Lifetime Data Anal - Analysis of cure rate survival data under proportional odds model.

Tópicos

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Resumo

Due to significant progress in cancer treatments and management in survival studies involving time to relapse (or death), we often need survival models with cured fraction to account for the subjects enjoying prolonged survival. Our article presents a new proportional odds survival models with a cured fraction using a special hierarchical structure of the latent factors activating cure. This new model has same important differences with classical proportional odds survival models and existing cure-rate survival models. We demonstrate the implementation of Bayesian data analysis using our model with data from the SEER (Surveillance Epidemiology and End Results) database of the National Cancer Institute. Particularly aimed at survival data with cured fraction, we present a novel Bayes method for model comparisons and assessments, and demonstrate our new tool's superior performance and advantages over competing tools.

Resumo Limpo

due signific progress cancer treatment manag surviv studi involv time relaps death often need surviv model cure fraction account subject enjoy prolong surviv articl present new proport odd surviv model cure fraction use special hierarch structur latent factor activ cure new model import differ classic proport odd surviv model exist curer surviv model demonstr implement bayesian data analysi use model data seer surveil epidemiolog end result databas nation cancer institut particular aim surviv data cure fraction present novel bay method model comparison assess demonstr new tool superior perform advantag compet tool

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