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E-raamat: Data and Safety Monitoring Committees in Clinical Trials

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(John Hopkins Bloomberg School of Public Health, Baltimore, Maryland, USA)
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Data and Safety Monitoring Committees in Clinical TrialsSuurem pilt
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Praise for the first edition:

"Given the authors years of experience as a statistician and as a founder of the first DMC in pharmaceutical industry trials, I highly recommend this booknot only for experts because of its cogent and organized presentation, but more importantly for young investigators who are seeking information about the logistical and philosophical aspects of a DMC."

-S. T. Ounpraseuth, The American Statistician

In the first edition of this well-regarded book, the author provided a groundbreaking and definitive guide to best practices in pharmaceutical industry data monitoring committees (DMCs). Maintaining all the material from the first edition and adding substantial new material, Data and Safety Monitoring Committees in Clinical Trials, Second Edition is ideal for training professionals to serve on their first DMC as well as for experienced clinical and biostatistical DMC members, sponsor and regulatory agency staff.



The second edition guides the reader through newly emerging DMC responsibilities brought about by regulations emphasizing risk vs benefit and the emergence of risk-based monitoring. It also provides the reader with many new statistical methods, clinical trial designs and clinical terminology that have emerged since the first edition. The references have been updated and the very popular end-of-chapter Q&A section has been supplemented with many new experiences since the first edition.

New to the Second Edition:











Presents statistical methods, tables, listings and graphs appropriate for safety review, efficacy analysis and risk vs benefit analysis, SPERT and PRISMA initiatives.





Newly added interim analysis for efficacy and futility section.





DMC responsibilities in SUSARs (Serious Unexpected Serious Adverse Reactions), basket trials, umbrella trials, dynamic treatment strategies /SMART trials, pragmatic trials, biosimilar trials, companion diagnostics, etc.





DMC responsibilities for data quality and fraud detection (Fraud Recovery Plan)





Use of patient reported outcomes of safety





Use of meta analysis and data outside the trial





New ideas for training and compensation of DMC members

Jay Herson is Senior Associate, Biostatistics, Johns Hopkins Bloomberg School of Public Health where he teaches courses on clinical trials and drug development based on his many years experience in clinical trials in academia and the pharmaceutical industry.

Arvustused

"The book by Dr. Herson is written amazingly well. The book concentrates on pharmaceutical industrysponsored confirmatory clinical trials and can serve as excellent sources of knowledge for all the aspects of data safety monitoring committee (DMC) activities. A great feature of the book is the DMCounselor section at the end of each chapter, covering nearly 70 questions with answers, of which about 33% are for a DMC Chair, 30% for the DMC Biostatistician member, 30% for a DMC physician member, and the rest are for others (e.g., project manager)." ~ Daniel Jia, Journal of Biopharmaceutical Statistics

"Nicely written and readable cover-to-cover, the author walks through every facet of a Data Monitoring Committee (DMC) beginning with an overview of their past and current place in drug development, to how they are organized and interfaced with other committees, and on to the specifics of how a typical meeting is split into an open and closed session. From there it moves on to clinical issues, including how SAEs are categorized, statistical methods, including Bayesian and frequentist conditional power calculations, common biases and pitfalls, and guidance for how DMC decisions are made. It concludes with emerging issues due to new clinical trial designs mandated by the FDA to speed up the drug development process." ~Donna Pauler Ankerst, Biometrics

Preface to the First Edition xvii
Preface to the Second Edition xxi
List of Abbreviations
xxiii
1 Introduction
1(18)
1.1 What Is a Data Monitoring Committee (DMC)?
1(1)
1.2 Some Definitions
2(1)
1.3 DMC in Federal Government-Sponsored Clinical Trials versus Pharmaceutical Industry Clinical Trials
3(2)
1.4 Stewardship
5(1)
1.5 Some Recent History
5(2)
1.5.1 Development of DMCs in the Pharmaceutical Industry
5(1)
1.5.2 Guidance Documents: FDA, NIH, and ICH
6(1)
1.5.3 Other Vehicles for Patient Protection
7(1)
1.6 A DMC's Place in the Drug Development Cycle
7(6)
1.6.1 Phases of Drug Development
7(1)
1.6.2 Limitations of a Clinical Program for Revealing Safety Issues
7(3)
1.6.3 Postmarket Safety Actions
10(1)
1.6.4 Role of DMCs in Exploratory and Confirmatory Trials
10(2)
1.6.5 Blurring of Phases I, II, and III
12(1)
1.6.6 Investigator-Sponsored Trials
12(1)
1.6.7 Open Label Trials
13(1)
1.6.8 Emerging Trial Designs of Interest
13(1)
1.7 Pharmaceutical Industry Demographics
13(2)
1.7.1 Size of Companies
13(1)
1.7.2 Public versus Private Companies
14(1)
1.8 In Conclusion
15(4)
DMCounselor
15(4)
2 Organization of a Safety Monitoring Program for a Confirmatory Trial
19(18)
2.1 Members of the Safety Monitoring Team
19(4)
2.1.1 The Sponsor
19(1)
2.1.2 Data Monitoring Committee
20(1)
2.1.3 Data Analysis Center
21(1)
2.1.4 Institutional Review Board
22(1)
2.1.5 Other Committees That Might Be Involved
22(1)
2.1.6 Scope of DMC Authority
23(1)
2.2 How Is a DMC Created?
23(1)
2.3 Membership
24(4)
2.3.1 Physicians
24(1)
2.3.2 Biostatisticians
25(1)
2.3.3 How Many Members Are Needed?
25(1)
2.3.4 Ad Hoc Consultants
25(1)
2.3.5 Ubiquitous DMC Members
26(1)
2.3.6 Disclosure of DMC Membership
27(1)
2.3.7 Multiple Sponsorship
27(1)
2.3.8 From Where Are DMC Members Recruited?
28(1)
2.4 Term
28(1)
2.5 Conflicts of Interest and DMC Independence from Sponsor
28(1)
2.6 Compensation
29(1)
2.7 Liability and Indemnification
30(1)
2.8 Sponsor-DMC Relationship
30(1)
2.9 Interdisciplinary Training
31(1)
2.10 In Conclusion
31(6)
DMCounselor
31(6)
3 Meetings
37(26)
3.1 DMC Charter
37(1)
3.2 Types of Meetings
37(2)
3.2.1 Orientation or Organizational Meeting
38(1)
3.2.2 Data Review
39(1)
3.2.3 Ad Hoc
39(1)
3.3 Orientation Meeting
39(6)
3.3.1 Chair for Orientation Meeting
39(1)
3.3.2 Introduction of the Safety Monitoring Team
39(1)
3.3.3 Appointment of DMC Secretary
39(1)
3.3.4 Presentation of DMC Charter
40(1)
3.3.5 Masking Policy
40(1)
3.3.6 Investigator Brochure
41(1)
3.3.7 Protocol
41(1)
3.3.8 Informed Consent
42(1)
3.3.9 Data Flow
42(1)
3.3.10 Useful Software
43(1)
3.3.11 Review of Integrated Summary of Safety
43(1)
3.3.12 Policy on Review of Publications and Package Inserts
44(1)
3.3.13 Data Review Plan
44(1)
3.3.14 Schedule First Data Review Meeting
45(1)
3.4 Data Review Meetings
45(7)
3.4.1 Attendance
46(1)
3.4.2 Open Session
46(1)
3.4.2.1 Study Progress
46(1)
3.4.2.2 Data Quality
47(1)
3.4.2.3 Update on Pending Action Items
47(1)
3.4.2.4 Questions for the DMC
47(1)
3.4.2.5 Sample Agenda for Open Session
47(1)
3.4.3 Closed Session
48(1)
3.4.4 DMC Meetings for Open Label Trials
48(1)
3.4.5 Scheduling of Next Meeting
48(4)
3.4.6 Minutes
52(1)
3.5 Ad Hoc Meetings
52(1)
3.6 In Conclusion
52(11)
DMCounselor
53(10)
4 Clinical Issues
63(18)
4.1 Goals of Safety Analysis
63(1)
4.2 Definitions
64(3)
4.2.1 Adverse Event
65(1)
4.2.2 Serious Adverse Event
65(1)
4.2.3 Adverse Event Tiers
65(1)
4.2.4 Serious Adverse Event Reporting Requirements
65(1)
4.2.5 Serious Unexpected Suspected Adverse Reactions (SUSARs)
66(1)
4.3 Safety Data
67(5)
4.3.1 Pharmacovigilence Groups
67(1)
4.3.2 Case Report Forms
67(1)
4.3.3 Adverse Event Dictionary
67(1)
4.3.4 Adverse Event Severity
68(1)
4.3.5 Adverse Event Summary
69(2)
4.3.6 SAE Narratives
71(1)
4.3.7 Titration to Dose
72(1)
4.4 Deaths
72(1)
4.5 Impact of Multiregional (Global) Trials
72(2)
4.5.1 Cultural Issues
73(1)
4.5.2 Political Issues
73(1)
4.5.3 Medical/Surgical Practices Issues
74(1)
4.5.4 Data Quality Issues
74(1)
4.6 In Conclusion
74(7)
DMCounselor
76(5)
5 Statistical Issues
81(38)
5.1 Goals of Statistical Analysis
81(1)
5.2 Useful Data Displays
82(8)
5.2.1 Enrollment by Center, Ethnicity, and Stage of Disease
83(1)
5.2.2 Graph of Cumulative Patient Enrollment by Month
84(1)
5.2.3 Graph of Cumulative Patient Exposure to a Study Drug
84(1)
5.2.4 Treatment-Emergent Adverse Events
85(1)
5.2.4.1 Classification
85(1)
5.2.4.2 Example: The APPROVe Trial
86(1)
5.2.4.3 Incidence Calculation
87(1)
5.2.4.4 Incidence and Exposure Time Calculation
87(1)
5.2.4.5 Kaplan--Meier Time to First Occurrence
88(1)
5.2.4.6 Incidence at a Time Point after Treatment Start: Landmark Estimate
89(1)
5.2.4.7 Other Ways of Looking at Incidence
89(1)
5.2.5 Laboratory Data
90(1)
5.3 Analysis Methods: Frequentist
90(9)
5.3.1 What Is Frequentist Analysis?
90(1)
5.3.2 Hypothesis Tests
91(2)
5.3.3 Confidence Intervals
93(1)
5.3.3.1 Incidence
93(1)
5.3.3.2 Rate per 100 Patient Years
94(1)
5.3.3.3 Relative Risk
94(1)
5.3.3.4 Odds Ratio
95(1)
5.3.3.5 Poisson Rate Ratio
96(2)
5.3.3.6 Inference with Kaplan--Meier Landmark Estimates of Incidence
98(1)
5.3.4 Data Analysis without Statistics
99(1)
5.4 Power
99(2)
5.5 Multiplicity
101(3)
5.6 Analysis Methods: Likelihood
104(6)
5.7 Analysis Methods: Bayesian
110(1)
5.8 Safety Graphics
111(1)
5.9 In Conclusion
111(8)
DMCounselor
116(3)
6 Bias and Pitfalls
119(14)
6.1 What Is Bias?
119(1)
6.2 Sources of Bias
119(1)
6.3 Knowledge of Treatment Assignment
120(2)
6.3.1 By Sponsor Staff
120(1)
6.3.2 By the DMC
121(1)
6.4 Reporting Bias
122(5)
6.4.1 Investigator Level
122(1)
6.4.1.1 Knowledge of Treatment Assignment
122(1)
6.4.1.2 Incomplete Follow-Up
123(1)
6.4.1.3 Spontaneous versus Solicited Adverse Event Collection
123(1)
6.4.2 Analysis Level
124(1)
6.4.2.1 Early Termination Due to Efficacy
124(1)
6.4.2.2 Granularity Bias
124(3)
6.5 Competing Risks
127(2)
6.6 In Conclusion
129(4)
DMCounselor
130(3)
7 Data Monitoring Committee Decisions
133(34)
7.1 Types of DMC Decisions
133(1)
7.2 Decision-Making Environment
134(1)
7.3 Risk versus Benefit Analyses
135(3)
7.4 When a Safety Issue Arises
138(5)
7.4.1 Unmasking
138(1)
7.4.2 "Dear Investigator" Letter
139(1)
7.4.3 Modification of Informed Consent
140(1)
7.4.4 Protocol Modification
141(1)
7.4.5 Trial Termination
141(2)
7.4.6 Unmasking the Sponsor
143(1)
7.5 Information beyond the Present Trial
143(3)
7.6 Meta-Analysis
146(2)
7.7 Planned Interim Analyses Regarding Efficacy
148(4)
7.8 Final Meeting
152(1)
7.9 Special Problems with Infant Pharma Companies
153(1)
7.10 In Conclusion
154(13)
DMCounselor
155(12)
8 Emerging Issues
167(28)
8.1 Introduction
167(1)
8.2 Issues in New Clinical Trial Designs and Technologies
168(8)
8.2.1 Adaptive Designs
168(1)
8.2.1.1 Dropping a Dose or Treatment Group
168(1)
8.2.1.2 Adaptive Assignment to a Treatment Group
169(1)
8.2.1.3 Changing Objectives: Superiority to Noninferiority
169(1)
8.2.1.4 Seamless Transition: Phase II to Phase III
170(1)
8.2.1.5 Change in Effect Size of Interest
170(1)
8.2.1.6 Further Thoughts on Adaptive Designs
171(1)
8.2.2 Novel Designs in Oncology
172(1)
8.2.3 Dynamic Treatment Strategies (DTS) and a Sequential Multiple Assignment Randomization Trial (SMART)
173(1)
8.2.4 Pragmatic Trials and Patient-Reported Outcomes of Safety
174(2)
8.3 Biosimilar Designs
176(1)
8.4 In Vitro Companion Diagnostic Devices
176(2)
8.5 Real-Time SAE Reporting Using the Internet
178(1)
8.6 Centralized Risk-Based Monitoring
179(1)
8.7 Causal Inference
179(2)
8.8 Unmasking Potential of Biomarkers
181(1)
8.9 Issues Due to Maturing of DMC Processes and Evolution of the Pharmaceutical Industry
181(7)
8.9.1 Training of DMC Members
181(2)
8.9.2 Cost Control
183(1)
8.9.3 DMC Audit
184(1)
8.9.4 Internal Safety Review Committees and Still More Committees
184(1)
8.9.5 Mergers and Licensing
185(1)
8.9.6 Journal Policies Regarding Independent Reviews
186(1)
8.9.7 Fraud Detection
186(1)
8.9.8 Compensation of DMC Members
187(1)
8.10 Resignation from a DMC
188(1)
8.11 In Conclusion
189(6)
DMCounselor
190(5)
Glossary 195(14)
Appendix 209(8)
References 217(14)
Index 231
Jay Herson is Senior Associate, Biostatistics, Johns Hopkins Bloomberg School of Public Health where he teaches courses on clinical trials and drug development based on his many years experience in clinical trials in academia and the pharmaceutical industry.
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