Browsing by Author "Lorenzoni, G"
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- Dynamic Prediction of Survival After Curative Resection of Intrahepatic Cholangiocarcinoma: a Landmarking-Based AnalysisPublication . Spolverato, G; Capelli, G; Lorenzoni, G; Gregori, D; He, J; Popescu, I; Pinto Marques, H; Aldrighetti, L; Maithel, S; Pulitano, C; Bauer, T; Shen, F; Poultsides, G; Soubrane, O; Martel, G; Koerkamp, B; Itaru, E; Lv, Y; Pawlik, TBackground: The current study aimed to develop a dynamic prognostic model for patients undergoing curative-intent resection for intrahepatic cholangiocarcinoma (ICC) using landmark analysis. Methods: Patients who underwent curative-intent surgery for ICC from 1999 to 2017 were selected from a multi-institutional international database. A landmark analysis to undertake dynamic overall survival (OS) prediction was performed. A multivariate Cox proportional hazard model was applied to measure the interaction of selected variables with time. The performance of the model was internally cross-validated via bootstrap resampling procedure. Discrimination was evaluated using the Harrell's Concordance Index. Accuracy was evaluated with calibration plots. Results: Variables retained in the multivariable Cox regression OS model included age, tumor size, margin status, morphologic type, histologic grade, T and N category, and tumor recurrence. The effect of several variables on OS changed over time. Results were provided as a survival plot and the predicted probability of OS at the desired time in the future. For example, a 65-year-old patient with an intraductal, T1, grade 3 or 4 ICC measuring 3 cm who underwent an R0 resection had a calculated estimated 3-year OS of 76%. The OS estimate increased if the patient had already survived 1 year (79%). The discrimination ability of the final model was very good (C-index: 0.80). Conclusion: The long-term outcome for patients undergoing curative-intent surgery for ICC should be adjusted based on follow-up time and intervening events. The model in this study showed excellent discriminative ability and performed well in the validation process.