Development and External Validation of a Model to Predict Overall Survival in Patients With Resected Gallbladder Cancer

医学 胆囊癌 队列 AJCC分段系统 内科学 队列研究 肿瘤科 生存分析 外科 癌症 登台系统
作者
Elise A. J. de Savornin Lohman,Tessa J. J. de Bitter,Gerjon Hannink,Marianne F. T. Wietsma,Elisa Vink‐Börger,Irıs D. Nagtegaal,Thomas J. Hugh,Anthony J. Gill,Nazim Bhimani,Mahsa Ahadi,Rachel S. van der Post,Philip R. de Reuver
出处
期刊:Annals of Surgery [Ovid Technologies (Wolters Kluwer)]
卷期号:277 (4): e856-e863 被引量:10
标识
DOI:10.1097/sla.0000000000005154
摘要

The aim of this study was to develop and validate a clinical prediction model to predict overall survival in patients with nonmetastatic, resected gallbladder cancer (GBC).Although several tools are available, no optimal method has been identified to assess survival in patients with resected GBC.Data from a Dutch, nation-wide cohort of patients with resected GBC was used to develop a prediction model for overall survival. The model was internally validated and a cohort of Australian GBC patients who underwent resection was used for external validation. The performance of the American Joint Committee on Cancer (AJCC) staging system and the present model were compared.In total, 446 patients were included; 380 patients in the development cohort and 66 patients in the validation cohort. In the development cohort median survival was 22 months (median follow-up 75 months). Age, T/N classification, resection margin, differentiation grade, and vascular invasion were independent predictors of survival. The externally validated C-index was 0.75 (95%CI: 0.69-0.80), implying good discriminatory capacity. The discriminative ability of the present model after internal validation was superior to the ability of the AJCC staging system (Harrell C-index 0.71, [95%CI: 0.69-0.72) vs. 0.59 (95% CI: 0.57-0.60)].The proposed model for the prediction of overall survival in patients with resected GBC demonstrates good discriminatory capacity, reasonable calibration and outperforms the authoritative AJCC staging system. This model can be a useful tool for physicians and patients to obtain information about survival after resection and is available from https:// gallbladderresearch.shinyapps.io/Predict_GBC_survival/.
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