## 4 Discussion
For instance, age may exert a greater impact on long-term outcomes (7 years), as the cumulative effects of comorbidities and physiological aging become increasingly pronounced over time. The AUC values derived from our nomograms indicated suboptimal-to-good performance. Furthermore, when using the cut-off value of each variable, utilization of the nomograms revealed significant differences in 5- and 7-year BCR-free survival rates, as shown by the Kaplan-Meier curves (Figure 3). The variables age and %PC may have contributed to the good discriminative performance of our nomograms for high-risk PCa patients. In our patient cohort, age, cT stage, biopsy GS, and %PC were all significantly associated with BCR-free survival (Figure 1). The dose fractionation of CIRT and the duration of ADT were not significantly associated with BCR-free survival. While the impact of age on PCa outcomes remains controversial, some studies have demonstrated that advanced age may be correlated with better treatment outcomes in PCa patients who receive RT, including CIRT, with lower incidences of BCR, metastases, and CSM [13; 31]. This suggests that older patients may have less aggressive PCa, such as variations in hormone levels at different ages and more comorbidities [13; 31]. In the present study, we also found that our high-risk PCa patients over 70 years old also showed significantly better BCR-free survival compared with younger patients (Figure 1a). Although age was integrated into both nomograms to predict 5- and 7-year BCR-free survival, the impact of advanced age on BCR-free events increased with prolonged observation periods (Figure 1a). Given that the number of healthy aged patients undergoing CIRT combined with ADT is increasing, BCR-free survival may improve further in the future. Because CIRT combined with ADT is as effective and safe in the elderly as it is in young patients with high-risk PCa [13,14], it may be the optimal treatment for high-risk PCa, especially in the elderly. %PC was selected as a variable in the 7-year BCR-free survival nomogram according to the LASSO coefficient solution path. The addition of %PC, along with the three routine risk factors, to the nomogram has the potential to enhance the overall accuracy of predictive models. %PC provides an estimation of the PCa volume [32]. Furthermore, %PC has been shown to be a valuable predictor of lymph node metastases in patients undergoing RP and extended pelvic lymph node dissection [33]. Our study has several limitations. First, this study was retrospectively analyzed using a database derived from prospective clinical trial data conducted at a single institution. Although the retrospective nature of the study might have affected the data quality, all data were uniformly reviewed and re-examined in this study. Second, the predictors utilized to create the two nomograms were slightly different between the Kaplan-Meier curves and LASSO regression multivariate model. To develop a better predictive model, LASSO selects a set of variables for which cross-validation will result in a smaller prediction error. Third, given that early recurrence after CIRT and ADT occurs rarely, the 5-year predictive model may have little practical value in clinical settings. Nonetheless, it proves valuable in identifying high-risk PCa patients susceptible to aggressive early recurrence. Fourth, the validity of the nomograms was not evaluated through external validation. To ensure their predictive accuracy, external validation should be conducted in diverse populations, irrespective of the satisfactory internal validation results. Given that the patients in this study were predominantly Japanese, external validation in other ethnic cohorts could enhance the generalizability of the nomograms. Moreover, external validation is necessary to compare the utility of our nomogram with other predictive models, such as the Candiolo nomogram.