Abstract
Biomarker targeted two-stage adaptive design is used increasingly in early-stage clinical trials in a variety of therapeutic areas including oncology, where the sample size of the trial is re-estimated based on the first stage data. In such trials often the sample size is moderate, and so incorporating prior information and using robust methods are desirable.
Highlights
Biomarker targeted two-stage adaptive design is used increasingly in early-stage clinical trials in a variety of therapeutic areas including oncology, where the sample size of the trial is re-estimated based on the first stage data
Biomarker targeted design is an important step towards precision medicine, which can improve efficiency of randomized clinical trial [1,2]
The final sample size re-estimation is based on the positive predict value (PPV), the proportion of true positives among test positives, estimated from the first stage data, deviates slight from a more common adaptive designs [14,15,16]
Summary
Biomarker targeted design is an important step towards precision medicine, which can improve efficiency of randomized clinical trial [1,2]. The two or three stage designs are commonly used in recent phase IIb-IIIa trials comparing treatment vs control. Such sequential monitoring has become an integral part of clinical trial. Gao, Roy, and Tan [12,13] proposed a two-stage adaptive design for biomarker targeted population where only biomarker positive subjects enter the trial study.
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