Development and Internal Validation of a Nomogram for Predicting Renal Function after Partial Nephrectomy
Development and Internal Validation of a Nomogram for Predicting Renal Function after Partial Nephrectomy
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DOI：
10.1016/j.euo.2018.06.015
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发表时间：
2019-02-01
影响因子：
8.2
通讯作者：
Kaouk, Jihad
中科院分区：
文献类型：
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作者：
Bertolo, Riccardo;Garisto, Juan;Kaouk, Jihad
肾功能丧失可能是肾部分切除术（PN）后的临床影响事件。我们的目的是建立一个模型来预测接受PN的患者的肾功能丧失。从我们的机构数据库中提取了2008年至2017年间连续接受PN伴热缺血的1897名患者的数据。肾功能丧失定义为PN后3个月时估计的肾小球滤过率（eGFR）方面的慢性肾脏疾病分期升高。基于包括年龄、性别、体重指数、基线eGFR、RENAL评分和缺血时间的多变量模型构建列线图。使用676例患者的完整数据进行间隔验证和校准。绘制了1000次自助重复的受试者操作特征（ROC）曲线，以及观察到的发生率与诺模图预测的概率。我们还应用了极端的训练与测试程序，称为留一交叉验证。经过内部验证，ROC曲线下面积为76%。该模型表现出良好的校准。在27%概率的分期上调临界值下，预测分期上调的阳性预测值为86%。患者总结：在这份报告中，我们建立了一个模型来预测肾肿瘤部分切除术后肾功能的丧失。将基线特征和缺血时间输入我们的模型，可以早期识别肾部分切除术后肾功能下降风险较高的患者，具有良好的预测能力。(C)2018由Elsevier B.V.代表欧洲泌尿外科协会发布。
Loss of renal function can be a clinically impactful event after partial nephrectomy (PN). We aimed to create a model to predict loss of renal function in patients undergoing PN. Data for 1897 consecutive patients who underwent PN with warm ischemia between 2008 and 2017 were extracted from our institutional database. Loss of renal function was defined as upstaging of chronic kidney disease in terms of the estimated glomerular filtration rate (eGFR) at 3 mo after PN. A nomogram was built based on a multivariable model comprising age, sex, body mass index, baseline eGFR, RENAL score, and ischemia time. Interval validation and calibration were performed using data from 676 patients for whom complete data were available. Receiver operator characteristic (ROC) curves with 1000 bootstrap replications were plotted, as well as the observed incidence versus the nomogram-predicted probability. We also applied the extreme training versus test procedure known as leave-one-out cross-validation. After internal validation, the area under the ROC curve was 76%. The model demonstrated excellent calibration. At an upstaging cutoff of 27% probability, upstaging was predicted with a positive predictive value of 86%.Patient summary: In this report, we created a model to predict postoperative loss of renal function after partial nephrectomy for renal tumors. Inputting baseline characteristics and ischemia time into our model allows early identification of patients at higher risk of renal function decline after partial nephrectomy with good predictive power. (C) 2018 Published by Elsevier B.V. on behalf of European Association of Urology.