Individualized Prognostic Insights: CONUT-GBRS for Survival Prediction in Gallbladder Cancer

个体化预后评估:CONUT-GBRS评分在胆囊癌生存预测中的应用

阅读:2

Abstract

BACKGROUND: The most suitable prognostic prediction system for gallbladder cancer (GBC) is yet to be determined. This study aims to establish a combined score integrating preoperative patients' nutritional and immune status and pathological parameters to forecast the survival outcomes following curative-intent surgery of GBC. METHODS: This retrospective study included patients diagnosed with GBC based on postoperative pathological examinations. The patients underwent curative surgery at West China Hospital of Sichuan University (China) between January 2014 and December 2022. Using the controlling nutritional status (CONUT) score and gallbladder cancer predictive risk score (GBRS), we generated the CONUT-GBRS for every patient, and the patients were divided into two groups based on the optimal cutoff value. Comparisons were made between the two groups regarding clinicopathologic features and survival. RESULTS: The optimal cutoff value for the CONUT-GBRS was 1.39. There were 99 and 201 individuals in the high and low CONUT-GBRS groups, respectively. Patients with high CONUT-GBRS experienced poorer overall survival and disease-free survival compared with those with low CONUT-GBRS, even after propensity score matching analysis. Both univariate and multivariate Cox analyses established that CONUT-GBRS stood as an independent prognostic factor for GBC patients. Subgroup analysis indicated that CONUT-GBRS was also an effective predictor of prognosis in patients with incidental GBC. CONCLUSION: The CONUT-GBRS serves as an advantageous, straightforward, and cost-effective prognostic tool for GBC, offering valuable prognostic insights and guiding the tailoring of individualized treatment strategies to improve patient outcomes.

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。