Fitting Cure Rate Model to Breast Cancer Data of Cancer Research Center

Baghestani, Ahmad Reza; Zayeri, Farid; Akbari, Mohammad Esmaeil; Shojaee, Leyla; Khadembashi, Naghmeh; Shahmirzalou, Parviz

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자료유형: 학술저널

저자정보: Baghestani, Ahmad Reza (Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical sciences) Zayeri, Farid (Department of Biostatistics, School of Allied Medical Sciences, Shahid Beheshti University of Medical sciences) Akbari, Mohammad Esmaeil (Cancer Research Center, Shahid Beheshti University of Medical sciences) Shojaee, Leyla (Cancer Research Center, Shahid Beheshti University of Medical sciences) Khadembashi, Naghmeh (Department of Englishsh language, School of Allied Medical Sciences, Shahid Beheshti University of Medical sciences) Shahmirzalou, Parviz (Cancer Research Center, Shahid Beheshti University of Medical sciences)

저널정보: 아시아태평양암예방학회 Asian Pacific journal of cancer prevention : APJCP Asian Pacific journal of cancer prevention : APJCP 제16권 제17호

발행연도: 2015.1

수록면: 7,923 - 7,927 (5page)

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Background: The Cox PH model is one of the most significant statistical models in studying survival of patients. But, in the case of patients with long-term survival, it may not be the most appropriate. In such cases, a cure rate model seems more suitable. The purpose of this study was to determine clinical factors associated with cure rate of patients with breast cancer. Materials and Methods: In order to find factors affecting cure rate (response), a non-mixed cure rate model with negative binomial distribution for latent variable was used. Variables selected were recurrence cancer, status for HER2, estrogen receptor (ER) and progesterone receptor (PR), size of tumor, grade of cancer, stage of cancer, type of surgery, age at the diagnosis time and number of removed positive lymph nodes. All analyses were performed using PROC MCMC processes in the SAS 9.2 program. Results: The mean (SD) age of patients was equal to 48.9 (11.1) months. For these patients, 1, 5 and 10-year survival rates were 95, 79 and 50 percent respectively. All of the mentioned variables were effective in cure fraction. Kaplan-Meier curve showed cure model's use competence. Conclusions: Unlike other variables, existence of ER and PR positivity will increase probability of cure in patients. In the present study, Weibull distribution was used for the purpose of analysing survival times. Model fitness with other distributions such as log-N and log-logistic and other distributions for latent variable is recommended.

#Breast neoplasms #cure fraction #cure rate model #negative binomial distribution #survival analysis

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Baghestani, Ahmad Reza

소속기관 Department of Biostatistics, Faculty of Paramedical Sciences, Shahid Beheshti University of Medical