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

Bayesian Kaplan-Meier Prostate cancer Survival Therapy type

Journal

Iranian journal of public health
ISSN: 2251-6093
Titre abrégé: Iran J Public Health
Pays: Iran
ID NLM: 7505531

Informations de publication

Date de publication:
Sep 2022
Historique:
received: 15 04 2021
accepted: 17 06 2021
entrez: 6 2 2023
pubmed: 7 2 2023
medline: 7 2 2023
Statut: ppublish

Résumé

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. 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. 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 ( 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.

Sections du résumé

Background UNASSIGNED
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 UNASSIGNED
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 UNASSIGNED
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 (
Conclusion UNASSIGNED
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.

Identifiants

pubmed: 36743368
doi: 10.18502/ijph.v51i9.10566
pii: IJPH-51-2108
pmc: PMC9884364
doi:

Types de publication

Journal Article

Langues

eng

Pagination

2108-2116

Informations de copyright

Copyright © 2022 Askari Tajabadi et al. Published by Tehran University of Medical Sciences.

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Auteurs

Nahid Askari Tajabadi (N)

Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.

Hamid Pakmanesh (H)

Department of Urology, Shahid Bahonar Hospital, Kerman University of Medical Sciences, Kerman, Iran.

Moghaddameh Mirzaee (M)

Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.

Yunes Jahani (Y)

Modeling in Health Research Center, Institute for Futures Studies in Health, Kerman University of Medical Sciences, Kerman, Iran.
Department of Biostatistics and Epidemiology, School of Public Health, Kerman University of Medical Sciences, Kerman, Iran.

Classifications MeSH