Sara Kammerer1,2, Tobias Meister3, Heiner Wolters4, Matthias Lessing5, Anna Hüsing6, Dirk Domagk5,7, Martin Floer3,5, Christian Wilms6, Hartmut Schmidt6, Norbert Senninger4, Gabriele Köhler8, Hauke Sebastian Heinzow6. 1. Department of Radiology, University of Münster, Muenster, Germany. 2. Department of Neuroradiology, University of Frankfurt, Frankfurt, Germany. 3. Department of Gastroenterology, HELIOS Albert-Schweitzer Hospital, Göttingen University Teaching Hospital, Northeim, Germany. 4. Department of General and Visceral Surgery, University of Münster, Münster, Germany. 5. Department of Medicine B, University of Münster, Münster, Germany. 6. Department of Transplant Medicine, University of Münster, Münster, Germany. 7. Department of Medicine I, Josephs-Hospital Warendorf, Münster University Teaching Hospital, Warendorf, Germany. 8. Department of Pathology, University of Münster, Münster, Germany.
Abstract
BACKGROUND: Perihilar cholangiocarcinomas are often considered incurable. Late diagnosis is common. Advanced disease therefore frequently causes questioning of curative surgical outcome. AIM: This study aimed to develop a prediction model of curative surgery in patients suffering from perihilar cholangiocarcinomas based on preoperative endosonography and computer tomography. METHODS: A cohort of 81 patients (median age 67 (54-75) years, 62% male) with perihilar cholangiocarcinoma was retrospectively analyzed. Multivariate logistic regression analysis of staging variables taken from the European Staging System was performed and applied to ROC analysis. RESULTS: The correlation of predicted rates of eligibility for surgery with actual rates reached AUC values between 0.652 and 0.758 for endosonography and computer tomography (p < 0.05 each). Best prediction for curative surgical option was achieved by combining endosonography and computer tomography (AUC: 0.787; 95% CI 0.680-0.893, p < 0.0001). A predictive model (pSurg) was developed using multivariate analysis. CONCLUSIONS: Our predictive web-based model pSurg with inclusion of T, N, M, B, PV, HA and V stage of the recently published European Staging System for perihilar cholangiocarcinoma results in highly significant predictability for curative surgery when combining preoperative endosonography and computer tomography, thus allowing for better patient selection in terms of possibility of curative surgery.
BACKGROUND: Perihilar cholangiocarcinomas are often considered incurable. Late diagnosis is common. Advanced disease therefore frequently causes questioning of curative surgical outcome. AIM: This study aimed to develop a prediction model of curative surgery in patients suffering from perihilar cholangiocarcinomas based on preoperative endosonography and computer tomography. METHODS: A cohort of 81 patients (median age 67 (54-75) years, 62% male) with perihilar cholangiocarcinoma was retrospectively analyzed. Multivariate logistic regression analysis of staging variables taken from the European Staging System was performed and applied to ROC analysis. RESULTS: The correlation of predicted rates of eligibility for surgery with actual rates reached AUC values between 0.652 and 0.758 for endosonography and computer tomography (p < 0.05 each). Best prediction for curative surgical option was achieved by combining endosonography and computer tomography (AUC: 0.787; 95% CI 0.680-0.893, p < 0.0001). A predictive model (pSurg) was developed using multivariate analysis. CONCLUSIONS: Our predictive web-based model pSurg with inclusion of T, N, M, B, PV, HA and V stage of the recently published European Staging System for perihilar cholangiocarcinoma results in highly significant predictability for curative surgery when combining preoperative endosonography and computer tomography, thus allowing for better patient selection in terms of possibility of curative surgery.
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Authors: Miguel Angel Suarez-Munoz; Jose Luis Fernandez-Aguilar; Belinda Sanchez-Perez; Jose Antonio Perez-Daga; Beatriz Garcia-Albiach; Ysabel Pulido-Roa; Naiara Marin-Camero; Julio Santoyo-Santoyo Journal: World J Gastrointest Oncol Date: 2013-07-15