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05 June 2018

There has been a surge in designing clinical trials based on the assumption that a biomarker is predictive of treatment response. Patients are stratified by their biomarker signature, and one tests the null hypothesis of no treatment effect in either the full population or the targeted subgroup. However, in order to verify the predictability of a biomarker, it is essential that hypothesis be tested in the non-targeted subgroup too. In a Phase IIB oncology trial with progression free survival (PFS) endpoint, the data obtained can inform the Phase III design whether to restrict recruitment to just the targeted subgroup or not.

We propose a two-stage randomised Phase II population enrichment trial design, with PFS as the primary endpoint comparing an experimental drug with a control treatment. We adaptively test the null hypotheses of hazard ratios in both the targeted as well as the non-targeted subgroups, with strong control of the familywise error rate. It is assumed that the hazard ratio of the targeted subgroup is much less than that of non-targeted, since the drug is expected to be more beneficial for the biomarker-positive subpopulation.

Simulations for an example trial in non-small cell lung cancer show that the probability of recommending an enriched Phase III trial increases significantly with the hazard ratio in the non-targeted subgroup, and illustrate the efficiency achieved. Our adaptive design testing first in the non-targeted subgroup followed by testing in the targeted subgroup for a randomised controlled trial constitutes part of the proof of a biomarker’s predictability.

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