Transcript
- 1. Philadelphia, PA
February 22-23, 2010
Highlights from ExLPharmas 5th Data Monitoring Committees/DSMB - 2. The Role of DMCs/DSMBs in Adaptive Trials:The Impact of
DMCs/DSMBs on Decisions for Dosage Changes or Changes in Sample
Size
2 - 3. DSMB/DMC
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Data Safety Monitoring Board (DSMB) or Data Monitoring Committee (DMC) as defined in FDA Guidance Establishment and Operation of Clinical Trial Data Monitoring Committees:
a group of individuals with pertinent expertise that reviews on a regular basis accumulating data from one or more ongoing clinical trials.
DMC advises the sponsor regarding the continuing safety of trial subjects and those yet to be recruited to the trial, as well as the continuing validity and scientific merit of the trial. - 4. DSMB/DMC
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DSMB periodically inspects interim looks at the data (prior to all planned patients being treated and followed) and makes recommendations about trial design/conduct based on these interim looks including:
Continue trial as initially planned.
Safety:
Potentially stop the trial early if reasonable evidence of harm of new product (or dose) or control product
Often based on incidence of AEs or serious AEs
DMC safety recommendations not necessarily based on formal statistical rules - 5. DSMB/DMC
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Example of DSMB Safety Recommendation
Double-blinded trial (randomized): Placebo versus Experimental treatment in high risk population
Patients scheduled to be treated over several months
After the first 40 patients were enrolled (20 in each treatment group) and treated for 1 day to several weeks, DSMB inspected unblinded data:
Experimental treatment had 4 life threatening serious adverse events (SAEs)
Placebo group had none
P-value=0.1060
DSMB Recommendation was to terminate study despite non-significant safety p-value - 6. DSMB/DMC
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Example of DSMB Safety Recommendation (contd)
DMC Recommendation to stop trial was not easy
Perhaps benefit of drug outweighed the risk? Tough to tell at this early stage, but it was thought perhaps it was best not to wait to find out.
Sponsor does not necessarily need to follow DSMB recommendation
E.g., Sponsor may decide:
Continue trial as is
Temporarily halt trial until further investigation
Discuss with DSMB/DMC & regulatory agency reason for not following recommendation - 7. DSMB/DMC
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Example of DSMB Safety Recommendation (contd)
Sponsor does not necessarily need to follow DSMB recommendation (contd)
Potential issue if trial continues:
Sponsor was made aware of the 4 experimental group SAEs during DSMB deliberations
Will this awareness affect subsequent study conduct (even unintentionally), causing bias in remaining safety data?
Perception of bias?
Suppose SAE prevalence evened out at end of study? - 8. DSMB/DMC
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DSMB periodically inspects interim looks at the data (prior to all patients being treated and followed) and makes recommendations about trial conduct including:
Efficacy (Adapt the trial) (contd):
Change primary endpoint (not common -- in my experience)
Remove non-efficacious dose(s) (for multi-dose trials);
Requires formal statistical rules in order to:
Not increase Type I Error rate or significance level (chance of a false positive trial)
Minimize Type II Error rate (chance of false negative trial)
DSMB/DMC unblinded or partially unblinded - 9. DSMB/DMC Committee Composition
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Discussed in Section 4.1 of FDA Guidance
Sponsor/Steering Committee appoints DMC
CRO also sometimes asked by Sponsor to appoint DMC
Members consist of
At least 2 clinicians
At least 1 statistician
May also have other members; e.g.,
Ethicist for high risk/vulnerable populations
Non-scientist; e.g., consumer rep; patient (not in trial) - 10. DSMB/DMC Committee Composition
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Ideally, DSMB/DMC members should have
Experience in indication being studied
Clinical trials experience
DSMB/DMC experience
Especially important for statistician on DSMB/DMC
All members may not have all 3
Opinion: Especially important for
Statistician to have at least b and c;
Clinician/physician to have at least a (and b); - 11. DSMB/DMC Committee Composition
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Statistician should also have:
Experience in statistical methods for clinical trials
Experience in statistical rules for adapting design
Members should be independent from Sponsor
Not a sponsor employee
Not an investigator
No involvement in the study conduct or analysis planning
No serious conflicts of interests
All potential conflicts disclosed prior to each meeting - 12. DSMB/DMC Committee Composition
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Each DSMB/DMC has a chair.
Chosen by sponsor and other DSMB/DMC members
FDA Guidance: chair capable of facilitating discussion/integrating different points of view.
Chair provides DSMB/DMCs recommendation of future study conduct to sponsor or steering committee
After inspection of interim data, DSMB/DMC members vote on a recommendation for future conduct of study
Works best if odd number of DSMB/DMC voting members - 13. Statisticians in DSMBs
Often 3 statisticians involved in the DSMB/DMC process
DSMB/DMC Statistician
Voting member of DSMB/DMC; helps interpret statistical aspect of results to other voting members, especially adaptive results and statistical repercussions of adapting the design.
Analysis Statistician
Generates interim results (often not a Sponsor employee)
Unblinded to treatment group for each patient
Independent Statistician
Presents results to DSMB/DMC; answers DSMB/DMC statistical questions
Non-voting
Go-between between DSMB and Analysis Statistician
All statisticians are not to be involved in analysis of final data or analysis planning - 14. Fixed Design
Fixed clinical trial design (2 treatments)
Compare cure rate across two anti-infectives:
Specify an appropriate (superiority) null and alternative hypothesis:
H0: E = C
H1: E C
where E and Care the true sensitivities of the experimental and control diagnostic, respectively.
To calculate sample size, make assumption of the true E, C
Determine sample size required to yield adequate power to reject H0 in favor of H1 at a given significance level
14 - 15. Fixed Design
Fixed clinical trial design example (contd)
For determining sample size, assume
E =0.80 and C =0.70
Two-sided 0.05 level of significance (false positive rate)
Desire 80% Power
1:1 Treatment Allocation
Sample size per group (using two-sample z-test for proportions): 294 per group
15 - 16. Adaptive Trial Designs
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Adaptive designs allow for re-designing the trial at some point during the trial, usually based on interim look(s) at aggregate efficacy data
Stop trial for futility of experimental diagnostic
Stop trial for overwhelming efficacy
Increase sample size to ensure adequate (conditional) power by end of study
Decrease sample size if (conditional) power >>original power
Remove non-efficacious dose in dose-finding study
Change primary endpoint - 17. Adaptive Trial Designs
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The interim look at the data can be blinded or unblinded.
Adapting the design of the study often has statistical repercussions, especially if re-design is based on an unblinded analysis
Here, we will focus on adapting trial based on an unblinded interim analysis.
Also may have operational repercussions - 18. Issues to Consider
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Once DSMB gives recommendations arrive, could bias in final results occur?
If DSMB says increase the sample size by xx:
if Sponsor follows recommendation, study personnel may realize the product may be efficacious, and just needs a little more sample size to prove its efficacy with good confidence.
Cause bias in future study conduct?
If Sponsor does not follow recommendation, does Sponsor feel product then has small chance of being efficacious and bias remainder of study?
E.g., may move resources off study, slowing study down or reducing quality? - 19. Issues to Consider
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Once DSMB gives recommendations arrive, bias could result
If DSMB/DMC recommends continue the study as is,
Study personnel who may not understand the requirement for overwhelming efficacy, may think the product is not efficacious, otherwise study would have stopped for efficacy?
Causes bias on remaining study personnel? - 20. Dosage Change
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Most pivotal (Phase III) drug/biologic trials contain one dose of the experimental treatment and a control group
Some Phase III may contain more than one dose of experimental however (especially those that may skip Phase II to get product to market faster in case of serious illness, e.g., ALS)
Many Phase IIs have multiple doses of experimental to determine the dose of study in future pivotal Phase III - 21. Dosage Change
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Suppose we have a trial with multiple doses of experimental treatment, and one control group
Formal efficacy rules can be built in to drop inefficacious dose after interim analysis;
E.g., drop dose(s) with CP