Abstract
Predictive and prognostic biomarkers are increasingly important in clinical research and practice. Biomarker studies are frequently embedded in randomized clinical trials with biospecimens collected at baseline and assayed for biomarkers, either in real time or retrospectively. This article proposes efficient estimation strategies for two study settings in terms of biomarker ascertainment: a complete-data setting in which the biomarker is measured for all subjects in the trial, and a two-phase sampling design in which the biomarker is measured retrospectively for a random subsample of subjects selected in an outcome-dependent fashion. In both settings, efficient estimating functions are characterized using semiparametric theory and approximated using data-adaptive machine learning methods, leading to estimators that are consistent, asymptotically normal and (approximately) efficient under general conditions. The proposed methods are evaluated in simulation studies and applied to real data from two biomarker studies, one in each setting.
Funding Statement
This research was supported in part by the intramural research programs of the Eunice Kennedy Shriver National Institute of Child Health and Human Development and the National Heart, Lung and Blood Institute, National Institutes of Health.
Research of W. Zhang was partially supported by the National Natural Science Foundation of China [grant numbers 12001522, 72091212].
Acknowledgments
This manuscript was prepared using data from Data set NCT00644228-D1 from the NCTN/NCORP Data Archive of the National Cancer Institute’s (NCI’s) National Clinical Trials Network (NCTN). Data were originally collected from clinical trial NCT number NCT00644228 “Lenalidomide and Dexamethasone With or Without Bortezomib in Treating Patients With Previously Untreated Multiple Myeloma.” All analyses and conclusions in this manuscript are the sole responsibility of the authors and do not necessarily reflect the opinions or views of the clinical trial investigators, the NCTN, the NCORP or the NCI.
Citation
Wei Zhang. Zhiwei Zhang. James F. Troendle. Aiyi Liu. "Data-adaptive efficient estimation strategies for biomarker studies embedded in randomized trials." Ann. Appl. Stat. 16 (4) 2250 - 2265, December 2022. https://doi.org/10.1214/21-AOAS1588
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