The Chair of the PRC will distribute the materials to the members of the PRC and will – Set a deadline for the return of the members’ comments (using the assessment section of Checklist 2a) and – Schedule meetings of the committee. It is at the discretion of the PRC to invite to its meetings representatives from the sponsor’s institution. Preliminary Decision by the PRC – The PRC will evaluate a proposed study and then decide on its adoption or rejection. – When a project has been rejected by the PRC, the PRC chairperson or co-chairperson will present and defend the decision either at the next regular meeting of the working group or within 4 weeks after the application. – If the PRC is undecided, it may postpone its decision until the next regular meeting of the working group, at which the reasons against an immediate adoption have to be given. The members of the working group who are present at the meeting will then adopt or reject the proposal by simple majority vote. – Upon an affirmative decision by the PRC, its Chair will immediately forward to the CI the complete data material submitted by the sponsor (including the Investigator’s Brochure). The Chair should strive for a well-balanced consideration of all working group members in the nomination of CIs. Notification of the Working Group Members Unless the trial protocol already contained a comprehensive summary (‘synopsis’) that complies with the templates shown in Attachments 1 and 2 of ‘SOP 03: Preparation and Structure of Trial Protocols’, the CI will write such a summary and distribute it to all working group members via the PRC chairperson. Each working group member may request the full version of the trial protocol within 4 weeks (unless not otherwise agreed by contract).

ment 2) and return it to the PRC Chairperson within 2 weeks (unless otherwise specified). On this checklist, the investigator candidates may suggest modifications to the study protocol. The CI will then incorporate suggested modifications, in concert with the sponsor. The sponsor and the chairperson(s) of the respective Working Group(s), will jointly determine a maximal number of centers that should reasonably participate in the study. It is the responsibility of the CI that the final version of the study protocol complies with change requests of both PRC members and participating working group members. In case of considerable, and in particular conflicting, wishes for changes, the PRC chairperson and the chairperson of the Working Groups will jointly decide whether a second round of the above consent procedure may be necessary. Ethics Committee Approval The CI applies for the vote of the Ethics Committee relevant for the local institution. Upon approval by the Ethics Committee, the CI will forward a copy of the decision and the trial protocol (and any amendment) to the sponsor and the PRC chairperson. Study Activation The chairpersons of the respective working groups will circulate the final version of the synopsis of the trial protocol to all members of the respective working group (CESARPhase I, CESAR-Phase II, CESAR-Phase III) and thus activate the study. The CI will present the study at the next scheduled meeting of the Working Group. It is the obligation of the sponsor to ensure compliance with applicable local regulatory requirements before it supplies trial medication to the investigator’s site and authorizes the use of the product in humans (for details see ‘SOP 6: Selecting the Participating Centers and Activation of a Trial’).

Appendix

Attachment 1: Checklist 2a: Project Evaluation by the Project Review Committee (PRC) Attachment 2: Checklist 2b: Vote on Project/Trial Protocol by PRC Members Attachment 3: Flow of Information during Protocol Review

Consent on the Protocol among Clinical Investigators Working group members who wish to participate in a given study have to complete Checklist 2b (see Attach-

6

Onkologie 2003; 26 (suppl 6): 5–10

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

SOP 02: Evaluation and Selection of a Clinical Trial Proposal for CESAR

Onkologie 2003; 26 (suppl 6): 5–10

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Onkologie 2003; 26 (suppl 6): 5–10

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Onkologie 2003; 26 (suppl 6): 5–10

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

Onkologie 2003; 26 (suppl 6): 11–14

Version 01 Approval: June 28, 2001 Implementation: June 29, 2001

SOP 03: Preparation and Structure of Trial Protocols

Background/Objectives

SOP 3 provides a list of essential items of a clinical trial protocol and makes specific recommendations on how individual items may be put into practice. These guidelines are to ensure a reliable and rapid orientation of both investigators and the parties involved in the review process. The standard languages to be used for writing trial protocols are German and English. Trial protocols written in English must additionally include a German study title and a German summary and vice versa.

Structure of a Trial Protocol

According to chapter 6 of the ICH-GCP guidelines [1], the contents of a trial protocol should generally include the following topics. However, site specific information may be provided on separate protocol page(s), or addressed in a separate agreement, and some of the information listed below may be contained in other protocol referenced documents, such as an Investigator’s Brochure. This list should be checked when the protocol for a clinical trial is prepared (numbers in brackets refer to the numbering of chapters within ICH-GCP). General Information (6.1) – Protocol title, protocol identifying number, and date. Any amendment(s) should also bear the amendment number(s) and date(s). – Name and address of the sponsor and monitor (if other than the sponsor). – Name and title of the person(s) authorized to sign the protocol and the protocol amendment(s) for the sponsor. – Name, title, address, and telephone number(s) of the sponsor’s medical expert for the trial. – Name and title of the investigator(s) who is (are) responsible for conducting the trial, and the address and telephone number(s) of the trial site(s).

# 2003 S. Karger GmbH, Freiburg Fax +49 761 4 52 07 14 E-mail [email protected] www.karger.com

Accessible online at: www.karger.com/onk

– Name, title, address, and telephone number(s) of the qualified physician who is responsible for all trial-site related medical decisions (if other than investigator). – Name(s) and address(es) of the clinical laboratory(ies) and other medical and/or technical department(s) and/ or institutions involved in the trial. Please note: A model cover page for trial protocols to be submitted to the respective working group is appended as Attachment 1; the study title must be given in German and English. Inclusion into the protocol of addresses and relevant contact persons for participating institutions is not advisable as this may lead to the need of amendments if a new institution is included during an ongoing study (see also ‘SOP 7: Data Flow, Monitoring and Archiving’). Background Information (6.2) – Name and description of the investigational product(s). – A summary of findings from nonclinical studies that potentially have clinical significance and from clinical trials that are relevant to the trial. – Summary of the known and potential risks and benefits, if any, to human subjects. – Description of and justification for the route of administration, dosage, dosage regimen, and treatment period(s). – A statement that the trial will be conducted in compliance with the protocol, Good Clinical Practice and the applicable regulatory requirement(s). – Description of the population to be studied. – References to literature and data that are relevant to the trial and that provide background for the trial. Trial Objectives and Purpose (6.3) A detailed description of the objectives and the purpose of the trial. Please note: Including, for example, a description of the practical problems in the target indication from a medical perspective.

Trial Design (6.4) The scientific integrity of the trial and the credibility of the data from the trial depend substantially on the trial design. A description of the trial design should include: – A specific statement of the primary endpoints and the secondary endpoints, if any, to be measured during the trial. – A description of the type/design of trial to be conducted (e.g. double-blind, placebo-controlled, parallel design) and a schematic diagram of trial design, procedures and stages. – A description of the measures taken to minimize/avoid bias, including: Randomization, Blinding. – A description of the trial treatment(s) and the dosage and dosage regimen of the investigational product(s), including also a description of the dosage form, packaging, and labeling of the investigational product(s). – The expected duration of subject participation and a description of the sequence and duration of all trial periods, including follow-up, if any. – A description of the ‘stopping rules’ or ‘discontinuation criteria’ for individual subjects, parts of trial, and entire trial. – Accountability procedures for the investigational product(s), including the placebo(s) and comparator(s), if any. – Maintenance of trial treatment randomization codes and procedures for breaking codes. – The identification of any data to be recorded directly on the case report forms (CRFs) (i.e. no prior written or electronic record of data) and to be considered to be source data. Selection and Withdrawal of Subjects (6.5) – Subject inclusion criteria. – Subject exclusion criteria. – Subject withdrawal criteria (i.e. terminating investigational product treatment/trial treatment) and procedures specifying: When and how to withdraw subjects from the trial/ investigational product treatment, The type and timing of the data to be collected for withdrawn subjects, Whether and how subjects are to be replaced, The follow-up for subjects withdrawn from investigational product treatment/trial treatment. Please note: See also ‘SOP 9: Statistical Design and Analysis’. Treatment of Subjects (6.6) – The treatment(s) to be administered, including the name(s) of all the product(s), the dose(s), the dosing

12

Onkologie 2003; 26 (suppl 6): 11–14

schedule(s), the route/mode(s) of administration, and the treatment period(s), including the follow-up period(s) for subjects for each investigational product treatment/trial treatment group/arm of the trial. – Medication(s)/treatment(s) permitted (including rescue medication) and not permitted before and/or during the trial. – Procedures for monitoring subject compliance. Assessment of Efficacy (6.7) – Specification of the efficacy parameters. – Methods and timing for assessing, recording, and analyzing of efficacy parameters. Please note: Regarding the assessment of efficacy, the Note for Guidance on Evaluation of Anticancer Medicinal Products in man (CPMP/EWP/205/95) [2] will be followed: 3.6.1 Objective responses. An objective response is defined as a measurable reduction in the tumor burden, (assessed by reduction of the target lesion/other indicator). When multiple lesions are present, representative lesions may be selected for the assessment of medicinal product activity but no progression of other/new lesions should occur during the study period. The objective response rate will have to be documented according to international standards [e.g. 3 or 4]. Whenever a tumor marker (e.g. biochemical, molecular biology) is a valid measure of the therapeutic effects on tumor burden, it can be used to define efficacy of the medicinal product on the neoplastic disease. In this case both the use of this marker and the validation of the measures should be fully justified. External independent review of the responses should be undertaken, according to the objectives of the trial.

Deviations from these recommendations are permitted in exceptional cases but have to be justified. For example, modifications are necessary when drugs for hematological indications are investigated. In a trial of endocrinologically active ingredients or immunomodulating agents, the WHO criteria [4] have to be supplemented as follows if long-term stabilization of a tumor (‘no change’) is to be interpreted as an objective tumor ‘response’: A ‘no change’ finding of an indicator lesion shall be interpreted as an objective response only if – There is documented proof of tumor progression as established by objective procedures during the period preceding the trial period (increase in the size of the indicator lesion by at least 25% during period ‘X’ or occurrence of new lesions) and – The duration of subsequent stabilization is at least twice as long as the pre-study period of observation, i.e., ‘2 X’. Assessment of Safety (6.8) – Specification of safety parameters. – The methods and timing for assessing, recording, and analyzing safety parameters.

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

– Procedures for eliciting reports of and for recording and reporting adverse event and intercurrent illnesses. – The type and duration of the follow-up of subjects after adverse events. Please note: Standard criteria are the ‘Common Toxicity Criteria’ [5] developed by the NCI (Bethesda), on which the standard CRFs presented in ‘SOP 4: Data Collection Forms (Case Report Forms)’ are based. The current version of the CTC list can be obtained through the internet: http://ctep.cancer.gov/forms/CTCAEv3/.pdf. Statistics (6.9) – A description of the statistical methods to be employed, including timing of any planned interim analysis(ses). – The number of subjects planned to be enrolled. In multicenter trials, the numbers of enrolled subjects projected for each trial site should be specified. Reason for choice of sample size, including reflections on (or calculations of) the power of the trial and clinical justification. – The level of significance to be used. – Criteria for the termination of the trial. – Procedure for accounting for missing, unused, and spurious data. – Procedures for reporting any deviation(s) from the original statistical plan (any deviation(s) from the original statistical plan should be described and justified in protocol and/or in the final report, as appropriate). – The selection of subjects to be included in the analyses (e.g. all randomized subjects, all dosed subjects, all eligible subjects, evaluable subjects). See also ‘SOP 9: Statistical Design and Analysis’. Direct Access to Source Data/Documents (6.10) The sponsor should ensure that it is specified in the protocol or other written agreement that the investigator(s)/institution(s) will permit trial-related monitoring, audits, IRB/IEC review, and regulatory inspection(s), providing direct access to source data/documents. Quality Control and Quality Assurance (6.11) Ethics (6.12) Description of ethical considerations relating to the trial.

Supplements (6.16) Please note: Since the protocol and the clinical trial/study report are closely related, further relevant information can be found in the ICH Guideline for Structure and Content of Clinical Study Reports. In order not to make the protocol itself too long, the following documents should be kept separately, e.g. in a study file: – Set of Case Report Forms, – Relevant regulations and guidelines such as the Declaration of Helsinki – Investigator’s Brochure, – Approval by the Ethics Committee (or to be added upon receipt), – Insurance conditions and copy of the insurance policy, – Model of the patient identification list, – Drug accountability form. See also Attachment 2: Model for an English Synopsis of the Trial Protocol.

Standard Format of Individual Protocol Elements

The following formats should be used for trial protocols of CESAR: – Cover page (model for trial protocol written in English): see Attachment 1, – Summary of the trial protocol (model for English synopsis): see Attachment 2.

References 1 ICH-GCP: EMEA: Note for Guidance on Good Clinical Practice (CPMP/ICH/135/95). 2 EMEA: Committee for Proprietary Medicinal Products (CPMP). Note for guidance on evaluation of anticancer medicinal products in man (CPMP/EWP/205/95; rev. 1). 3 RECIST: Therasse P, Arbuck S, Eisenhauer EA, Wanders J, Kaplan RS, Rubinstein L, Verweij J, Van Glabbeke M, van Oosterom AT, Christian MC, Gwyther SGNew guidelines to evaluate the response to treatment in solid tumors. European Organization for Research and Treatment of Cancer, National Cancer Institute of the United States, National Cancer Institute of Canada. J Natl Cancer Inst 2000;92:205–216. 4 WHO: World Health Organization (WHO): WHO Handbook for Reporting Results of Cancer Treatment. Geneva, WHO, 1979. 5 CTC: National Cancer Institute (NCI): Common Toxicity Criteria (CTC); current version. http://ctep.info.nih.gov/reporting/ctc.html.

Data Handling and Record Keeping (6.13) Financing and Insurance (6.14) Financing and insurance if not addressed in a separate agreement. Publication Policy (6.15) Publication policy is detailed in the Bylaws under ‘XIV’.

SOP 03: Preparation and Structure of Trial Protocols

Appendix

Attachment 1: Template for the Cover Page of a Clinical Trial Protocol Attachment 2: Template for the Synopsis of a Clinical Trial Protocol

Onkologie 2003; 26 (suppl 6): 11–14

13

14

Onkologie 2003; 26 (suppl 6): 11–14

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

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Onkologie 2003; 26 (suppl 6): 15–22

Version 01 Approval: June 28, 2001 Implementation: June 29, 2001

SOP 04: Data Collection Forms (Case Report Forms)

Background

The format, extent, and language of data collection forms (Case Report Forms (CRFs)) are generally not prescribed in detail by guidelines on Good Clinical Practice. As a general rule, however, CRFs should provide a complete documentation of all findings as required by the trial protocol and other relevant observations. CRFs should be adapted to the requirements of a particular study. Examples for CRFs used for phase II studies conducted by CESAR are appended to this SOP. These need to be adapted according to protocol requirements of individual trials. Additional parameters not included in the sample CRFs may be recorded on additional, study-specific forms. In exceptional cases – in particular for phase I studies or when multicenter phase II studies are performed in cooperation with other study groups – CRFs provided by a sponsor may be used. However, such forms should contain as a minimum at least the parameters required by the standard CRFs of CESAR. The decision as to the use of such forms will be made by the Chair of the working group in consultation with the Coordinating Investigator (see ‘SOP 2: Evaluation and Selection of a Clinical Trial Proposal for CESAR’) and the statistician of CESAR’s data center.

Logistic Considerations

The sponsor will supply the investigators participating in a clinical trial with an appropriate number of CRFs, including the supplementary, study-specific forms. Preferably, standard CRFs and supplementary forms should be provided in a folder and arranged in the chronological order as they will be used.

have first been written down or printed out must be retained and must be available in case of an audit or inspection. The CRF may be used as source document, e.g. for clinical data that are primarily or exclusively required for a clinical trial. If an investigator decides to do so, he/she should declare this to the monitor before the start of a trial to avoid subsequent arguments about appropriate maintenance of source documents. See below for adverse events recording. Entries All entries on CRFs should be made in indelible dark ballpoint or ink pen or the like. Do not use a pencil. Corrections All corrections must be made in a way which do not obscure the original entry (do not use masking fluids); the correct data must be inserted, dated and initialed by the investigator (with an explanation if necessary). Adverse Event Recording For trials under the auspices of CESAR, it has been decided that the Common Toxicity Criteria (CTC) [1], as defined and published by the National Cancer Institute (NCI) of the USA, will be used to classify and grade the symptom status and adverse event observations. Because of the complexity of the current CTC list, it is inconvenient for ‘bed-side’ assessment and recording. Moreover, CRF sections for adverse events may differ between sponsors of different trials and may not be optimal for being used as recording tool. Therefore, a 2-page ‘Symptom Checklist’ that covers all symptom categories of CTC and that takes into account the needs of the clinical routine, is proposed for use as source document for adverse event recording (Attachment 3).

General Remarks on Case Report Form Handling

Source Documents Good Clinical Practices, as defined by ICH-GCP guidelines, require that documents in which trial-related data

# 2003 S. Karger GmbH, Freiburg Fax +49 761 4 52 07 14 E-mail [email protected] www.karger.com

Accessible online at: www.karger.com/onk

Laboratory Units The units given on the CRFs are mandatory, in case other units are used by the laboratory of a study center, it is the

responsibility of the data center to convert these to the required units. Comments Conspicuous laboratory findings, e.g. values outside the normal range or pronounced changes during the study period, need to be commented on. Abnormalities or changes considered to be ‘tumor-related’ have to be marked as such. ‘Additional Findings’ In case additional data beyond those required by the trial protocol are documented these have to be marked as such and should be commented on. Signatures CRFs with a signature field marked ‘investigator’ may only be signed by a person whom the Principal Investigator (working group member of CESAR) has declared as ‘investigator’ in the list of authorized study personnel. Entries of effect parameters made by individuals other than an investigator (e.g. clinical research physician, clinical re-

16

Onkologie 2003; 26 (suppl 6): 15–22

search associate, documentation assistant, etc.) should be signed by the individual making the entry. References 1 CTC: National Cancer Institute (NCI). Common Toxicity Criteria (CTC); current version. http://ctep.info.nih.gov/reporting/ctc.html.

Appendix

Attachment 1: Phase I/II Data Collection Forms/Case Reports Forms Attachment 2 (not included in this print version of the SOPs): Common Terminology Criteria for Adverse Events (CTCAE), version 10, June 2003 see http://ctep.info.nih.gov/ reporting/ctc.html. If a new version is released during an ongoing trial, a protocol amendment will be required before that new version can be used. Attachment 3: Current Symptoms/Adverse Event Checklist

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

SOP 04: Data Collection Forms (Case Report Forms)

Onkologie 2003; 26 (suppl 6): 15–22

17

pN

Tag

Monat

Monat

Datum:

Diagnose / Beschwerden

[ M / J ]

Unterschrift:

[ M / J ]

Datum Beginn / Ende

Monat

Monat

Grading:

Jahr

Prüfarzt:

(Prüfarzt)

[ M / J ] [ M / J ]

(wenn ja, welche?)

(2) m

bleibende Beeinträchtigungen

(1) w

Pat.Nr.:

(Bitte nicht ausfüllen!)

Dok-Nr.

Geschlecht:

Datum Beginn / Ende

Andere Stadieneinteilung:

Tag

Behandlungsart

Jahr

Geburtsdatum:

Jahr

Seite 1

Ersterhebung

Jahr

Tag

4. Vor- / Begleiterkrankung:

Lokalisation:

Datum des ersten Rezidivnachweises:

pT

pM

Primärtumor-Lokalisation:

Datum der Erstdiagnose:

Histologie:

Tag

(Vorname, Nachname)

3. Tumordaten:

Initialen:

2. Patientendaten:

Datum der Ersterhebung:

Klinik:

Studienprotokoll (Kurzbezeichnung)

1. Studiendaten:

Central European Society for Anticancer Drug Research EWIV

Phase II Studie 2000/x Kombinationstherapie von Medikament A und Medikament B bei Patienten mit Krankheit C

Seite 2

Ersterhebung

Art * [ T / M / J ] [ T / M / J ]

Datum Beginn / Ende Herddosis (Gy) / Substanzen

Geburtsdatum:

Initialen:

H

Datum:

Unterschrift: (Prüfarzt)

Methode vorbestrahlt *** (z.B. CT, Rö)

Bemerkungen

(Tumorparameter bei Studienbeginn bzw. Tag 0):

Größe Tumor* Auswertbarkeit** (cm x cm x cm)

1 = Metastasen, 2 = Primärtumor, 3 = Lokalrezidiv: a = stabil, b = progredient 1 = meßbar, 2 = auswertbar, 3 = nicht auswertbar 0 = nein, 1 = ja, 9 = unbekannt

Organ / Lokalisation

Kommentar:

* ** ***

G

F

sonstige

E

D

C

B

A

Indikatorläsion

6. Tumorausbreitung:

Jahr

Erfolg ***

Monat

Nachname

dok.Progression vor Studienbeginn? *** falls ja, Datum:

Ziel **

Tag

Vorname

(Bitte nicht ausfüllen!)

Dok-Nr.

* 1 = Operation, 2 = Bestrahlung, 3 = Hormontherapie, 4 = zytostatische Behandlung, 5 = andere ** 1 = kurativ, 2 = palliativ, 3 = adjuvant, 4 = unbekannt *** 1 = komplette Remission (CR), 2 = partielle Remission (PR), 3 = keine Änderung (NC), 4 = Progression (PD), 5 = nicht beurteilbar

Lokalisation

5. Tumorspezifische Vorbehandlungen:

Central European Society for Anticancer Drug Research EWIV

Phase II Studie 2000/x Kombinationstherapie von Medikament A und Medikament B bei Patienten mit Krankheit C

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Onkologie 2003; 26 (suppl 6): 15–22

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

Seite 3

Ersterhebung

Gewicht:

Tag

Monat

Jahr

,

kg

Größe:

cm

Tag

Vorname

Körperoberfläche:

Geburtsdatum:

Initialen:

x10 9 /l

mm n.W.

g/l

%

sec

Thrombozyten

Lymphozyten

BKS

Fibrinogen

Prothrombinzeit

Partielle Thromboplastinzeit

(Prüfarzt)

x10 9 /l

Datum:

Unterschrift:

.

x10 9 /l

Granulozyten

Kommentar:

.

x10 9 /l

Leukozyten

.

/

.

.

Vol%

Hämatokrit

.

g/100 ml

Jahr

Hämoglobin

Monat

Einheit

Tag

Laborwerte

Datum:

8. Laborbefund vor Therapiebeginn (Tag 0):

,

Monat

m²

Jahr

Nachname

(Bitte nicht ausfüllen!)

Dok-Nr.

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AZ (WHO 0-4)*

Untersuchungsdatum:

7. Körperlicher Befund vor Therapiebeginn (Tag 0):

Central European Society for Anticancer Drug Research EWIV

Phase II Studie 2000/x Kombinationstherapie von Medikament A und Medikament B bei Patienten mit Krankheit C

Seite 4

mmol/l Kalium

Unterschrift:

mmol/l Natrium

Datum:

Kommentar:

.

mmol/l Magnesium

.

.

mmol/l Kalzium

. U/l

mmol/l Serumglukose

.

.

.

.

.

Amylase

U/l

U/l

U/l

U/l

U/l

µmol/l

µmol/l

g/l

mmol/l

g/l

Gamma-GT

LDH

Alkalische Phosphatase

SGPT (ALAT)

SGOT (ASAT)

Bilirubin

Albumin

Gesamteiweiß

Harnstoff

Eiweiß im Urin

µmol/l

Einheit

Jahr

µmol/l

Monat

Kreatinin

Tag

Harnsäure

Laborwerte

Datum:

(Prüfarzt)

Ersterhebung

8. Laborbefund vor Therapiebeginn (Tag 0):

Central European Society for Anticancer Drug Research EWIV

Phase II Studie 2000/x Kombinationstherapie von Medikament A und Medikament B bei Patienten mit Krankheit C

Geburtsdatum:

Initialen:

Tag

Vorname

Monat

Jahr

Nachname

(Bitte nicht ausfüllen!)

Dok-Nr.

SOP 04: Data Collection Forms (Case Report Forms)

Onkologie 2003; 26 (suppl 6): 15–22

19

nein nein nein

3. Lunge / Atmungsorgane

4. Niere und Blase

5. Neurologische Symptome

Tag

Vorname

nein nein nein

9. Allgemeine Symptome

10. Fieber / Infektion / Grippeähnliche Symptome

11. Weitere Befunde ja

ja

ja

ja

ja

ja

ja

ja

ja

ja

ja

(Prüfarzt)

* vgl. CTC-Checkliste

Nr. lt. Checkliste:

Symptom * :

Nr. lt. Checkliste:

Symptom * :

Nr. lt. Checkliste:

Symptom * :

Datum:

Unterschrift:

Seite 6

.

.

.

* von: bis:

* von: bis:

*

Unterschrift:

Beobachtungszeitraum

Beobachtungszeitraum

(Prüfarzt)

von: bis: Gegenmaßnahme:

Grad

Gegenmaßnahme:

Grad

Gegenmaßnahme:

Grad

Tag

Vorname

Monat

Jahr

Nachname

(Bitte nicht ausfüllen!)

Dok-Nr.

Geburtsdatum:

Initialen:

Beobachtungszeitraum

Ersterhebung

Phase II Studie 2000/x Kombinationstherapie von Medikament A und Medikament B bei Patienten mit Krankheit C

9. Symptome vor Therapiebeginn (Tag 0)

Datum:

Jahr

Kommentar:

Monat

Nachname

Central European Society for Anticancer Drug Research EWIV

Kommentar:

Symptome bitte auf Seite 6 mit Hilfe der CTC-Checkliste genau spezifizieren!

nein

nein

8. Haut / Allergien

7. Sinnesorgane

nein

nein

2. Herz / Kreislauf

6. Endokrines System

Geburtsdatum:

Initialen:

(Bitte nicht ausfüllen!)

Dok-Nr.

Wurden Symptome beobachtet? nein

Seite 5

Ersterhebung

1. Gastro-Intestinaltrakt

Symptomgruppe

9. Symptome

Central European Society for Anticancer Drug Research EWIV

Phase II Studie 2000/x Kombinationstherapie von Medikament A und Medikament B bei Patienten mit Krankheit C

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Onkologie 2003; 26 (suppl 6): 15–22

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

Tag

Monat

(2) PR

Tag

Monat

Jahr

Datum:

Kommentar:

Obduktion:

(3) therapiebedingt

(1) ja

(2) Therapieeinfluß möglich

Todesursache: (1) tumorbedingt

Todesdatum:

4. Überlebensdaten:

von Tag Monat

(6) nicht beurteilbar

Unterschrift:

(2) nein

bis

(Prüfarzt)

(5) unbekannt

(4) andere Ursache, welche?

letztes Beobachtungsdatum:

Datum der Progredienz (bzw. Verdacht auf Progredienz):

(3) NC

Späte Nebenwirkungen der Therapie, welche?

(5) 'Early Death'

(4) PD

(1) CR

Bestes Ansprechen mit:

3. Abschließende retrospektive Erfolgsbeurteilung:

Jahr

Tag

Tag

Tag

Monat

Monat

Monat

(8) andere Gründe, welche?

(4) keine Weiterverfolgung (lost to follow-up) (9) fehlende Angaben

(7) protokollgemäßes Ende der Behandlung

(3) Exzessive Toxizität

Jahr

Jahr

Jahr

Jahr

Jahr

Nachname

Monat

Monat

(6) Protokollverletzung

Tag

(5) Verweigerung der Therapie

Ende bzw. letzte Applikation am:

(2) Tod

Jahr

Pat.Nr.:

Tag

Vorname

(Bitte nicht ausfüllen!)

(1) Tumorprogression

Ursachen für Beendigung:

Beginn am:

2. Therapie:

Geburtsdatum:

Initialen:

Dok-Nr.

Gesamtzahl der Verlaufsbeobachtungen bzw. verabreichter Kurse:

Abschlußerhebung

Studienprotokoll (Kurzbezeichnung)

1. Studiendaten:

Central European Society for Anticancer Drug Research EWIV

Phase II Studie 2000/x Kombinationstherapie von Medikament A und Medikament B bei Patienten mit Krankheit C

Seite 1

Post Study Tag

Vorname

Monat

yes yes

no no

11. Blutungen 12. Leberfunktion

24. Weitere Syndrome

23. Geschlechtsorgane

22. Zweittumor

21. Niere / Urogenitaltrakt

20. Lunge / Atmungsorgane

19. Schmerzen

18. Augen / Sehvermögen

17. Neurologie

16. Bewegungsapparat

15. Stoffwechsel

13. Infektion / Febrile Neutropenie 14. Lymphsystem

Symptomgruppe

no

no

no

no

no

no

no

no

no

no

no

no

Datum:

Kommentar:

Unterschrift: (Prüfarzt)

yes

yes

yes

yes

yes

yes

yes

yes

yes

yes

yes

yes

Wurden Symptome beobachtet?

Toxizitäten bitte im UE-Bogen mit Hilfe der CTC-Checkliste genau spezifizieren!

yes

yes

yes

yes

yes

yes

no

no

no

no

no

no

yes

yes

yes

yes

10. Gastro-Intestinaltrakt

9. Endokrines System

8. Dermatologie / Haut

7. Konstitutionelle Symptome

6. Gerinnung

5. Herz / Kreislauf (allgemein)

no

no

no

no

Wurden Symptome beobachtet?

4. Herz / Kreislauf (Arrhythmien)

3. Blut / Knochenmark

2. Gehör

1. Allergien / Immunologie

Symptomgruppe

Jahr

Nachname

(Bitte nicht ausfüllen!)

Untersuchungstermin Nr.:

Geburtsdatum:

Initialen:

Dok-Nr.

6. Symptombeurteilung (vgl. NCI-CTC-Liste Version 2.0 vom 30.01.98, überarbeitet 23.03.98)

Central European Society for Anticancer Drug Research EWIV

Phase II Studie 2000/x Kombinationstherapie von Medikament A und Medikament B bei Patienten mit Krankheit C

SOP 04: Data Collection Forms (Case Report Forms)

Onkologie 2003; 26 (suppl 6): 15–22

21

.

.

.

*

Datum:

Kommentar:

von: bis:

* von: bis:

*

Unterschrift:

Dok-Nr.

Tag

Vorname

Monat

Beobachtungszeitraum

Beobachtungszeitraum

Zusammenhang **

Zusammenhang **

Zusammenhang **

Jahr

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(Bitte nicht ausfüllen!)

Untersuchungstermin Nr.:

Geburtsdatum:

Initialen:

Beobachtungszeitraum

(Prüfarzt)

von: bis:

Gegenmaßnahme:

Grad

Gegenmaßnahme:

Grad

Gegenmaßnahme:

Grad

* vgl. CTC-Checkliste ** 1 = sicher, 2 = wahrscheinlich, 3 = möglich, 4 = unwahrscheinlich, 5 = unklar

Nr. lt. Checkliste:

Symptom * :

Symptomgruppe * :

Nr. lt. Checkliste:

Symptom * :

Symptomgruppe * :

Nr. lt. Checkliste:

Symptom * :

Symptomgruppe * :

Seite 2

Post Study

Unerwünschte Ereignisse

Central European Society for Anticancer Drug Research EWIV

Phase II Studie 2000/x Kombinationstherapie von Medikament A und Medikament B bei Patienten mit Krankheit C

Tag Monat Jahr

Wochen nach Therapiebeginn

Seite 3

Post Study

Organ / Lokalisation

Auswertbarkeit* Größe (cm x cm x cm)

Tag

Vorname

Methode subjektive CT, Bewertung ** (z.B. Rö)

(4) Progression

Datum:

Kommentar:

Unterschrift:

Laborparameter oder Symptom(e) lt. CTC:

(Prüfarzt)

(4) andere, welche?

(3) Therapieabbruch am

(2) Therapieverschiebung um

Maßnahmen: (1) Dosiserniedrigung

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8. Therapieerfolg:

Monat

Bemerkungen

Tag

Monat

Jahr

Tage

% der Solldosis

(5) nicht beurteilbar

Jahr

Nachname

(Bitte nicht ausfüllen!)

Untersuchungstermin Nr.:

Geburtsdatum:

Initialen:

Dok-Nr.

1 = meßbar, 2 = auswertbar, 3 = nicht auswertbar 1 = starke Zunahme, 2 = geringe Zunahme, 3 = unverändert 4 = geringe Abnahme, 5 = starke Abnahme 6 = nicht mehr vorhanden, 9 = nicht beurteilbar; Beurteilung ist auf den vorangegangenen Beobachtungszeitpunkt zu beziehen! * **

H

G

F

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D

C

B

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Eintrag bitte in gleicher Reihenfolge wie auf dem Ersterhebungsbogen!

Datum:

Beurteilung:

7. Tumorausbreitung:

Central European Society for Anticancer Drug Research EWIV

Phase II Studie 2000/x Kombinationstherapie von Medikament A und Medikament B bei Patienten mit Krankheit C

22

Onkologie 2003; 26 (suppl 6): 15–22

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

from – to

from – to

Anorexia Constipation Duodenal ulcer Gastric ulcer Mouth dryness Pancreatitis Ascites Dehydration Dyspepsia Gastritis

Gastrointestinal

Gynecomastia SIADH Hot flashes Cushing

Endocrine

Alopecia Nail-changes Pruritus Desquamation Dry skin Photosensibility

Dermatology/Skin

Fatigue Sweating Fever Weight gain

Constitutional Symptoms

Acute vasc. leak syndrome Edema Pericardial effusion Cardiac ischemia Hypertension

Cardiovascular

Conduction abnormality Sinus bradycardia Syncope Nodal arrhythmia Sinustachycardia

from - to

from - to

from - to

from - to

from - to

from – to

Cardiovascular (Arrhythmia)

External auditory canal Inner ear

Auditory/Hearing

Allergic reaction Serum sickness Allergic rhinitis

relation y n nk

relation y n nk

relation y n nk

relation y n nk

relation y n nk

Weight loss Rigors, chills Other

relation y n nk

relation y n nk

grade

relation y n nk

Mucositis Stomatitis Colitis Diarrhea Dysphagia Ileus Nausea Vomiting Other

Feminisation Hypothyroidism Masculinization Other No; if Yes, please tick and specify

grade

Urticaria Woundinfecition Hand-foot skin reaction Pigmentation changes Erythema Other No; if Yes, please tick and specify

grade

No; if Yes, please tick and specify

grade

Phlebitis Card. left-ventr. function Hypotension Thrombosis/embolism Other No; if Yes, please tick and specify

grade

Vasovagal episode Palpitations Supraventr. arrhythmia Ventricular arrhythmia Other No; if Yes, please tick and specify

grade

Middle ear Other No; if Yes, please tick and specify

grade

Vasculitis Autoimmune reaction Other No; if Yes, please tick and specify

grade

No; if Yes, please tick and specify

from - to

from - to

from - to

from - to

from - to

from - to

from - to

from - to

grade

grade

grade

grade

grade

grade

grade

grade

relation y n nk

relation y n nk

relation y n nk

relation y n nk

relation y n nk

relation y n nk

relation y n nk

relation y n nk

(affix label if available)

Date of birth:

(Use CTC list to correctlly assign current CTC grade)

Date of assessment: Allergy/Immunology

Patient name: _______________________________

Current Symptoms / Adverse Events Checklist from - to

from - to

from – to

from - to

from – to

from – to

from - to

from – to

Erectile impotence Libido

from - to

Sexual/Reproductive function

Incontinence Urinary retension Dysuria

Renal/Genitourinary

ARDS FEV Stridor Cough Singultus Hypoxie

Pulmonary

Abdominal pain (cramps) Bone pain Hepatic pain Pelvic pain Tumor pain Arthralgia Chest pain Myalgia

Pain

Conjunctivitis Cataract Glaucoma

Allergy/Immunology

Aphasia CNS ischemia Extrapyramidal Mood alteration Neuropathy-sensory Speech impairment Meningismus Confusion Hallucinations

Neurology

Arthritis Muscle weakness

Musculoskeletal

Lymphedema

Lymphatics

Infection Catheter related

from – to

Infection/Febrile Neutropenia

Hemorrhage/bleeding Hematuria Epistaxis Hemoptysis

Hemorrhage relation y n nk

Hematemesis Petechiae Other

relation y n nk

relation y n nk

relation y n nk

relation y n nk

Neuropathy cran. Seizure(s) Ataxia Dizziness Insomnia Neuropathy-motor Memory loss Other

relation y n nk

relation y n nk

Pleuritic pain Dysmenorrhoe Arthritis Headache Neuropathic pain Rectal pain Other

relation y n nk

Pleural effusions Dyspnea Pneumonitis Pneumothorax Other

relation y n nk

grade

relation y n nk

Vaginal dryness Other

Pollakisuria Renal failure Other No; if Yes, please tick and specify

grade

No; if Yes, please tick and specify

grade

No; if Yes, please tick and specify

grade

Dry eye Tearing Other No; if Yes, please tick and specify

grade

No; if Yes, please tick and specify

grade

Myalgia Other No; if Yes, please tick and specify

grade

Other No; if Yes, please tick and specify

grade

Fever + Neutropenia Other No; if Yes, please tick and specify

grade

No; if Yes, please tick and specify

grade

No; if Yes, please tick and specify

from - to

from - to

from - to

from - to

from - to

from - to

from - to

from - to

from - to

from - to

grade

grade

grade

grade

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relation y n nk

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relation y n nk

relation y n nk

relation y n nk

relation y n nk

Onkologie 2003; 26 (suppl 6): 23–33

Version 01 Approval: June 28, 2001 Implementation: June 29, 2001

SOP 05: Patient Information and Informed Consent

Background

Adequate patient information with particular emphasis on the fact that participation in the study is voluntary is a particular concern of the ‘Declaration of Helsinki’ [1] and Guidelines on Good Clinical Practice. Great care must therefore be taken in formulating and adapting a written patient information sheet to the particular requirements of a given study. The written patient information must be submitted to the relevant Ethics Committee together with the trial protocol.

Elements of Information to Patients

There are no regulations specifying the format of the patient information sheet. Information material should be written in layperson’s terms. According to ICH-GCP [2; chapter 4.8.10], both the informed consent discussion and the written informed consent form and any other written information to be provided to subjects should include explanations of the following: – That the trial involves research. – The purpose of the trial. – The trial treatment(s) and the probability for random assignment to each treatment. – The trial procedures to be followed, including all invasive procedures. – The subject’s responsibilities. – Those aspects of the trial that are experimental. – The reasonably foreseeable risks or inconveniences to the subject and, when applicable, to an embryo, fetus, or nursing infant. – The reasonably expected benefits. When there is no intended clinical benefit to the subject, the subject should be made aware of this. – The alternative procedure(s) or course(s) of treatment that may be available to the subject, and their important potential benefits and risks.

# 2003 S. Karger GmbH, Freiburg Fax +49 761 4 52 07 14 E-mail [email protected] www.karger.com

Accessible online at: www.karger.com/onk

– The compensation and/or treatment available to the subject in the event of trial-related injury. – The anticipated prorated payment, if any, to the subject for participating in the trial (comment: commonly not accepted for studies in patients). – The anticipated expenses, if any, to the subject for participating in the trial. – That the subject’s participation in the trial is voluntary and that the subject may refuse to participate or withdraw from the trial, at any time, without penalty or loss of benefits to which the subject is otherwise entitled. – That the monitor(s), the auditor(s), the IRB/IEC, and the regulatory authority(ies) will be granted direct access to the subject’s original medical records for verification of clinical that procedures and/or data, without violating the confidentiality of the subject, to the extent permitted by the applicable laws and regulations and that, by signing a written informed consent form, the subject or the subject’s legally acceptable representative is authorizing such access. – That records identifying the subject will be kept confidential and, to the extent permitted by the applicable laws and/or regulations, will not be made publicly available. If the results of the trial are published, the subject’s identity will remain confidential. – That the subject or the subject’s legally acceptable representative will be informed in a timely manner if information becomes available that may be relevant to the subject’s willingness to continue participation in the trial. – The person(s) to contact for further information regarding the trial and the rights of trial subjects, and whom to contact in the event of trial-related injury. – The foreseeable circumstances and/or reasons under which the subject’s participation in the trial may be terminated. – The expected duration of the subject’s participation in the trial. – The approximate number of subjects involved in the trial.

Please note: Ethics Committees commonly require the inclusion of standard text sections, e.g. on mandatory insurance of trial subjects (with local address, policy number, as well as phone and fax numbers of the insurance). Clear and simple definitions of technical terms are mandatory. Since these requirements are not uniform, it may be necessary to prepare alternative versions of the patient information sheet for individual participating centers. In order not to delay the activation of a study, all members of the study group are expected to inform the Coordinating Investigator and sponsor of any such standard elements. It is the responsibility of each participating center to provide the sponsor with a copy of the adapted information sheet together with the approval by the relevant Ethics Committee. Model Texts

Attached are model texts for the patient information sheet and the informed consent form. The texts contain the mini-

24

Onkologie 2003; 26 (suppl 6): 23–33

mal elements required for all studies. These have to be supplemented with additional details as needed for a particular study and investigational drug.

References 1 Der Welta¨rztebund: Deklaration von Helsinki – Empfehlung fu¨r rzte, die in der biomedizinischen Forschung am Menschen ta¨tig sind. (revised in Edinburgh, October 2000). 2 ICH-GCP: EMEA. Note for Guidance on Good Clinical Practice (CPMP/ICH/135/95).

Appendix

Attachment 1: Model Patient Information/Informed Consent (Template for phase II studies; NCI/Bethesda) Attachment 2: Dokumentvorlage fu¨r Patienten-Einversta¨ndniserkla¨rung (Template for Patient Information/Informed Consent derived from template of the NCI)

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

SOP 05: Patient Information and Informed Consent

Onkologie 2003; 26 (suppl 6): 23–33

25

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26

Onkologie 2003; 26 (suppl 6): 23–33

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Onkologie 2003; 26 (suppl 6): 23–33

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SOP 05: Patient Information and Informed Consent

Onkologie 2003; 26 (suppl 6): 23–33

33

Onkologie 2003; 26 (suppl 6): 34–35

Version 01 Approval: June 28, 2001 Implementation: June 29, 2001

SOP 06: Selecting the Participating Centers and Activation of a Trial

Background

If there are more candidates than the planned maximum number of participating study centers, a selection will be made as outlined in this SOP. The Chairperson(s) of the respective working group will announce the participating centers in consultation with the sponsor after he/she has received responses from all centers to whom participation was offered.

In order to comply with the principles of GCP, it is necessary to carefully coordinate activities both before starting a trial and throughout its duration. For practical reasons, there will be a limit for the maximum number of centers that can participate in a trial, to ensure adequate monitoring and to minimize differences among study centers, e.g. regarding patient selection and assessments. For reasons to exclude a center from an ongoing study; see below.

Competing Studies Selection of Suitable Trial Centers

ICH-GCP defines the conditions that must be met by investigators and study centers participating in clinical trials that comply with Good Clinical Practice (GCP). According to these guidelines, it is the responsibility of the sponsor to select suitable centers and to continuously monitor their suitability throughout the study. This responsibility is shared by the monitor as the principal communication link between investigators and the sponsor. Responsibilities of the investigator besides his/her professional qualifications and a thorough familiarity with the properties of the investigational product are described in section 4.1.2 of ICHGCP. The criteria to be met by trial centers are summarized in the Selection Criteria for Membership in a clinical Working Group of CESAR (see ‘SOP 01: Clinical Investigations in CESAR’). Each study center participating in a multicenter trial must satisfy the above criteria. A uniform level of information of all participants must be ensured by establishing proper procedures for data flow among all parties involved (see ‘SOP 7: Data Flow, Monitoring, and Archiving’). The Chairperson(s) of the respective working group, in consultation with the sponsor, selects the centers to participate in a study that is to be conducted under the auspices of CESAR. This holds in particular if more centers wish to participate than is reasonable for a given study.

# 2003 S. Karger GmbH, Freiburg Fax +49 761 4 52 07 14 E-mail [email protected] www.karger.com

Accessible online at: www.karger.com/onk

If CESAR has several disease-oriented studies with overlapping patient selection criteria ongoing at the same time, each center may participate in only one of them. This holds for phase II/III trials only. In order to minimize a selection bias and the duration of a study, it is expected that an institution will not participate in a study of CESAR if it is concurrently engaged in a non-CESAR study with similar selection criteria.

Exclusion from an Ongoing Study

The Coordinating Investigator (CI) can exclude a participating center from further patient accrual for an ongoing trial in case of the following deficiencies: – Significant failure to achieve the predicted rate of patient accrual. – Repeated nonadherence to the trial protocol despite documented reminders. – Repeated delays in the completion and submission of Case Report Forms. – Submission of data that cannot be validated. – Repeated accrual of ineligible patients. – Repeated failure of the (principal) investigator or his authorized deputy to be available during site visits by the monitor or the extramural review board.

– Repeated failure to cooperate in quality assurance measures as defined in ‘SOP 11. Quality Assurance’.

A study will be activated once the following criteria have been satisfied: – The CI has integrated the change requests from the Project Committee and participating working group members into a final version of the protocol.

– A sufficient number of working group members have declared their interest to participate in the clinical trial. – Approval by the Ethics Committee that is relevant for the CI. – Written information of all participating centers of the study. – The sponsor has met all applicable regulatory prerequisites (insurance, notification of the trial to regulatory authorities, drug import certification, etc.). Patient accrual at a center can start after the initiation visit by the monitor.

SOP 01: Clinical Investigations in CESAR

Onkologie 2003; 26 (suppl 6): 34–35

Study Activation

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Version 01 Approval: June 28, 2001 Implementation: June 29, 2001

SOP 07: Data Flow, Monitoring, and Archiving

Background

CRF Submission Paths

SOP 07 outlines the data flow among the parties involved in the conduct of a phase I or phase II or phase III trial. The procedures specified in this SOP primarily concern the documentation of results on the Case Report Forms (CRFs), their verification by the monitor of the study, the entry of the data into the computerized data base and their validation at the data center of the CESAR. The flow of information as specified below and the verification of the study data for each individual patient by the monitor of the sponsor aims at ensuring that strict standards regarding data quality are implemented for all studies performed by CESAR.

CRF submission paths are depicted in figure 1.

Patient Registration

As a rule, the eligibility of a patient for entering a phase I or phase II or phase III study should be verified by an independent assessor before the patient receives the first dose of the study medication. Each study protocol must specify the reporting lines, i.e. the role of CESAR’s data center and of the sponsor’s study monitor, as well as any registration forms to be used. The general procedure is as follows: – The investigator performs all screening investigations and compares the patient characteristics with the inclusion and exclusion criteria of the protocol. If the investigator considers a patient eligible for the study, he will transmit the relevant information to data center or the monitor. – The data center or the monitor will immediately check the entries in this form against the eligibility check data. Any discrepancies that may affect the patient’s eligibility for the study will be jointly clarified by the sponsor and the coordinating investigator. Any decision will be documented in writing.

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Notes Regarding Data Submission Paths

– Direct entry of data into a computerized documentation system by investigators is acceptable if the procedures are agreed upon with the Data Center of CESAR. – Each addition to or modification of a CRF must be dated and initialled by the investigator. Changes must be made in a way which does not obscure the original entry (use of masking fluids is not allowed); if required, the reason for the correction must be given. – A written query may be issued to resolve any data discrepancy. This will allow for changes without the risks associated with repeated mailing of original documents.

Trial Documentation

– Study monitoring is the responsibility of the monitor of the sponsor and follows the procedures defined in the sponsor’s own SOP. – The monitor of the sponsor is responsible for the timely transmission of the CRFs to the data center of the CESAR. – The monitor of the sponsor makes sure that queries and requests for additions to or corrections of the CRFs are promptly (within 4 weeks) attended to and dealt with according to the data submission paths described in section 8.2 of ICH-GCP [1]. At the end of one reporting interval (typically one treatment cycle), the investigator has 4 weeks for submission of the completed CRFs to the monitor, unless otherwise specified in the trial protocol. It is the monitor’s obligation to report to the Coordinating Investigator (CI) the failure of an investigator to comply with the timely completion of CRFs.

Site Visit Report 1.

Completion of the CRFs by the investigator and/or staff member designated by the investigator

2.

Signing of the CRFs by the investigator

3.

Submission (in person/by mail) of the original CRFs to the monitor of the sponsor by the investigator

4.

Site visit by the monitor of the sponsor for verification of CRF ENTRIES

5.

Submission of the original CRFs to the data center and of photocopies to the Coordinating Investigator by the monitor of the sponsor

6.

Computerized input of the data from the original CRFs at the data center

6.1 Questions that arise at this point at the data center and require corrections/additional data items to be recorded on the CRFs will be forwarded to the monitor of the sponsor together with the original CRFs. Alternatively, a question may be resolved by issuing a written query form that is to be completed by the investigator and which becomes a supplement to the original, unmodified CRF.

The monitor will write a site visit report after each site visit and summarize the relevant findings, specifically any action items, in a letter to the clinical investigator, with a copy to the CI.

Archiving of Essential Documents

Archiving of documents relating to a clinical trial must comply with EEC guidelines [2]. Refer to section 8 of ICH-GCP for a complete list of ‘essential documents’ and the assignment of respective archiving obligations to investigator and/or sponsor. – The monitor is responsible for archiving at the sponsor’s institution of the originals of all completed CRFs from the clinical trial. Each principal investigator should retain in the study files copies of those CRFs that were completed under his/her responsibility. – The investigator shall archive a copy of the approval by the Ethics Committee, his/her patient identification list, the originals of the signed informed consent forms, the patient files and other source documents. – All source documents and trial-related documents must be made available for inspection at the request of relevant authorities. The documents must be archived for the minimum period required by the institution, but not less than 15 years. No original of a trial-related document should be disposed without prior written agreement by the sponsor.

References

6.2 After validation of data entry at the data center according to the SOPs established by the center, the originals of the CRFs will be returned to the monitor for archiving.

1 ICH-GCP: EMEA: Note for Guidance on Good Clinical Practice (CPMP/ICH/135/95). 2 Guideline 91/507/EEC, as revised July 19, 1991.

Fig. 1. CRF submission paths.

SOP 07: Data Flow, Monitoring, and Archiving

Onkologie 2003; 26 (suppl 6): 36–37

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Version 01 Approval: June 28, 2003 Implementation: June 29, 2003

SOP 07a: Monitoring of a Trial under CESAR Responsibility

Background

Core ‘SOP 07: Data Flow, Monitoring, and Archiving’ was written under the assumption that a trial is sponsored by a pharmaceutical company that also takes the responsibility of monitoring according to Good Clinical Practice (GCP). The SOP 07a is a supplement to SOP 07 and describes the monitoring procedures in more detail. It is applicable if – The supplier of an investigational drug decides to contract the monitoring responsibility to CESAR, or if – CESAR decides to conduct a trial under its sole responsibility, including the sponsor responsibility of ensuring trial monitoring. The Chair of a CESAR working group in close cooperation with the Coordinating Investigator (CI) of a trial has to ensure that appropriately instructed, trained, and experienced persons, e.g. a clinical research associate or a research nurse with particular experience in the conduct of clinical trials according to GCP, are available to perform the monitoring activities defined in this SOP.

For each clinical trial site a trial initiation visit will be performed. The visit should be as close to the start as possible, preferably after receipt of the trial medications at the site but before first drug administration to trial subjects. Each clinical trial should be monitored during its active phase. Each visit to an investigator’s site will be recorded in a Monitoring Log form, indicating visitor, date, and purpose of the visit. The first monitoring visit should be performed soon after the investigator has enrolled (randomized) trial subjects (patients) and the data are available for review. Subsequent monitoring visits should be conducted at a regular interval. The frequency of monitoring visits may be adjusted depending on the nature of the trial, the enrollment rate, and the performance of the site. The closeout visit should be performed as soon as possible after the last subject (patient) has completed the trial procedures at that trial site. Activities before a Trial Initiation Visit

General Considerations and Procedures

All monitoring activities, including phone calls, must be documented in writing. A report template may be used as guide or checklist for items to be covered during a site visit. Where appropriate and required, a template may be adapted to the requirements of a particular study. Available report templates should be used for reporting of visits or other contacts. Relevant observations on items not covered by a generic report template should be reported as well, using an attachment, as applicable. Each report has to be submitted to a supervisor (e.g. the CI or his/her designee) for review. Investigators and relevant site personnel should be notified, in writing, about problems noted that require corrective action(s).

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Activities before a trial initiation visit will include the following: – Check which regulatory documents, if any, are outstanding. – Ensure that the following items have been shipped to the investigational site or that shipping arrangements are made for Investigational product(s) (‘trial medication’), Case Report Forms (CRFs), Investigator’s file, Additional trial-specific materials, if needed (e.g. laboratory supplies, specimen containers, special forms, equipment). – Contact the investigator and/or trial coordinator to schedule a mutually convenient time for the trial initia-

tion visit. Every effort should be made to include in the visit pertinent site personnel, like investigator, study coordinator/nurse, pharmacist, and sub-investigator(s) as applicable. – Review budget and proposed payment schedule (e.g. financial agreement or contract).

Activities during a Trial Initiation Visit

– Record the visit in the Monitoring Log. – The trial initiation visit will include the review of the following: Clinical trial protocol and trial conduct, CRFs, Investigator files, including essential documents to be retained, Investigation product(s) and other trial-specific material(s) if applicable, Regulatory compliance (including identification of source documentation, adverse event (AE) reporting procedures and authorized study personnel), Emergency code break if applicable, Frequency of monitoring visits. – As necessary, the following will be re-evaluated: Investigational site facilities, Facilities for storage of investigational product(s), Time frame for the trial in relation to subject selection criteria and availability, Any trial-related issues. – Retrieve outstanding trial and regulatory documents. Activities Following a Trial Initiation Visit

– Complete the Initiation Visit Report and forward it to the superior for review. – Write a follow-up letter to investigator (or study personnel): Providing requested information, Requesting any additional information and action items as necessary, Summarize the relevant findings of the trial initiation visit within the letter or an attached copy of the Initiation Visit Report, for inclusion into the investigator’s file. – Arrange for initial study payment (if appropriate). – File the Initiation Visit Report, regulatory and trial documents, and any correspondence. Activities before a Monitoring Visit

– Review the following items to ensure that appropriate actions are taken and outstanding documents are retrieved during the monitoring visit:

SOP 07a: Monitoring of a Trial under CESAR Responsibility

Previous monitoring visit reports or contacts for outstanding issues, Current enrolment status – reported serious adverse events (SAEs), Trial supplies provided so far, Data discrepancy forms (DDFs) or data query forms and working copies of CRFs, if available, Outstanding data issues, Outstanding laboratory issues, Outstanding regulatory documents, if any. – Contact the investigator and/or trial coordinator to schedule a mutually convenient time for the trial monitoring visit and to identify items that should be sorted out before the monitoring visit. Request for the visit, as applicable: Participation of pertinent site personnel (i.e. investigator and/or sub-investigator, study coordinator, nurse, and pharmacist), Availability of applicable documents for review (i.e. signed Informed Consent forms, CRFs, etc.), Outstanding documents or issues to be resolved during the monitoring or to be completed or collected for review and/or retrieval. – Gather any documents or materials necessary for the visit.

Activities during a Monitoring Visit

– Record the visit in the Monitoring Log. – Review/assess the following: Enrolment status, rate of enrolment, and drop-outs, CRFs and data query forms if applicable, Source documents and informed consent forms; AEs and SAEs, Investigational products (i.e. amount on stock, retest/expiry date, storage conditions, dispensing logs), Protocol compliance (e.g. selection criteria, dosing schedule, concomitant treatments, laboratory tests, and sampling), Regulatory compliance (e.g. investigator’s file up to date; continued acceptability of the site, personnel, and equipment; laboratory certificates and normal ranges up to date; SAE reporting up to date; Institutional Review Board (IRB) or Ethics Committee submissions and approval up to date), – Retrieve outstanding trial and regulatory documents, if any, as well as completed and verified CRFs according to individual trial requirements. – Discuss with the investigator and staff – if possible during the same visit – discrepancies and recommended corrective action(s).

Onkologie 2003; 26 (suppl 6): 38–40

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Activities Following a Monitoring Visit

– Complete the Monitoring Visit Report and forward it to the supervisor for review. – Write a follow-up letter to investigator (or study personnel): Summarize the relevant findings of the monitoring visit, Provide requested information, Request any additional information as necessary. – Arrange for interim payments, if appropriate. – Forward retrieved CRFs for data processing. – File the Monitoring Visit Report, retrieved regulatory and other trial documents, and any correspondence.

Activities before a Closeout Visit

– Review the following items to ensure that appropriate actions are taken and outstanding documents are retrieved during the closeout visit: Previous Monitoring Visit Reports or contacts for outstanding issues, Enrolment status, Reported SAEs, Investigational products provided, Data queries and working copies of CRFs, if available, Outstanding data issues, Outstanding laboratory issues, Outstanding regulatory documents, if any. – Discuss with appropriate trial medication owner’s personnel the requirements for shipment of investigational products and other materials, as applicable. – Contact the investigator and/or trial coordinator to schedule a mutually convenient time for the trial closeout visit.

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– Request remaining regulatory and other documents to be completed and made available for review/retrieval, including: Patient Identification List (for checking purpose only: compare with available CRFs), CRFs, Data discrepancy forms as far as available, Laboratory reports, Study medication records, Final information on SAEs. Activities during a Closeout Visit

– Record the visit in the Monitoring Log. – Review/assess the following: (To be defined specifically for each study). – Retrieve outstanding trial and regulatory documents, if any, as well as completed and verified CRFs. – Discuss with the investigator and the staff discrepancies and recommended corrective action(s). Activities Following a Closeout Visit

– Complete the Closeout Visit Report and forward it to the supervisor for review. – Write a follow-up letter to investigator(s)/study personnel outlining final disposition of the study to include information regarding retention of documents, expectation of audits or inspections by regulatory authorities and submission of a final report to the IRB and a copy provided to the CI. – Verify receipt of return drug shipment. – Forward retrieved CRFs for data processing. – Arrange for final payments related to the site. – File the Closeout Visit Report, retrieved regulatory and other trial documents, and any correspondence.

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

Onkologie 2003; 26 (suppl 6): 41–42

Version 01 Approval: June 28, 2001 Implementation: June 29, 2001

SOP 08: Reporting of Adverse Events

Definitions

An adverse event (AE) is any untoward medical occurrence in a patient or clinical investigation subject administered a pharmaceutical product and which does not necessarily have a causal relationship with this treatment. An AE can therefore be any unfavorable and unintended sign, including an abnormal laboratory or vital (ECG, etc.) finding, symptom or disease temporally associated with the use of a medicinal (investigational) product, whether or not considered being related to the medicinal (investigational) product. Serious adverse event (SAE) means any untoward medical occurrence that at any dose – Results in death, – Is life-threateningA, – Requires inpatient hospitalization or prolongation of existing hospitalization, – Results in persistent or significant disability or incapacity, – Is a congenital anomaly/birth defect, or – Is another medically important conditionB. A The term ‘life-threatening’ in the definition of ‘serious’ refers to an event in which the patient is at risk of death at the time of the event; it does not refer to an event which hypothetically might have caused death if it were more severe. B Medically important conditions that may not result in death, be life-threatening, or require hospitalization may be considered as SAE when, based upon appropriate medical judgement, they may jeopardize the patient or may require intervention to prevent one of the outcomes listed in the definition above. Examples of such events are intensive treatment in an emergency room or at home for allergic bronchospasm; blood dyscrasias or convulsions that do not result in hospitalization; or development of drug dependency or drug abuse [1].

Please note: The term ‘severe’ is often used to describe the intensity (severity) of an event (as in mild, moderate, or severe pain); the event itself may be of relatively minor medical significance (such as severe headache). This is not the same as ‘serious’, which is based on patient/event out-

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come or action criteria usually associated with events that pose a threat to patient’s life or vital functioning. Seriousness (not severity) serves as a guide for defining regulatory reporting obligations. The term ‘toxicity’ which, for historical reasons, is frequently used in clinical trials of anticancer agents, as a result of the experience with aggressive alkylating cytostatic agents, might suggest in everyday language use a causal relationship between the trial medication and the AE. Within the context of a clinical trial, however, it is essential to record all AEs and to then give a separate judgment as to the likelihood of a causal relationship (see below). It is particularly important in early clinical trials of a new drug substance (so called ‘new chemical entities’) to ensure an unbiased documentation and assessment of any observed AEs. The Investigator’s Brochure and/or the clinical trial protocol must specify those AEs that have been observed in preceding clinical trials and for which a causal relationship to the investigational drug has been assumed. Whenever possible, an autopsy should be performed after an AE with fatal outcome to determine the cause of death.

Documentation

All AEs including abnormal laboratory values must be documented and commented upon on the Case Report Forms (CRFs).

Immediate Reporting of Serious or Unexpected Adverse Events

SAEs must be reported by the investigator to the sponsor and Coordinating Investigator (CI) immediately by telephone or fax. Following this initial oral report, the investigator must promptly complete a Serious Adverse Event Reporting Form and fax it to the sponsor. The sponsor will then immediately inform the CI.

If required, the sponsor will also notify the relevant authorities. If AEs or SAEs might threaten the safety of the study subjects or impair the conduct of the study, the CI must inform the relevant Ethics Committees and the other participating centers. Details are given in the current trial protocol. The reporting requirements as outlined above and in particular timing guidelines must be specified in all trial protocols. A clinical trial protocol may, however, explicitly exclude from this immediate reporting obligation a particular SAE that is expected to frequently occur during a clinical trial.

Classification/Grading

For many years AEs were generally classified and graded according to the system suggested by the WHO. This system describes symptoms separately for the different organ systems affected and gives a grading of symptoms and of deviations of laboratory values from normal ranges according to intensity on a 5-point scale (grade 0 to grade 4). Recently, the so-called Common Toxicity Criteria (CTC) (see Appendix and ‘SOP 4: Data Collection Forms (Case Report Forms)’) that were developed by the National Cancer Institute (NCI) of the USA have increasingly been used in oncological trials, e.g. in EORTC studies. The CTC provide a more differentiated description of symptoms than the WHO system. Because of these advantages, it is now commonly recommended to use the CTC instead of the WHO classification. ‘Variants’ of these two classifications exist and are also used in clinical trials. For these reasons, it is absolutely mandatory to exactly specify the system to be used and append the applicable version to the trial protocol. As a rule, the CTC scale is used in studies performed by CESAR. For symptoms not included in the CTC scale, it is recommended to use the following grading: – Mild: occurrence of symptoms which are perceived but do not involve impairment of the affected subject; – Moderate: occurrence of symptoms that interfere with normal daily activity; – Severe: occurrence of symptoms that impair work or normal daily activity; – Life-threatening: occurrence of symptoms that may directly lead to death. Note: There is an unfortunate coincidence in terminology between the general description of grade 4 intensity in the CTC scale and one criterion to classify an AE as serious: ‘life-threatening’. An AE that is assigned grade 4 according to CTC definition must not be reported immediately if the investigator decides that this event does not meet any of the ICH criteria for a SAE (see above for definition). If an investigator is in doubt about the applicable reporting

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obligations he should consult with the sponsor’s study monitor. Because of the complexity of the CTC, it is recommended to use structured data sheets that are suitable for ‘bedside’ recording of observations to ensure complete assessment and consistent documentation at baseline and follow-up evaluations. The appendix to ‘SOP 04: Data Collection Forms (Case Report Forms)’ provides an example for such a form.

Evaluation of a Relationship

The criteria to be used for evaluating a possible causal relationship between an AE and the investigational preparation have to be specified in the trial protocol (see ‘SOP 03: Preparation and Structure of Trial Protocols’). This specification can be based on the following scale adapted from Karch and Lasagna [2]: Definite – Temporal relationship to the administration of the trial drug and – Course following a known reaction pattern and – Improvement of the symptoms after dose reduction or discontinuation of the drug and – Recurrence of the symptoms after re-administration of the drug; Probable – Temporal relationship to the administration of the drug and – At least one of the following criteria is met: Course following a known reaction pattern, Improvement of the symptoms after dose reduction, The patient’s current health status provides no other explanation for the event; Possible – Temporal relationship to the administration of the drug and – At least one of the following criteria is met: Course following a known reaction pattern, The event may also have been caused by other factors; Unlikely – No temporal relationship to the administration of the drug or – Other factors are more likely to have caused the event; Unclear – Available information is insufficient for evaluation.

References 1 Federal Register § 312.32 IND safety reports. 2 Karch FE, Lasagna L: Adverse drug reactions – a critical review. JAMA 1975;234:1236–1241.

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

Onkologie 2003; 26 (suppl 6): 43–47

Version 01 Approval: June 28, 2001 Implementation: June 29, 2001

SOP 09: Statistical Design and Analysis

Background

Statistical design and analysis of a CESAR study on the efficacy and/or safety of an anticancer drug should comply with ICC-GCP guidelines on statistical principles for clinical trials. Therefore, when not stated otherwise explicitly, the ICH-E9 guideline [1] and its rules will be applied to a CESAR study. The subsequent paragraphs will give specific guidance to special issues of CESAR trials. The respective ICH-E9 guideline will be cited below where applicable in its issue from February 1998. The biometric center (BC) of CESAR is responsible for contributing biostatistical expertise during the planning and the analysis stage of a CESAR study. Its mission is to support and to promote the scientific advancement of anticancer drug research. The tasks of the BC are guided by the primary objective(s) of a study and the goal of accomplishing a successful clinical trial. Therefore, the BC contributes especially to – The statistical design of the study and the determination of the minimal number of patients required, – The standardized documentation and the recording of the study data in accordance with the trial protocol, – The computerized storage, processing, and statistical analysis of the data, – The interpretation and reporting of the trial results in cooperation with the sponsor, the monitor, the Principal Investigator, and the clinical investigators. Specifically the BC is committed – For phase I studies to the Determination of appropriate dose ranges and identification of the maximal tolerable dose (MTD), Drug safety analysis; – For phase II studies to the Determination of the anticancer activity of the trial drug in terms of objective (measurable) criteria, Drug safety analysis;

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– For phase III studies to the Determination of a treatment effect in comparative randomized clinical trials on anti-cancer drug efficacy, Drug safety analysis. Statistical Issues of the Trial Protocol

The BC shall assume responsibility for the statistical sections of the trial protocol and play an active part in the protocol’s formulation or provide the expertise necessary for its completion. The tasks involve at least the following items: – Ensuring the adequate definition of the endpoint(s) and the clinically important effects as a prerequisite for establishing the statistical design, – Specification of statistical hypotheses and error probabilities in phase II–III studies, – Mode of randomization and blinding as well as conditions for breaking the code, – Calculation of the minimal number of patients to be enrolled in the study, – Rule(s) for stopping patient accrual, – Statistical analysis plan. The BC will review the trial protocol and the trial’s Case Report Forms (CRFs) with regard to at least the following aspects: – Statistical evaluability of the study endpoints such as survival time, time to progression, tumor response rate, duration of remission or incidence of adverse event, – Definition of the study population (inclusion/exclusion criteria) and analysis sets (e.g. for the intent-to-treat analysis and the per protocol analysis), – CRFs and the logistics of the data flow, – Patient evaluability criteria. Statistical Study Design

Phase I Study: The trial protocol will specify a sequential dose escalation scheme (e.g. a choice of doses according to

the modified Fibonacci scheme) and implement a stopping rule for each dose, e.g. the traditional escalation rule or a modified continual reassessment rule [2, 3]. Phase II Study: The selection of a treatment plan must allow for early termination of a regimen that turns out to be ineffective, e.g., implementing a plan from the class of the optimal two-stage designs. The plan should control the probability of inadvertently rejecting an effective agent/regimen and the probability of falsely accepting an ineffective agent [4]. Phase III Study: The trial protocol has to specify the type of statistical hypotheses to be tested for the efficacy statement (e.g. superiority, equivalence, noninferiority, [1, section 3.3]) and the statistical error probabilities which are the error of the 1st kind (a-error, significance level) and the error of the 2nd kind (b-error) which defines the power of the trial. If more than one endpoint is considered as primary (e.g. survival and toxicity in combination), specific designs have to be implemented to prevent erroneous results arising from multiple testing. Were applicable the design should identify primary and secondary endpoints [1, section 2.2.2]. Patient Registration and Control of the Study

Phase I Study: The BC will keep a list of the patients entered on the study. This list contains at least the following information: – Study identification, – Institution/investigator identification, – Patient identification by initials, date of birth, and running number, – Date of registration at sponsor’s institution or at the BC as defined in the study protocol, – Target dose on admission. Phase II Study: The BC will keep a list of the patients entered on the study, in particular to ensure that the statistical rule for stopping patient accrual is adhered to. This list uses the patient data submitted to the BC for the eligibility check (see ‘SOP 7: Data Flow, Monitoring, and Archiving’) and contains at least the following information: – Study identification, – Institution/investigator identification, – Patient identification by initials, date of birth, and running number, – Date of registration at sponsor’s institution. The BC will compare the number of recruited cases with the target sample size of the study at regular intervals. Once the total number of patients or a relevant proportion of the target number for the continuation of the study have been enrolled, the BC will notify the sponsor and the Coordinating Investigator (CI). The BC, the sponsor, and the CI will then jointly decide on the continuation of patient accrual.

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When a two-stage design is used and the initial accrual goal of evaluable patients has been met, the BC will instruct the CI and the sponsor to promptly determine the result of the relevant study endpoint (typically tumor response) for each evaluable subject. This requires temporary closure of patient accrual and will be decided on in concert with the sponsor and the CI. When a randomized phase I/II study is performed, the BC will be responsible for the randomization of patients to the different treatment arms, unless otherwise specified in the study protocol. Phase III Study: The BC will keep a list of the patients entered to ensure that the statistical rule for stopping patient accrual is adhered to. This list uses the patient data submitted to the BC for the eligibility check (see ‘SOP 7: Data Flow, Monitoring, and Archiving’) and contains at least the following information: – Study identification, – Institution/investigator identification, – Patient identification by initials, date of birth, and running number, – Date of registration at sponsor’s institution. The BC will compare the number of evaluable cases with the target sample size of the study at regular intervals for check-up with the interim analysis plan of the trial and will notify the CI and the sponsor when decisions have to be made. The BC is responsible for the randomization of patients into the different treatment arms (randomization procedure, randomization list, recording of randomization and information of CI and the sponsor). The rules for implementing and performing the randomization will be those of ICH E9, 2.3.2 [1]. Unless otherwise specified in the study protocol the BC will be responsible for ensuring blinding [see also 1, section 2.3.1]. Intergroup Studies: In intergroup studies, the BC of CESAR will be involved in the biostatistical analysis at least as a reviewer. Details have to be agreed on by the sponsor and the BC and must be laid down in writing. Statistical Analysis

Statistical Documentation of Study Data All data, findings, and other observations to be recorded as stipulated by the study protocol will be computerized. Data entry into the computer is based on the CRFs and, where appropriate, its attachments. As a rule, all study data reported on the CRFs will be included in the statistical analysis. Comments will be entered as such only if they are explicitly requested by the study protocol. The presence/absence of comments in free format on individual CRFs will be identified by a separate entry. The data will be handled by the BC according to procedures which comply with ICH-GCP guidelines, including quality assurance,

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

e.g. by implementation of a double entry system. Details deviating from the procedures specified below have to be documented in study-specific procedures. Computer Entry System and Data Management The BC uses a computer entry system and data management software the use, function, description, and documentation of which are documented in detail in the BC’s own SOP. Quality Assurance All data are entered from the original (firstst page/white page) of the CRFs (see ‘SOP 7: Data Flow, Monitoring, and Archiving’). Corrections and Missing Data: If a form contains contradictory or unclear entries, it will be returned to the responsible investigator via the study monitor while a copy is kept on file at the BC. Query handling follows the procedures defined in ‘SOP 7: Data Flow, Monitoring, and Archiving’. The guidelines for correcting computerized data are specified in the BC’s SOP. After each updating of the database, the BC makes a list of CRFs that are still missing or have not been submitted in time and forwards it to the monitor of the sponsor. Laboratory Values: As a rule, laboratory values are entered using the units given on the CRFs. For each laboratory of an institution which performs laboratory tests for a study patient, the form ‘Validated Laboratory Normal Ranges’ has to be completed, sent to the BC and to the monitor of the sponsor, and kept in file at the BC. If other units than those required on the CRFs are used, that different unit has to be given on the CRFs and on ‘Validated Laboratory Normal Ranges’ together with the conversion factor used. Unless otherwise specified, the monitor of sponsor is responsible for the correct conversion and the correct entry on the CRF in the units prespecified by the CRF. If laboratory tests for an individual patient are performed by different laboratories, the name of the laboratory has to be given for each laboratory value recorded on the CRF.

phase III study. The Full Analysis Set and the Per Protocol Set of patients is defined within this population of patients eligible for the study according to the ICH-GCP [1, section 5.2]. Patient Evaluability This section defines guidelines for the assessment of evaluability of study patients for biostatistical analysis and aims at implementing measures to reduce selection bias. A distinction is made between complete and partial evaluability (e.g. patient not evaluable for response but evaluable for safety). – As a rule, the data of each patient eligible for a study (see ‘Patient Eligibility’) are checked for evaluability on the basis of the criteria specified in the study protocol. – The evaluability check will typically take into account the following elements of the study: Inclusion/exclusion criteria, Time schedule of patient presentation at the institution, data recording and measurement, Compliance with the treatment plan, Completeness and quality of the documentation, Concomitant disease(s), Concomitant treatment(s). – The decision to fully or partly exclude a patient from an analysis will be made by the BC in concert with the sponsor and the CI. – The reasons for complete or partial exclusion from analysis must be specified in a written report on a case-bycase basis, which should be included in the Biometrical Report. – Patient data that are excluded from statistical analysis shall be listed separately in the Biometrical Report. – Evaluability for response to treatment in phase II studies. If not specified otherwise in the study protocol all patients who were eligible for a phase II study are evaluable for response if they received the trial drug for at least 1 cycle or at least for 4 weeks (treatment limit) and if the documentation is adequate for the assessment of response. – Evaluability for safety. All patients who were eligible for a study are evaluable for safety if they received the trial drug at least once and if the documentation is adequate. – The statistical analysis of a comparative trial, in particular a phase III trial, has to include always a confirmative statistical analysis for intent-to-treat, e.g. by an evaluation of the full analysis set according to ICH-GCP [1, section 5.2].

Patient Eligibility All patients who are registered by the clinical investigators to be included into the study are considered as of being recruited (enrolled) for the study. This is documented by the application with the monitor of the sponsor or by the application with the BC (e.g. in the case of the request for a randomization in a phase III trial). Special application forms should be used for patient registration. All patients who have been successfully checked for the correctness of the in/exclusion criteria and who have been confirmed by the monitor of the sponsor or the BC as of being included into the study are eligible for the study. These patients represent the intent-to-treat population of a phase II or

Statistical Analysis Statistical analysis is performed according to the statistical analysis plan specified in the study protocol. Some impor-

SOP 09: Statistical Design and Analysis

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tant aspects regarding the analysis of phase I–III studies are regulated in the subsequent sections. Survival: Overall survival will be evaluated statistically by applying the methods for censored survival times. This includes the descriptive analysis using Kaplan-Meier estimates of the survival curve, the log-rank test for the comparisons of survival curves, and the use of the Cox proportional hazard regression model for adjusting the treatment comparison for the effect of confounding prognostic factors. Risk ratios will be calculated with their 95% confidence intervals on the basis of the results of the Cox regression and where it is possible also based on the numbers of observed (O) and expected (E) events (for the basic methodology see [5]). For testing a noninferiority alternative of survival the method described by Wellek [6] is used. Response: The endpoint tumor response is assessed through the rate of objective responses. It is defined as the quotient of the number of patients evaluated as complete or partial remissions (CR or PR) and the number of patients evaluable for response. The variability of the response rate is evaluated by calculating the 95% confidence interval. For study populations of up to n ¼ 100 cases, this calculation uses the exact limits from Geigy’s tables [7]. Eligible patients lost during the first 4 weeks or the first treatment cycle are listed separately in the response tables. The reasons for the loss of a patient or discontinuation of treatment in individual cases must be specified. At least the following cases shall be distinguished: – Early death within first cycle / 4 weeks, – Early progression within first cycle / 4 weeks, – Lost to follow-up, – Lack of evaluation/missing documentation, – Treatment refused by patient, – Treatment discontinued by investigator. In addition, an intent-to-treat response rate is calculated, which includes all eligible patients. Unless otherwise stated, the response evaluation is based on the RECIST and/or the WHO criteria and the assessment of the tumor lesions of a patient is within a prespecified window of treatment cycles designated for response evaluation (e.g. from the end of treatment cycle 2 until the end of treatment cycle 4). Further analyses, e.g. response including the status of ‘persistent status quo’ or ‘no change’ [see 8]; ‘SOP 3: Preparation and Structure of Trial Protocols’) or so-called ‘best response’ based on a maximum interval of individual patient follow-up, are considered as secondary response evaluation, unless specified differently in the study protocol. Safety: All eligible patients are evaluable for safety if they have received the investigational drug at least once and documentation is adequate. For analysis of an individual safety parameter, an initial value prior to the start of treatment must be available for comparison.

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Cases excluded from safety analysis are reported separately with reasons for their exclusion. Partial exclusion of patients is permissible (e.g. exclusion from the analysis of single safety parameters) without affecting that patient’s general evaluabilty. [see also 1, section 6.1–6.5]. Interim Reports: An interim analysis is any analysis intended to compare treatment arms with respect to efficacy or safety at any time prior to formal completion of a trial. Because the number, methods and consequences of these comparisons affect the interpretation of the trial, all interim analyses should be carefully planned in advance and described in the protocol. Not every oncological trial requires interim analyses or implementation of group-sequential design. A clinical trial on the efficacy of a treatment assessed through overall survival as endpoint may recruit the majority of patients much faster than the data are available to perform an interim analysis with a proportion of the total population planned for this study (recruitment overruns the interim analysis). When an interim analysis is planned with the intention of deciding whether or not to terminate a trial, this is usually accomplished by the use of a group-sequential design which employs statistical monitoring schemes [1, section 4.5]. Among others, the following measures should be taken: – The protocol should describe the schedule of interim analyses or, at least, the considerations which will govern its generation. – The execution of an interim analysis should be a completely confidential process, at least, with respect to the endpoint(s) or any other endpoint which could affect the results of the primary endpoint(s). Interim reports regarding the primary endpoint(s) of all open studies are presented at the regular meetings of Phase I, Phase II or Phase III Working Groups of CESAR Such reports contain the following information: – Administrative data on patient accrual rate, patients off study, eligibility, and evaluability, – Summary of patient characteristics, – Statement on the status of a study without giving results on the endpoints, – Summary of the most important safety parameters from the CTC checklist. A summary statement on study endpoints (e.g. overall survival, time to progression, response rate) is only allowed if this statement is ensured not to interfere with the ongoing patient accrual and to imply any bias to the study result. It is not allowed to unblind the results of any study endpoints in a randomized phase III trial. Final Analysis: The final analysis is done on the basis of the complete documentation of all cases and serves as a basis for the study report and for the publication of the results. It will be done in accordance with the statistical analysis plan outlined in the trial protocol. The analysis includes at least the following variables:

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

– Patient characteristics Age, Sex, Performance status, Stage of the disease, Localization of metastases, Prior treatment, Concomitant disease(s); – Treatment-related data Duration of treatment, Cumulative dose, Reason for discontinuation of treatment, Dose intensity; – Study endpoints Survival, Response, Toxicity (according to CTC criteria, including baseline values and extreme values).

Biometric Report / Statistical Report

The final analysis (cf. ‘Statistical Analysis’) serves as a basis for the preparation of the Biometric Report/Statistical Report of the results of the statistical analyses performed by the BC. This report will be sent to the sponsor and the CI. The report provides a detailed description of the results of the study including their biostatistical interpretation. The guidelines for writing the Statistical Report are defined in the data center’s SOP ‘Statistical Report’. The biometric report/statistical report gives a detailed description of the study population and will comply with the CONSORT Statement [9]. It comprises at least the following items: – Registered patients, – Eligible patients, – Protocol violations including a detailed description, – Evaluable cases, – Patients evaluable for survival times, – Patients evaluable for response, – Patients evaluable for safety. The biometric report/statistical report covers at least the following areas: – Patient characteristics, – Results of treatment, – Safety. Part of the results can be summarized in tables. The report must be sent to the CI within 12 weeks of receipt of the last patient documentation.

SOP 09: Statistical Design and Analysis

Documentation and Archiving of Study Data

Data Listing: The data listing is a reproduction of the CRFs. As a rule, a full listing is compiled after completion of the (final) analyses for a given study. This listing will be made available to the CI and the sponsor. Data Exchange: All exchange of data within the BC and between the BC and the sponsor will be validated. The procedures are defined in the SOP ‘Data Transfer between BC and Sponsor’ established by the BC. Confidentiality, Security and Archiving of Data: The study data are saved on appropriate media (e.g. on a file server with a routinely implemented data security backup) on a daily basis after completion of data entry. Backups of the data are made at regular intervals, at least every 4 weeks. Data used for any interim and final analysis will be stored on a diskette or a CD. Protection of the data from unauthorized users is ensured by a password. The backup storage files are kept in the study files together with the CRFs, protected from any unauthorized access. Hardware Configuration and Software Used at the BC: Electronic data processing for analyses conducted by the BC of CESAR is performed in the Biostatistics Unit at the Deutsches Krebsforschungszentrum (DKFZ, German Cancer Research Center). The computer systems available for data management and analysis comprise PCs in NOVELL net of the data processing center of the DKFZ and the decentralized networks of the Biostatistics Unit (SUN Cluster). As a rule, statistical analyses are performed using SAS [9] or Splus in its most recent version. Additional statistical tasks can be done with validated software of the Biostatistics Unit of the DKFZ. Detailed information on the currently used computer systems, the versions of SAS and additional software is provided in the BC’s SOP, which also defines the validation of nonstandard software. References 1 ICH E9: Note for Guidance on Statistical Principles for Clinical Trials, CPMP/ICH/363/96, 5 February 1998. 2 Edler L: Overview of phase I trials; in Crowley J (ed): Handbook of Statistics in Clinical Oncology. New York, Marcel Dekker, 2001,pp 1–34. 3 Hanauske AR, Edler L: New clinical trial designs for phase I studies in hematology and oncology. Principles and practice of the continual reassessment model. Onkologie 1998;19:404–409. 4 Edler L: Statistical requirements of phase I studies. Onkologie 1990;13: 90–95. 5 Kalbfleisch JD, Prentice RA: Statistical Analysis of Failure Time Data. New York, Wiley, 1980. 6 Wellek S: A log-rank test for equivalence of two survivor functions. Biometrics 1993;49:877–881. 7 Wissenschaftliche Tabellen Geigy, Teilband Statistik, 8. Auflage. Basel, Geigy, 1980. 8 Edler L, Flechtner H: Remission in Phase-II und Phase-III Studien: Kriterien und Voraussetzungen. Onkologie 1987;10:330–339. 9 Begg C, Cho M, Eastwood S, et al: Improving the quality of reporting of randomized controlled trials. The Consort Statement. JAMA 1996;276:637–639. 10 SAS Institute Inc: SAS Procedures Guide, Version 6, 3rd ed. Cary, SAS Institute Inc., 1990.

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SOP 10: Study Report and Publication

Study Report

It is the responsibility of the sponsor of a clinical study that the results of that study are being analyzed and reported. Preferably, an integrated study report should be prepared that complies with the ICH guideline E3: Structure and Contents of a Study Report. The discussion and medical conclusions of the study report have to be based on the analyses of the data as presented in the statistical section of the report or in a separate Statistical Report (see ‘SOP 09: Statistical Design and Analysis’). The report must discuss the quality assurance measures used (see ‘SOP 11: Quality Assurance’) and the implications of the results for the further development of the investigational drug(s) and for the disease-related treatment options. The manuscript for publication must be prepared on the basis of the study report.

Responsibility for Publication

The Coordinating Investigator (CI) is responsible for the publication of the study results, according to the bylaws (XIV). In particular, it is his/her job to select the authors for a publication, to determine the order of authors, to designate an author to prepare the draft, and to choose the journal to which the manuscript shall be submitted. In case of disagreement, he/she should try to find a consensus but finally the results determined in the bylaws have to be followed.

Authorship for Publications

Every publication (abstracts as well as full papers) must include a statement to the effect that the study was performed by CESAR. In addition, all investigators and the sponsor should be acknowledged in the appropriate location of a full paper.

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All publications on clinical studies that were conducted under the auspices of CESAR have to comply with the statutes of CESAR. In brief, the following rules will apply: In these publications the name CESAR has to be mentioned in capital letters in the title and/or under the authorship. Results deriving from collaborative internal work of CESAR has first to be published as CESAR publication as long as this has not been otherwise agreed upon, e.g. with the sponsor. No such information may be provided outside of CESAR without written acceptance by the president of CESAR, the vice-president of CESAR, or the chairperson(s) of the working group, the CI, and the sponsor unless otherwise agreed upon in writing. Each of these individuals/parties has to have a period of 30 days to react. Thereafter, in case of lack of response, the application is approved. The CI has to consider the following individuals as authors for a publication: The CI and the investigators who have contributed significantly to the study by entering evaluable patients. In case of phase I studies the CI will be the first author only under the condition that his patient allocation to the study was equivalent to the mean contribution of all study participants. Individuals who have performed and evaluated pharmacokinetic investigations have to be considered equivalently. In addition to these, the chairperson(s) of the respective working group, the biostatistician, the data manager and last but not least the president or vice-president of CESAR will be considered as coauthors. Authorship for phase II and phase III studies comprises the CI as first author under the condition that his patient allocation to the study was equivalent to the mean contribution of all study participants. In addition, coauthorship will be guaranteed to investigators of those 5 institutions with the main contribution – in order of their patient recruitment – and double coauthorship to investigators of institutions entering 20% of all patients of a study. Further persons to be mentioned as coauthors are the same as detailed above for phase I procedure.

The sponsor will be coauthor only upon separate agreement. Persons who have additionally contributed to the results of a study, not indicated in detail above will be mentioned under ‘Acknowledgement’. In addition to these, other individuals who have made substantial contributions to the study may be chosen as coauthors. An investigator who has been excluded from the study for any of the reasons specified in ‘SOP 06: Selecting the Participating Centers and Activation of a Trial’ will not be listed as coauthor.

Publication of Data from an Ongoing Study

As stipulated above, the policy is that any publication is written on the basis of a formal report that has passed appropriate quality control procedures. For this reason, interim results may only be published if these are backed up by an interim analysis that has been performed or approved by the data center of CESAR. As a rule, abstracts written before an official report has been prepared should only present the study design, the current status of patient accrual and the expected dates of closure of patient accrual and presentation of the final report. No interim results on a primary endpoint should be published from an ongoing study.

Time Schedule

Completion of the study report in the shortest possible time should be attempted to ensure that decisions on further studies can be based on valid analyses and conclusions on preceding studies. Usually, the signed study report should be available within 2 months after receipt of the statistical report or the respective report section of the integrated report. A longer period may be acceptable under certain circumstances, for example, if completion of test drug or metabolite assays are time-limiting for the completion of pharmacokinetic analyses. A first manuscript draft for publication is to be written not later than 3 months after receipt of the statistical report. In case the CI does not respect these time lines, the chairperson(s) of the leading working group will determine an alternative principal author. The coauthors (including the sponsor’s representative) must submit their written approval of the manuscript or request for modification(s) to the principal author within 4 weeks after receipt of the draft. In case they do not respond, their tacit agreement is assumed.

SOP 10: Study Report and Publication

Publication of Data from Single Institutions

An investigator who wishes to separately present the data that his/her institution has contributed to a study of CESAR may do so only after a joint publication of the results by the study group is available. Nevertheless, also for doing so, a written acceptance by the president of CESAR and the vice-president of CESAR must be given. In case of persisting refusal of the acceptance of several publications by the president(s) of CESAR, the general assembly may be approached by the applicants for a final decision.

Press Release and Information to the Public

Information about study results at the request of the press or the public may only be given by the CI after consultation of the sponsor and the chairperson(s) of the working group or the president(s) of CESAR.

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SOP 11: Quality Assurance

Background/Objectives

It is the main objective of CESAR to improve the treatment of cancer patients by conducting studies required for the approval of new anticancer drugs. It is therefore important that all observations and findings are properly documented for verification. This supports the reliability of the data and ensures that the conclusions presented are correctly derived from the raw data. The quality assurance measures required by CESAR, the pharmaceutical industry and the national associations for medical oncology jointly form a comprehensive quality assurance program.

Monitoring

Studies are monitored by the sponsor’s monitors in accordance with the guidelines defined in the sponsor’s own SOPs. The procedure is to be specified in detail in the study protocol (see ‘SOP 03: Preparation and Structure of Trial Protocols’). This applies also to the situation of CESAR-sponsored studies.

Quality Assurance by the Sponsor/Inspection by Relevant Authorities

The quality assurance department of a sponsor’s institution or a corresponding auditor that has been contracted by the sponsor is entitled to conduct audits at the participating investigators’ institutions and, if appropriate, at the data center (if study data are analyzed at the center). A statement to this effect must be included in the study protocol (see ‘SOP 03: Preparation and Structure of Trial Protocols’). Audits follow the procedures specified in the sponsor’s SOPs. Drug regulatory authorities to whom the data of a study have been submitted, as well as the authorities in charge of the monitoring of clinical studies in the respective territory of study conduct are entitled to inspect

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the investigational sites as well as the original records of the study. System Audits of CESAR

Auditors The Project Review Committee (PRC)/Quality Assurance Committee (QUAC) appoints 2 auditors who may be but must not necessarily be members of the respective working group. No person may serve as auditor for an audit at his own institution. Conduct of a System Audit The auditors will arrange a date for the audit at a member’s institution 4 weeks in advance. The system uudit comprises the following items (see also ‘SOP 1: Clinical Investigations in CESAR’): – Local Ethics Committee; – adequate staff for/with Patient care by physicians and other authorized (e.g. nursing) personnel, A local representative (medical doctor) available, Performing specialist examinations (e.g. radiography), Documentation, Drug accountability (storage, distribution and return of trial medication); – Adequate facilities for performing clinical studies with Access to hospital beds for inpatient observation, Direct access to an intensive care unit, Resuscitation equipment, Quality assurance implemented for diagnostic procedures (e.g., participation in quality assurance programs); – Adequate facilities for keeping of the study materials (study files/trial medication) in a secure, limited-access area; – Adequate facilities for the archiving of the study documentation after completion of a study;

– 100% source data verification for at least 5 study patients; – Protocol violations (patients not eligible or not evaluable for investigator-related reasons); – Timely reporting of serious adverse events or other adverse events with an obligation for expedited reporting; – Evaluation and verification of a list of patients entered on phase I/II studies (by indications).

After closure of a study and prior to closure of the data base for statistical analysis (see ‘SOP 9: Statistical Design and Analysis’) a response evaluation meeting will be held. At this meeting of investigators, the case reports of all patients

entered on the study will be presented. The documented findings of imaging procedures such as conventional radiography, computed tomography, ultrasound, and magnetic resonance imaging will be verified by re-evaluating the corresponding source documentation (i.e. x-ray films, etc.). Evaluability and tumor response will be decided on in consensus with stringent interpretation of the study protocol and the criteria specified therein. If such consensus decision deviates from the primary assessment of the investigator, the corresponding entry in the Case Report Form (CRF) will be corrected accordingly, either by correcting the original CRF or by writing a notice of change that will be attached to the CRF. Special care has to be taken that a copy of the corrected CRF or the notice of change is included in the documentation to be retained by the investigator and that the data base of the study is corrected accordingly. In addition, the meeting shall discuss all aspects of the study that are relevant for the quality of the results and data analysis. The results of this meeting will be considered in the statistical analyses, the final report, and publications of the study. Any disagreement about the evaluation of study data among the quality assurance representatives of the sponsor, and CESAR will be resolved by consensus at the study evaluation meeting. Such meetings of investigators will be convened by the Coordinating Investigator (CI). Attendance is mandatory for an authorized investigator from each center involved in the study. In addition, the CI may invite experts such as radiologists or other oncologists.

SOP 11: Quality Assurance

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Support of the Quality Assurance Committee by the Data Center The data center will issue a quarterly status report on CESAR’s studies. This report will include incremental information on recruitment rates as well as information regarding items 7–9 (‘Conduct of a System Audit’) for all participating institutions. The members of the QUAC will routinely receive this report as a monitoring tool and as an aid for planning and conducting an audit. Reports After a system audit, the auditors will send a report to the audited member, the Chair of the working group and the data center. Study Evaluation Meetings/Response Evaluation Meetings

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SOP 12: Validation of Bioanalytical Methods

Background and Objectives

A bioanalytical method is a set of procedures involved in the collection, processing, storage, and analysis of a biological matrix for a chemical compound. The availability of selective and sensitive bioanalytical methods is a prerequisite for the generation of reliable data on pharmacokinetics, bioavailability, and bioequivalence of drugs. These methods should allow the quantification of drugs and their metabolites in biological matrices, e.g. plasma, urine, and cerebrospinal fluid, and must be validated with respect to their reliability for the intended use. Bioanalytical method validation comprises all criteria determining data quality, such as selectivity, accuracy, precision, recovery, sensitivity, and stability. This SOP is applicable for the analysis of preclinical as well as clinical samples. A specific, unique chemical moiety that would be found in a biological matrix is referred to as analyte.

Types of Method Validation

Full Validation A full validation is required – If the method is developed and implemented for the first time, – If a new drug entity is analyzed, or – If metabolites are added to an existing assay for quantification. Partial Validation A partial validation can be performed if validated bioanalytical methods have been modified. It can range from the determination of a within-day accuracy and precision to a nearly full validation. Typical situations for a partial validation are – Method transfers between laboratories and analysts, – Instrument and/or software platform changes, – Changes in species within the same matrix, – Changes in matrix within the same species,

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– Change in analytical methodology, and – Change in sample processing procedures. Cross Validation In a cross validation two bioanalytical methods for the same analyte are compared. Cross validations are necessary when two or more bioanalytical methods are used to generate data within the same study. They should be conducted with spiked matrix standards and subject samples. A cross validation should be also considered when – Sample analyses within a single study are conducted in more than one laboratory or – Data generated using different analytical techniques in different studies are included in a regulatory submission.

Validation Parameters

In this section the fundamental parameters for the validation of a chemical assay, e.g. gas chromatography (GC), high-performance liquid chromatography (HPLC) or capillary electrophoresis (CE), are described. For immunoassays special considerations have to be taken into account (see below ‘Special Considerations for Immunoassays’). Selectivity Selectivity is the ability of an analytical method to differentiate and quantify in a sample the analyte in the presence of other components. For selectivity, analyses of blank samples of the respective biological matrix should be obtained from at least 6 sources. Each blank sample should be tested for interference which could originate from endogenous matrix components, metabolites, decomposition products and concomitant medication. Accuracy The accuracy of an analytical method describes the closeness of mean test results obtained by the method to the nominal value (concentration) of the analyte. Accuracy is

determined by replicate analysis of samples containing known amounts of analyte. Accuracy should be measured using a minimum of 3 concentrations and 5 determinations per concentration. The mean value should be within 15% of the nominal value except at lower limit of quantification (LLOQ, see below), where it should not deviate by more than 20%. The deviation of the mean from the nominal value (relative error) serves as the measure of accuracy. Precision The precision of an analytical method describes the closeness of individual measures of an analyte when the procedure is applied repeatedly to multiple aliquots of a single homogeneous volume of biological matrix. Precision should be measured using a minimum of 3 concentrations and 5 determinations per concentration. The imprecision determined as coefficient of variation (CV) at each concentration level should not exceed 15% except for the LLOQ (see below), where it should not exceed 20%. Precision is further subdivided into – Within-day precision, which assesses precision during a single analytical run, and – Between-day precision, which measures precision with time, and may involve different analysts, equipment, reagents, and laboratories. Recovery The recovery of an analyte is the detector response obtained from an amount of the analyte added to and extracted from the biological matrix, compared to the detector response obtained for the nominal concentration of the pure authentic standard. Recovery experiments should be performed by comparing the analytical results for extracted samples at three concentrations with unextracted standards that represent 100% recovery. Recovery of the analyte need not be 100% but the extent of recovery of an analyte and an internal standard should be consistent, precise, and reproducible. Calibration Curve The relationship between the experimental response value and known concentrations of the analyte is referred to as calibration curve. A calibration curve should be prepared in the same biological matrix as the samples in the intended study by spiking the matrix with known concentrations of the analyte. In case that there is not enough blank sample availiable, e.g. from cerebrospinal fluid, an appropriate calibration matrix should be selected, e.g. 0.9% NaCl, and the response obtained from both matrices should be compared. Concentration of standards should be chosen on the basis of the concentration range expected in a particular study. A calibration curve should consist of a blank sample (matrix sample processed without internal standard), a zero

SOP 12: Validation of Bioanalytical Methods

sample (matrix sample with internal standard), and 5–8 non-zero samples covering the expected range, including the LLOQ. Calibration curve fitting should be performed by applying the simplest model that adequately describes the concentration-response relationship using appropriate weighting and statistical tests for goodness-of-fit. The following conditions should be met in developing a calibration curve: – 15% deviation of standards other than LLOQ from nominal concentration and – 20% deviation of the LLOQ from nominal concentrations. At least 4 out of 6 non-zero standards should meet the above criteria, including the LLOQ and the calibration standard at the highest concentration. Lower Limit of Quantification The LLOQ is the lowest concentration of an analyte that can be measured with acceptable accuracy and precision. The lowest standard on the calibration curve should be accepted as LLOQ if the following conditions are met: – The analyte response should be at least 5 times the response compared to blank response. – The analyte response should be reproducible with an imprecision of maximum 20% and an accuracy of 80–120%. Stability The stability of the analyte in the biological matrix at intended storage temperatures should be established. Moreover, the stability should be investigated at ambient temperature over a time period that encompasses the duration of typical sample preparation, sample handling, and analytical run time. The procedure should also include an evaluation of analyte stability in stock solution for at least 6 h. The influence of freeze/thaw cycles should be studied – at least 3 cycles at 2 concentrations in triplicate. All stability determinations should use a set of samples prepared from a freshly made stock solution of the analyte in the appropriate blank, interference-free biological matrix.

Validation Report

A specific, detailed description of the bioanalytical method, the validation experiments and the validation results will be written in form of a report by the laboratory responsible for drug analysis. The validation report covers all validation parameters described in ‘Validation Parameters’.

Routine Drug Analysis

This section describes the validation parameters that should be evaluated during routine application of a validated bioanalytical method to a particular study.

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Following a successful validation, analysis of biological samples can be done by single determination. The need for duplicate analysis may arise for special cases, e.g. for labile analytes, when precision and accuracy tolerances are difficult to achieve. In this case, a rationale for duplicate analysis should be developed a priori. System Suitability Based on the analyte and technique, a specific system suitability test or sample should be identified to assure the optimum operation of the system employed. Calibration A matrix-based calibration curve should be generated for each run and should be used for calculating the analyte concentration in the unknown samples assayed with that run. It is important to use a calibration curve that covers the entire range of concentrations in the unknown samples. Estimation of unknowns by extrapolations below the LLOQ or above the upper range is not acceptable. Instead, the calibration curve should be re-determined or samples should be re-assayed after dilution with the matrix. Quality Control Samples Duplicate quality control (QC) samples at a minimum of 3 concentrations (one within 3 of the LLOQ, one in the midrange, and one approaching the high end of the range) should be incorporated into each run. There should be a minimum of 5% QCs relative to the number of samples in a run or 6 total QC samples, whichever is greater. Acceptance Criteria The results of the QC samples provide the basis for accepting or rejecting a run. At least 67% (4 out of 6) of the QC samples must be within 15% of their respective nominal values. 33% of the QC samples (but not all replicates at the same concentration) may be outside the 15% range of the nominal value. Repeat Analysis A guideline for repeat analysis should be established a priori. Anticipated reasons for repeating analysis should be defined, e.g. sample processing errors, equipment failure, poor chromatography. The rationale for the repeat analysis should be clearly documented.

Special Considerations for Immunoassays

Most of the bioanalytical validation parameters and principles mentioned above are also applicable to immunoassays. However, there are some specific differences which are described in this section.

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Selectivity As for chemical assays, immunoassays must be shown to be selective for the analyte. Two types of selectivity have to be considered: – ‘Specific’ nonselectivity (interference from compounds that are physicochemically similar to the analyte), e.g. cross-reactivity of metabolites, concomitant medication or endogenous compounds: If possible, the immunoassay should be compared with a validated reference method, e.g. HPLC, using study samples. – ‘Nonspecific’ nonselectivity (interference from matrix components): Calibration curves in biological fluids should be compared with those in buffer in order to detect matrix effects. Accuracy and Precision Criteria for accuracy and precision of immunoassays should match those of chemical assays. Both upper limit of quantification as well as LLOQ must be defined by acceptable accuracy and precision.

Recovery If separation is employed prior to assay for study samples but not for standards, it is necessary to assess efficiency and reproducibility of recovery and use recovery in determining results. Calibration Curve Calibration curves of immunoassays are essentially nonlinear and in general require more concentration points to define the fit than do chemical assays. A minimum of 6 nonzero calibrator concentrations, run in duplicate, is required. Routine Drug Analysis Due to the greater inherent imprecision of immunoassays, QC sample acceptance criteria in routine assay implementation are 25% for accuracy. Thus, at least 67% of QC samples must be within 25% of their nominal values, with no more than 2 at the same concentration level exceeding 25% of nominal values.

Documentation and Archiving of Analytical Data

The data generated for bioanalytical method establishment and the QCs should be documented and available for data audit and inspection. In particular, documentation should comprise – An operational description of the analytical method, – Evidence of purity and identity of drug standards, metabolite standards, and internal standards used in validation experiments and routine analysis,

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

– All available full, partial and cross validation reports (see ‘Validation Report’), – Typical chromatograms, electropherograms or mass spectrograms, if applicable, – Summary tables containing information on sample processing and storage, including sample identification, collection dates, storage prior to shipment, information on shipment batch, and storage prior to analysis, – Summary tables of analytical runs of clinical and preclinical samples, including assay run identification, date and time of analysis, assay method, analysts, start and stop times, duration, significant equipment and material changes, and any potential issues or deviation from the established method, – Summary tables of calibration curve data, – Summary information on QC data used for accepting the analytical run, – Data tables from analytical runs of clinical and preclinical samples, including assay run identification, sample identification, and raw data, – Complete serial chromatograms from 5–20% of subjects with calibration and QC samples from those analytical runs,

SOP 12: Validation of Bioanalytical Methods

– Reasons for missing samples, – Documentation for repeat analyses, including the initial and repeat analysis results, the reported result, and the reason for the repeat analysis, – Documentation for re-integrated data, including initial and repeat integration results, the method used for reintegration, the reported result, and the reason for the re-integration. The documents should be archived for no less than 10 years.

References Kromidas S: Handbuch Validierung in der Analytik. Weinheim, VCH, 2000. U.S. Department of Health and Human Services, FDA, CDER and CVM: Guidance for Industry: Bioanalytical Method Validation, 2001. Shah VP, Midha KK, Dighe S, et al: Analytical methods validation: Bioavailability, bioequivalence and pharmacokinetic studies. Pharm Res 1992;9: 588–592. Shah VP, Midha KK, Findlay JWA, et al: Bioanalytical method validation – a revisit with a decade of progress. Pharm Res 2000;17:1551–1557.

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Version 01 Approval: November 15, 2002 Implementation: November 15, 2002

SOP 13: Pharmacokinetic Data Analysis

Background and Objectives

Pharmacokinetic studies are an integrated part of the development program of a new drug. They are intended to define the time course of drug and major metabolite concentrations in plasma and other biological fluids in order to obtain information on absorption, distribution, metabolism, and elimination. In preclinical studies, pharmacokinetics (PK) is often used to interpret toxicological results. Animal toxicokinetic data can be used to guide dosage selection and escalation schemes in phase I dose tolerance studies. Pharmacokinetically guided dose escalation (PGDE) schemes are an example of the use of preclinical pharmacokinetic data for clinical dose finding in phase I studies. In clinical studies, PK is mainly required for dose finding and dose escalation studies. In phase II and phase III studies, the randomized concentration-controlled clinical trial should be regarded as alternative to the traditional dosecontrolled trial, particularly if interindividual variability of pharmacokinetic parameters is large. Population pharmacokinetic data analysis may reveal the influence of patientspecific factors on pharmacokinetic parameters providing valuable information for dosage individualization. For certain drugs, particularly those with a narrow therapeutic range, PK is used in clinical routine to adapt drug dosage to the individual patient (therapeutic drug monitoring). The statistical evaluation problem of pharmacokinetic data is defined by the tasks to describe the time course of the amount or concentration of the drug in the body and its compartments and to determine rate constants by which the drug reaches the target organs/tissues, by which the drug is activated or bound and by which it is eliminated from the body.

Relevant Pharmacokinetic Parameters

The following pharmacokinetic parameters should be determined for each new drug:

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– Total clearance (CL), – Fraction of dose excreted unchanged in urine (fe), – Volume of distribution at steady state (Vss), – Volume of distribution during the terminal phase (VZ), – Blood/plasma concentration ratio, – Terminal half-life (t1/2 Z), – Fraction of unbound drug in plasma (fu), – Bioavailable fraction of dose (F), if applicable, and – Absorption rate constant (ka), if applicable. For each dosage regimen the following parameters should be known as well: – Area under the plasma concentration time curve (AUC), – Maximum concentration (Cmax), – Minimum concentration (Cmin) after repeated dosing, and – Time of Cmax (tmax). In addition, the effective and toxic concentrations should be assessed. Study Considerations

In order to generate reliable pharmacokinetic data, special care has to be taken regarding study design, sample collection, and processing. Study Design The determinants of a study design are: – Route, mode and schedule of drug administration, and – Sites, methods and time points of sampling. The number of subjects to be examined and the number of samples to be taken from each subject should be planned in advance on the basis of appropriate statistical considerations. Blood Sampling Blood should be sampled at predetermined time points by vein puncture or through an indwelling cannula. If the drug was administered intravenously, sampling should be

performed in the arm opposite to that used for drug administration to avoid contamination. If possible, 1 ml blood should be withdrawn through the cannula prior to sampling and discarded. The exact collection time of each blood sample must be documented in a Case Report Form in conjunction with any irregularity or reasons for deviations. Samples should be filled in tubes containing an adequate anticoagulant and centrifuged immediately for separation of plasma under standardized conditions. It should be clarified that the anticoagulant does not interfere with the drug or its metabolites. Urine Collection Urine is collected in adequate containers according to the predetermined sampling intervals. Appropriate measures have to be taken in order to guarantee complete urine collection within a sampling interval. Urine volume and pH should be determined immediately after the end of a sampling interval. Sample Processing and Transport Samples should be divided into aliquots, if possible, frozen immediately and stored at an appropriate temperature. Samples should be shipped to the laboratory on dry ice and kept frozen until analysis.

Data Handling

Data Entry Spread sheet interfaces (e.g. MS Excel or Lotus 123) connected with databases (e.g. MS Access, dBASE) facilitate a straightforward data entry and are helpful in solitary evaluations. For routine applications and comprehensive drug development programs, interfaces to integrated preclinical and clinical databases are more efficient. It is recommended to separate primary data and modeling software to avoid uncontrolled data modifications. Data Editing Data editing should include a set of procedures for detecting and correcting errors. Criteria for declaring data usable or unusable (e.g. time of blood sampling missing, concentrations with missing dosing information) should be predefined in the study protocol or in a study/project-specific SOP.

should be excluded from data analysis, particularly if they have a disproportionate effect on estimated parameters.

Noncompartmental Data Analysis

Noncompartmental analysis (NCA) does not require the assumption of a specific compartmental model for the drug of interest. However, a relatively large number of data points is required for a reliable estimation of pharmacokinetic parameters. Estimation of Terminal Elimination Rate Constant A minimum requirement is to have 3–4 observations in the terminal slope. By means of log-linear regression on those observations, the terminal elimination rate constant (lz) can be estimated. Estimation of AUC and AUMC The AUC and the area under the first moment curve (AUMC) can be estimated by means of the linear trapezoidal rule or by the log-linear trapezoidal rule. In general, the linear trapezoidal rule should be applied for increasing or equal concentrations and the log-linear trapezoidal rule for decreasing concentrations. For calculating AUC and AUMC from zero to infinity, the extrapolated area from the last sampling time to infinity has to be added to the sum of individual trapezoidal areas. The extrapolated area should not exceed 20–25% of the total area. Calculation of Pharmacokinetic Parameters Using the primary parameters lz, AUC and AUMC, the following pharmacokinetic parameters can be calculated according to standard equations: CL, VZ, Vss, and t1/2 Z.

Compartmental Data Analysis

Compartment models have served for a long time as paradigm of pharmacokinetic modeling. Program systems have been designed either as compartment model library or as compartment model generator where the user defines the model. Dosing schedules are translated to input functions depending on the site of administration (e.g. perorally, intraperitoneally, intravenously), the duration of administration (e.g. bolus, continuous infusion), or delays in time.

Outliers Raw data should be carefully examined to determine if there are values not fitted well by the model (outliers). The reason for declaring a data point to be an outlier should preferably be specified prospectively in the study protocol. Physiological or study-related events that led to the exclusion of an outlier should be explained in the data report (see below ‘Pharmacokinetic Report’). Outliers

Model Selection The simplest model is the one-compartment model with a central compartment. More complicated are multicompartment models where kinetic rates of the exchange between the compartments have to be estimated from the available data. Using the mass balance principle, linear kinetic equations are established as ordinary differential equations. The

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complexity of the multicompartment models and the resulting system of differential equations depends on the identifiability of the model parameters. Sufficient concentration data must be available for each subject in order to solve his/her kinetic equations. Obtaining Initial Estimates The numerical solution of the system equations of a compartment model (i.e. the solution of the system of differential equations) requires the definition of starting values of the kinetic parameters to be statistically estimated iteratively. The stripping method or the peeling of exponential functions is useful to define a set of initial values. Initial estimates are particularly important when data have a lot of scatter or do not span a large enough range of time points to define a full curve. If there are several local minima in addition to an absolute minimum, poor initial values may result in convergence to an unwanted point and hence lead to parameter estimates that are implausible. Selection of Minimization Algorithm It is the goal of the curve fitting procedure to minimize the differences between the observed and predicted concentrations. The most commonly employed criteria are ordinary least squares (OLS), weighted least squares (WLS), and extended least squares (ELS). Among the numerical approaches to the minimization of the objective function approximate solutions have been used. The Downhill Simplex or Nelder-Mead algorithm is based on the geometry of the parameter space and the Powell method on directed one-dimensional minimization. Gradient methods, e.g. the Gauss-Newton or the Levenberg-Marquardt method, require the first derivatives. Second derivatives are used by quasi Newton type methods. Avoidance of local minima is tempted by the use of varying initial values, parameter perturbation (genetic algorithms) or simulated annealing. Choice of Weights Weighting schemes are applied to account for heterogeneity in the variance of the data, particularly if the data span a few or several orders of magnitude. In these instances weights should be assigned to the observations which result in parameter estimates that enable the model to fit low values as well as high values. For many data sets it is appropriate to weight each observation by the reciprocal of the predicted value, or by the square of the predicted value. If weighting is applied, the weighted residuals should be comparable for all data included in the analysis. Assessing Goodness-of-Fit The agreement between model and data (goodness-of-fit) must be checked by diagnostic plots. It is usually evaluated by analyzing the residuals between observed and predicted concentrations. The residuals should be randomly distribu-

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ted around the predicted curve. Residual plots (residual versus time and residual versus concentration) should be used as diagnostic tools. Discrimination between Models For discrimination between models the F-test, the Akaike Information Criterion (AIC), and the Schwarz Criterion (SC) can be used. The probability that additional parameters are without effect on the sum of least squares is defined by an F distribution. The AIC penalizes the sum of squares by the number of parameters. The SC penalizes the sum of squares by the number of parameters multiplied by the square root of the number of observations. Influence of single measurements and single individuals can be investigated by importance sampling and a sensitivity analysis.

Physiologically Based Pharmacokinetic Models

Physiologically based pharmacokinetic models (PBPK models) define drug kinetics in terms of the physiology, anatomy and biochemistry of the organism and are composed of compartments which represent body organs and tissues. Further assumptions concern drug uptake, clearance, and allometric scaling. The body compartments are linked together by a flow network. A PBPK model is defined by a system of deterministic kinetic equations (mass balance equations) of the amount or the concentration of the drug in the compartments as a function of time and initial dose. PBPK models are more complex than compartment models and they usually involve a larger number of parameters.

Pharmacokinetic/Pharmacodynamic Modeling

PK studies the time-dependent fate of a drug and its breakdown products after administration. Pharmacodynamics (PD) is the study of biological effects induced by the drug’s effective amount or concentration. Observed PK and PD can be linked by PK/PD modeling. The resulting PK/PD models allow the description of the complete time course of the desired and/or undesired effects in response to a drug therapy. When reliable and repeated measurement of the individual PD is possible this approach should be applied in preclinical and clinical trials.

Population Pharmacokinetic Data Analysis

Standard Two-Stage Approach The standard two-stage stage approach (STS) refers to fitting a pharmacokinetic model to the data of each individual. Afterwards summary statistics are computed for the

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

total collection of individual parameter estimates. Using this approach, the interindividual variance tends to be overestimated. Moreover, it is not applicable when the individual data are too sparse for individual model fits. Nonlinear Mixed-Effects Modeling Approach (Population Modeling; see «SOP 14: Population Pharmacokinetic Analysis») With this type of modeling not only pharmacokinetic parameters but also interindividual variance parameters are estimated. Mixed-effects or population models are more appropriate than the STS for the analysis of interindividual variation in PK. The parameters of a population model are population means, shift parameters, and interindividual and residual variance parameters. A population pharmacokinetic data analysis should include relevant covariates, e.g. age, weight, gender, creatinine clearance, co-medication, and concomitant diseases. Quantitative relationships between covariates and pharmacokinetic parameters often help predict individual PK before any individual data have been obtained. The modeling of covariate relationships is of special interest in drug development in order to identify subgroups which may need specific dosage recommendations.

Pharmacokinetic Report

Pharmacokinetic data should be summarized in a report which should at least include information on the: – Characteristics of the subjects included in the study, – Dosage regimen and the drug formulation administered, – Sample collection, processing and transport to the laboratory,

SOP 13: Pharmacokinetic Data Analysis

– Method used for drug analysis and its validation (see ‘SOP 12: Validation of Bioanalytical Methods’), – Software, including the main mathematical equations, used for pharmacokinetic data analysis, – Special procedures or criteria used during data analysis (e.g. model definition, initial value settings, minimization algorithm, weighting, model discrimination methods, model diagnostics), – Methods and software used for statistical analysis, – Tables with individual pharmacokinetic parameters and raw data, if appropriate, and – An appropriate graphical presentation of the data. Plots of observed values and model predictions are standard, but should not be restricted to the mean concentration curves. These plots should be supplemented by both raw and weighted residual plots. Preferably, an integrated report should be prepared that correlates clinical findings and pharmacokinetic parameters. For logistic considerations, such an integrated report may contain a separately prepared pharmacokinetic report as an appendix. As a minimum, clinical and pharmacokinetic reports should cross-reference each other. References Derendorf H, Lesko LJ, Chaikin P, et al: Pharmacokinetic/pharmacodynamic modeling in drug research and development. J Clin Pharmacol 2000;40:1399–1418. Gabrielsson J, Weiner D: Pharmacokinetic and Pharmacodynamic Data Analysis: Concepts and Applications, 3. ed. Stockholm, Swedish Pharmaceutical Press, 2000. U.S. Department of Health and Human Services, FDA, CDER and CBER: Guidance for Industry: Population Pharmacokinetics, 1999. Yacobi A, Skelly JP, Shah VP, Benet LZ: Integration of Pharmacokinetics, Pharmacokinetics and Toxicokinetics in Rational Drug Development. New York, Plenum Publishing Corporation, 1993.

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Version 01 Approval: June 20, 2003 Implementation: June 21, 2003

SOP 14: Population Pharmacokinetic Analysis

Background and Objectives

Pharmacokinetic studies are an essential component of drug development (see ‘SOP 13: Pharmacokinetic Data Analysis’). The relevant data are usually obtained from groups of animals, healthy volunteers, or patients. ‘Population Pharmacokinetics’ refers to a method of pharmacokinetic data analysis that is especially suited to data from groups of individuals, or ‘populations’. The objective of population pharmacokinetic analyses is to estimate not only the typical (mean) pharmacokinetic parameters of a population but also to obtain quantitative (and statistically correct) information on the extent and the sources of pharmacokinetic variability. This is useful for assessing the probability of drug concentrations that will be below or above the therapeutic range with a uniform dosing scheme, for setting up dose recommendations for subpopulations with altered pharmacokinetics, and as a basis for adaptive individual dosing in the case of drugs with a narrow therapeutic range. The extent of pharmacokinetic variability between and within individuals is often not obvious to non-specialists. Individual clearances as determined in groups of 20–30 individuals usually vary by a factor of 4–5 or more; the same variability, then, exists in the total area under the plasma concentration-time curve ðAUCÞ and in the concentration at steady state ðCss Þ under continuous dosing. Both AUC and Css are related to tumor response and toxicity [1–4]. Thus, the analysis of pharmacokinetic variability can help understand why therapy fails in individual cases and is a prerequisite for an individual optimization of drug therapy. The basic paramaters of a population model are population mean and interindividual and residual variance parameters. These are fitted simultaneously. A population analysis does not require an analysis of individual kinetic profiles (even though it allows for this). Even sparse data, like only one or two concentration measurements per patient, can be analyzed. Variations of dose, route of administration, and dosing and sampling schedule within the

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same study are not a problem. Thus, this method is particularly useful with data which are obtained under incompletely controlled conditions in clinical routine care. The successful application of population models requires a solid grasp of pharmacokinetic and statistical concepts and considerable technical experience with specialized software. Experience shows that, for a beginner, it will usually take several months of full-time work to become productive in this field. This document concentrates on standard procedures for data analysis. The US Food and Drug Administration has issued a guidance on population pharmacokinetics [5] containing a broader discussion of scientific and regulatory issues and additional recommendations, especially on study design and execution and on data handling.

Study Design and Execution

Standard procedures have been described in ‘SOP 13: Pharmacokinetic Data Analysis’, section ‘Study Considerations’ and in [5, 6]. A few points are emphasized here. The design of a study that will be followed by a population analysis may be less rigorous than that of a study where the data will be analyzed for each individual separately. Dosing and sampling schedules may vary between individuals. There is no need for discrete dose groups; doses may be varied on a continuous scale in order to check whether pharmacokinetics are linear over the entire dose range. No separate groups of patients with pronounced hepatic or renal function impairment need to be recruited in order to look for a dependence of pharmacokinetics on organ function. Patients with a wide range of hepatic or renal function parameter values must be included for this purpose but the variation may be continuous as typically found in non-selected patients of a phase III or phase IV study. Even though a population analysis can accommodate sparse data, some extensive sampling data are needed for

determining the appropriate ‘structural’ model (how many compartments, first-order versus zero-order absorption, lag time yes/no etc.). These data may come from a previous study. If a study with sparse sampling is planned, then the question whether pharmacokinetics will be linear over the entire range of doses to be applied should have been investigated and answered in a preceding study with complete concentration-time profiles, e.g. a phase I study. If such data are available it is useful to include them in the population analysis of sparse data from a subsequent study. The sampling times should cover three or more half-lives during the terminal phase of disposition. Optimal sampling time points should be determined if results from a study with extensive sampling are available. The ‘optimal’ time points, in this context, are those where the measurements are most informative with regard to the pharmacokinetic parameters of interest (most often clearance) [7, 8]. These time points should be translated into ‘time windows’ if the data are to be acquired in a clinical setting (e.g. 4–6 h, 22–28 h); this will prevent the temptation of recording false sampling times when samples could not be drawn at the exact scheduled time. The effect of inaccurately documented sampling or dosing times, typically an inflation of residual variation, is even more detrimental in a population analysis than in a conventional analysis because false data from only one or few individuals will affect the parameter estimation for the entire population. A documentation of infusion times and rates which is just copied from the study design can be grossly inaccurate like, for example, in the case of major fluctuations in the infusion rate, or, when an infusion by intravenous drip came to completion well ahead of the scheduled time. Infusion pumps should be employed whenever possible to eliminate this source of errors. Studying patients on more than one occasion, e.g. during more than one cycle of chemotherapy, may allow one to distinguish the variability between different occasions within the same patient from the variability between patients. Pharmacokinetic variability will all appear as being interindividual when only data from single occasions are available [9]. This may result in overly optimistic expectations as to the benefit from dose adjustments that are based on individual plasma concentration measurements [5, 9].

sively as it may become an explanatory variable later in the modeling process. Weights and heights should be measured rather than found out by asking the patient. Weight measurements should be repeated in cancer patients who are monitored for more than one cycle of chemotherapy. ASCII tables with blanks or commas as field separators are most easily transferable between databases and modeling programs. All data, including the covariate information, should be sorted by individual and by time rather than being stored in separate blocks. The exclusion of faulty data is even more important in population analyses than in individual modeling because grossly false data in one individual (like plasma concentration values that keep rising after the documented end of an infusion) can jeopardize the success of the analysis for the entire population. As pointed out in SOP 13, exclusion criteria for faulty data should be defined before modeling starts. Excluding these data before modeling starts will also save a great deal of time by avoiding the repeated fitting of identical models to slightly differing data sets. It will also prevent the temptation to modify the exclusion criteria in order to make the data fit an inappropriate model. (An ‘inappropriate model’ is also one that underestimates residual variability because exclusions have been made in hindsight to ‘improve’ the fit.) All exclusions must be documented. Assembling concentration data while a study is still running and doing a preliminary model analysis of the data, say, of the first 20–30 patients will help in detecting sources of erroneous data or information gaps at an early stage.

Data Analysis

See ‘SOP 13: Pharmacokinetic Data Analysis’, section ‘Data Handling’, and [5] for appropriate procedures. A few selected points are emphasized here. Information on covariates, in addition to sex, race, age, weight and height, such as concomitant diseases, co-medication, smoking habits, should be collected rather exten-

Preparatory Graphical Analysis Extensive graphical analyses should precede every population model analysis. This is the basis for devising the ‘structural model’; the structural model is the ‘kinetic’ part of the population model, like, for instance, a two-compartment linear model, or a two-compartment model with saturable elimination. It is later assumed to hold for all individuals even though the individual data will often not contain enough information to support this assumption. All concentration-time data should be plotted by individual (one plot for each individual) to check for implausible data and to gather information on the number of disposition phases in individuals with extensive sampling. These plots may also indicate that a lag time parameter will be needed. Linearity should be checked for by a plot of individual AUCs versus dose if a subset of individuals with complete concentration-time profiles is available (use the trapezoidal rule to calculate AUCs, see ‘SOP 13: Pharmacokinetic Data Analysis’, section ’Noncompartmental

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Data Analysis’). If such data are not available, the decision whether to use a linear or a non-linear structural model will have to be based on data from a preceding study with extensive sampling (e.g. phase I), or on information from the literature. Both linearity and the number of disposition phases should be examined in a semi-logarithmic plot of all individual concentration-time data for treatment groups with a similar mode of administration (dosing at about the same time point by the same route; same duration of infusions); each individual should be represented by one line (‘spaghetti plot’). A trend in the terminal elimination phase to be flatter in individuals with high concentrations may indicate saturable elimination even when only one dose or a very narrow range of doses was used in the population. Median concentration-time profiles should be plotted for separate dose groups where applicable. A robust smoother, like LOWESS [10], may be substituted for the median concentrations when the number of individuals varies between sampling time points. A plot of median plasma concentrations versus time by dose group, where concentrations are expressed as fractions of dose per unit volume (‘dose-normalized’), should be made when a similar mode of administration was applied over a range of doses in order to check whether the location of these curves is independent of dose. Basic Model A population model is a combination of a ‘structural model’ (see preceding section) with models of interindividual and residual variability. An important goal of pharmacokinetic population analyses (often the most important one) is the identification of predictable (non-random) components of interindividual variability (depending on covariates like sex, age, co-medication etc.). This goal is achieved in two steps: The data are first described by a model where all variability between individuals is assumed to be random (‘basic’ or ‘descriptive’ model). In a second step, the results are graphically examined for systematic effects of covariates and a sequence of refined models of interindividual variability is tested which includes effects of covariates. Structural Model The structural model is the deterministic part of a population model. It defines the pharmacokinetic processes behind the data much in the same way as do the traditional models for individual concentration-time profiles (cf. ‘SOP 13: Pharmacokinetic Data Analysis’, sections ‘Compartmental Data Analysis’, ‘PBPK Models’; and ‘PK/PD Modeling’). The number of disposition phases assumed for the population should usually be the maximum number that was found in any individuals in the preparatory graphical analysis (section ‘Data Analysis’). The structural model must be non-linear if the ‘spaghetti plot’ or the plot of AUC by dose group indicates non-linearity even if there

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is no individual concentration time profile that exhibits non-linearity. The population approach will allow to estimate mean population parameters of a non-linear model (like mean vmax or mean kM ) in this case while the more traditional approach of fitting individual profiles one by one would have a problem of overparameterization. Structural pharmacokinetic models should be expressed in terms of ‘primary pharmacokinetic parameters’ [11], i.e. clearances and volumes, rather than rate constants because is is then easier to set up hypotheses about the influence of covariates like weight, sex, age, or of concomitant diseases which, for example, alter hepatic or renal function or plasma protein concentration. Interindividual Variation As said before, the first step in a population analysis is to treat all interindividual variability as random. Individual kinetic parameters are only modeled as functions of population means and individual random deviations at this stage. The most commonly used basic model for individual clearance, for example, is the following: CLi ¼ CL ehCL; i ;

ð1Þ

where CLi is the clearance of individual i, i ¼ 1; . . . ; n (n ¼ total number of individuals), CL is the mean population clearance, and hCL is a random variable with mean zero and variance wCL 2. This model implies that clearance cannot be negative and, thus, is preferable over models like CLi ¼ CL þ hCL; i . Also, if the distribution of hCL is symmetrical, the exponential model implies that the distribution of individual clearances is skewed to the right which is a commonly observed feature of distributions of pharmacokinetic parameters [12]. The models for distribution volumes and distribution clearances, as well as the models for lag time and first- or zero-order constants of absorption, should bet set up similarly. Weight is the only covariate that may be incorporated in the basic model of interindividual variability. Both theoretical reasons [13] and a large body of empirical evidence [14] justify the assumption that, in principle, volumes are proportional to weight and clearances are proportional to the 3/4 power of weight. Making this assumption part of the basic model will facilitate the identification of influential covariates other than weight in the second step. For example, systematic deviations of individual clearances from the expected dependence on weight may then allow one to identify an influence of sex, age, or plasma protein concentration which might go unnoticed if the dependence on weight is assigned unlimited flexibility so that it is able to describe too much of interindividual variability. The decision whether to incorporate weight as a covariate in the basic model should be made before the data analysis is started. Individual weights should always be related to a standard weight, like 70 kg. This leads to the following

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

form of the models for the interindividual variability of clearances and volumes if weight is part of the basic model: BWi 0:75 hCL; i e ; ð2Þ CLi ¼ CL 70 kg Vi ¼ V

BWi hV; i e ; 70 kg

ð3Þ

where BWi is the individual body weight expressed in kg. In the example, the estimates of CL and V represent the mean clearance and distribution volume of ‘typical’ subjects weighing 70 kg. Body weight, as determined by weighing on a scale, may be replaced by ‘lean body weight’, a figure calculated from height and weight for a better representation of the total mass of the tissues which determine drug disposition: LBWmen ¼ 1:10 weight ðkgÞ 128 ðweight ðkgÞ=heightðcmÞÞ2 ; LBWwomen ¼ 1:07 weight ðkgÞ 148 ðweight ðkgÞ=heightðcmÞÞ2 : Body surface area (BSA), on the average, is proportional to BW2=3 ¼ BW0:67 . Thus, applying a fixed dose per unit BSA is roughly the same as dosing in proportion to clearance under the model of Eq. 2.

interindividual variance model will often give an estimate close to zero for some of the interindividual variance or covariance parameters. These should then be fixed to zero to make the model more stable. A useful model for the interindividual variability of bioavailability, F, is the following: Fi ¼

1 1þe

ln ðF=ð1FÞÞþhF; i

;

ð4Þ

where Fi is the bioavailability in individual i and F is the mean bioavailability, i.e. the value of F that results if hF; i is zero. The equation represents a ‘logistic’ model [15]; it implies that Fi varies from 0 to 1 as hF; i varies from 1 to þ1. The total number of interindividual variance and covariance parameters should be reduced as long as the objective function (usually a log-likelihood) does not deteriorate significantly. Changes in the log-likelihood should be tested for significance using the likelihood-ratio test [16] with a 0:05. Residual Variation A ‘multiplicative’ model should be used for residual variability if the measured observations span more than one order of magnitude:

The above model for CLi and Vi and similar models for other individual kinetic parameters, are composed of ‘fixed effects’, like CL, V and BWi , and of ‘random effects’, like hCL; i and hV; i . This is why population models, as defined here, are also often called ‘mixed-effects’ models. Individual clearance and volume parameters may be correlated for reasons other than body weight. For example, for a low-extraction drug that is strongly bound to plasma albumin, both clearance and distribution volume will be roughly proportional to the fraction unbound in plasma and, hence, will be correlated. The basic model of interindividual variability should then include an additional floating parameter for the covariance of the ‘h’s’ on clearance and volume, wCL; V . The number of possible variance and covariance parameters quickly increases with the number of structural parameters in the population model. For example, a one-compartment model with first-order absorption and lag time, having four structural parameters, could have up to ten interindividual variance and covariance parameters. Given the extent of residual variation that is usually encountered in pharmacokinetics, no more than about one half of all possible interindividual variance and covariance parameters will be identifiable. The decision which ones to select for the basic population model is somewhat arbitrary. Clearance and the central volume of distribution should always be assigned an interindividual variance parameter. Covariance parameters should only be used where a covariance has to be expected a priori. It will hardly be possible to estimate an interindividual variance for both a rate constant of absorption and lag time. An initial fit of the basic

where yij is the observed concentration in individual i at time j, ybij is the ‘mixed-effects predictions’ as derived from the individual parameters (Vi ; CLi etc.) and e is another random variable with mean zero and variance s 2. The variance s 2 will practically always have to be assumed to be the same in all patients. The above residual variance model implies a constant coefficient of variation over the entire observable concentration range. With this model, care must be taken that the data set has no observation where the predicted concentration is zero, e.g. at the time of the first dose, because the predicted residual variance for this observation will be zero, causing a division by zero in computing the likelihood. Note that, with the above model, the expected residual, ybij e, is proportional to the predicted concentration. Weighting the observations such that the weights depend on the observations themselves, e.g. wij ¼ 1=yij or wij ¼ 1=y2ij , is discouraged because it causes the weights to be random variables which has been shown to result in imprecise parameter estimates [17]. Semi-logarithmic plots of measured concentrations versus time will sometimes exhibit a residual variation that ‘shrinks’ at higher concentrations; a model where the residual error is proportional to the square root of the predicted concentration is then preferable: qﬃﬃﬃﬃﬃ ð6Þ yij ¼ ybij þ ybij eij :

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yij ¼ ybij ð1 þ eij Þ ;

ð5Þ

63

This model implies that the variance rather than the standard deviation of the observations is proportional to the model prediction. An additive residual variance model: yij ¼ ybij þ eij

ð7Þ

should only be considered when the measurements to be modeled all fall within one order of magnitude.

Explanatory Model

An important objective of pharmacokinetic population analyses is to discover relationships between observable covariates and individual kinetic parameters which explain part of the interindividual variability that has all been ascribed to random effects in the basic model. One such relationship may already have been incorporated in the basic model: the body weight dependence of clearance and volume parameters. If it has not been part of the basic model it should be tested as the first covariate in building the explanatory model. Other covariates which often influence individual kinetic parameters in a systematic, predictable way are: age, sex, plasma protein concentration, impairment of hepatic or renal function by concomitant diseases, co-medication, smoking habit, race, genetically determined deficiency of drug-metabolizing enzymes. Quantitative modeling of the influence of cavariates is of special interest in drug development because it will allow one to determine whether subgroups of patients need special dosage recommendations. For drugs with a narrow therapeutic range which require continuous monitoring of individual plasma concentrations or effects, models of covariate relationships help determine the best starting dose for the individual patient. Hypotheses about the influence of covariates should be derived from general pre-existing pharmacokinetic knowledge and from the results of earlier studies of the compound under investigation. For example, a possible dependence of drug clearance on individually determined creatinine clearance should be tested if a compound is known to be excreted unchanged to an appreciable extent. Or, the influence of a co-medication should be investigated if it is known to induce or inhibit one of the primary metabolizing enzymes. Another example is the influence of plasma albumin on the distribution volume of a drug which is highly albumin-bound (also on clearance if it is a low-extraction drug). Hypotheses testing should start with estimating the individual deviations from the mean population parameters (‘h’s’, see Eqs. 2, 3) by a Bayesian procedure (for example, the POSTHOC function of NONMEM [18]). The individual deviations should be plotted versus the hypothesized influential covariates in order to check whether there is any trend in accordance with the hypoth-

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esis. If so, a fixed dependence of the pharmacokinetic parameter in question on the individual covariate values should be incorporated in the population model by introducing a ‘shift parameter’. As an example, a dependence of drug clearance on individual creatinine clearance may be modeled in the following way: CLi ¼ CL ðBWi =70Þ0:75 ð1 q ð120 mL=min CrCLi ÞÞ ehCL; i ;

ð8Þ

where CrCLi is individual creatinine clearance expressed in mL/min and q is a ‘shift parameters’ describing the systematic dependence of drug clearance on individual creatinine clearance (other symbols: see the explanation to Eqs. 14.1–14.3). Covariate models should always be set up such that the mean population parameter represents the mean parameter value of typical individuals (‘centering of covariates’); for example, in the model shown above, CL is the mean clearance of individuals with body weight ¼ 70 kg and creatinine clearance ¼ 120 mL/min. Expressions like: CLi ¼ ðCL ðBWi =70Þ0:75 þ q CrCLi Þ ehCL; i should be avoided because they tend to generate correlations beCL and q^ in the example) tween parameter estimates (d which will jeopardize the identification of potentially important covariates. The appropriateness of the functional form of the assumed covariate relationship should be checked by repeating the plot of individual ‘h’s’ versus the observed covariate values. No trend should remain after including the covariate model. Correlations between observed covariates, like a correlation between age and creatinine clearance, must be checked for by explorative plots. Only one of a pair of correlated covariates can be included in the model. Covariate relationships should be added to the model one at a time, the most likely ones first as suggested by pre-existing evidence. Covariate relationships which improve the fit significantly but were not expected from previous evidence should be documented as interesting new findings which may be confirmed in a subsequent trial.

Goodness of Fit

Residuals The agreement between the final model and the data must be demonstrated by diagnostic plots; these plots are also helpful at all steps of the model-building process. A plot of the measured concentrations versus the ‘mixed-effects predictions’ must not show a systematic disagreement; the ‘mixed-effects predictions’, in this context, are those defined by the mean population parameters, individual body weight, other individual covariate values, and the Bayesian estimates of the individual random deviations from the mean population parameters (‘h’s’, cf. Eq. 1). The residual variance model should be solved for e; e.g. e ¼ yij =ybij 1

Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV

for the multiplicative model (Eq. 7). This quantity should be computed for each data point and should be plotted versus time; it should be symmetrically distributed around zero without a time-dependence. If there is systematic disagreement between the data and the mixed-effects predictions, either with increasing concentration or with time, then the structural model is inadequate and must be revised, e.g. by adding a compartment, by adding a lag time parameter, by assuming zero-order rather than first-order absorption, or by introducing non-linearity. Individual Random Deviations From the Mean Population Parameters The individual random deviations from the mean population parameters (h’s), as estimated by a Bayesian procedure, must be symmetrically distributed around zero. If they are not, then the mixed-effects predictions may still be adequate so that the structural model is acceptable (see preceding section). However, the estimated fixed-effects parameters (the mean population and the shift parameters) do not point to the central tendency of the data in this case and predictions of future outcomes based on these estimates would be misleading. Even the interindividual variance estimates are probably wrong (too large) in this situation resulting in false predictions of the variability of future outcomes, e.g. when the risk of exceeding a critical concentration, or the probability of staying below an effective concentration, are to be estimated. The interindividual variance model, including the modeled influence of covariates, must be revised then. Plots of the distributions of the estimated individual h’s can be of high explorative value by revealing distinct subgroups of patients with extraordinary kinetic behavior which were not expected from previous evidence. Sometimes these plots lead to the detection of false data that are still in the data set despite of the initial checks, or of errors resulting from special constellations in individual

dosing or sampling histories that were not thought of when formatting the data for the model fitting program. Excluding patients or data points just because they are ‘outliers’ should be a last resort because such cases are likely to come up in future patient populations again. Such cases should be documented verbally. Simulation Check The residuals between the data and the fixed-effects predictions cannot be evaluated by inspection of plots alone. The reason is that they depend not only on residual variability but also on the distributions of the individual kinetic parameters which, in turn, depend one the distributions of random variables (h’s) as well as observed covariates. For each of the kinetic parameters, its interindividual distribution affects the residuals from the fixedeffects predictions in a different way, depending on where and how it occurs in the model equations. It is therefore practically impossible to evaluate the residuals from the fixed-effects predictions by plotting alone. This evaluation, however, is necessary in order to get an idea whether the estimated fixed-effects parameters correctly describe the data. A useful way to accomplish this evaluation is to simulate data based on the estimated population parameters: mean parameters, shift parameters, interindividual and residual variance parameters. The simulation must be done under the design of the original data set so that doses, administration times, sampling times, and covariate values are all the same for the observed and the simulated data. The entire set of the original observations may then be plotted versus time, along with summary statistics like the 5, 50, and 95% quantiles; these statistics should coincide with the same statistics computed from the simulated data. The simulations may be repeated many times in order to judge to what extent discrepancies between the statistics of the simulated and the observed data are acceptable [19].

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Standard Operating Procedures for Clinical Trials of the CESAR Central European Society for Anticancer Drug Research – EWIV