ArticleJGH open : an open access journal of gastroenterology and hepatology2021
Validation of a two-step approach combining serum biomarkers and liver stiffness measurement to predict advanced fibrosis.
Article in JGH open : an open access journal of gastroenterology and hepatology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 6 citations in OpenAlex.
- Accuracy of prognostic serological biomarkers in predicting liver fibrosis severity in people with metabolic dysfunction-associated steatotic liver disease: a meta-analysis of over 40,000 participants.Frontiers in nutrition · 2024Pooled it
- Management of MASLD/MASH: challenges, innovations, and the future of patient-centered care in Japan.Journal of gastroenterology · 2026Review
- Noninvasive strategies for metabolic dysfunction-associated steatotic liver disease assessment and referral in Japan.World journal of gastroenterology · 2026Review
- Article
- Identifying advanced MAFLD in a cohort of T2DM and clinical features.Frontiers in endocrinology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
11 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND AND
aimThe Gut and Obesity in Asia Workgroup recently reported that a two-step approach using fibrosis scores followed by liver stiffness measurement (LSM) could accurately detect patients with non-alcoholic fatty liver disease (NAFLD) having advanced fibrosis in low-risk fibrosis populations. This study aimed to validate the utility of this approach using a Japanese health checkup registry.
methodsThis cross-sectional study included subjects who underwent a health checkup from 2014 to 2019. Using estimated fibrosis stage measured by LSM as a standard, we calculated the percentage of misclassification from assessments made based on fibrosis scores (NAFLD fibrosis score [NFS] or Fibrosis-4 score [FIB-4]) and LSM, alone or in combination.
resultsOf 630 subjects with NAFLD, 4 (0.8%) had advanced fibrosis. In the first-step evaluation, only 21.4-38.0% of subjects needed further testing. This approach was associated with a high specificity of approximately 100% and a negative predictive value of 99.7%. The percentage of misclassification based on NFS or FIB-4 values followed by LSM in all subjects and using LSM after NFS or FIB-4 determination only in subjects with indeterminate/high NFS or FIB-4 values (two-step approach) was 0% and 0.3% and 0.16% and 0.3%, respectively. In addition, very few false negatives occurred for both NFS and FIB-4.
conclusionThe two-step approach helps to identify the subjects with NAFLD who have advanced fibrosis during a routine health checkup and is associated with only a few false negatives.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.