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Phase II Design Strategies. Sally Hunsberger Ovarian Cancer Clinical Trials Planning Meeting May 29, 2009. Single arm Phase II study. Fact or fiction: Using single arm phase II study designs reduces the number of patients needed in drug development.
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Phase II Design Strategies Sally Hunsberger Ovarian Cancer Clinical Trials Planning Meeting May 29, 2009
Single arm Phase II study • Fact or fiction: • Using single arm phase II study designs reduces the number of patients needed in drug development
True: If the specified null rate is correct • How bad can things get if the null rate is specified incorrectly? • Need to consider the drug development cost (in terms of patients) • End of phase II if don’t go to phase III • End of phase II if go to phase III
Evaluation of designs • Look at expected sample size E[N] • E[N]=NII+NIII(P{continuing to phase III})
Phase II Design parameters • PFS as primary endpoint • Type I error and II error of .1 • Median null PFS = 3 months • Interesting activity would result in a median PFS of 4.5 (hazard ratio=1.5) • Minimum follow up=3 months • Sample size = 69
Phase III design parameters • OS as primary endpoint • Type I error 1-sided .025 • Median null OS = 6 months • Interesting activity would result in a median OS of 7.8 (hazard ratio=1.3) • Minimum follow up = 6 months • Sample size = 692
Under the null of no treatment benefit • What happens if we set the null bar too low • Go to phase III too often and this will increase the Expected sample size,E[N].
Under null hypothesis of no Treatment effect Null assumption is 3 months *Truth agrees with assumption. E[N] for a randomized phase II study is 271 with α=β=.1
Under the alternative of a treatment benefit • What happens if we set the null bar too high • Do not go to phase III often enough • This will decrease power of finding a treatment benefit at the end of drug development
Under Alternative hypothesis of a Treatment effect Null assumption is 3 months Treatment benefit of a hazard ratio of 1.5 *Truth agrees with assumption. Probability of concluding a benefit when a randomized phase II study is used .81
If we need a randomized phase II how can we speed up drug development • Phase II/III design • Futility analysis based on PFS • Study power for a conclusion on OS
Simulation study results • Performed simulation study so I could have correlated PFS and OS • Comparison designs: • Sequence of a randomized phase II study and then a randomized phase III • Skip phase II go right to a phase III with a futility analysis based on OS (appropriate if you don’t expect an effect on PFS)
Over all probability of concluding a benefit when it exists is .81
Conclusions • Single arm studies may appear to use less patients but if the null bar is set incorrectly this could have a major impact on E[N] and the probability of identifying a beneficial treatment • When there is no true treatment effect setting the bar two low increases the E[N] • When there is a true treatment effect and the bar is set too high the probability of identifying a beneficial treatment is reduced
Conclusions • integrated phase II/III design works well under the global null. • E[N] and E[T] were no larger than that of a randomized phase II study • E[N] and E[T] smaller than skipping the phase II study • integrated II/III better than the separate randomized phase II study under the global alternative • did not increase E[T] and E[N] when compared to skipping the phase II component.