Efficient screening of predictive biomarkers for individual treatment selection.
empirical Bayes
false discovery rate
optimal discovering procedure
propensity score
Journal
Biometrics
ISSN: 1541-0420
Titre abrégé: Biometrics
Pays: United States
ID NLM: 0370625
Informations de publication
Date de publication:
03 2021
03 2021
Historique:
received:
07
05
2019
revised:
27
03
2020
accepted:
30
03
2020
pubmed:
16
4
2020
medline:
26
10
2021
entrez:
16
4
2020
Statut:
ppublish
Résumé
The development of molecular diagnostic tools to achieve individualized medicine requires identifying predictive biomarkers associated with subgroups of individuals who might receive beneficial or harmful effects from different available treatments. However, due to the large number of candidate biomarkers in the large-scale genetic and molecular studies, and complex relationships among clinical outcome, biomarkers, and treatments, the ordinary statistical tests for the interactions between treatments and covariates have difficulties from their limited statistical powers. In this paper, we propose an efficient method for detecting predictive biomarkers. We employ weighted loss functions of Chen et al. to directly estimate individual treatment scores and propose synthetic posterior inference for effect sizes of biomarkers. We develop an empirical Bayes approach, namely, we estimate unknown hyperparameters in the prior distribution based on data. We then provide efficient screening methods for the candidate biomarkers via optimal discovery procedure with adequate control of false discovery rate. The proposed method is demonstrated in simulation studies and an application to a breast cancer clinical study in which the proposed method was shown to detect the much larger numbers of significant biomarkers than existing standard methods.
Substances chimiques
Biomarkers
0
Types de publication
Journal Article
Research Support, Non-U.S. Gov't
Langues
eng
Sous-ensembles de citation
IM
Pagination
249-257Subventions
Organisme : Japan Society for the Promotion of Science
ID : JP15K15954
Organisme : Japan Society for the Promotion of Science
ID : JP16H07406
Organisme : Japan Society for the Promotion of Science
ID : JP17K19808
Organisme : Japan Science and Technology Agency
ID : JPMJCR18Z9
Organisme : Core Research for Evolutional Science and Technology
ID : JPMJCR1412
Informations de copyright
© 2020 The International Biometric Society.
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