Crocerossa Fabio, Fiori Cristian, Capitanio Umberto, Minervini Andrea, Carbonara Umberto, Pandolfo Savio D, Loizzo Davide, Eun Daniel D, Larcher Alessandro, Mari Andrea, Grosso Antonio Andrea, Di Maida Fabrizio, Hampton Lance J, Cantiello Francesco, Damiano Rocco, Porpiglia Francesco, Autorino Riccardo
Division of Urology, VCU Health, Richmond, VA, USA.
Department of Urology, Magna Graecia University, Catanzaro, Italy.
Eur Urol Open Sci. 2022 Mar 3;38:52-59. doi: 10.1016/j.euros.2022.02.005. eCollection 2022 Apr.
Long-term renal function after partial nephrectomy (PN) is difficult to predict as it is influenced by several modifiable and nonmodifiable variables, often intertwined in complex relations.
To identify variables influencing long-term renal function after PN and to assess their relative weight.
A total of 457 patients who underwent either robotic ( = 412) or laparoscopic PN ( = 45) were identified from a multicenter international database.
The 1-yr estimated glomerular filtration rate (eGFR) percentage loss (1YPL), defined as the eGFR percentage change from baseline at 1 yr after surgery, was the outcome endpoint. Predictors evaluated included demographic data, tumor features, and operative and postoperative variables. Bayesian multimodel analysis of covariance was used to build all possible models and compare the fit of each model to the data via model Bayes factors. Bayesian model averaging was used to quantify the support for each predictor via the inclusion Bayes factor (BF). High-dimensional undirected graph estimation was used for network analysis of conditional independence between predictors.
Several models were found to be plausible for estimation of 1YPL. The best model, comprising postoperative eGFR percentage loss (PPL), sex, ischemia technique, and preoperative eGFR, was 207 times more likely than all the other models regarding relative predictive performance. Its components were part of the top 44 models and were the predictors with the highest BF. The role of cold ischemia, solitary kidney status, surgeon experience, and type of renorraphy was not assessed.
Preoperative eGFR, sex, ischemia technique, and PPL are the best predictors of eGFR percentage loss at 1 yr after minimally invasive PN. Other predictors seem to be irrelevant, as their influence is insignificant or already nested in the effect of these four parameters.
Kidney function at 1 year after partial removal of a kidney depends on sex, the technique used to halt blood flow to the kidney during surgery, and kidney function at baseline and in the early postoperative period.
部分肾切除术（PN）后的长期肾功能难以预测，因为它受到多个可改变和不可改变的变量影响，这些变量之间的关系往往错综复杂。
确定影响PN术后长期肾功能的变量，并评估它们的相对权重。
设计、地点和参与者：从一个多中心国际数据库中识别出457例行机器人辅助（n = 412）或腹腔镜PN（n = 45）的患者。
以术后1年估计肾小球滤过率（eGFR）百分比下降（1YPL）作为结局终点，1YPL定义为术后1年eGFR相对于基线的百分比变化。评估的预测因素包括人口统计学数据、肿瘤特征以及手术和术后变量。采用贝叶斯多模型协方差分析构建所有可能的模型，并通过模型贝叶斯因子比较每个模型与数据的拟合度。使用贝叶斯模型平均法通过包含贝叶斯因子（BF）量化对每个预测因素的支持度。采用高维无向图估计对预测因素之间的条件独立性进行网络分析。
发现有几个模型对估计1YPL似乎合理。最佳模型包括术后eGFR百分比下降（PPL）、性别、缺血技术和术前eGFR，就相对预测性能而言，其可能性是所有其他模型的207倍。其组成部分属于前44个模型，是BF最高的预测因素。未评估冷缺血、孤立肾状态、外科医生经验和肾缝合类型的作用。
术前eGFR、性别、缺血技术和PPL是微创PN术后1年eGFR百分比下降的最佳预测因素。其他预测因素似乎无关紧要，因为它们的影响不显著或已包含在这四个参数的效应中。
部分肾切除术后1年的肾功能取决于性别、手术中用于阻断肾脏血流的技术以及基线期和术后早期的肾功能。
