已有多种模型预测非转移性肾肿瘤手术后的肾功能，但其准确度和临床效用尚未得到正式评估。综述了适用于非转移性肾肿瘤部分肾切除（PN）或根治性肾切除（RN）后中长期（> 3个月）预测术后肾功能的预测模型，仅包括术前或可改变术中变量。根据PRISMA指南（PROSPERO ID：CRD42022303492），使用MEDLINE、Embase和Web of Science数据库进行了英语文献的系统评价。根据预测模型研究风险评估工具评估了偏倚风险。 总体上，共纳入了18项研究的21个预测模型（9个仅适用于PN；8个仅适用于RN；4个适用于PN或RN）。大多数研究依赖于回顾性患者队列，并具有偏倚风险和关于拟议模型整体适用性的高度关注。患者、肾脏、手术、肿瘤和提供者相关因素在95%、86%、100%、61%和0%的模型中被包括在预测因素之中。除了一种模型之外，所有模型都包括患者年龄和术前肾功能，而只有少数考虑到患者性别、种族、合并症、肿瘤大小/复杂性和手术方法。无论是模型构建策略还是性能指标报告中都存在显著异质性。五项研究报告了六个模型的外部验证，而三项通过决策曲线分析评估了它们的临床实用性。 针对肾癌手术后预测肾功能已有多种模型可供选择。其中大多数还不适用于常规临床实践，而仅有一部分已经经过外部验证，可能对非转移性癌症候选手术患者和临床医生具有价值。 我们审查了可用于预测非转移性肾癌部分或全部切除后的肾功能的工具。大多数模型包括患者和肾脏特征，例如年龄、合并症和术前肾功能，而一些模型还包括肿瘤特征和术中变量。一些模型已经通过其他研究小组的验证，并显示出为非转移性肿瘤手术患者改善咨询方面的前景。 版权所有© 2022年欧洲泌尿科学会。由Elsevier B.V.出版。保留所有权利。

A variety of models predicting postoperative renal function following surgery for nonmetastatic renal tumors have been reported, but their validity and clinical usefulness have not been formally assessed.To summarize prediction models available for estimation of mid- to long-term (>3 mo) postoperative renal function after partial nephrectomy (PN) or radical nephrectomy (RN) for nonmetastatic renal masses that include only preoperative or modifiable intraoperative variables.A systematic review of the English-language literature was conducted using the MEDLINE, Embase, and Web of Science databases from January 2000 to March 2022 according to the PRISMA guidelines (PROSPERO ID: CRD42022303492). Risk of bias was assessed according to the Prediction Model Study Risk of Bias Assessment Tool.Overall, 21 prediction models from 18 studies were included (nine for PN only; eight for RN only; four for PN or RN). Most studies relied on retrospective patient cohorts and had a high risk of bias and high concern regarding the overall applicability of the proposed model. Patient-, kidney-, surgery-, tumor-, and provider-related factors were included among the predictors in 95%, 86%, 100%, 61%, and 0% of the models, respectively. All but one model included both patient age and preoperative renal function, while only a few took into account patient gender, race, comorbidities, tumor size/complexity, and surgical approach. There was significant heterogeneity in both the model building strategy and the performance metrics reported. Five studies reported external validation of six models, while three assessed their clinical usefulness using decision curve analysis.Several models are available for predicting postoperative renal function after kidney cancer surgery. Most of these are not ready for routine clinical practice, while a few have been externally validated and might be of value for patients and clinicians.We reviewed the tools available for predicting kidney function after partial or total surgical removal of a kidney for nonmetastatic cancer. Most of the models include patient and kidney characteristics such as age, comorbidities, and preoperative kidney function, and a few also include tumor characteristics and intraoperative variables. Some models have been validated by additional research groups and appear promising for improving counseling for patients with nonmetastatic cancer who are candidates for surgery.Copyright © 2022 European Association of Urology. Published by Elsevier B.V. All rights reserved.