ArticleAdvanced biomedical research2021
Determination of the Risk Factors for Breast Cancer Survival using the Bayesian Method, Yazd, Iran.
Article in Advanced biomedical research, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundThere are numerous sophisticated studies which have investigated risk factors of breast cancer (BC). The purpose of this paper is to use benefits of Bayesian modeling to involve such prior information in determining factors affecting the survival of women with BC in Yazd city. MATERIALS AND
methodsThe checklist included the characteristics of the patients and the factors studied. Then, from the records of patients referred to Radiotherapy Center of Shahid Ramezanzadeh, who had BC, from April 2005 to March 2012, the survival of 538 persons was recorded in the census. Data were analyzed by R software version 3.4.2, and 0.05 was considered the significance level.
resultsThe mean age of BC diagnosis was 48.03 ± 11016 years. The Bayesian Cox regression showed that surgery (hazard ratio [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 time.
conclusionThe parametric and cox models were compared with standard error, and Cox model was selected as an optimal model. Accordingly, stage, ki67, lymph node, ER, and surgery variables had a positive effect on death hazard.
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