Non-proportional hazards model with a PVF frailty term : application with a melanoma dataset

© 2024 Informa UK Limited, trading as Taylor & Francis Group.

Bibliographische Detailangaben
Veröffentlicht in:Journal of applied statistics. - 1991. - 52(2025), 1 vom: 18., Seite 1-27
1. Verfasser: Rosa, Karen C (VerfasserIn)
Weitere Verfasser: Calsavara, Vinicius F, Louzada, Francisco
Format: Online-Aufsatz
Sprache:English
Veröffentlicht: 2025
Zugriff auf das übergeordnete Werk:Journal of applied statistics
Schlagworte:Journal Article 62N02 62N03 Cure rate models generalized time-dependent log-log model maximum likelihood estimation random effects skin cancer
Beschreibung
Zusammenfassung:© 2024 Informa UK Limited, trading as Taylor & Francis Group.
Survival data analysis often uses the Cox proportional hazards (PH) model. This model is widely applied due to its straightforward interpretation of the hazard ratio under the assumption that the hazard rates for two subjects remain constant over time. However, in several randomized clinical trials with long-term survival data comparing two new treatments, it is frequently observed that Kaplan-Meier plots exhibit crossing survival curves. This violation of the PH assumption of the Cox PH model can not be applied to evaluate the treatment's effect on survival. This paper introduces a novel long-term survival model with non-PH that incorporates a frailty term into the hazard function. This model allows us to examine the effect of prognostic factors on survival and quantify the degree of unobservable heterogeneity. The model parameters are estimated using the maximum likelihood estimation procedure, and we evaluate the performance of the proposed models through simulation studies. Additionally, we demonstrate the applicability of our approach by fitting the models to a real skin cancer dataset
Beschreibung:Date Revised 15.05.2025
published: Electronic-eCollection
Citation Status PubMed-not-MEDLINE
ISSN:0266-4763
DOI:10.1080/02664763.2024.2354443