Spleen Stiffness-Based Algorithms Are Superior to Baveno VI Criteria to Rule Out Varices Needing Treatment in Patients With Advanced Chronic Liver Disease.


Journal

The American journal of gastroenterology
ISSN: 1572-0241
Titre abrégé: Am J Gastroenterol
Pays: United States
ID NLM: 0421030

Informations de publication

Date de publication:
20 Mar 2024
Historique:
received: 06 09 2023
accepted: 23 01 2024
medline: 19 3 2024
pubmed: 19 3 2024
entrez: 19 3 2024
Statut: aheadofprint

Résumé

The Baveno VI criteria have set the stage for noninvasive assessment of compensated advanced chronic liver disease (ACLD). The algorithm combining liver stiffness measurement (LSM, <20 kPa) and platelet count (>150,000/μL) safely avoids screening endoscopy for varices needing treatment (VNT) but identifies only a relatively low number of patients. We aimed to evaluate the value of spleen stiffness measurement (SSM) using spleen-dedicated elastography in ruling out VNT. In this real-life multicenter retrospective derivation-validation cohort, all consecutive patients with ACLD (defined by LSM ≥10 kPa) with available upper endoscopy, laboratory results, spleen diameter, LSM, and SSM measured with spleen-dedicated transient elastography were included. VNT were defined as medium-to-large varices or small varices with red spots. In the derivation cohort (n = 201, 11.9% VNT), SSM demonstrated excellent capability at identifying VNT (area under the receiver operating characteristic curve [AUROC] 0.88), outperforming LSM (AUROC 0.77, P = 0.03) and platelets (AUROC 0.73, P = 0.002). In comparison with Baveno VI criteria (33.8% spared endoscopies), the sequential Baveno VI plus SSM and a novel spleen size and stiffness model were able to increase the number of patients avoiding endoscopy (66.2% and 71.1%, respectively) without missing more than 5% of VNT. These findings were confirmed in an external validation cohort of patients with more advanced liver disease (n = 176, 34.7% VNT) in which the number of spared endoscopies tripled (27.3% and 31.3% for SSM-based algorithms) compared with Baveno VI criteria (8.5%). Spleen stiffness-based algorithms are superior to Baveno VI criteria in ruling out VNT in patients with ACLD and double the number of patients avoiding screening endoscopy.

Identifiants

pubmed: 38502095
doi: 10.14309/ajg.0000000000002708
pii: 00000434-990000000-01023
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Informations de copyright

Copyright © 2024 by The American College of Gastroenterology.

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Auteurs

Emma Vanderschueren (E)

Department of Gastroenterology and Hepatology, University Hospital Leuven, Leuven, Belgium.
Department of Chronic Diseases, Metabolism and Aging (CHROMETA), Catholic University of Leuven, Leuven, Belgium.

Angelo Armandi (A)

Metabolic Liver Disease Research Program, I Department of Internal Medicine, University Medical Center of the Johannes Gutenberg University, Mainz, Germany.
Division of Gastroenterology and Hepatology, Department of Medical Sciences, University of Turin, Turin, Italy.

Wilhelmus Kwanten (W)

Laboratory of Experimental Medicine and Paediatrics (LEMP), University of Antwerp (UA), Antwerp, Belgium.
Department of Gastroenterology & Hepatology, University Hospital Antwerp, Antwerp, Belgium.

David Cassiman (D)

Department of Gastroenterology and Hepatology, University Hospital Leuven, Leuven, Belgium.
Department of Chronic Diseases, Metabolism and Aging (CHROMETA), Catholic University of Leuven, Leuven, Belgium.

Sven Francque (S)

Laboratory of Experimental Medicine and Paediatrics (LEMP), University of Antwerp (UA), Antwerp, Belgium.
Department of Gastroenterology & Hepatology, University Hospital Antwerp, Antwerp, Belgium.

Jörn M Schattenberg (JM)

Department of Internal Medicine, Saarland University Medical Center, Homburg, Germany.

Wim Laleman (W)

Department of Gastroenterology and Hepatology, University Hospital Leuven, Leuven, Belgium.
Department of Chronic Diseases, Metabolism and Aging (CHROMETA), Catholic University of Leuven, Leuven, Belgium.

Classifications MeSH