Prediction of Early Recurrence After Surgery for Liver Tumor (ERASL): An International Validation of the ERASL Risk Models

肝肿瘤手术后早期复发预测(ERASL):ERASL风险模型的国际验证

阅读:1

Abstract

BACKGROUND: This study aimed to assess the performance of the pre- and postoperative early recurrence after surgery for liver tumor (ERASL) models at external validation. Prediction of early hepatocellular carcinoma (HCC) recurrence after resection is important for individualized surgical management. Recently, the preoperative (ERASL-pre) and postoperative (ERASL-post) risk models were proposed based on patients from Hong Kong. These models showed good performance although they have not been validated to date by an independent research group. METHODS: This international cohort study included 279 patients from the Netherlands and 392 patients from Japan. The patients underwent first-time resection and showed a diagnosis of HCC on pathology. Performance was assessed according to discrimination (concordance [C] statistic) and calibration (correspondence between observed and predicted risk) with recalibration in a Weibull model. RESULTS: The discriminatory power of both models was lower in the Netherlands than in Japan (C statistic, 0.57 [95% confidence interval {CI} 0.52-0.62] vs 0.69 [95% CI 0.65-0.73] for the ERASL-pre model and 0.62 [95% CI 0.57-0.67] vs 0.70 [95% CI 0.66-0.74] for the ERASL-post model), whereas their prognostic profiles were similar. The predictions of the ERASL models were systematically too optimistic for both cohorts. Recalibrated ERASL models improved local applicability for both cohorts. CONCLUSIONS: The discrimination of ERASL models was poorer for the Western patients than for the Japanese patients, who showed good performance. Recalibration of the models was performed, which improved the accuracy of predictions. However, in general, a model that explains the East-West difference or one tailored to Western patients still needs to be developed.

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。