Evidence map›Paper›PMID 35836771›Full record

ArticleJournal of clinical and translational hepatology2022

Advantages of a Novel Model for Predicting Hepatic Fibrosis in Chronic Hepatitis B Virus Carriers Compared with APRI and FIB-4 Scores.

Na-Ling Kang, Qing-Fa Ruan, De-Sheng Zhang, Xue-Ping Yu, Zhen-Ting Hu, Zhi-Min Lin, Lu-Ying Wu, Meng-Xin Lin, Zu-Xiong Huang, Jia-Ji Jiang and 3 more

Open access · diamondAbstract read
In one paragraph

Article in Journal of clinical and translational hepatology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
1.6field-weighted citation impact, top 17% of its field
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

6 citing papers in PubMed, 10 citations in OpenAlex.

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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

13 authors at 4 institutions in 1 country.

Na-Ling KangDepartment of Hepatology, Hepatology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China.
Qing-Fa RuanHepatology Center, Xiamen Hospital of Traditional Chinese Medicine, Xiamen, Fujian, China.
De-Sheng ZhangDepartment of Pharmacy, the First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China.
Xue-Ping YuDepartment of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China.
Zhen-Ting HuDepartment of Infectious Disease, The Affiliated Hospital of Putian College, Putian, Fujian, China.
Zhi-Min LinDepartment of Gastroenterology, The Second Affiliated Hospital of Xiamen Medical College, Xiamen, Fujian, China.
Lu-Ying WuDepartment of Hepatology, Hepatology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China.
Meng-Xin LinDepartment of Infectious Diseases, The First Hospital of Quanzhou Affiliated to Fujian Medical University, Quanzhou, Fujian, China.
Zu-Xiong HuangHepatology, Mengchao Hepatobiliary Hospital of Fujian Medical University, Fuzhou, Fujian, China.
Jia-Ji JiangDepartment of Hepatology, Hepatology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China.
Yu-Rui LiuDepartment of Hepatology, Hepatology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China.
Ri-Cheng MaoDepartment of Infectious Diseases, Shanghai Key Laboratory of Infectious Diseases and Biosafety Emergency Response, National Medical Center for Infectious Diseases, Huashan Hospital, Fudan University, Shanghai, China.ORCID https://orcid.org/0000-0001-5534-8299
Da-Wu ZengDepartment of Hepatology, Hepatology Research Institute, The First Affiliated Hospital, Fujian Medical University, Fuzhou, Fujian, China.ORCID https://orcid.org/0000-0003-3818-0062
Fujian Medical University · CNFirst Affiliated Hospital of Xiamen University · CNFudan University · CNPutian University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background and Aims: Aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis-4 index (FIB-4) are widely used to assess liver fibrosis in chronic hepatitis B virus (HBV) infection. Currently, the definition of normal alanine aminotransferase (ALT) is controversial. We aimed to examine the diagnostic value of APRI and FIB-4 in chronic HBV carriers with different upper limits of normal (ULNs) for ALT. Methods: 581 chronic HBV carriers were divided into the following four groups based on different ULNs for ALT: chronic HBV carriers I, II, III, and IV. Furthermore, 106 chronic HBV carriers formed an external validation group. Predictive values of APRI and FIB-4 were elucidated using the area under the curve (AUC). A liver fibrosis-predictive model-GPSA (named for its measure of gamma glutamyl transpeptidase, platelet count, HBsAg and albumin) was developed using multivariate logistic regression analysis. Results: In chronic HBV carriers I, the AUCs of APRI and FIB-4 were 0.680 and 0.609 for significant fibrosis and 0.678 and 0.661 for cirrhosis, respectively. The AUCs of GPSA for significant fibrosis in the training group, internal group, and external validation group were 0.877, 0.837, and 0.871, respectively. The diagnostic value of GPSA differed among chronic HBV carriers I, II, III, and IV, with AUCs for significant fibrosis being 0.857, 0.853, 0.868, and 0.905 and AUCs for cirrhosis being 0.901, 0.905, 0.886, and 0.913, respectively. GPSA showed a higher diagnostic value than APRI and FIB-4 for predicting significant fibrosis in the four groups. Conclusions: The GPSA model allows for accurate diagnosis of liver fibrosis in chronic HBV carriers with different ULN for ALT.

Indexed as

APRIChronic HBV carriersFIB-4HBVLiver fibrosis

Identifiers

PMID35836771
PMCPMC9240253
OpenAlexW4281612485

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.