Department of Urological Minimally Invasive, Robotic Surgery and Kidney Transplantation, Careggi Hospital, University of Florence, Florence, Italy; Department of Urology, University Hospitals Leuven, Leuven, Belgium.
Department of Urological Minimally Invasive, Robotic Surgery and Kidney Transplantation, Careggi Hospital, University of Florence, Florence, Italy; Department of Experimental and Clinical Medicine, University of Florence, Florence, Italy.
Eur Urol Oncol. 2023 Apr;6(2):137-147. doi: 10.1016/j.euo.2022.11.007. Epub 2023 Jan 9.
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.
已有多种模型用于预测非转移性肾肿瘤手术后的肾功能，但尚未对其有效性和临床实用性进行正式评估。
总结目前仅纳入术前或术中可改变变量的用于预测部分肾切除术（PN）或根治性肾切除术（RN）后非转移性肾肿瘤中、长期（>3 个月）术后肾功能的预测模型。
根据 PRISMA 指南（PROSPERO ID：CRD42022303492），使用 MEDLINE、Embase 和 Web of Science 数据库对 2000 年 1 月至 2022 年 3 月的英文文献进行系统评价。根据预测模型研究风险偏倚评估工具评估风险偏倚。
共纳入 18 项研究的 21 个预测模型（仅 PN 相关 9 个；仅 RN 相关 8 个；PN 或 RN 相关 4 个）。大多数研究依赖于回顾性患者队列，存在高风险偏倚，且对所提出模型的整体适用性存在高关注。预测因素包括患者、肾脏、手术、肿瘤和提供者相关因素，分别占模型的 95%、86%、100%、61%和 0%。除 1 个模型外，所有模型均包含患者年龄和术前肾功能，仅有少数模型考虑了患者性别、种族、合并症、肿瘤大小/复杂性和手术方式。模型构建策略和报告的性能指标均存在显著异质性。5 项研究报告了 6 个模型的外部验证，3 项研究使用决策曲线分析评估了其临床实用性。
目前有多种模型可用于预测肾癌手术后的肾功能。其中大多数模型尚未准备好常规临床应用，而少数模型已得到外部验证，可能对患者和临床医生具有一定价值。
我们回顾了用于预测非转移性癌症行部分或全部肾切除术后肾功能的工具。大多数模型包含患者和肾脏特征，如年龄、合并症和术前肾功能，少数模型还包含肿瘤特征和术中变量。一些模型已通过其他研究小组进行了验证，对于改善候选手术的非转移性癌症患者的咨询似乎很有前景。
