Early prediction of decompensation (EPOD) score: Non-invasive determination of cirrhosis decompensation risk.


Journal

Liver international : official journal of the International Association for the Study of the Liver
ISSN: 1478-3231
Titre abrégé: Liver Int
Pays: United States
ID NLM: 101160857

Informations de publication

Date de publication:
03 2022
Historique:
revised: 10 12 2021
received: 15 09 2021
accepted: 05 01 2022
pubmed: 11 1 2022
medline: 4 3 2022
entrez: 10 1 2022
Statut: ppublish

Résumé

Decompensation is a hallmark of disease progression in cirrhotic patients. Early detection of a phase transition from compensated cirrhosis to decompensation would enable targeted therapeutic interventions potentially extending life expectancy. This study aims to (a) identify the predictors of decompensation in a large, multicentric cohort of patients with compensated cirrhosis, (b) to build a reliable prognostic score for decompensation and (c) to evaluate the score in independent cohorts. Decompensation was identified in electronic health records data from 6049 cirrhosis patients in the IBM Explorys database training cohort by diagnostic codes for variceal bleeding, encephalopathy, ascites, hepato-renal syndrome and/or jaundice. We identified predictors of clinical decompensation and developed a prognostic score using Cox regression analysis. The score was evaluated using the IBM Explorys database validation cohort (N = 17662), the Penn Medicine BioBank (N = 1326) and the UK Biobank (N = 317). The new Early Prediction of Decompensation (EPOD) score uses platelet count, albumin, and bilirubin concentration. It predicts decompensation during a 3-year follow-up in three validation cohorts with AUROCs of 0.69, 0.69 and 0.77, respectively, and outperforms the well-known MELD and Child-Pugh score in predicting decompensation. Furthermore, the EPOD score predicted the 3-year probability of decompensation. The EPOD score provides a prediction tool for the risk of decompensation in patients with cirrhosis that outperforms well-known cirrhosis scores. Since EPOD is based on three blood parameters, only, it provides maximal clinical feasibility at minimal costs.

Sections du résumé

BACKGROUND & AIMS
Decompensation is a hallmark of disease progression in cirrhotic patients. Early detection of a phase transition from compensated cirrhosis to decompensation would enable targeted therapeutic interventions potentially extending life expectancy. This study aims to (a) identify the predictors of decompensation in a large, multicentric cohort of patients with compensated cirrhosis, (b) to build a reliable prognostic score for decompensation and (c) to evaluate the score in independent cohorts.
METHODS
Decompensation was identified in electronic health records data from 6049 cirrhosis patients in the IBM Explorys database training cohort by diagnostic codes for variceal bleeding, encephalopathy, ascites, hepato-renal syndrome and/or jaundice. We identified predictors of clinical decompensation and developed a prognostic score using Cox regression analysis. The score was evaluated using the IBM Explorys database validation cohort (N = 17662), the Penn Medicine BioBank (N = 1326) and the UK Biobank (N = 317).
RESULTS
The new Early Prediction of Decompensation (EPOD) score uses platelet count, albumin, and bilirubin concentration. It predicts decompensation during a 3-year follow-up in three validation cohorts with AUROCs of 0.69, 0.69 and 0.77, respectively, and outperforms the well-known MELD and Child-Pugh score in predicting decompensation. Furthermore, the EPOD score predicted the 3-year probability of decompensation.
CONCLUSIONS
The EPOD score provides a prediction tool for the risk of decompensation in patients with cirrhosis that outperforms well-known cirrhosis scores. Since EPOD is based on three blood parameters, only, it provides maximal clinical feasibility at minimal costs.

Identifiants

pubmed: 35007409
doi: 10.1111/liv.15161
doi:

Types de publication

Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

640-650

Subventions

Organisme : Medical Research Council
ID : MC_PC_17228
Pays : United Kingdom
Organisme : Medical Research Council
ID : MC_QA137853
Pays : United Kingdom

Commentaires et corrections

Type : CommentIn

Informations de copyright

© 2022 The Authors. Liver International published by John Wiley & Sons Ltd.

Références

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Auteurs

Annika R P Schneider (ARP)

Institute of Applied Microbiology - iAMB, Aachen Biology and Biotechnology - ABBt, RWTH Aachen University, Aachen, Germany.
Systems Pharmacology & Medicine, Bayer AG, Leverkusen, Germany.

Carolin V Schneider (CV)

Division of Translational Medicine and Human Genetics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Department of Genetics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Kai Markus Schneider (KM)

Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Vanessa Baier (V)

Institute of Applied Microbiology - iAMB, Aachen Biology and Biotechnology - ABBt, RWTH Aachen University, Aachen, Germany.

Steffen Schaper (S)

Systems Pharmacology & Medicine, Bayer AG, Leverkusen, Germany.

Christian Diedrich (C)

Systems Pharmacology & Medicine, Bayer AG, Leverkusen, Germany.

Katrin Coboeken (K)

Systems Pharmacology & Medicine, Bayer AG, Leverkusen, Germany.

Hannah Mayer (H)

Systems Pharmacology & Medicine, Bayer AG, Leverkusen, Germany.

Wenyi Gu (W)

Medical Department I, Frankfurt University Hospital, Leverkusen, Germany.

Jonel Trebicka (J)

Medical Department I, Frankfurt University Hospital, Leverkusen, Germany.
European Foundation for Study of Chronic Liver Failure, Barcelona, Spain.

Lars M Blank (LM)

Institute of Applied Microbiology - iAMB, Aachen Biology and Biotechnology - ABBt, RWTH Aachen University, Aachen, Germany.

Rolf Burghaus (R)

Clinical Pharmacometrics, Bayer AG, Wuppertal, Germany.

Joerg Lippert (J)

Clinical Pharmacometrics, Bayer AG, Wuppertal, Germany.

Daniel J Rader (DJ)

Division of Translational Medicine and Human Genetics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Department of Genetics, The Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Christoph A Thaiss (CA)

Department of Microbiology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Institute for Immunology, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.
Institute for Diabetes, Obesity, and Metabolism, Perelman School of Medicine, University of Pennsylvania, Philadelphia, Pennsylvania, USA.

Jan-Frederik Schlender (JF)

Systems Pharmacology & Medicine, Bayer AG, Leverkusen, Germany.

Christian Trautwein (C)

Department of Medicine III, University Hospital Aachen, Aachen, Germany.

Lars Kuepfer (L)

Institute for Systems Medicine, University Hospital RWTH Aachen, Aachen, Germany.

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