Department of Urology and Andrology, Kansai Medical University, 2-3-1 Shin-machi, Hirakata, Osaka, 573-1191, Japan.
Sci Rep. 2021 Nov 18;11(1):22526. doi: 10.1038/s41598-021-01539-1.
There are several nephrometry scoring systems for predicting surgical complexity and potential perioperative morbidity. The R.E.N.A.L. scoring system, one of the most well-known nephrometry scoring systems, emphasizes the features on which it is based (Radius, Exophytic/endophytic, Nearness to collecting system or sinus, Anterior/posterior, and Location relative to polar lines). The ability of these nephrometry scoring systems to predict loss of renal function after robotic partial nephrectomy (RPN) remains controversial. Therefore, we verified which combination of factors from nephrometry scoring systems, including tumor volume, was the most significant predictor of postoperative renal function. Patients who underwent RPN for cT1 renal tumors in our hospital were reviewed retrospectively (n = 163). The preoperative clinical data (estimated glomerular filtration rate [eGFR], comorbidities, and nephrometry scoring systems including R.E.N.A.L.) and perioperative outcomes were evaluated. We also calculated the tumor volume using the equation applied to an ellipsoid by three-dimensional computed tomography. The primary outcome was reduced eGFR, which was defined as an eGFR reduction of ≥ 20% from baseline to 6 months after RPN. Multivariable logistic regression analyses were used to evaluate the relationships between preoperative variables and reduced eGFR. Of 163 patients, 24 (14.7%) had reduced eGFR. Multivariable analyses indicated that tumor volume (cutoff value ≥ 14.11 cm, indicating a sphere with a diameter ≥ approximately 3 cm) and tumor crossing of the axial renal midline were independent factors associated with a reduced eGFR (odds ratio [OR] 4.57; 95% confidence interval [CI] 1.69-12.30; P = 0.003 and OR 3.50; 95% CI 1.30-9.46; P = 0.034, respectively). Our classification system using these two factors showed a higher area under the receiver operating characteristic curve (AUC) than previous nephrometry scoring systems (AUC = 0.786 vs. 0.653-0.719), and it may provide preoperative information for counseling patients about renal function after RPN.
有几种用于预测手术复杂性和潜在围手术期发病率的肾肿瘤影像学评分系统。RENAL 评分系统是最著名的肾肿瘤影像学评分系统之一，它强调了其基于的特征（半径、外生性/内生性、靠近集合系统或窦、前/后和相对于极线的位置）。这些肾肿瘤影像学评分系统预测机器人辅助部分肾切除术 (RPN) 后肾功能丧失的能力仍存在争议。因此，我们验证了肾肿瘤影像学评分系统中的哪些因素组合，包括肿瘤体积，是预测术后肾功能的最重要指标。我们回顾性分析了我院因 cT1 肾肿瘤行 RPN 的患者（n=163）。评估了术前临床数据（估算肾小球滤过率 [eGFR]、合并症和肾肿瘤影像学评分系统，包括 RENAL）和围手术期结果。我们还使用三维计算机断层扫描计算了肿瘤体积。主要结果是 eGFR 降低，定义为 RPN 后 6 个月 eGFR 较基线降低≥20%。使用多变量逻辑回归分析评估术前变量与 eGFR 降低之间的关系。在 163 名患者中，有 24 名（14.7%）出现 eGFR 降低。多变量分析表明，肿瘤体积（截值≥14.11cm，提示直径≥约 3cm 的球体）和肿瘤跨越轴向肾中线是与 eGFR 降低相关的独立因素（优势比 [OR] 4.57；95%置信区间 [CI] 1.69-12.30；P=0.003 和 OR 3.50；95% CI 1.30-9.46；P=0.034）。我们使用这两个因素的分类系统显示出比以前的肾肿瘤影像学评分系统更高的受试者工作特征曲线下面积（AUC）（AUC=0.786 与 0.653-0.719），它可能为患者提供 RPN 后肾功能的术前信息。
