Georg Semmler1, Elias Laurin Meyer2, Karin Kozbial3, Philipp Schwabl1, Stefanie Hametner-Schreil4, Alberto Zanetto5, David Bauer1, David Chromy1, Benedikt Simbrunner1, Bernhard Scheiner1, Albert F Stättermayer1, Matthias Pinter1, Rainer Schöfl4, Francesco Paolo Russo5, Helena Greenfield6, Michael Schwarz7, Caroline Schwarz7, Michael Gschwantler7, Sonia Alonso López8, Maria Luisa Manzano9, Adriana Ahumada10, Rafael Bañares11, Mònica Pons12, Sergio Rodríguez-Tajes13, Joan Genescà14, Sabela Lens13, Michael Trauner3, Peter Ferenci3, Thomas Reiberger1, Mattias Mandorfer15. 1. Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria; Vienna Hepatic Hemodynamic Lab, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria. 2. Institute for Medical Statistics, Center for Medical Statistics, Informatics and Intelligent Systems, Medical University Vienna, Vienna, Austria. 3. Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria. 4. Internal Medicine IV, Ordensklinikum Linz Barmherzige Schwestern, Linz, Austria. 5. Gastroenterology and Multivisceral Transplant Unit, Department of Surgery, Oncology, and Gastroenterology, Padua University Hospital, Padua, Italy. 6. Vienna Hepatic Hemodynamic Lab, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria. 7. Department of Gastroenterology and Hepatology, Klinikum Ottakring, Vienna, Austria. 8. Liver Unit, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto De Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain. 9. Liver Unit, Hospital Universitario 12 De Octubre, Madrid, Spain. 10. Liver Unit, Hospital General Universitario Gregorio Marañón, Madrid, Spain. 11. Liver Unit, Hospital General Universitario Gregorio Marañón, Madrid, Spain; Instituto De Investigación Sanitaria Gregorio Marañón (IiSGM), Madrid, Spain; Universidad Complutense de Madrid, Madrid, Spain; Centro de Investigación Biomédica En Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Madrid, Spain. 12. Liver Unit, Department of Internal Medicine, Hospital Universitari Vall d'Hebron, Vall d'Hebron Institut de Recerca (VHIR), Vall d'Hebron Barcelona Hospital Campus, Universitat Autònoma de Barcelona, Barcelona, Spain. 13. Centro de Investigación Biomédica En Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Madrid, Spain; Liver Unit, Hospital Clínic, Universitat de Barcelona, Barcelona, Spain; August Pi i Sunyer Biomedical Research Institute (IDIBAPS), Universitat de Barcelona, Barcelona, Spain. 14. Centro de Investigación Biomédica En Red de Enfermedades Hepáticas y Digestivas (CIBERehd), Instituto de Salud Carlos III, Madrid, Spain; Liver Unit, Department of Internal Medicine, Hospital Universitari Vall d'Hebron, Vall d'Hebron Institut de Recerca (VHIR), Vall d'Hebron Barcelona Hospital Campus, Universitat Autònoma de Barcelona, Barcelona, Spain. 15. Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria; Vienna Hepatic Hemodynamic Lab, Division of Gastroenterology and Hepatology, Department of Internal Medicine III, Medical University of Vienna, Vienna, Austria. Electronic address: mattias.mandorfer@meduniwien.ac.at.
Abstract
BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) is a major cause of morbidity and mortality in patients with advanced chronic liver disease (ACLD) caused by chronic hepatitis C who have achieved sustained virologic response (SVR). We developed risk stratification algorithms for de novo HCC development after SVR and validated them in an independent cohort. METHODS: We evaluated the occurrence of de novo HCC in a derivation cohort of 527 patients with pre-treatment ACLD and SVR to interferon-free therapy, in whom alpha-fetoprotein (AFP) and non-invasive surrogates of portal hypertension including liver stiffness measurement (LSM) were assessed pre-/post-treatment. We validated our results in 1,500 patients with compensated ACLD (cACLD) from other European centers. RESULTS: During a median follow-up (FU) of 41 months, 22/475 patients with cACLD (4.6%, 1.45/100 patient-years) vs. 12/52 decompensated patients (23.1%, 7.00/100 patient-years, p <0.001) developed de novo HCC. Since decompensated patients were at substantial HCC risk, we focused on cACLD for all further analyses. In cACLD, post-treatment-values showed a higher discriminative ability for patients with/without de novo HCC development during FU than pre-treatment values or absolute/relative changes. Models based on post-treatment AFP, alcohol consumption (optional), age, LSM, and albumin, accurately predicted de novo HCC development (bootstrapped Harrel's C with/without considering alcohol: 0.893/0.836). Importantly, these parameters also provided independent prognostic information in competing risk analysis and accurately stratified patients into low- (~2/3 of patients) and high-risk (~1/3 of patients) groups in the derivation (algorithm with alcohol consumption; 4-year HCC-risk: 0% vs. 16.5%) and validation (3.3% vs. 17.5%) cohorts. An alternative approach based on alcohol consumption (optional), age, LSM, and albumin (i.e., without AFP) also showed a robust performance. CONCLUSIONS: Simple algorithms based on post-treatment age/albumin/LSM, and optionally, AFP and alcohol consumption, accurately stratified patients with cACLD based on their risk of de novo HCC after SVR. Approximately two-thirds were identified as having an HCC risk <1%/year in both the derivation and validation cohort, thereby clearly falling below the cost-effectiveness threshold for HCC surveillance. LAY SUMMARY: Simple algorithms based on age, alcohol consumption, results of blood tests (albumin and α-fetoprotein), as well as liver stiffness measurement after the end of hepatitis C treatment identify a large proportion (approximately two-thirds) of patients with advanced but still asymptomatic liver disease who are at very low risk (<1%/year) of liver cancer development, and thus, might not need to undergo 6-monthly liver ultrasound.
BACKGROUND & AIMS: Hepatocellular carcinoma (HCC) is a major cause of morbidity and mortality in patients with advanced chronic liver disease (ACLD) caused by chronic hepatitis C who have achieved sustained virologic response (SVR). We developed risk stratification algorithms for de novo HCC development after SVR and validated them in an independent cohort. METHODS: We evaluated the occurrence of de novo HCC in a derivation cohort of 527 patients with pre-treatment ACLD and SVR to interferon-free therapy, in whom alpha-fetoprotein (AFP) and non-invasive surrogates of portal hypertension including liver stiffness measurement (LSM) were assessed pre-/post-treatment. We validated our results in 1,500 patients with compensated ACLD (cACLD) from other European centers. RESULTS: During a median follow-up (FU) of 41 months, 22/475 patients with cACLD (4.6%, 1.45/100 patient-years) vs. 12/52 decompensated patients (23.1%, 7.00/100 patient-years, p <0.001) developed de novo HCC. Since decompensated patients were at substantial HCC risk, we focused on cACLD for all further analyses. In cACLD, post-treatment-values showed a higher discriminative ability for patients with/without de novo HCC development during FU than pre-treatment values or absolute/relative changes. Models based on post-treatment AFP, alcohol consumption (optional), age, LSM, and albumin, accurately predicted de novo HCC development (bootstrapped Harrel's C with/without considering alcohol: 0.893/0.836). Importantly, these parameters also provided independent prognostic information in competing risk analysis and accurately stratified patients into low- (~2/3 of patients) and high-risk (~1/3 of patients) groups in the derivation (algorithm with alcohol consumption; 4-year HCC-risk: 0% vs. 16.5%) and validation (3.3% vs. 17.5%) cohorts. An alternative approach based on alcohol consumption (optional), age, LSM, and albumin (i.e., without AFP) also showed a robust performance. CONCLUSIONS: Simple algorithms based on post-treatment age/albumin/LSM, and optionally, AFP and alcohol consumption, accurately stratified patients with cACLD based on their risk of de novo HCC after SVR. Approximately two-thirds were identified as having an HCC risk <1%/year in both the derivation and validation cohort, thereby clearly falling below the cost-effectiveness threshold for HCC surveillance. LAY SUMMARY: Simple algorithms based on age, alcohol consumption, results of blood tests (albumin and α-fetoprotein), as well as liver stiffness measurement after the end of hepatitis C treatment identify a large proportion (approximately two-thirds) of patients with advanced but still asymptomatic liver disease who are at very low risk (<1%/year) of liver cancer development, and thus, might not need to undergo 6-monthly liver ultrasound.
Authors: Francesco Paolo Russo; Alberto Zanetto; Elisa Pinto; Sara Battistella; Barbara Penzo; Patrizia Burra; Fabio Farinati Journal: Int J Mol Sci Date: 2022-01-02 Impact factor: 5.923
Authors: Kelley G Núñez; Tyler Sandow; Jai Patel; Mina Hibino; Daniel Fort; Ari J Cohen; Paul Thevenot Journal: Cancers (Basel) Date: 2022-03-25 Impact factor: 6.639