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Semiparametric estimation of the cure fraction in population‐based cancer survival analysis
Author(s) -
Gu Ennan,
Zhang Jiajia,
Lu Wenbin,
Wang Lianming,
Felizzi Federico
Publication year - 2020
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/sim.8693
Subject(s) - estimation , population , medicine , mortality rate , demography , statistics , breast cancer , survival analysis , cancer , fraction (chemistry) , epidemiology , surveillance, epidemiology, and end results , proportional hazards model , cancer registry , econometrics , mathematics , environmental health , chemistry , management , organic chemistry , sociology , economics
With rapid development in medical research, the treatment of diseases including cancer has progressed dramatically and those survivors may die from causes other than the one under study, especially among elderly patients. Motivated by the Surveillance, Epidemiology, and End Results (SEER) female breast cancer study, background mortality is incorporated into the mixture cure proportional hazards (MCPH) model to improve the cure fraction estimation in population‐based cancer studies. Here, that patients are “cured” is defined as when the mortality rate of the individuals in diseased group returns to the same level as that expected in the general population, where the population level mortality is presented by the mortality table of the United States. The semiparametric estimation method based on the EM algorithm for the MCPH model with background mortality (MCPH+BM) is further developed and validated via comprehensive simulation studies. Real data analysis shows that the proposed semiparametric MCPH+BM model may provide more accurate estimation in population‐level cancer study.