A non-socially-sensitive predictive model of prostate cancer for Asian males with benign prostatic hyperplasia: A multi-site cross-sectional case-control study

Abstract

Background: Benign prostatic hyperplasia (BPH) is common in aging Asian males and is associated with an excess risk of developing prostate cancer (PCa). However, discussions about socially-sensitive experiences such as sexual activity, which can significantly predict PCa risk, may be considered stigmatized in Asian culture. This study aimed to develop a predictive model for PCa risk in Asian males with BPH using non-socially-sensitive information.

Methods: A cross-sectional case-control study, with PCa patients as the cases and remaining as the controls, was conducted on a cohort of Taiwanese males with BPH from four medical institutions. Patients who met the inclusion criteria were enrolled, excluding those aged over 86 years or who had received human papillomavirus (HPV) vaccination. Non-socially-sensitive variables such as obesity, occupational exposure, HPV infection, and PCa family history score (FH score) were included in a fully adjusted logistic regression model, and depicted using a nomogram.

Results: Among 236 BPH patients, 45.3% had PCa. Obesity, occupational exposure, HPV infection, and family history of PCa were significantly associated with PCa risk. The FH score (OR = 1.89, 95% CI = 1.03-3.47, P = 0.041) had the highest impact, followed by HPV infection (OR = 1.47, 95% CI = 1.03-2.11, P = 0.034), occupational exposure (OR = 1.32, 95% CI = 1.15-1.51, P <0.001), and obesity (OR = 1.22, 95% CI = 1.07-1.41, P = 0.005). The nomogram accurately depicted the predictive risk, and the model demonstrated robust performance compared to individual factors. In addition, the subgroup analysis results showed elderly age group could obtain more favorable predictive performance in our proposed model (AUC = 0.712).

Conclusion: This non-socially-sensitive predictive model for PCa risk in Taiwanese males with BPH integrates multiple factors that could provide acceptable PCa risk-predictive performance, especially for elderly BPH patients over 70 years, aiding clinical decision-making and early cancer detection.

Fig 1. The predictive performance of proposed model for PCa risk in all patients.

(a) Nomogram for PCa risk prediction of benign prostatic hyperplasia patients. (b) The predicted probability versus actual probability of proposed model for PCa with 250 and 500 resampling using bootstrap method. (c) Comparison results of predictive performance between proposed model and single risk factors of PCa. PCa, prostate cancer. OE, Occupational exposure. HPV, human papillomavirus. FH score, Family history severity score.

Fig 2. Subgroup analysis results for elder patients aged over 70 years (n = 127).

(a) Nomogram for PCa risk prediction of benign prostatic hyperplasia patients. (b) The predicted probability versus actual probability of the proposed model for PCa with 250 and 500 resampling using the bootstrap method. (c) Comparison results of predictive performance between the proposed model and single risk factors of PCa. PCa, prostate cancer. OE, Occupational exposure. HPV, human papillomavirus. FH score, Family history severity score.