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.
2020
Moekotte, A. L.; van Roessel, S.; Malleo, G.; Rajak, R.; Ecker, B. L.; Fontana, M.; Han, H. -S.; Rabie, M.; Roberts, K. J.; Khalil, K.; White, S. A.; Robinson, S.; Halimi, A.; Zarantonello, L.; Fusai, G. K.; Gradinariu, G.; Alseidi, A.; Bonds, M.; Dreyer, S.; Jamieson, N. B.; Mowbray, N.; Al-Sarireh, B.; Mavroeidis, V. K.; Soonawalla, Z.; Napoli, N.; Boggi, U.; Kent, T. S.; Fisher, W. E.; Tang, C. N.; Bolm, L.; House, M. G.; Dillhoff, M. E.; Behrman, S. W.; Nakamura, M.; Ball, C. G.; Berger, A. C.; Christein, J. D.; Zureikat, A. H.; Salem, R. R.; Vollmer, C. M.; Salvia, R.; Besselink, M. G.; Abu Hilal, M.; Aljarrah, R.; Barrows, C.; Cagigas, M. N.; Lai, E. C. H.; Wellner, U.; Aversa, J.; Dickson, P. V.; Ohtsuka, T.; Dixon, E.; Zheng, R.; Kowalski, S.; Freedman-Weiss, M.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11568/1055959
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