Department of Urology, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China.
Department of Imaging, National Cancer Center, National Clinical Research Center for Cancer, Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing China.
Int Braz J Urol. 2022 Sep-Oct;48(5):784-794. doi: 10.1590/S1677-5538.IBJU.2021.0859.
Nomogram can be built to predict the pathological T3a upstaging from clinical T1a in patients with localized renal cell carcinoma before surgery.
Renal cell carcinoma (RCC) patients with clinical T1a (cT1a) disease who are upstaged to pathological T3a (pT3a) have reduced survivals after partial nephrectomy. We aimed to develop a nomogram-based model predicting pT3a upstaging in RCC patients with preoperative cT1a based on multiple preoperative blood indexes and oncological characteristics.
Between 2010 and 2019, 510 patients with cT1a RCC were individually matched according to pT3a upstaging and pathological T1a (pT1a) at a 1:4 ratio using clinicopathologic features. Least absolute shrinkage and selection operator regression analysis was used to identify the most important risk factor from 40 peripheral blood indicators, and a predictive model was established. Multivariate logistic regression analysis was performed with the screened blood parameters and clinical data to identify significant variables. Harrell's concordance index (C-index) was applied to evaluate the accuracy of the model for predicting pT3a upstaging in patients with cT1a RCC.
Out of 40 blood indexes, the top ranked predictor was fibrinogen (FIB). Age, the ratio of the tumor maximum and minimum diameter (ROD), FIB, and tumor size were all independent risk factors for pT3a upstaging in multivariate analysis. A predictive ARFS model (Age, ROD, FIB, tumor Size) was established, and the C-index was 0.756 (95% CI, 0.681-0.831) and 0.712 (95% CI, 0.638-0.785) in the training and validation cohorts, respectively.
Older age, higher ROD, increased FIB level, and larger tumor size were independent risk factors for upstaging. The ARFS model has a high prediction efficiency for pT3a upstaging in patients with cT1a RCC.
可以建立列线图来预测术前局限性肾细胞癌患者中从临床 T1a 到病理 T3a 的升级。
肾细胞癌 (RCC) 患者术前 T1a (cT1a) 疾病升级为病理 T3a (pT3a) ，行部分肾切除术患者的生存率降低。我们旨在基于多个术前血液指标和肿瘤学特征，为术前 cT1a 的 RCC 患者开发一种基于列线图的预测 pT3a 升级模型。
在 2010 年至 2019 年期间，根据术前 cT1a 肿瘤最大和最小直径比 (ROD) ，使用临床病理特征对 510 例 cT1a RCC 患者进行了个体匹配，按 pT3a 升级和病理 T1a (pT1a) 以 1:4 的比例进行匹配。使用最小绝对收缩和选择算子回归分析从 40 个外周血指标中确定最重要的危险因素，并建立预测模型。使用筛选的血液参数和临床数据进行多变量逻辑回归分析，以确定显著变量。Harrell 一致性指数 (C-index) 用于评估该模型在预测 cT1a RCC 患者 pT3a 升级中的准确性。
在 40 个血液指标中，排名最高的预测因子是纤维蛋白原 (FIB)。年龄、肿瘤最大和最小直径比 (ROD)、纤维蛋白原 (FIB) 和肿瘤大小在多变量分析中均为 pT3a 升级的独立危险因素。建立了预测 ARFS 模型 (年龄、ROD、FIB、肿瘤大小) ，C 指数分别为 0.756(95%CI，0.681-0.831)和 0.712(95%CI，0.638-0.785)，在训练和验证队列中。
年龄较大、ROD 较高、FIB 水平升高和肿瘤体积增大是升级的独立危险因素。ARFS 模型对预测 cT1a RCC 患者的 pT3a 升级具有较高的预测效率。
