Volume 17, Issue 4 (11-2018)                   TB 2018, 17(4): 70-80 | Back to browse issues page

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Mohamadzadeh M, Falahzadeh H, Pahlevani N, Pahlevani V. The superiority of Bayesian method in the analysis of 8-year survival of breast cancer and its determinants in Yazd. TB. 2018; 17 (4) :70-80
URL: http://tbj.ssu.ac.ir/article-1-2622-en.html
Shahid Sadoughi University of Medical Sciences, Yazd, Iran. , vida.pahlevani@gmail.com
Abstract:   (605 Views)
Introduction: Breast cancer is one of the common diseases among women with various factors involved in its development. The aim of this study was to determine the factors affecting the survival of women with breast cancer in Yazd using Cox's model as Bayesian and Classic.
Method: A population-based study of 538 breast cancer women registered in the clinical database of the Ramezanzade Radiotherapy Center from the April 2005 until March 2012. Comprehensive data on prognostic factors, comorbidity and treatment together with complete follow-up for survival were used to evaluate improvements in mortality. Data was analyzed by R 3.4.2. 0.05 was considered as the significance level.
Findings: The mean age of breast cancer diagnosis was 48.03±11016 years. The 1, 5  and 8-year cumulative survivals for breast cancer patients were 0.976 ,0.898, 0.823 and 0.737 respectively. Bayesian Cox regression showed thatSurgery (HR=1.631  95%PI; 1.102-2.422) ki67 (HR = 3.260. 95%PI; 1.6308-6.372) stage (HR=5.620, 95%PI; 4.079-7.731)   lymph node (HR= 1.765, 95%PI; 1.127-2.790)  and ER(HR = 2. 600  95%PI; 2.023-3.354) were significantly related to survival.
Discussion Due to a very low error (<0/0001) and a shorter confidence interval for the risk ratio, the Cox Bayesian model of optimal model was selected and according to the variables of the stage of disease and lymph node involvement and the type of surgery and the markers Ki67 and ER on the risk Death has a positive impact. The use of the Bayesian method in survival analysis gives greater credibility to previous results.
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Type of Study: Research | Subject: Special
Received: 2017/11/8 | Accepted: 2018/02/14 | Published: 2018/12/8

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