Eric Trépo1, Nicolas Goossens2, Naoto Fujiwara3, Won-Min Song4, Antonio Colaprico5, Astrid Marot6, Laurent Spahr7, Pieter Demetter8, Christine Sempoux9, Gene Y Im10, Joan Saldarriaga9, Thierry Gustot11, Jacques Devière11, Swan N Thung12, Charlotte Minsart13, Thomas Sersté14, Gianluca Bontempi5, Karim Abdelrahman6, Jean Henrion15, Delphine Degré11, Valerio Lucidi16, Laura Rubbia-Brandt17, Venugopalan D Nair18, Christophe Moreno11, Pierre Deltenre19, Yujin Hoshida20, Denis Franchimont11. 1. Department of Gastroenterology, Hepatopancreatology, and Digestive Oncology, C.U.B. Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium; Laboratory of Experimental Gastroenterology, Université Libre de Bruxelles, Brussels, Belgium. Electronic address: etrepo@ulb.ac.be. 2. Division of Liver Diseases, Department of Medicine, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Division of Gastroenterology and Hepatology, Geneva University Hospital, Geneva, Switzerland. 3. Division of Liver Diseases, Department of Medicine, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York. 4. Division of Liver Diseases, Department of Medicine, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York; Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York. 5. Interuniversity Institute of Bioinformatics in Brussels (IB)(2), Brussels, Belgium; Machine Learning Group (MLG), Department d'Informatique, Université Libre de Bruxelles, Brussels, Belgium. 6. Division of Gastroenterology and Hepatology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland. 7. Division of Gastroenterology and Hepatology, Geneva University Hospital, Geneva, Switzerland. 8. Department of Pathology, C.U.B. Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium. 9. Service of Clinical Pathology, Lausanne University Hospital, Institute of Pathology, Lausanne, Switzerland. 10. Recanati/Miller Transplantation Institute, Division of Liver Diseases, Department of Medicine, The Icahn School of Medicine at Mount Sinai, New York, New York. 11. Department of Gastroenterology, Hepatopancreatology, and Digestive Oncology, C.U.B. Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium; Laboratory of Experimental Gastroenterology, Université Libre de Bruxelles, Brussels, Belgium. 12. Mount Sinai Liver Cancer Program, (Divisions of Liver Diseases, Hematology and Medical Oncology, Department of Medicine, Department of Pathology, Recanati Miller Transplantation Institute), Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York. 13. Laboratory of Experimental Gastroenterology, Université Libre de Bruxelles, Brussels, Belgium. 14. Department of Gastroenterology, Hepatopancreatology, and Digestive Oncology, C.U.B. Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium; Department of Hepatogastroenterology, Centre Hospitalier Universitaire Saint-Pierre, Brussels, Belgium. 15. Service d'Hépato-Gastroentérologie, Hôpital de Jolimont, Haine-Saint-Paul, Belgium. 16. Department of Abdominal Surgery, Hôpital Erasme, Centre de Chirurgie Hépato-Biliaire de l'ULB, Université Libre de Bruxelles, Brussels, Belgium. 17. Division of Pathology, University Hospital, Geneva, Switzerland. 18. Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York. 19. Department of Gastroenterology, Hepatopancreatology, and Digestive Oncology, C.U.B. Hôpital Erasme, Université Libre de Bruxelles, Brussels, Belgium; Division of Gastroenterology and Hepatology, Centre Hospitalier Universitaire Vaudois, University of Lausanne, Lausanne, Switzerland; Service d'Hépato-Gastroentérologie, Hôpital de Jolimont, Haine-Saint-Paul, Belgium. 20. Division of Liver Diseases, Department of Medicine, Tisch Cancer Institute, Icahn School of Medicine at Mount Sinai, New York, New York. Electronic address: yujin.hoshida@mssm.edu.
Abstract
BACKGROUND & AIMS: Patients with severe alcoholic hepatitis (AH) have a high risk of death within 90 days. Corticosteroids, which can cause severe adverse events, are the only treatment that increases short-term survival. It is a challenge to predict outcomes of patients with severe AH. Therefore, we developed a scoring system to predict patient survival, integrating baseline molecular and clinical variables. METHODS: We obtained fixed liver biopsy samples from 71 consecutive patients diagnosed with severe AH and treated with corticosteroids from July 2006 through December 2013 in Brussels, Belgium (derivation cohort). Gene expression patterns were analyzed by microarrays and clinical data were collected for 180 days. We identified gene expression signatures and clinical data that are associated with survival without liver transplantation at 90 and 180 days after initiation of corticosteroid therapy. Findings were validated using liver biopsies from 48 consecutive patients with severe AH treated with corticosteroids, collected from March 2010 through February 2015 at hospitals in Belgium and Switzerland (validation cohort 1) and in liver biopsies from 20 patients (9 received corticosteroid treatment), collected from January 2012 through May 2015 in the United States (validation cohort 2). RESULTS: We integrated data on expression patterns of 123 genes and the model for end-stage liver disease (MELD) scores to assign patients to groups with poor survival (29% survived 90 days and 26% survived 180 days) and good survival (76% survived 90 days and 65% survived 180 days) (P < .001) in the derivation cohort. We named this assignment system the gene signature-MELD (gs-MELD) score. In validation cohort 1, the gs-MELD score discriminated patients with poor survival (43% survived 90 days) from those with good survival (96% survived 90 days) (P < .001). The gs-MELD score also discriminated between patients with a poor survival at 180 days (34% survived) and a good survival at 180 days (84% survived) (P < .001). The time-dependent area under the receiver operator characteristic curve for the score was 0.86 (95% confidence interval 0.73-0.99) for survival at 90 days, and 0.83 (95% confidence interval 0.71-0.96) for survival at 180 days. This score outperformed other clinical models to predict survival of patients with severe AH in validation cohort 1. In validation cohort 2, the gs-MELD discriminated patients with a poor survival at 90 days (12% survived) from those with a good survival at 90 days (100%) (P < .001). CONCLUSIONS: We integrated data on baseline liver gene expression pattern and the MELD score to create the gs-MELD scoring system, which identifies patients with severe AH, treated or not with corticosteroids, most and least likely to survive for 90 and 180 days.
BACKGROUND & AIMS: Patients with severe alcoholic hepatitis (AH) have a high risk of death within 90 days. Corticosteroids, which can cause severe adverse events, are the only treatment that increases short-term survival. It is a challenge to predict outcomes of patients with severe AH. Therefore, we developed a scoring system to predict patient survival, integrating baseline molecular and clinical variables. METHODS: We obtained fixed liver biopsy samples from 71 consecutive patients diagnosed with severe AH and treated with corticosteroids from July 2006 through December 2013 in Brussels, Belgium (derivation cohort). Gene expression patterns were analyzed by microarrays and clinical data were collected for 180 days. We identified gene expression signatures and clinical data that are associated with survival without liver transplantation at 90 and 180 days after initiation of corticosteroid therapy. Findings were validated using liver biopsies from 48 consecutive patients with severe AH treated with corticosteroids, collected from March 2010 through February 2015 at hospitals in Belgium and Switzerland (validation cohort 1) and in liver biopsies from 20 patients (9 received corticosteroid treatment), collected from January 2012 through May 2015 in the United States (validation cohort 2). RESULTS: We integrated data on expression patterns of 123 genes and the model for end-stage liver disease (MELD) scores to assign patients to groups with poor survival (29% survived 90 days and 26% survived 180 days) and good survival (76% survived 90 days and 65% survived 180 days) (P < .001) in the derivation cohort. We named this assignment system the gene signature-MELD (gs-MELD) score. In validation cohort 1, the gs-MELD score discriminated patients with poor survival (43% survived 90 days) from those with good survival (96% survived 90 days) (P < .001). The gs-MELD score also discriminated between patients with a poor survival at 180 days (34% survived) and a good survival at 180 days (84% survived) (P < .001). The time-dependent area under the receiver operator characteristic curve for the score was 0.86 (95% confidence interval 0.73-0.99) for survival at 90 days, and 0.83 (95% confidence interval 0.71-0.96) for survival at 180 days. This score outperformed other clinical models to predict survival of patients with severe AH in validation cohort 1. In validation cohort 2, the gs-MELD discriminated patients with a poor survival at 90 days (12% survived) from those with a good survival at 90 days (100%) (P < .001). CONCLUSIONS: We integrated data on baseline liver gene expression pattern and the MELD score to create the gs-MELD scoring system, which identifies patients with severe AH, treated or not with corticosteroids, most and least likely to survive for 90 and 180 days.
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