Two-stage penalized regression screening to detect biomarker-treatment interactions in randomized clinical trials.

ABSTRACT: High-dimensional biomarkers such as genomics are increasingly being measured in randomized clinical trials. Consequently, there is a growing interest in developing methods that improve the power to detect biomarker-treatment interactions. We adapt recently proposed two-stage interaction detecting procedures in the setting of randomized clinical trials. We also propose a new stage 1 multivariate screening strategy using ridge regression to account for correlations among biomarkers. For this multivariate screening, we prove the asymptotic between-stage independence, required for familywise error rate control, under biomarker-treatment independence. Simulation results show that in various scenarios, the ridge regression screening procedure can provide substantially greater power than the trad

SUBMITTER: Wang J 

PROVIDER: S-EPMC7613856 | biostudies-literature | 2022 Mar

REPOSITORIES: biostudies-literature