Acute kidney injury after nephron sparing surgery and microwave ablation: focus on incidence, survival impact and prediction.

To compare acute kidney injury (AKI) incidence between nephron sparing surgery (NSS) and microwave ablation (MWA) for T1a RCC patients, reveal the effect of AKI on survival prognosis, construct AKI nomogram and use Law of Total Probability for survival probability (SP) prediction. Patients were studied retrospectively after NSS ( = 1267) or MWA ( = 210) from January 1, 2011 to June 30, 2017. Using one to one Propensity Score Matching (PSM), 158 pairs of patients were identified for the cohort study. AKI incidence, risk factors and impact on survival outcomes were analyzed using Chi-square test, logistic and cox regression analysis. AKI risk and SP were predicted by nomogram and Law of Total Probability. The performance of the nomogram was assessed with respect to its discrimination, calibration, and clinical usefulness. AKI occurred more commonly in NSS (27.85%) cohort, when compared to MWA (17.72%) cohort ( = 0.032), but treatment modality was not independently predictive of AKI occurrence (odds ratio [OR]: 0.598; 95% confidence interval [CI]: 0.282-1.265;  = 0.178). The 5-yr overall survival (OS) was lower in AKI patients (73.5%) compared with non-AKI patients (94.8%;  < 0.001). AKI was an independent risk factor for all-cause mortality in RCC patients (hazard ratio [HR]: 2.820; 95% confidence interval [CI]: 1.110-7.165;  = 0.029). Predictors for both NSS- and MWA-related AKI included tumor diameter, baseline eGFR and CCI score. RENAL score and tumor blood supply can predict AKI after NSS and MWA, respectively. The AKI normograms demonstrated good discrimination, with AUCs >0.86, excellent calibration and net benefits at the decision curve analysis with probabilities ≥5%. SP predicted by Law of Total Probability was comparable to actual OS. AKI was an early indicator for poor overall survival in RCC patients. It can be predicted by several oncological parameters. Nomogram and Law of Total Probability can accurately predict AKI risk and SP.