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]=N II +N III (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].

True Median PFSP{continuing}E[N] 3*3* * Truth agrees with assumption. E[N] for a randomized phase II study is 271 with α=β=.1 Under null hypothesis of no Treatment effect Null assumption is 3 months

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

True Median PFSP{continuing}Probability of concluding a OS benefit at the end of Phase III 3*3* * Truth agrees with assumption. Probability of concluding a benefit when a randomized phase II study is used.81 Under Alternative hypothesis of a Treatment effect Null assumption is 3 months Treatment benefit of a hazard ratio of 1.5

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)

DesignsGlobal NullGlobal Alternative α1α1 t1t1 E[N]E[T]E[N]E[T] Futility based on overall survival Sequence of Phase II and Phase III Integrated II/III with (f 1 =0) Integrated II/III with (f 1 =3) 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.