Introduction: Ampullary adenocarcinoma (AAC) is a rare malignancy with great morphological heterogeneity, which complicates the prediction of survival and, therefore, clinical decision-making. The aim of this study was to develop and externally validate a prediction model for survival after resection of AAC. Materials and methods: An international multicenter cohort study was conducted, including patients who underwent pancreatoduodenectomy for AAC (2006–2017) from 27 centers in 10 countries spanning three continents. A derivation and validation cohort were separately collected. Predictors were selected from the derivation cohort using a LASSO Cox proportional hazards model. A nomogram was created based on shrunk coefficients. Model performance was assessed in the derivation cohort and subsequently in the validation cohort, by calibration plots and Uno's C-statistic. Four risk groups were created based on quartiles of the nomogram score. Results: Overall, 1007 patients were available for development of the model. Predictors in the final Cox model included age, resection margin, tumor differentiation, pathological T stage and N stage (8th AJCC edition). Internal cross-validation demonstrated a C-statistic of 0.75 (95% CI 0.73–0.77). External validation in a cohort of 462 patients demonstrated a C-statistic of 0.77 (95% CI 0.73–0.81). A nomogram for the prediction of 3- and 5-year survival was created. The four risk groups showed significantly different 5-year survival rates (81%, 57%, 22% and 14%, p < 0.001). Only in the very-high risk group was adjuvant chemotherapy associated with an improved overall survival. Conclusion: A prediction model for survival after curative resection of AAC was developed and externally validated. The model is easily available online via www.pancreascalculator.com.
Development and external validation of a prediction model for survival in patients with resected ampullary adenocarcinoma
Napoli N.;Boggi U.;
2020-01-01
Abstract
Introduction: Ampullary adenocarcinoma (AAC) is a rare malignancy with great morphological heterogeneity, which complicates the prediction of survival and, therefore, clinical decision-making. The aim of this study was to develop and externally validate a prediction model for survival after resection of AAC. Materials and methods: An international multicenter cohort study was conducted, including patients who underwent pancreatoduodenectomy for AAC (2006–2017) from 27 centers in 10 countries spanning three continents. A derivation and validation cohort were separately collected. Predictors were selected from the derivation cohort using a LASSO Cox proportional hazards model. A nomogram was created based on shrunk coefficients. Model performance was assessed in the derivation cohort and subsequently in the validation cohort, by calibration plots and Uno's C-statistic. Four risk groups were created based on quartiles of the nomogram score. Results: Overall, 1007 patients were available for development of the model. Predictors in the final Cox model included age, resection margin, tumor differentiation, pathological T stage and N stage (8th AJCC edition). Internal cross-validation demonstrated a C-statistic of 0.75 (95% CI 0.73–0.77). External validation in a cohort of 462 patients demonstrated a C-statistic of 0.77 (95% CI 0.73–0.81). A nomogram for the prediction of 3- and 5-year survival was created. The four risk groups showed significantly different 5-year survival rates (81%, 57%, 22% and 14%, p < 0.001). Only in the very-high risk group was adjuvant chemotherapy associated with an improved overall survival. Conclusion: A prediction model for survival after curative resection of AAC was developed and externally validated. The model is easily available online via www.pancreascalculator.com.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
