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Updated: Jan 21, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
On restricted optimal treatment regime estimation for competing risks data
Jie Zhou1, Jiajia Zhang1, Wenbin Lu2
1Department of Epidemiology and Biostatistics, University of South Carolina, 915 Greene Street, Columbia, SC 29208, USA.
Abstract:
It is well accepted that individualized treatment regimes may improve the clinical outcomes of interest. However, positive treatment effects are often accompanied by certain side effects. Therefore, when choosing the optimal treatment regime for a patient, we need to consider both efficacy and safety issues. In this article, we propose to model time to a primary event of interest and time to severe side effects of treatment by a competing risks model and define a restricted optimal treatment regime based on cumulative incidence functions. The estimation approach is derived using a penalized value search method and investigated through extensive simulations. The proposed method is applied to an HIV dataset obtained from Health Sciences South Carolina, where we minimize the risk of treatment or virologic failures while controlling the risk of serious drug-induced side effects.
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