Predicting the need for adjuvant radiation therapy according to EAU guidelines among patients with unfavorable intermediate-risk prostate after radical prostatectomy

Abstract Objective: To develop and internally validate a multivariable model for preoperatively predicting the indication for adjuvant radiation therapy after radical prostatectomy according to current guideline recommendations of the European Association of Urology (EAU) in National Comprehensive Cancer Network (NCCN) unfavorable intermediate-risk prostate cancer patients. Methods: Within a high-volume center database (01/2010-08/2024), we identified NCCN unfavorable intermediate-risk prostate cancer patients. Univariable logistic regression models addressed indication for adjuvant radiation therapy according to current guideline recommendations of the EAU (2026). Multivariable logistic regression models included the most informative, statistically significant preoperative predictors. Accuracy was quantified after 2000 bootstrap resamples for internal validation with Harrell’s concordance index (c-index). Results: Of 9652 patients, 1154 (12%) had indication for adjuvant radiation therapy. Indication for adjuvant radiation therapy was associated with higher prostate volume (> 45 and 25–45 cm 3 ), higher preoperative PSA value (continuous), suspicious clinical tumor stage (cT2), higher absolute number of positive biopsy cores and higher relative proportion of positive biopsy cores (both continuous), higher Gleason Grade Group on biopsy (GGG 3) and multiple intermediate-risk factors (3 and 2). Multivariable model c-index for the prediction of the indication for adjuvant radiation therapy was 0.709 (95% CI 0.689–0.722). Conclusions: In NCCN unfavorable intermediate-risk prostate cancer patients, preoperative patient and clinical tumor characteristics can be reliably used to predict the indication for adjuvant radiation therapy after radical prostatectomy according to current EAU guideline recommendations (2026). Prior to clinical application, the present multivariable model should be externally validated.