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Updated: May 31, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
Application of hazard models for patients with breast cancer in Cuba
Abstract:
There has been a rapid development in hazard models and survival analysis in the last decade. This article aims to assess the overall survival time of breast cancer in Cuba, as well as to determine plausible factors that may have a significant impact in the survival time. The data are obtained from the National Cancer Register of Cuba. The data set used in this study relates to 6381 patients diagnosed with breast cancer between January 2000 and December 2002. Follow-up data are available until the end of December 2007, by which time 2167 (33.9%) had died and 4214 (66.1%) were still alive. The adequacy of six parametric models is assessed by using their Akaike information criterion values. Five of the six parametric models (Exponential, Weibull, Log-logistic, Lognormal, and Generalized Gamma) are parameterized by using the accelerated failure-time metric, and the Gompertz model is parameterized by using the proportional hazard metric. The main result in terms of survival is found for the different categories of the clinical stage covariate. The survival time among patients who have been diagnosed at early stage of breast cancer is about 60% higher than the one among patients diagnosed at more advanced stage of the disease. Differences among provinces have not been found. The age is another significant factor, but there is no important difference between patient ages.
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