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Construction of a survival prediction model for high-and low -grade UTUC after tumor resection based on “SEER database”: a multicenter study

机译:基于“SEER数据库”的肿瘤切除后高和低级utuc生存预测模型的构建:多中心研究

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There are differences in survival between high-and low-grade Upper Tract Urothelial Carcinoma (UTUC). Our study aimed to develop a nomogram to predict overall survival (OS) of patients with high- and low-grade UTUC after tumor resection, and to explore the difference between high- and low-grade patients. Patients confirmed to have UTUC between 2004 and 2015 were selected from the Surveillance, Epidemiology and End Results (SEER) database. The UTUCs were identified and classified as high- and low-grade, and 1-, 3- and 5-year nomograms were established. The nomogram was then validated using the Chinese multicenter dataset (patients diagnosed in Shandong, China between January 2010 and October 2020). In the high-grade UTUC patients, nine important factors related to survival after tumor resection were identified to construct nomogram. The C index of training dataset was 0.740 (95% confidence interval [CI]: 0.727–0.754), showing good calibration. The C index of internal validation dataset was 0.729(95% CI:0.707–0.750). On the other hand, Two independent predictors were identified to construct nomogram of low-grade UTUC. The C index was 0.714 (95% CI: 0.671–0.758) for the training set,0.731(95% CI:0.670–0.791) for the internal validation dataset. Encouragingly, the nomogram was clinically useful and had a good discriminative ability to identify patients at high risk. We constructed a nomogram and a corresponding risk classification system predicting the OS of patients with an initial diagnosis of high-and low-grade UTUC.
机译:高级和低级上部尿路上皮癌(UTUC)之间存在存活差异。我们的研究旨在开发一个NOMA图,以预测肿瘤切除后高压和低级UTUC患者的整体存活(OS),并探讨高级和低级患者之间的差异。从2004年至2015年之间确认有UTUC的患者选自监测,流行病学和最终结果(SEER)数据库。鉴定了UTUC,并将其归类为高,低级和低级,并建立了1-,3和5年的载体图。然后使用中国多中心数据集(2010年1月至10月20日期间)的中国多中心数据集(山东诊断的患者验证了NOM图。在高档尾骨患者中,鉴定了肿瘤切除后与存活相关的9个重要因素,以构建墨迹图。 C训练数据集的C指数为0.740(95%置信区间[CI]:0.727-0.754),显示出良好的校准。内部验证数据集的C指数为0.729(95%CI:0.707-0.750)。另一方面,鉴定了两个独立的预测因子以构建低级utuc的载体。 C指数为培训集的0.714(95%CI:0.671-0.758),内部验证数据集0.731(95%CI:0.670-0.791)。令人鼓舞的是,NOM图是临床上有用的,并且具有良好的鉴别能力,以识别高风险的患者。我们构建了一种NOM图和相应的风险分类系统,预测患者的OS初步诊断高级utuc。

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