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Outline. Background and how DSMBs arose and functionGroup sequential methodsExamples. Suggested Reading . Ellenberg S, Fleming TR, DeMets DLData Monitoring Committees in Clinical Trials. A Practical PerspectiveJohn Wiley
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1. Interim Analyses ofClinical Trials
2. Outline Background and how DSMBs arose and function
Group sequential methods
Examples
3. Suggested Reading Ellenberg S, Fleming TR, DeMets DL
Data Monitoring Committees in Clinical Trials. A Practical Perspective
John Wiley & Sons, LTD, 2002
4. Research on Human Subjects and Data Monitoring Committees Nuremburg Code (1949)
Declaration of Helsinki (1964)
Belmont Report (1979)
Greenberg Report (1967)
FDA Guidance on DMCs (2006)
5. Structure for Cooperative Studies (Greenberg Report)
6. Monitoring Committee Acronyms PAB = Policy advisory board
DSMB = Data and Safety Monitoring Board
DMC = Data Monitoring Committee
ESMB = Efficacy and safety monitoring board
OSMB = Observational study monitoring board
7. Responsibilities Steering Committee
Study design
Patient recruitment and follow-up
Data collection
Quality assurance
Study reports DMC or DSMB
Safety of patients
Protection of integrity of study
Review of blinded data on safety and efficacy of treatments
Review of trial conduct, amendments and external data
8. Starting Point A randomized study
Uncertainty with respect to the relative safety and benefits of treatments to be compared
Protocol to address the scientific question
Informed consent with explicit or implicit mention of interim monitoring
Plan for timely data collection and safety monitoring
9. In the End Want… Confidence in the answer
A report in which you can specify:
- Number of interim analyses
- Reason for stopping, if early
- Monitoring guidelines used
- DSMB membership
10. Interim AnalysesRationale Safety is best assured by comparing the rate of adverse events with a control group
Studies should not stop before there is a definitive answer and should not continue longer than necessary to obtain one
Regular assessment of the relevance of the question
Regular assessment of whether the trial will address the question posed
11. Reasons for Early Terminationof Clinical Trials Based on accumulated data from the trial:
Unequivocal evidence of treatment benefit or harm
Unexpected, unacceptable side effects
No emerging trends and no reasonable chance of demonstrating benefit
Based on overall progress of the trial:
Failure to include enough patients at a sufficient rate
Lack of compliance in a large number of patients
Poor follow-up
Poor data quality
12. Today All NIH sponsored clinical trials are required to have a data monitoring plan
NIH-sponsored trials with clinical endpoints have a DSMB
Many industry sponsored studies have a DSMB
The FDA has prepared a guidance document that will likely result in many more industry-sponsored trials with a DSMB
There is considerable variation in operating procedures for DSMBs
13. When is an Independent DSMB Needed Early phase studies
Monitoring usually at local level; independent DMC not usually needed.
Phase III & IV studies with morbidity/mortality outcomes; pivotal phase III trials
Frail populations, e.g., children, elderly
Trial with substantial uncertainty about safety, e.g., gene therapy
14. DSMBComposition: Multidisciplinary Clinical experts in the subject matter area
Biostatisticians with expertise in clinical trials and preferably in the subject matter area
Others depending on the nature of the study, e.g., ethicist, pharmacologist, patient advocate
Senior investigators without significant conflicts of interest
15. Independence of DSMB: Voting members should not be part of the investigative team or work for the sponsor
There should be a clear “need to know” policy for non-DSMB members, e.g., the statistician preparing interim summaries needs to know and may be an employee of the sponsor or member of the investigative team
Members should state potential conflicts
17. Two-Hat Model: In-house statistician who does everything Same person(s) participates in protocol development, interim analyses and writing papers (Steering Committee)
Model used by many NIH-sponsored trials
May be only option for small company
Important to keep a poker face
18. Protocol amendments may be influenced by knowledge of interim data
Difficult to avoid arousing suspicion
“…even unintentional non-verbal communication (e.g., nervousness, smiling) may reveal some of that knowledge.”
Draft Guidance Document: On the Establishment and Operation of Clinical Trial Data Monitoring Committee, FDA, November 2001. Disadvantage of Two-Hat Model
19. One Hat Models Two statisticians, one who works with the investigators on the protocol and the other who carries out interim analyses
1 in-house and 1 external
2 in-house
2 external
Are there enough statisticians?
20. One Hat (2 Statisticians) vs. Two Hats (1 Statistician) Leakage less likely
More “objective” DSMB reports
Greater external credibility
Greater knowledge of study/field
More thoughtful DSMB reports
Cheaper
Professionally more rewarding
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21. Rules of the Game Charter with lines of reporting stated
Role in review of protocol and amendments
Open and closed sessions for DSMB meeting (open – closed – executive or closed – open - closed)
For early stopping for efficacy, there should be proof beyond a reasonable doubt
Guidelines should not be too restrictive, e.g., number of interim analyses
22. Rules of the Game (cont.) Ability to schedule meetings and request additional analyses deemed necessary
Non-blind monitoring
Minutes of open and closed session
Specify minutes-taker
23. Outline of Charter Membership and voting rules
Meeting format and frequency
Reporting responsibilities
Stopping guidelines
Minutes
Procedures to ensure confidentiality (treatment codes, disposition of reports)
Conflicts of interest
24. DSMB Meeting Format Open Session
Progress report using open data
Sponsor, e.g., NIH, Executive Committee, Protocol Chairs, DSMB and unblinded statisticians
Closed Session
Blinded data by treatment group
DSMB and unblinded statisticans only
Executive Session (DSMB only)
Debriefing Session
DSMB, Sponsor, Executive Committee, Protocol Chairs, and unblinded statisticians
25. DSMB Confidentiality Interim data reviewed by the DSMB must remain confidential
Members must not share interim data with anyone outside DSMB
Leaks can affect
Patient recruitment
Protocol compliance
Outcome assessment
Trial integrity and support
26. Sponsor
Executive committee
Steering committee
DSMB Decision Making Based on Interim Analyses
27. Recommendation No one other than statistician who prepares the report is present during review of treatment comparisons
It is generally inappropriate for the sponsor (NIH or industry) or the FDA to be present or to be given interim treatment summaries
The inclusion of others requires justification – “need to know”
28. Open Statistical Report – Findings for All Treatment Groups Combined Outline of the study design
Major protocol changes
Study accrual by month and by institution
Eligibility violations
Baseline characteristics
Days between randomization and initiation of treatment
Adherence
Attendance at scheduled visits
Reporting delays for key events
Length of follow-up data available
Assessment of sample size assumptions
29. DSMB Reporting Inclusion of irrelevant material interferes with the primary job of the DSMB and makes members testy
Highlight most important results
30. Controversial Issues About Open Data? Risk factor or marker changes known to be on the pathway between treatment and clinical endpoint
Adherence to individual treatment assignments
Total number of events (all treatment groups combined)
When should there be a middle ground, e.g., safety data?
31. Closed Statistical Report Detailed statistical commentary explaining issues raised by closed report figures and tables (by coded treatment group, with codes given to DSMB members)
Summary of closed report data presented at prior DSMB meetings
Repeat of the open report information, in greater detail by treatment group
Analyses of primary and secondary efficacy endpoints
Analyses of adverse events and overall safety data
Treatment discontinuations and crossovers
Listing and summary of major events, e.g., deaths and serious adverse events (SAEs)
32. A Typical Safety Section of DMC Report – Important Not to Miss Forest for Trees! 100-300 pages
Line listings
Adverse event frequencies
All events
Emerging events
Severe events
Events leading to discontinuation of treatment
Laboratory data
Frequency of abnormal findings
Average changes over time
33. Typical Questions/Problems Are you counting events or patients?
What time period do %’s pertain to?
Did you collect events after patients discontinue treatment?
Which terms do I look at to determine how many patients experienced a heart attack?
Are patients being counted more than once -
Single event and more than one name?
Multiple events occurring at different points of follow-up?
Suppose I just want to know how many patients in each arm have experienced severe depression?
34. DMC Report – Mood Disturbances
36. Pitfalls of Lumping versus Splitting:Myocardial Infarction
37. Should Level of Severity be Considered in the Collection of Safety Data? Yes
Lower grade events in earlier phase studies
More severe events only in large outcome studies
38. Should Level of Perceived Relationship to Study Treatment be Considered in the Collection of Safety Data?
39. How Can the Data be Summarized to Facilitate DMC Reviews? A priori agreement on a data analysis plan, that includes:
A hierarchy of events and associated composites:
Death
Death or serious AE
Death or serious AE or treatment D/C due to AE
Death, serious AE, treatment D/C due to AE, or grade 4 event
Categories of events of interest (granularity)
Interim efficacy as well as safety for assessing risk/benefit
For key events, a history of previous interim analyses
40. Summary -1 A DSMB can be most effective in its role of protecting the interests of patients if it is independent of the sponsor and trial investigators – peer review works!
Operating procedures should be agreed upon in advance
An informed statistician who performs interim analyses is important
To carry out interim analyses data must be collected in a timely way
Reports should focus on comparisons of clinical outcomes and their validity
41. Summary - 2 Collect less data and do it well.
Focus on complete collection of severe events irrespective of perceived relationship to treatment
Collect these events over the entire duration of the study
Develop a data analysis and reporting plan for adverse events before the study.
Prepare reports in a manner to allow DMC members to easily assess emerging signals.
Include interim efficacy analyses with safety analyses in order to assess risk/benefit.