Graduate School of Peking Union Medical College and Chinese Academy of Medical Sciences, No. 9 Dongdan Santiao, Dongcheng District, Beijing, 100730, China.
Department of Colorectal Surgery, National Cancer Center/National Clinical Research Center for Cancer/Cancer Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, No. 17 Nanli, Panjiayuan, Chaoyang District, Beijing, 100021, China.
J Cancer Res Clin Oncol. 2023 Oct;149(13):11223-11231. doi: 10.1007/s00432-023-05016-2. Epub 2023 Jun 24.
This study aimed to establish and validate nomograms to predict the probability of intravesical recurrence (IVR) after radical nephroureterectomy (RNU) for upper urinary tract epithelial carcinoma (UTUC).
Clinical data of 528 patients with UTUC after RNU were collected from two medical centers between 2009 and 2020. We used the least absolute shrinkage and selection operator (LASSO) regression to select variables for multivariable Cox regression analysis in the training cohort and included independent risk factors into nomogram models predicting IVR-free survival (IVRFS). Another center was applied as the external cohort to validate the predictive accuracy and discriminative ability of the nomogram by performing area under the receiver operating curve (AUC), consistency index (C-index), and calibration curve.
History of bladder cancer, tumor size, preoperative urine cytology, postoperative instillation, Ki-67, and platelet-to-lymphocyte ratio (PLR) were identified as independent risk factors for IVR. The prognosis model including these predictors demonstrated excellent discriminatory performance in both the training cohort (C-index, 0.814) and external validation cohort (C-index, 0.748). The calibration plots of the nomogram revealed good consistency in both cohorts. Finally, patients could be classified into two risk groups based on scores obtained from the nomogram, with significant differences in IVRFS.
Our study provided a reliable nomogram for predicting the probability of IVR in patients with UTUC after RNU. Risk stratification based on this model may assist urologists make optimal clinical decisions on the management of UTUC.
本研究旨在建立和验证列线图，以预测上尿路上皮癌（UTUC）患者行根治性肾输尿管切除术（RNU）后膀胱内复发（IVR）的概率。
收集了 2009 年至 2020 年两个医疗中心 528 例接受 RNU 治疗的 UTUC 患者的临床资料。我们使用最小绝对收缩和选择算子（LASSO）回归在训练队列中选择多变量 Cox 回归分析的变量，并将独立的危险因素纳入预测 IVR 无复发生存（IVRFS）的列线图模型中。另一个中心被用作外部队列，通过绘制受试者工作特征曲线（AUC）下面积、一致性指数（C-index）和校准曲线来验证列线图的预测准确性和判别能力。
膀胱癌病史、肿瘤大小、术前尿液细胞学检查、术后灌注、Ki-67 和血小板与淋巴细胞比值（PLR）被确定为 IVR 的独立危险因素。包括这些预测因子的预后模型在训练队列（C 指数为 0.814）和外部验证队列（C 指数为 0.748）中均具有出色的判别性能。列线图的校准图显示两个队列均具有良好的一致性。最后，根据列线图获得的评分，患者可分为两个风险组，两组之间 IVRFS 差异有统计学意义。
本研究为预测 RNU 治疗后 UTUC 患者 IVR 概率提供了一种可靠的列线图。基于该模型的风险分层可能有助于泌尿科医生在 UTUC 的管理方面做出最佳的临床决策。
