Predicting recurrence after radical nephroureterectomy for upper tract urothelial carcinoma: Development and validation of the JIKEI-YAYOI score.

BACKGROUND

Recent clinical trials have highlighted the benefits of adjuvant therapies for upper tract urothelial carcinoma (UTUC), although their application remains limited by patient-specific factors. This study aimed to develop a prognostic model to predict postoperative outcomes and identify patients who would benefit from adjuvant therapy.

METHODS

We conducted a retrospective analysis of 700 UTUC patients who underwent radical nephroureterectomy at Jikei University Hospital and its affiliated institutions (development cohort), and 405 patients treated at Mayo Clinic (validation cohort). Patients who received neoadjuvant or adjuvant chemotherapy were excluded. In the development cohort, clinical and pathological variables were analyzed to construct a risk prediction model for postoperative recurrence. Statistical analyses included Kaplan-Meier estimation, Cox proportional hazards regression, and internal validation using bootstrapping. The model was externally validated using data from the validation cohort.

RESULTS

The final model incorporated pT stage, pN stage, tumor grade, and lymphovascular invasion, resulting in the novel "JIKEI-YAYOI" risk score (range: 0-7). The model demonstrated excellent discrimination (C-index: 0.815) and calibration. Patients were stratified into low, intermediate, and high-risk groups, each with distinct recurrence-free survival rates. The JIKEI-YAYOI score provided accurate, individualized risk predictions, facilitating clinical decision-making regarding adjuvant therapy.

CONCLUSION

The JIKEI-YAYOI score reliably predicts disease recurrence following radical surgery for UTUC, supporting personalized patient management and informed decisions about adjuvant therapy.