Xiao Ruotao, Qin Yanchun, Liu Lei, Chen Zhigang, Yang Bin, Xu Chuxiao, He Wei, Liu Cheng, Ma Lulin
Department of Urology, Peking University Third Hospital, Beijing, China.
J Cancer. 2021 Aug 28;12(21):6301-6309. doi: 10.7150/jca.60268. eCollection 2021.
This study aims to develop and validate a nomogram based on a novel platelet index score (PIS) to predict prognosis in patients with renal cell carcinoma (RCC). We retrospectively analyzed the data of 759 consecutive patients with RCC. The Kaplan-Meier curves were performed to analyze the platelet parameters and PIS was established. The patients were randomly divided into training (N=456, 60%) and validation cohorts (N=303, 40%). The nomogram was created based on the factors determined by multivariable Cox proportional hazard regression of the training cohort. We assessed the discrimination and calibration of our nomogram in both training and validation cohorts. And then the nomogram was compared with other reported models. High platelet count (PLT>285×10/L) and low platelet distribution width (PDW≤10.95fL) were associated with shorter progression-free survival (PFS). Thus, PLT and PDW were incorporated in a novel score system called PIS. On multivariable analysis of training cohort, PIS, American Joint Committee on Cancer (AJCC) stage, and sarcomatoid differentiation were independent prognostic factors, which were all selected into the nomogram. The nomogram exhibited good discrimination in both training (C-index: 0.835) and validation cohorts (C-index: 0.883). The calibration curves also showed good agreement between prediction and observation in both cohorts. The C-index of the nomogram (C-index: 0.8100.902) for predicting 2-year, 3-year, and 4-year PFS were significantly higher than Leibovich (C-index: 0.7720.813), SSIGN (C-index: 0.7750.876), Cindolo (C-index: 0.6420.798), Yaycioglu (C-index: 0.6480.804), MSKCC (C-index: 0.7610.862), Karakiewicz (C-index: 0.7470.851), and AJCC stage models (C-index: 0.7590.864). The nomogram based on a novel PIS could offer better risk stratification in patients with RCC.
本研究旨在开发并验证一种基于新型血小板指数评分(PIS)的列线图,以预测肾细胞癌(RCC)患者的预后。我们回顾性分析了759例连续RCC患者的数据。绘制Kaplan-Meier曲线以分析血小板参数并建立PIS。患者被随机分为训练组(N = 456,60%)和验证组(N = 303,40%)。基于训练组多变量Cox比例风险回归确定的因素创建列线图。我们在训练组和验证组中评估了列线图的区分度和校准度。然后将该列线图与其他已报道的模型进行比较。高血小板计数(PLT>285×10/L)和低血小板分布宽度(PDW≤10.95fL)与无进展生存期(PFS)较短相关。因此,PLT和PDW被纳入一种名为PIS的新型评分系统。在训练组的多变量分析中,PIS、美国癌症联合委员会(AJCC)分期和肉瘤样分化是独立的预后因素,均被选入列线图。该列线图在训练组(C指数:0.835)和验证组(C指数:0.883)中均表现出良好的区分度。校准曲线在两个队列中也显示出预测值与观察值之间的良好一致性。该列线图预测2年、3年和4年PFS的C指数(C指数:0.8100.902)显著高于Leibovich(C指数:0.7720.813)、SSIGN(C指数:0.7750.876)、Cindolo(C指数:0.6420.798)、Yaycioglu(C指数:0.6480.804)、MSKCC(C指数:0.7610.862)、Karakiewicz(C指数:0.7470.851)和AJCC分期模型(C指数:0.7590.864)。基于新型PIS的列线图可为RCC患者提供更好的风险分层。