During this presentation, Ron Kershner, Ph.D. discussed the responsibilities of DMCs from the perspective of protecting patient safety and providing critical, independent oversight to key study objectives. Drawing on past clinical trials to illustrate key points, Ron addressed DMC operational considerations, such as meeting frequency and content, control of information, data cleaning issues and scope/format of data tabulations.

1. 2 0 11 FA L L B I O M E T R I C S W E B I N A R S E R I E S
The Role of Data Monitoring
Committees
Sept. 20, 2011 Presented by Ronald Kershner, Ph.D.

2. Ronald Kershner, Ph.D.
 Vice President, Biostatistics and Data
Operations
 25+ years of clinical research experience
– Includes over 24 NDAs in various therapeutic
areas
– Served on over 20 data monitoring committees
 Authored more than 30 publications and
presentations with a recent focus on eClinical
technologies and independent data
monitoring committees
 Ph.D. in Statistics from Cornell University
2011 FALL BIOMETRICS WEBINAR SERIES

3. Today’s Topics
3
1) Reasons for DMCs
2) Roles, objectives and set-up for DMCs
3) Operational considerations
4) Statistical considerations: p-value adjustments
5) Where companies get it wrong
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4. Reasons for DMCs
 Ethics
 Insurance
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5. Reasons for DMCs: Ethics
5
 Oversight function to insure patient safety
 Monitor and be able to quickly react to any
untoward safety events
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6. Reasons for DMCs: Insurance
6
Operational Issue
 Provide oversight function of study progress
 Insure study will have reasonable likelihood of
achieving basic objectives
– Futility probability
 Early warning system for operational issues
– Critical design parameters
– Sample size considerations may warrant adaptive
design
 Stop early
– No efficacy or unacceptable safety
– Early, compelling, untoward, unexpected efficacy
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7. Roles, Objectives and Set-up for
DMCs
 DMC
 Executive Committee
 Data Analysis Center
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8. DMC Charter
8
 Define roles and
responsibilities of
DMC members
 Communication with
Executive Committee
 Scope of data reviews
 Structure and timing of
meetings
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9. Committee Roles
9
DMC Executive Committee
 Review data tabulations  Responsible for study
from ongoing clinical trial oversight and conduct
 Deliberations are  Membership: company,
confidential investigators
 Make recommendations to  Decision makers
Executive Committee
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10. DMC Members
10
Who to include: Who NOT to include:
 Independent clinical members  Company/sponsor/client
– Therapeutic area experts  Study investigators
– No vested interest in  Investigator’s company
company or outcome of contact
trial  Individuals who can change or
 Independent statistician influence patient recruitment
 Individuals with data
classification responsibilities
 Individuals who could control
or change study design,
objectives or planned
analyses
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11. Key Points
Comparing the Committees
11
DMC Executive Committee
 Independent  Company representation
 Access to data  Investigator representation
 No decisions, (optional)
recommendations to  NO access to data
Executive Committee  Decision makers, based on
recommendations from
DMC
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12. Number of Meetings
12
 Function of
– Recruitment rate
– Size of study
 Can be more frequent for AEs
 Conference calls, web conferences, or face-to
face
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13. DMC Meetings
13
Open Sessions Closed Sessions Minutes
 Executive  DMC Only  Document
Committee  Unblinded data deliberations
 DMC review  Confidentiality is
 No unblinded data key
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14. Assure Confidentiality of Interim
Results
14
Case Study:
Sepsis
 Potential blockbuster with estimated
$1B/year market potential
 NYT: 12 Feb 1993
 Centoxin
– Efficacy endpoint in pivotal study
changed based on knowledge of
interim results
– NDA terminated
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15. Data for DMC Member Review
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What information needs to be provided to the
DMC members for meetings?
✓ Patient accounting
a)
✓ Demographics/medical history
b)
ALL OF
✓ Enrollment summaries
c)
THESE
✓ AEs/SAEs – coded summaries
d)
✓ Basic efficacy summaries
e)
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16. Operational Considerations
 Keep review scope focused
– “Interim analysis” is not final analysis
 Emphasize simple tables and graphics, not
listings
 Information needs to be current
– Current is more important than clean
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17. Example: Lab Data
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 Hematology, LFTs
 2-year study
 Lab panels every month
 6 LFTs X 24 visits = 144 displays
 Don’t use: Normal range shift tables? Change
from baseline?
 Consider: Use 1 table to display any value
outside a biologically significant boundary at any
time
– Biologically significant = 3 or 4X upper limit or
CDC toxicity level
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18. Plan for Rapid Retrieval of
Outcomes
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Important to minimize time lag between CRF at site versus in-
house
EDC Paper CRFs
 Very helpful alternative to  Short forms, worksheets
paper  Phone calls
 Make sure data is entered  Working/temporary
at the sites databases
 Help Desk support
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19. Other Considerations
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 Resource intensive process, particularly for
paper CRFs
– Monitoring
– Programming
– Data Management
 Additional analysis requests based on DMC
input and reviews
– More tables, ad hoc requests
Should company be made aware?
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20. Statistical Considerations:
p-value Adjustments
 When DMC looks at interim data, p-value
adjustments are necessary
– Avoid over reaction to early trends
– Maintain nominal alpha level of 0.05 for the
final analysis
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21. P-value adjustments
21
 Multiple looks require an adjustment to the p-
value
 Need to control overall Type I error rate
 Type I error = 0.05 for one look
= 0.14 for 5 looks
= 0.20 for 10 looks
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22. Control type I error and maintain
nominal 0.05 alpha for final
analysis
22
Interim analyses utilize p-values at levels of
approx. 0.0001 at each look versus 0.05 at each
look
e.g., 6 interim analyses (6 looks):
Final alpha = 0.05 – 6*0.0001 = 0.0494
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23. Z Values for Clofibrate-Placebo
Differences in Proportion of Deaths
by Month
23
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24. Key Points
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 There are sound reasons to have a DMC
monitor ongoing data
 P-value adjustments need to be made
 P-value adjustments for interim looks can be
very small and final alpha can be maintained
very near 0.05
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25. Where Companies Get it Wrong
 Administrative analyses
 DMC for safety only
 Blinding the DMC
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26. Administrative Analyses
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 Look at data with no intent to modify study
 Look at data for operational (“insurance”) issues
 Since no intent to change, no adjustment of p-
values should be necessary
 If efficacy data are involved, adjustment is
needed
– Always a potential to overreact to early trends
– Major red flag
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27. Safety Only?
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Should DMCs be used for review of safety only?
✗ Yes
a) DMC needs access
both efficacy and safety
✓ No
b) to assess risk and benefit
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28. Restrict Monitoring for Safety Only
28
Case Study:
AMD
 Limited Phase II dosing information
 First major entry into patients was
two large Phase III studies
– Limited safety data
 Efficacy endpoint: mean difference of >
2 lines between treatment and placebo
after two years of therapy
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29. Restrict Monitoring for Safety Only
29
Case Study:
AMD
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30. Restrict Monitoring for Safety Only
30
Case Study:
AMD
 Results: only 1 of 2 studies
showed significance
 Reason: high placebo response
rate
2011 FALL BIOMETRICS WEBINAR SERIES

31. Blinding of Data
31
Does the data need to be blinded for the DMC
review?
✗ Yes
a)  Not an FDA or ICH requirement
 Imposed by companies to:
– “Prevent bias”
✓ No
b) – “Avoid over reaction to early
trends”
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32. ICH E9
32
Interim analysis requires unblinded access to
treatment group assignments - 4.1
Interim analysis …involves access to …
unblinded data and results - 4.5
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33. Controlling Bias…Overreaction
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 The DMC does not make decisions
 DMC has no vested interest (unlike company)
 Monitoring boundaries are in place
 Degree of empowerment of DMC comes from
Executive Committee and is described in the
Charter
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34. Summary
 Patient safety is key
 DMC is an independent group
 Charter describes roles and
responsibilities
 Monitoring boundaries are needed
 DMC needs to be unblinded and needs to
assess both benefit and risk
2011 FALL BIOMETRICS WEBINAR SERIES

35. Upcoming Webinars
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Register at www.premier-research.com/webinars
▪ IVR/IWR…More than just Randomization
11 October at 11:00 am EDT
Speakers: Bruce Bailey and Ryan Michaud
▪ Streamlining Data Management Start-up
15 November at 11:00 am EST
Speaker: Cheryl Silva
▪ Strategies for Implementing CDISC
13 December at11:00 am EST
Speaker: Thomas Kalfas
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36. Questions?
Ronald Kershner, Ph.D.
Vice President, Biostatistics and Data Operations
Centre Square West
1500 Market Street, Suite 3500
Philadelphia, PA 19102
Telephone: 215.282.5444
ron.kershner@premier-research.com
2011 FALL BIOMETRICS WEBINAR SERIES