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Evaluating Influential Factors to Survival in Patients with Breast Cancer Using Bayesian Method
Mahan Bahman Ziyari1 , Amal Saki Malehi1 , Maedeh Raesizadeh1 , Mohammad Seghatoleslami1 , Mehran Hoseinzade1 , Elham Maraghi 2
1- Ahvaz Jundishapur University of Medical Sciences
2- Ahvaz Jundishapur University of Medical Sciences , e.maraghi@gmail.com
Abstract:   (72 Views)
Background and Aim: Breast cancer is the most important cause of cancer death in women. The purpose of this study was to evaluate the effect of Estrogen Receptor (ER), Human Epidermal Growth Receptor (HER2) and other factors on post-surgical survival of patients with breast cancer using Bayesian approach in proportional hazards parametric survival models.
Materials and Methods: This study is a retrospective one. In this study, the data of 165 breast cancer patients who underwent surgery at Ahvaz Healing Diagnostic Center during 2004-2014 were recorded in a data collection form. The variables of age, tumor size, number of lymph nodes involved, grade, ER status and HER2 status were evaluated. Survival time was calculated from the date of surgery to death, or termination of study (September 2015), by month. In the Bayesian approach of parametric survival analysis models with proportional hazards, the lateral distribution of parameters was estimated using the MCMC. Also, the efficiency of the models was evaluated using the information deviation criterion. All data analysis steps were performed in Stata15 software. Significance coefficients of the model were determined using the 95% Credible Interval.
Results: The mean and standard deviation of age were 46.40 and 9.94 years, respectively. Deviance information criterion for Weibull parametric model was lower than other parametric models. Based on the Bayesian estimation of the Weibullchr('39')s proportional hazards parametric model, tumor size (HR = 1.40), the number of involved lymph nodes (HR = 1.016), Ki67 status (HR = 1.115), tumorchr('39')s grade (HR = 1.022), HER2 status (HR = 1.760) and ER status (HR = 1.381) had a positive effect on time to death.
Conclusion: Based on the Bayesian proportional hazards Weibull model, tumor size, the number of involved lymph nodes, Ki67, tumorchr('39')s grade, HER2 and ER had a positive effect on time to death.
Keywords: Breast cancer, Survival Analysis, Proportional Hazards Parametric Models, Bayesian Estimation, Estrogen Receptor (ER), Human Epidermal Growth Receptor (HER2)
     
Type of Study: Research | Subject: General
Received: 2019/10/6 | Accepted: 2020/12/19
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Ethics code: IR.AJUMS.REC.1398.034


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مجله علمی دانشگاه علوم پزشکی کردستان Scientific Journal of Kurdistan University of Medical Sciences
مجله علمی دانشگاه علوم پزشکی کردستان Scientific Journal of Kurdistan University of Medical Sciences
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