Preoperative Prediction Model for Early Recurrence of Intrahepatic Cholangiocarcinoma after Surgical Resection: Development and External Validation Study

肝内胆管癌手术切除后早期复发的术前预测模型:开发和外部验证研究

阅读:1

Abstract

PURPOSE: We aimed to develop a preoperative risk scoring system to predict early recurrence (ER) of intrahepatic cholangiocarcinoma (ICCA) after resection, utilizing clinical and computed tomography (CT) features. MATERIALS AND METHODS: This multicenter study included 365 patients who underwent curative-intent surgical resection for ICCA at six institutions between 2009 and 2016. Of these, 264 patients from one institution constituted the development cohort, while 101 patients from the other institutions constituted the external validation cohort. Logistic regression models were constructed to predict ER based on preoperative variables and were subsequently translated into a risk scoring system. The discrimination performance of the risk scoring system was validated using external data and compared to the American Joint Committee on Cancer (AJCC) TNM staging system. RESULTS: Among the 365 patients (mean age, 62±10 years), 153 had ER. A preoperative risk scoring system that incorporated both clinical and CT features demonstrated superior discriminatory performance compared to the postoperative AJCC TNM staging system in both the development (area under the curve [AUC], 0.78 vs. 0.68; p=0.002) and validation cohorts (AUC, 0.69 vs. 0.66; p=0.641). The preoperative risk scoring system effectively stratified patients based on their risk for ER: the 1-year recurrence-free survival rates for the low, intermediate, and high-risk groups were 85.5%, 56.6%, and 15.6%, respectively (p < 0.001) in the development cohort, and 87.5%, 58.5%, and 25.0%, respectively (p < 0.001) in the validation cohort. CONCLUSION: A preoperative risk scoring system that incorporates clinical and CT imaging features was valuable in identifying high-risk patients with ICCA for ER following resection.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。