|Title||Enriched biomarker-driven clinical trials.|
|Publication Type||Web Article|
|Year of Publication||2019|
|Authors||Wang, Xiaofei, Jianwen Cai, and Stephen L. George|
|Series Title||Wiley StatsRef: Statistics Reference Online|
Commonly used designs for clinical trials involving biomarkers include targeted design, biomarker‐stratified design (BSD), and biomarker‐guided (strategy) design (BGD). This article gives details of these designs and discusses their strengths and drawbacks. For these designs, efficiency of testing certain treatment parameters can often be improved by enrichment, increasing the proportion of biomarker‐positive patients, especially when the proportion of biomarker positives is low in the underlying patient population. An enriched biomarker‐stratified design (EBSD) enriches the cohort of randomized patients by directly oversampling the relevant patients with the true biomarker based on the biomarker value. When the cost or difficulty of assessing the true biomarker for all patients prior to randomization is high, one can also improve efficiency by oversampling biomarker positives based on a cheaper auxiliary variable or a surrogate biomarker that correlates with the true biomarker, using an auxiliary‐variable‐enriched biomarker‐stratified design (AEBSD). For both enriched designs, we discuss how to choose the optimal enrichment proportion when testing a single hypothesis or two hypotheses simultaneously.
|Original Publication||Enriched biomarker-driven clinical trials.|