Optimal treatment regimes for competing risk data using doubly robust outcome weighted learning with bi-level variable selection. Comput Stat Data Anal 2021 Jun;158
Date
05/18/2021Pubmed ID
33994608Pubmed Central ID
PMC8117077DOI
10.1016/j.csda.2021.107167Scopus ID
2-s2.0-85100560774 (requires institutional sign-in at Scopus site) 4 CitationsAbstract
The goal of the optimal treatment regime is maximizing treatment benefits via personalized treatment assignments based on the observed patient and treatment characteristics. Parametric regression-based outcome learning approaches require exploring complex interplay between the outcome and treatment assignments adjusting for the patient and treatment covariates, yet correctly specifying such relationships is challenging. Thus, a robust method against misspecified models is desirable in practice. Parsimonious models are also desired to pursue a concise interpretation and to avoid including spurious predictors of the outcome or treatment benefits. These issues have not been comprehensively addressed in the presence of competing risks. Recognizing that competing risks and group variables are frequently present, we propose a doubly robust estimation with adaptive L 1 penalties to select important variables at both group and within-group levels for competing risks data. The proposed method is applied to hematopoietic cell transplantation data to personalize the graft source choice for treatment-related mortality (TRM). While the existing medical literature attempts to find a uniform solution ignoring the heterogeneity of the graft source effects on TRM, the analysis results show the effect of the graft source on TRM could be different depending on the patient-specific characteristics.
Author List
He Y, Kim S, Kim MO, Saber W, Ahn KWAuthors
Kwang Woo Ahn PhD Professor in the Institute for Health and Equity department at Medical College of WisconsinSoyoung Kim PhD Associate Professor in the Institute for Health and Equity department at Medical College of Wisconsin
Wael Saber MD, MS Professor in the Medicine department at Medical College of Wisconsin
