Evidence map›Paper›PMID 20101779›Full record

ArticleWorld journal of gastroenterology2010

Staging of liver fibrosis in chronic hepatitis B patients with a composite predictive model: a comparative study.

Sheng-Di Wu, Ji-Yao Wang, Lei Li

Abstract readComparative Study
In one paragraph

Article in World journal of gastroenterology, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

21 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
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  12. Performance of common imaging techniquesWorld journal of clinical cases · 2019
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  18. Clinical approaches to non-alcoholic fatty liver disease.World journal of gastroenterology · 2014
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Sheng-Di WuDivision of Gastroenterology and Hepatology, Department of Internal Medicine, Zhongshan Hospital, Fudan University, Shanghai 200032, China.
Ji-Yao Wang
Lei Li

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

aimTo evaluate the efficacy of 6 noninvasive liver fibrosis models and to identify the most valuable model for the prediction of liver fibrosis stage in chronic hepatitis B (CHB) patients.

methodsSeventy-eight CHB patients were consecutively enrolled in this study. Liver biopsy was performed and blood serum was obtained at admission. Histological diagnosis was made according to the METAVIR system. Significant fibrosis was defined as stage score > or = 2, severe fibrosis as stage score > or = 3. The diagnostic accuracy of 6 noninvasive liver fibrosis models, including serum aspartate aminotransferase (AST) to platelet ratio index (APRI), FIB-4, Forn's index, Fibrometer, Hepascore, and Shanghai Liver Fibrosis Group's index (SLFG), was investigated.

resultsThe APRI, FIB-4 and Forn's index under receiver operating characteristic curve (AUROC) for significant fibrosis were 0.71, 0.75 and 0.79, respectively, with a diagnosis accuracy of 67%, 77% and 80%, respectively, and 0.80, 0.87 and 0.86, respectively, under the AUROC for severe fibrosis. The Hepascore, SLFG, and Fibrometer were 0.80, 0.83 and 0.85, respectively under the AUROC for significant fibrosis (P < 0.01). The diagnosis accuracy of Hepascore and SLFG was 86% and 88%, respectively. The Hepascore, SLFG, and Fibrometer were 0.95, 0.93, and 0.94, respectively, under the AUROC for severe fibrosis (P < 0.01).

conclusionThe models containing direct serum markers have a better diagnostic value than those not containing direct serum markers.

Indexed as

AdultBiomarkersFemaleHepatitis B, ChronicHumansLiverLiver CirrhosisMaleMiddle AgedModels, BiologicalPredictive Value of TestsYoung AdultBiomarkers

Identifiers

PMID20101779
PMCPMC2811806

What OpenQuestion holds

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Registered trials

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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.