Authors
Vinicius F Calsavara
Published in
Biometrical journal. Biometrische Zeitschrift. Volume 68. Issue 5. Pages e70158.
Abstract
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.
PMID:
42629638
Bibliographic data and abstract were imported from PubMed on 22 Aug 2026.
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