The Evaluation of Survival Rate in Patients with Prostate Cancer by Bayesian Weibull Parametric Accelerated Failure-Time Model

Abstract

Background: Prostate cancer is the most prevalent malignancy in men. This study was carried out to determine effective factors on the survival rate of patients diagnosed with prostate cancer in Kerman, Iran.
 Methods: The present study was conducted as a retrospective cohort of 238 patients diagnosed with prostate cancer from 2011 to 2019 in Kerman, Iran. First, the demographic and clinical information of patients were collected. Then, the information on patient survival up to June 2019 was tracked, and their latest statuses of death or survival were recorded. Kaplan-Meier method, log-rank test, and Bayesian Weibull parametric accelerated failure- time model were used for data analysis. Data analysis was carried out by Stata and SAS.
 Results: The mean age of patients in the diagnosis was 73.28±10.08 year. The patient’s 1, 2, 3 and 5-years of overall survival rates were equal to 78.54%, 65.97%, 56.64% and 49.30, respectively. Patients under surgical therapy relatively held longer survival times compared to the rest of the therapies. Patients under chemotherapy had shorter survival times. Age at diagnosis, occupation, chemotherapy, surgery, education, and smoking variables significantly affected patients’ survival (P<0.05).
 Conclusion: Patients' survival duration increases if the disease is diagnosed at younger ages and its preliminary development stages. Smoking cessation is strongly recommended after diagnosis, as it is associated with a lower survival rate. Patients who underwent radical prostatectomy surgery showed higher survival rates than radiotherapy, hormone ablation, or chemotherapy. Moreover, patients with higher education had more prolonged survival.