Objective:

To develop and validate a predictive model for radiotherapy-related genitourinary toxicity requiring hospital admission in patients with localized prostate cancer, enhancing clinical decision-making.

Key Findings:

• Diabetes, smoking, and bladder outlet obstruction (BOO) without TURP were strong independent predictors of hospitalisation for genitourinary toxicity, highlighting the need for targeted interventions.
• Patients with BOO without TURP had the lowest 10-year event-free survival rates (20%), indicating a critical area for clinical focus.
• Baseline stress urinary incontinence was a significant predictor but was excluded from the final model due to multicollinearity, suggesting the need for careful variable selection in predictive modeling.

Interpretation:

The predictive model can help identify patients at high risk for genitourinary toxicity post-radiotherapy, potentially guiding clinical decision-making and patient management strategies.

Limitations:

• The study is based on a single registry, which may limit generalizability to broader populations.
• Potential for missing data and reliance on historical patient records may introduce bias, affecting the robustness of the findings.

Conclusion:

The developed model offers a valuable tool for predicting post-radiation genitourinary complications, aiding in the management of localized prostate cancer patients and improving patient outcomes.