Predictive risk-score model to select patients with intrahepatic cholangiocarcinoma for adjuvant chemotherapy. Issue 2 (February 2023)

• Record Type: Journal Article
• Authors: Endo, Yutaka; Moazzam, Zorays; Alaimo, Laura; Lima, Henrique A.; Munir, Muhammad M.; Shaikh, Chanza F.; Guglielmi, Alfredo; Aldrighetti, Luca; Weiss, Matthew; Bauer, Todd W.; Alexandrescu, Sorin; Poultsides, George A.; Kitago, Minoru; Maithel, Shishir K.; Marques, Hugo P.; Martel, Guillaume; Pulitano, Carlo; Shen, Feng; Cauchy, François; Koerkamp, Bas G.; Endo, Itaru; Pawlik, Timothy M.
• Is Part Of: HPB. Volume 25:Issue 2(2023)
• Page Start: 229
• Page End: 238
• Publication Date: 2023-02
• Subjects: Liver -- Diseases -- Periodicals; Biliary tract -- Diseases -- Periodicals; Pancreas -- Diseases -- Periodicals; 616.362005
• DOI: 10.1016/j.hpb.2022.10.011
• Languages: English
• ISSNs: 1365-182X

Abstract

Abstract: Background: The aim of this study was to develop a predictive model to identify individuals most likely to derive overall survival (OS) benefit from adjuvant chemotherapy (AC) after hepatic resection of intrahepatic cholangiocarcinoma (ICC). Methods: Patients who underwent hepatic resection of ICC between 1990 and 2020 were identified from a multi-institutional database. Factors associated with worse OS were identified and incorporated into an online predictive model to identify patients most likely to benefit from AC. Results: Among 726 patients, 189 (26.0%) individuals received AC. Factors associated with OS on multivariable analysis included CA19-9 (Hazard Ratio [HR]1.17, 95%CI 1.04–1.31), tumor burden score (HR1.09, 95%CI 1.04–1.15), T-category (T2/3/4, HR1.73, 95%CI 1.73–2.64), nodal disease (N1, HR3.80, 95%CI 2.02–7.15), tumor grade (HR1.88, 95%CI 1.00–3.55), and morphological subtype (HR2.19, 95%CI 1.08–4.46). A weighted predictive score was devised and made available online (https://yutaka-endo.shinyapps.io/ICCrisk_model_for_AC/ ). Receipt of AC was associated with a survival benefit among patients at high/medium-risk (high: no AC, 0% vs. AC, 20.6%; medium: no AC, 36.4% vs. 40.8%; both p < 0.05) but not low-risk (low: no AC, 65.1% vs. AC, 65.1%; p = 0.73) tumors. Conclusion: An online predictive model based on tumor characteristics may help identify which patients may benefit the most from AC following resection of ICC.