August 20, 2003FDA Antiviral Drugs Advisory Committee Meeting 1 Statistical Considerations for...

August 20, 2003 FDA Antiviral Drugs Advisory Committee Meeting

1

Statistical Considerations for Topical Microbicide

Phase 2 and 3 Trial Designs:

A Regulatory Perspective

Rafia Bhore, Ph.D.

Greg Soon, Ph.D.

Division of Antiviral Drug Products

Food and Drug Administration


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Outline• Phase 2/3 Clinical Trial Design: An

Example• Two Arms or Three Arms ?• p-value (Single Trial vs. Two Trials)• Criteria for a “Win”/Success• Power Considerations• Sample Size Estimates• Other Considerations


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Phase 2/3 Clinical Trial Design

An Example


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To establish safety and efficacy of investigational microbicide in preventing HIV infection

Test Group Control Group 1 Control Group 2

Microbicide “Placebo”+ +

Condom Condom Condom-only

(“no-treatment”)


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Two Arms or Three Arms?


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“Placebo” Arm

• “Placebo” provides a means to blinding investigators and participants

• Maximizes the likelihood of obtaining an unbiased estimate of efficacy

• Can we assume “Placebo” is inert?– Antimicrobial activity of “Placebo” not

known/not proven.– Protective effect or harmful effect?


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Condom-only (“No-Treatment”) Arm

• Established standard for prevention of HIV

• Provide comparison of “real world” effectiveness in preventing transmission– Data on sexual behaviors associated with use

or non-use of microbicide products

• Single component of other arms containing gel + condom


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P-value (Single vs. Two Trials)(Significance Level = Probability of Type 1 error: false positive)


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Level of Evidence

Number of One-sided Two-sided Level ofTrials / 2 Evidence

1 0.025 0.05 One Trial

Single “large” 0.025^1.5 0.008 One-and-halfTrial

2 0.025 each 0.05 each Two Trials

Single “LARGE” 0.001 Two Trials

2 0.025^2 0.00125 Two Trials =0.000625

P-value <


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P-value (Two trials)

• Two trials (Regulatory Standards)– Trial 1 p-value < 0.05 (two-

sided)– Trial 2 p-value < 0.05 (two-

sided)

• Run in parallel or staggered in time?– If staggered, how much gap in time?


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P-value (One trial)

• Need to show as strong and robust evidence as two separate trials

• May not be repeatable– ethical concerns ?

• One trial: p-value < 0.001 (two-sided) (because 2x[0.025^2]=0.00125)

same as p-value < 0.0005 (one-sided)


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Replicating a Study Result• Probability of observing a statistically significant result

(e.g. p < 0.05) upon repetition of a clinical trial when the effect size observed in the first trial is assumed to be the true effect

Observed Probability of a significantp-value result (Power) in future

0.05 50%0.01 73%0.001 91%

Reference: Goodman (1992), Statistics in Medicine, 875-879


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Overall Level of Evidence

• p-value < 0.001 considered convincing

• p-value >= 0.01 would be inadequate

• p-value between 0.001 and 0.01 possibly adequate, provided that– results are consistent across various

subgroups

– other supportive evidence is strong


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Criteria for a “Win”/Success


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Definition of a “Win”

HIV infection rate in

Microbicide < “Placebo” p-value < 0.001 (two-sided)

AND

Microbicide < Condom-only p-value < 0.001 (two-sided)

Overall

= 0.001


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Why win versus “Placebo” arm?

• If the HIV infection rate in– Microbicide + Condom “Placebo”+Cond.

– Microbicide + Condom < Condom

– then is “Placebo” as effective as Microbicide? (does not prove efficacy of microbicide)


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Why win versus Condom-only?

• If the HIV infection rate in– Microbicide + Condom < “Placebo” + Cond.

– Microbicide + Condom Condom

– then the use of microbicide in conjunction with condom does not provide any additional protection than condom alone


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Definition of a “Win”

HIV infection rate in

Microbicide < “Placebo” p-value < 0.001 (two-sided)

AND

Microbicide < Condom-only p-value < 0.001 (two-sided)


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Sample Size Estimates


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Factors Affecting Sample Size

• HIV Seroincidence Rates in Control– 0.5, 6, 7, 9 per 100 person-years

• Effect Size (33%, 50%, … )

• Length of Follow-up– 12 / 24 months for each participant– Last patient completes 12 / 24 months

• Statistical Power (90%, 80%, …)


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Sample Size Estimates(Duration of study=24 months, Power=90%, =.001)

ControlRate

MicrobicideRate

EffectSize

Sample Size(N)

6% 4% 33% 12,5207% 4.67% 33% 10,7979% 6% 33% 8,5016% 3% 50% 4,9937% 3.5% 50% 4,3049% 4.5% 50% 3,385

Reference: Lachin,J. and M. Foulkes (Biometrics 1986)


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Power Considerations(Power = 1-Probability of Type II error [false negative])


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Example• Test two sets of hypotheses

H0: Microbicide+condom = “Placebo”+condom

HA: Microbicide+condom < “Placebo”+condom

H0: Microbicide+condom = Condom-only

HA: Microbicide+condom < Condom-only

• Calculate sample-size

– Power for each test is 90% at 33% reduction in HIV infection rate

from condom-only arm


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Power Curve:Varying Rates of Risk Reduction

from Placebo

-100% -67% -33% 0% 33% 67% 100%-50% 50%

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

33% reduction in HIV infection rate

Overall power for a win = 81.5%

Risk reduction rate from Placebo

Ove

rall

Po

we

r


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Other Considerations


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Follow-up

• Continue study until last subject enrolled completes at least 12 months on study

• Pro-active in following participants– actively pursue and identify reasons for

dropouts (safety issues?)– continue follow-up after study drug

discontinuation


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Condom + Microbicide Use Monitoring

• Collect data on use of condom and other barrier/drug use

• Efficacy evidence closely tied with compliance

• “Frequently” collect information on number of sexual acts

With microbicide Without microbicideWith condom x xWithout condom x x


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Allocation Ratio• Microbicide : Placebo : Condom-only

– Standard practice is to randomize 1:1:1– Alternatively randomize x: y: z

• e.g., 3:2:2 or 1.5:1:1– More participants in microbicide arm than control

groups. Same number in both control groups

– Alternative allocation ratios will optimize overall power to detect a difference and increase safety data on microbicide arm.


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Summary

• Three-arm design will ensure that the first generation of microbicides is appropriately studied

• Single trial to show same level of evidence as two separate trials

• Sample size depends on assumptions

• Length of follow-up important in observing HIV endpoints.


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Acknowledgments

Dr. Teresa Wu, Medical Officer

Dr. Debra Birnkrant, Director

Division of Antiviral Drug Products, FDA

August 20, 2003FDA Antiviral Drugs Advisory Committee Meeting 1 Statistical Considerations for...

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