Two-stage penalized regression screening to detect biomarker-treatment interactions in randomized clinical trials.
Publication Date
2022-03Journal Title
Biometrics
ISSN
0006-341X
Publisher
Wiley
Volume
78
Issue
1
Pages
141-150
Language
en
Type
Article
This Version
AO
VoR
Metadata
Show full item recordCitation
Wang, J., Patel, A., Wason, J. M., & Newcombe, P. J. (2022). Two-stage penalized regression screening to detect biomarker-treatment interactions in randomized clinical trials.. Biometrics, 78 (1), 141-150. https://doi.org/10.1111/biom.13424
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 traditional one-biomarker-at-a-time screening procedure in highly correlated data. We also exemplify our approach in two real clinical trial data applications.
Keywords
BIOMETRIC METHODOLOGY, biomarker, clinical trial, interaction, randomization, ridge regression, screening
Sponsorship
MRC (1965771)
Identifiers
biom13424
External DOI: https://doi.org/10.1111/biom.13424
This record's URL: https://www.repository.cam.ac.uk/handle/1810/335627
Rights
Licence:
http://creativecommons.org/licenses/by/4.0/
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