An experimental oncology immunotherapy may have the potential to be effective in a large number of tumor indications. We have considered a staggered approach for efficacy screening in subjects with an unmet medical need. A cohort of tumor indications is selected for the first wave investigation and the second wave investigation in a different cohort of tumor indications is initiated only after the drug has been demonstrated to be effective in the first wave. The effectiveness of an experimental immunotherapy is unknown at the planning stage, and the assumptions at the planning stage are subject to revision later on. How many tumor indications should be investigated in the first wave for the development program to be cost-effective amid the uncertainties? We attempt to answer this question by maximizing a benefit-cost ratio, defined to be the expected number of effective tumor indications correctly identified in the two waves (benefit) divided by the expected total sample size in the two waves and the subsequent trials for more definitive testing triggered by those with a positive outcome in the first wave (cost). It is found from the benefit-cost ratio analyses that, depending on resource availability, three to five tumor indications may be initiated in the first wave to properly balance the risk and benefit, and adequate investment is important to maintain the quality of statistical design.
Keywords: Decision analysis; Two-stage design; Type III error.
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