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.

Predictive risk-score model to select patients with intrahepatic cholangiocarcinoma for adjuvant chemotherapy

Alaimo, Laura;Guglielmi, Alfredo;
2022-01-01

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.
2022
Predictive risk-score model, intrahepatic cholangiocarcinoma, adjuvant chemotherapy
File in questo prodotto:
Non ci sono file associati a questo prodotto.

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11562/1085011
Citazioni
  • ???jsp.display-item.citation.pmc??? 0
  • Scopus 3
  • ???jsp.display-item.citation.isi??? 1
social impact