Elise A J de Savornin Lohman1, T J J de Bitter, G Hannink, M F T Wietsma, E Vink-Börger, I D Nagtegaal, T J Hugh, A J Gill, N Bhimani, M Seyed Ahadi, R S van der Post, Philip R de Reuver. 1. Radboud university medical center, Radboud institute for Health Sciences, Department of Surgery, Nijmegen, The Netherlands Department of Surgery, Erasmus MC, Rotterdam, the Netherlands Radboud university medical center, Radboud institute of Molecular Life Sciences, Department of Pathology, Nijmegen, The Netherlands Radboud university medical center, Radboud institute for Health Sciences, Department of Operating Rooms, Nijmegen, The Netherlands Royal North Shore Hospital, Upper GI Surgical Unit, University of Sydney, Australia University of Sydney, Sydney, New South Wales, Australia.
Abstract
OBJECTIVE: The aim of this study was to develop and validate a clinical prediction model to predict overall survival in patients with non-metastatic, resected gallbladder cancer (GBC). BACKGROUND: Although several tools are available, no optimal method has been identified to assess survival in patients with resected GBC. METHODS: 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 AJCC staging system and the present model were compared. RESULTS: 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's C-index 0.71, (95%CI 0.69-0.72) versus 0.59 (95%CI 0.57-0.60)). CONCLUSION: 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/.
OBJECTIVE: The aim of this study was to develop and validate a clinical prediction model to predict overall survival in patients with non-metastatic, resected gallbladder cancer (GBC). BACKGROUND: Although several tools are available, no optimal method has been identified to assess survival in patients with resected GBC. METHODS: 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 AJCC staging system and the present model were compared. RESULTS: 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's C-index 0.71, (95%CI 0.69-0.72) versus 0.59 (95%CI 0.57-0.60)). CONCLUSION: 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/.