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

Lookup NU author(s): Professor James WasonORCiD

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This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0).


Abstract

© 2021 The Authors. Biometrics published by Wiley Periodicals LLC on behalf of International Biometric Society. 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 traditional one-biomarker-at-a-time screening procedure in highly correlated data. We also exemplify our approach in two real clinical trial data applications.


Publication metadata

Author(s): Wang J, Patel A, Wason JMS, Newcombe PJ

Publication type: Article

Publication status: Published

Journal: Biometrics

Year: 2021

Pages: epub ahead of print

Online publication date: 15/01/2021

Acceptance date: 31/12/2020

Date deposited: 24/03/2021

ISSN (print): 0006-341X

ISSN (electronic): 1541-0420

Publisher: Wiley-Blackwell Publishing Ltd

URL: https://doi.org/10.1111/biom.13424

DOI: 10.1111/biom.13424


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Funding

Funder referenceFunder name
MC_UU_00002/6
MC_UU_00002/9
MR/R502303/1

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