Original Article

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.

1. Mousavi SM, Gouya MM, Ramazani R, et al (2009). Cancer incidence and mortality in Iran. Ann Oncol, 20: 556-63.
2. Zarei M, Mirzaee M, Alizadeh H,et al (2021). Investigation of the affective factors on the survival rate of patients with laryngeal cancer using Cox proportional hazards and Lin -Ying's additive hazards models. Med J Islam Repub Iran, 35:16.
3. Bray F, Ferlay J, Soerjomataram I, et al (2018). Global cancer statistics 2018: GLOBOCAN estimates of incidence and mortality worldwide for 36 cancers in 185 countries. CA Cancer J Clin, 68 (6): 394-424.
4. Shahesmaeili A, Malekpour Afshar R, Sadeghi A, et al (2018). Cancer Incidence in Kerman Province, Southeast of Iran: Report of an ongoing Population-Based Cancer Registry, 2014. Asian Pac J Cancer Prev, 19 (6):1533-1541.
5. Khalili P, Rezaeian M, Rajabi A, et al (2019). Geographical Distribution of Death due to Cancer in Kerman Province, Southeast Iran. Iran J Health Sci, 7 (3):21-30.
6. Rawla P (2019). Epidemiology of Prostate Cancer. World J Oncol, 10 (2):63-89.
7. Zahir ST, Nazemian MR, Zand S, et al (2014). Survival of patients with prostate cancer in Yazd, Iran. Asian Pac J Cancer Prev, 15 (2):883-6.
8. Wang Z, Ni Y, Chen J, et al (2020). The efficacy and safety of radical prostatectomy and radiotherapy in high-risk prostate cancer: a systematic review and meta-analysis. World J Surg Oncol, 18 (1):42.
9. El-Amm J, Aragon-Ching JB (2016). Targeting Bone Metastases in Metastatic Castration-Resistant Prostate Cancer. Clin Med Insights Oncol, 10(Suppl 1):11-9.
10. Msezane LP, Reynolds WS, Gofrit ON, et al (2008). Bladder neck contracture after robot-assisted laparoscopic radical prostatectomy: evaluation of incidence and risk factors and impact on urinary function. J Endourol, 22 (1):97-104.
11. Zelefsky MJ, Hollister T, Raben A, et al (2000). Five-year biochemical outcome and toxicity with transperineal CT-planned permanent I-125 prostate implantation for patients with localized prostate cancer. Int J Radiat Oncol Biol Phys, 47 (5):1261-6.
12. Zhang J, Lawson AB (2011). Bayesian Parametric Accelerated Failure Time Spatial Model and its Application to Prostate Cancer. J Appl Stat, 38 (2):591-603.
13. Wang S, Zhang J, Lawson AB (2016). A Bayesian normal mixture accelerated failure time spatial model and its application to prostate cancer. Stat Methods Med Res, 25 (2):793-806.
14. Lin DW, Porter M, Montgomery B (2009). Treatment and survival outcomes in young men diagnosed with prostate cancer: a Population-based Cohort Study. Cancer, 115 (13):2863-71.
15. Bechis SK, Carroll PR, Cooperberg MR (2011). Impact of age at diagnosis on prostate cancer treatment and survival. J Clin Oncol, 29 (2):235-41.
16. Sakr WA, Grignon DJ, Crissman JD, et al (1994). High grade prostatic intraepithelial neoplasia (HGPIN) and prostatic adenocarcinoma between the ages of 20-69: an autopsy study of 249 cases. In Vivo, 8 (3):439-43.
17. Tan L, Wang LL, Ranasinghe W, et al (2018). Survival outcomes of younger men (< 55 years) undergoing radical prostatectomy. Prostate Int, 6 (1):31-35.
18. Freedland SJ, Presti JC Jr, Kane CJ, et al (2004). Do younger men have better biochemical outcomes after radical prostatectomy? Urology, 63 (3):518-22.
19. Fairley L, Forman D, West R, et al (2008). Spatial variation in prostate cancer survival in the Northern and Yorkshire region of England using Bayesian relative survival smoothing. Br J Cancer, 99 (11):1786-93.
20. Zattoni F, Morlacco A, Matrone F, et al (2019). Multimodal treatment for high-risk locally-advanced prostate cancer following radical prostatectomy and extended lymphadenectomy. Minerva Urol Nefrol, 71 (5):508-515.
21. Weber BA, Roberts BL, Mills TL,et al (2008). Physical and emotional predictors of depression after radical prostatectomy. Am J Mens Health, 2 (2):165-71.
22. Ayati M, Ayati E, Nourozi MR, et al (2013). Prevalence of urinary incontinence and bladder neck stricture after radical prostatectomy in the case of localized prostate cancer at Imam Khomeini hospital, Tehran, during 2009-2012. Iran J Surg, 21 (2): 29-36.
23. Ferris MJ, Liu Y, Ao J, et al (2018). The addition of chemotherapy in the definitive management of high risk prostate cancer. Urol Oncol, 36 (11):475-487.
24. Kenfield SA, Stampfer MJ, Chan JM, et al (2011). Smoking and prostate cancer survival and recurrence. JAMA, 305 (24):2548-55.
25. Gansler T, Shah R, Wang Y, et al (2018). Smoking and Prostate Cancer-Specific Mortality after Diagnosis in a Large Prospective Cohort. Cancer Epidemiol Biomarkers Prev, 27 (6):665-672.
26. Kassim R, Osei E, Cronin K (2020). A review of the effects of tobacco smoking on cancer treatment: smoking cessation intervention should be integrated into the cancer care continuum. J Radiother Pract, 19 (1):84-92.
27. Blair A, Zahm SH, Pearce NE, et al (1992). Clues to cancer etiology from studies of farmers. Scand J Work Environ Health, 18 (4):209-15.
28. Kane CJ, Lubeck DP, Knight SJ, et al (2003). Impact of patient educational level on treatment for patients with prostate cancer: data from CaPSURE. Urology, 62 (6):1035-9.
29. Kilpelainen TP, Talala K, Taari K, et al (2020). Patients' education level and treatment modality for prostate cancer in the Finnish Randomized Study of Screening for Prostate Cancer. Eur J Cancer, 130:204-210.
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IssueVol 51 No 9 (2022) QRcode
SectionOriginal Article(s)
DOI https://doi.org/10.18502/ijph.v51i9.10566
Keywords
Survival Therapy type Kaplan-Meier Bayesian Prostate cancer

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How to Cite
1.
Askari Tajabadi N, Pakmanesh H, Mirzaee M, Jahani Y. The Evaluation of Survival Rate in Patients with Prostate Cancer by Bayesian Weibull Parametric Accelerated Failure-Time Model. Iran J Public Health. 2022;51(9):2108-2116.