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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.

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Gastroenterology 📖 저널 OA 12.1% 2022: 0/1 OA 2024: 2/10 OA 2025: 5/47 OA 2026: 8/62 OA 2022~2026 2026 Vol.170(2) p. 385-394
Retraction 확인
출처

PICO 자동 추출 (휴리스틱, conf 2/4)

유사 논문
P · Population 대상 환자/모집단
4 patients with MASLD was evaluated.
I · Intervention 중재 / 시술
추출되지 않음
C · Comparison 대조 / 비교
추출되지 않음
O · Outcome 결과 / 결론
[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.

Aceituno L, Bañares J, Pons M, Rivera-Esteban J, Sabiote C, Cammà C

📝 환자 설명용 한 줄

[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.

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APA Aceituno L, Bañares J, et al. (2026). 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.. Gastroenterology, 170(2), 385-394. https://doi.org/10.1053/j.gastro.2025.08.020
MLA Aceituno L, et al.. "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.." Gastroenterology, vol. 170, no. 2, 2026, pp. 385-394.
PMID 41212130 ↗

Abstract

[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.

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