The ANTICIPATE-NASH Models Stratify Better the Risk of Clinical Events Than Histology in Metabolic Dysfunction-Associated Steatotic Liver Disease Patients With Advanced Chronic Liver Disease
Aceituno, Laia (Vall d'Hebron Institut de Recerca (VHIR))
Bañares, Juan (Vall d'Hebron Institut de Recerca (VHIR))
Pons Delgado, Mònica (Vall d'Hebron Institut de Recerca (VHIR))
Rivera Esteban, Jesús (Hospital Universitario Puerta de Hierro Majadahonda (Madrid))
Sabiote, Clara (Vall d'Hebron Institut de Recerca (VHIR))
Cammà, Calogero (University of Palermo)
Ciancimino, Giacinta (University of Palermo)
Pennisi, Grazia (University of Palermo)
Tulone, Adele (University of Palermo)
Ma, Mang M. (University of Alberta. Department of Medicine)
Liu, X. (Gilead Sciences. Inc)
Watkins, Timothy R. (Gilead Sciences. Inc)
Billin, Andrew N. (Gilead Sciences. Inc)
Petta, Salvatore (University of Palermo)
Pericàs, Juan M. (Universitat Autònoma de Barcelona. Departament de Medicina)
Abraldes, Juan G. (University of Alberta. Department of Medicine)
Genescà Ferrer, Joan (Universitat Autònoma de Barcelona. Departament de Medicina)

Data:	2025
Resum:	Background & Aims: The reference for risk stratification and clinical trial selection of metabolic dysfunction-associated steatotic liver disease (MASLD) patients is fibrosis degree by histology. The noninvasive ANTICIPATE-NASH models have been validated for risk prediction of clinically significant portal hypertension (CSPH) and liver-related events (LRE). We assessed whether these models provide better risk stratification of events than histology. Methods: A multicenter cohort 1, including 699 biopsy specimen-proven F3-F4 patients with MASLD was evaluated. The end point was LRE (hepatic decompensation, hepatocellular carcinoma, transplantation, or liver-related death). We assessed (Cox regression) whether histology provided added value to ANTICIPATE-NASH and whether model predictions differed in F3/F4 patients. Results were validated in cohort 2 (1396 F3-F4 patients) from 4 clinical trials using the clinical regulatory end point. Results: In cohort 1, F3 and F4 were equally distributed. There were 56 LREs (8. 0%) during follow-up, concentrated in F4 (51 LREs). The ANTICIPATE-NASH model showed excellent discrimination (C statistic, 0. 93) for LRE, higher than histology (C statistic, 0. 67). Model calibration was excellent. Adding histology did not improve model prediction. Thresholds of ANTICIPATE-NASH above which F3 patients developed LREs and below which F4 patients did not were identified. Results were reproduced in cohort 2 with the regulatory end point, with higher model discrimination (C statistic, 0. 84) compared with histology (C statistic, 0. 64). Conclusions: In MASLD patients with F3/F4, the noninvasive ANTICIPATE-NASH models provide better risk stratification of clinical events than histologic classification. These models could be very useful for clinical trials by selecting patients at risk of clinical events and patients with higher chances of observed cirrhosis regression.
Ajuts:	Instituto de Salud Carlos III PI21/00691ISCIII Instituto de Salud Carlos III PI22/01770MIUR/PE00000019 CUP B73C22001250006
Drets:	Aquest document està subjecte a una llicència d'ús Creative Commons. Es permet la reproducció total o parcial, la distribució, i la comunicació pública de l'obra, sempre que no sigui amb finalitats comercials, i sempre que es reconegui l'autoria de l'obra original. No es permet la creació d'obres derivades.
Llengua:	Anglès
Document:	Article ; recerca ; Versió publicada
Matèria:	Predictive Models ; Clinical Events ; Steatotic Liver Disease
Publicat a:	Gastroenterology, 2025 , ISSN 1528-0012

DOI: 10.1053/j.gastro.2025.08.020

24 p, 4.8 MB

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