Assessing individual risk for prostate cancer

Area of Science:

• Urology
• Oncology
• Medical Informatics

Background:

• Prostate cancer (PC) screening relies on prostate-specific antigen (PSA) and digital rectal examination (DRE), which have limitations in accuracy.
• Developing a more precise risk assessment tool is crucial for effective PC screening.

Purpose of the Study:

• To create a clinical nomogram for estimating individual risk of prostate cancer (PC).
• To enhance PC risk prediction for patients undergoing screening using multiple known risk factors.

Main Methods:

• A cross-sectional study involved 3,108 men undergoing prostate biopsy.
• A predictive model was constructed using factors: age, family history of PC (FHPC), ethnicity, urinary symptoms, PSA, free:total PSA ratio, and DRE.
• The nomogram was validated for predicting any PC and high-grade PC (Gleason score ≥7).

Main Results:

• The nomogram, incorporating age, ethnicity, FHPC, symptoms, free:total PSA ratio, PSA, and DRE, achieved an AUC of 0.74 for any PC and 0.77 for high-grade PC.
• This performance significantly surpassed the AUC of 0.62 (any PC) and 0.69 (high-grade PC) from using PSA and DRE alone.
• Multivariate analysis confirmed all incorporated risk factors as significant predictors of PC.

Conclusions:

• The developed nomogram provides a superior tool for prostate cancer risk assessment compared to conventional screening.
• Integrating factors beyond PSA and DRE, including age, FHPC, ethnicity, and urinary symptoms, significantly improves predictive accuracy.
• This enhanced nomogram can aid clinicians in better stratifying patients for prostate cancer screening and subsequent management.