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Updated: Aug 23, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
A Novel Approach for Analyzing Non-Proportional Hazards With Long-Term Survivors: The Defective Yang-Prentice Model
1Department of Computational Biomedicine, Biostatistics Shared Resource, Cedars-Sinai Health Sciences University, Los Angeles, California, USA.
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In survival analysis, addressing non-proportional hazards and the presence of long-term survivors poses substantial methodological challenges, as traditional models often fail to capture these features adequately. To overcome these limitations, a novel long-term survival model is proposed that integrates the Yang and Prentice framework with a defective Gompertz distribution. The proposed model provides a robust approach for analyzing time-to-event data with non-proportional hazards and a cure fraction. Comprehensive simulation studies and an application to colorectal cancer data illustrate its flexibility in capturing time-varying hazard ratios and long-term survivors, making it a useful alternative to existing methods.
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