Yonsei nomogram: A predictive model of new-onset chronic kidney disease after on-clamp partial nephrectomy in patients with T1 renal tumors

Abstract

ObjectivesTo develop a predictive nomogram for chronic kidney disease-free survival probability in the long term after partial nephrectomy.MethodsA retrospective analysis was carried out of 698 patients with T1 renal tumors undergoing partial nephrectomy at a tertiary academic institution. A multivariable Cox regression analysis was carried out based on parameters proven to have an impact on postoperative renal function. Patients with incomplete data, <12 months follow up and preoperative chronic kidney disease stage III or greater were excluded. The study end-points were to identify independent risk factors for new-onset chronic kidney disease development, as well as to construct a predictive model for chronic kidney disease-free survival probability after partial nephrectomy.ResultsThe median age was 52 years, median tumor size was 2.5 cm and mean warm ischemia time was 28 min. A total of 91 patients (13.1%) developed new-onset chronic kidney disease at a median follow up of 60 months. The chronic kidney disease-free survival rates at 1, 3, 5 and 10 year were 97.1%, 94.4%, 85.3% and 70.6%, respectively. On multivariable Cox regression analysis, age (1.041, P = 0.001), male sex (hazard ratio 1.653, P < 0.001), diabetes mellitus (hazard ratio 1.921, P = 0.046), tumor size (hazard ratio 1.331, P < 0.001) and preoperative estimated glomerular filtration rate (hazard ratio 0.937, P < 0.001) were independent predictors for new-onset chronic kidney disease. The C-index for chronic kidney disease-free survival was 0.853 (95% confidence interval 0.815-0.895).ConclusionWe developed a novel nomogram for predicting the 5-year chronic kidney disease-free survival probability after on-clamp partial nephrectomy. This model might have an important role in partial nephrectomy decision-making and follow-up plan after surgery. External validation of our nomogram in a larger cohort of patients should be considered.