ArticleMedicine2022
How effective are APRI, FIB-4, FIB-5 scores in predicting liver fibrosis in chronic hepatitis B patients?
Article in Medicine, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.
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, 11 citations in OpenAlex.
- Correlation analysis of Th1/Th2 cytokines and liver fibrosis indicators in chronic hepatitis B patients.Journal of medical biochemistry · 2026Article
- The ratio of GGT to PLT indices is a predictive factor for the progression of liver fibrosis in NA-treated chronic hepatitis B patients with advanced fibrosis plus PEG-IFN α-2a therapy: a case-control study.BMC gastroenterology · 2025Article
- Inflammatory and fibrosis indices (UA/Alb, Fib/UA, UA/Cr, Cr/BW, AST/PLT, AST/ALT, FIB-4, and FIB-5) as predictors of preeclampsia-associated systemic dysfunction.BMC pregnancy and childbirth · 2025Article
- Efficacy of [Annals of nuclear medicine · 2025Article
- Useful Biomarkers for Preeclampsia: Evaluating the Diagnostic Potential of FIB-4 and FIB-5 Indices.Diagnostics (Basel, Switzerland) · 2025Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Liver fibrosis is the most important factor in the prognosis and treatment plan of patients with chronic hepatitis B (CHB). Aspartate aminotransferase (AST)-to-platelet ratio index (APRI), fibrosis index based on 4 factors (FIB-4), and fibrosis index based on 5 factors (FIB-5) scores are noninvasive fibrosis markers, and previous comparative studies have shown that they are as effective as liver biopsy in detecting liver fibrosis in different liver diseases. The aim of our study is to investigate whether existing scoring systems are effective in demonstrating fibrosis in CHB patients and to compare the APRI, FIB 4, and FIB 5 scores in differentiating early and advanced fibrosis in 123 patients who underwent liver biopsy for CHB infection. APRI, FIB-4, and FIB-5 scores of patients who underwent liver biopsy due to CHB were calculated by means of calculators and recorded to be compared with liver biopsies in terms of fibrosis scoring. One hundred twenty-three patients who underwent liver biopsy due to chronic hepatitis B were included in the study. APRI (area under the receiver-operating characteristic [ROC] curve 0.728), FIB-4 (area under the ROC curve 0.693) and FIB-5 (area under the ROC curve 0.643) scores were evaluated as significant predictors of advanced fibrosis. The scoring system with the highest positive and negative predictive value was evaluated as FIB-4. APRI, FIB-4, and FIB-5 scoring systems are appropriate scoring systems in the assessment of advanced fibrosis in patients with CHB. Our study is the first to compare APRI, FIB-4, and FIB-5 values in CHB patients, and more comprehensive studies are needed.
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.