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Development and external validation of a prediction model for survival in patients with resected ampullary adenocarcinoma

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. An i...

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Published in:European journal of surgical oncology 2020-09, Vol.46 (9), p.1717-1726
Main Authors: Moekotte, Alma L., van Roessel, Stijn, Malleo, Giuseppe, Rajak, Rushda, Ecker, Brett L., Fontana, Martina, Han, Ho-Seong, Rabie, Mohamed, Roberts, Keith J., Khalil, Khalid, White, Steven A., Robinson, Stuart, Halimi, Asif, Zarantonello, Laura, Fusai, Giuseppe K., Gradinariu, George, Alseidi, Adnan, Bonds, Morgan, Dreyer, Stephan, Jamieson, Nigel B., Mowbray, Nicholas, Al-Sarireh, Bilal, Mavroeidis, Vasileios K., Soonawalla, Zahir, Napoli, Niccolò, Boggi, Ugo, Kent, Tara S., Fisher, William E., Tang, Chung N., Bolm, Louisa, House, Michael G., Dillhoff, Mary E., Behrman, Stephen W., Nakamura, Masafumi, Ball, Chad G., Berger, Adam C., Christein, John D., Zureikat, Amer H., Salem, Ronald R., Vollmer, Charles M., Salvia, Roberto, Besselink, Marc G., Abu Hilal, Mohammed, Aljarrah, Ra'ed, Barrows, Courtney, Cagigas, Martha Navarro, Lai, Eric C.H., Wellner, Ulrich, Aversa, John, Dickson, Paxton V., Ohtsuka, Takao, Dixon, Elijah, Zheng, Richard, Kowalski, Stacy, Freedman-Weiss, Mollie
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Language:English
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Summary: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. 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. 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 
ISSN:0748-7983
1532-2157
DOI:10.1016/j.ejso.2020.04.011