Development and Validation of a Multivariable Nomogram Predictive of Post-Nephroureterectomy Renal Function

BACKGROUND AND OBJECTIVE: The timing of perioperative nephrotoxic chemotherapy for upper tract urothelial carcinoma (UTUC) remains controversial and strongly depends on predicted platinum eligibility after radical nephroureterectomy (RNU). The study objective was to develop and validate a multivariable nomogram to predict estimated glomerular filtration rate (eGFR) following RNU. METHODS: This was a multi-institutional retrospective study of patients with UTUC treated with RNU from 2000 to 2020 at seven high-volume referral centers. Use of adjuvant chemotherapy was risk-stratified. Patients were retrospectively randomly allocated 2:1 to discovery and validation cohorts. Discovery data were used to identify independent factors associated with GFR at 1-3 mo after RNU on linear regression, and backward selection was applied for model construction. Accuracy was defined as the percentage of predicted eGFR results within 30% of the corresponding observed eGFR. KEY FINDINGS AND LIMITATIONS: We included 1100 patients, of whom 733 were in the discovery and 367 were in the validation cohort. Multivariable predictors of postoperative eGFR decline included advanced age (odds ratio [OR] -0.18, 95% confidence interval [CI] -0.28 to -0.08), diabetes (OR -2.38, 95% CI -4.64 to -0.11), and hypertension (OR -2.24, 95% CI -4.16 to -0.32). Factors associated with favorable postoperative eGFR included larger tumor size (OR 10.57, 95% CI 7.4-13.74 for tumors >5 cm vs ≤2 cm) and preoperative eGFR (OR 0.44, 95% CI 0.39-0.49). A composite nomogram predicted postoperative eGFR with good accuracy in both the discovery (80.5%) and validation (78.6%) cohorts. Limitations include exclusion of patients who received neoadjuvant chemotherapy. CONCLUSIONS: A nomogram that incorporates ubiquitous preoperative clinical variables can predict post-RNU eGFR and was validated with an independent cohort. PATIENT SUMMARY: We developed a tool that uses patient data to predict eligibility for chemotherapy after surgery to remove the kidney and ureter in patients with cancer in the upper urinary tract.