Evidence map›Paper›PMID 34008117›Full record

SynthesisDigestive diseases and sciences2022

Liver Fibrosis in the Natural Course of Chronic Hepatitis B Viral Infection: A Systematic Review with Meta-Analysis.

Mei-Hong Lin, Hai-Qiong Li, Lin Zhu, Hai-Ying Su, Li-Shan Peng, Chuang-Yuan Wang, Cai-Ping He, Xie-Er Liang, Yan Wang

Abstract readMeta-AnalysisSystematic Review
PubMed Publisher
In one paragraph

Synthesis in Digestive diseases and sciences, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
23citing papers in PubMed, 1 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

23 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Observational
  3. Article
  4. Review
  5. Review
  6. Propionic acid secreted byLife metabolism · 2026
    Article
  7. Article
  8. Article
  9. Article
  10. Review
  11. Article
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  13. Article
  14. Article
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  16. Review
  17. Review
  18. Hepatic inflammatory responses in liver fibrosis.Nature reviews. Gastroenterology & hepatology · 2023
    Review
  19. Article
  20. Review
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

9 authors.

Mei-Hong LinDepartment of Infectious Disease and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Hai-Qiong LiDepartment of Infectious Disease and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Lin ZhuDepartment of Infectious Disease and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Hai-Ying SuDepartment of Infectious Disease and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Li-Shan PengDepartment of Infectious Disease and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Chuang-Yuan WangDepartment of Infectious Disease and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Cai-Ping HeBiomedical Research Center, Southern Medical University, Guangzhou, China.
Xie-Er LiangDepartment of Infectious Disease and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China.
Yan WangDepartment of Infectious Disease and Hepatology Unit, Nanfang Hospital, Southern Medical University, Guangzhou, China. Yanwang@smu.edu.cn.ORCID 0000-0001-6851-3054

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundQuantitative data are limited on the natural course of liver fibrosis in patients with chronic HBV infection (CHB).

aimsTo estimate the prevalence of fibrosis status including non-fibrosis, significant fibrosis, advanced fibrosis, and cirrhosis throughout the natural course of CHB.

methodsWe searched Cochrane library, EMBASE, PubMed, SCOPUS, Web of Science, and ScienceDirect from January 1993 to November 2019 for studies with histologic data on liver fibrosis in CHB natural course. CHB course was defined based on current criteria for identifying infection phases as recommended by international clinical practice guidelines, including the HBeAg-positive immune-tolerant, HBeAg-positive immune-active, HBeAg-negative immune-inactive, HBeAg-negative immune-reactive, and HBsAg-negative phases. Pooled prevalence rate of fibrosis status at each phase was obtained from random-effect meta-analyses.

resultsThirty-three studies with 9,377 adult participants (23.8-49.0 age years; 45.5-88.6% males) were eligible and finally included. The estimated prevalence of non-fibrosis, significant fibrosis, advanced fibrosis, and cirrhosis was, for HBeAg-positive immune-tolerant phase: 31.2% (95%CI 15.6-46.7), 16.9% (95%CI 7.8-26.1), 5.4% (95%CI 0.0-11.2), and 0.0% (95%CI 0.0-1.5); HBeAg-positive immune-active phase: 6.9% (95%CI 3.6-10.2), 50.6% (95%CI 39.2-61.9), 32.1% (95%CI 24.2-40.0), and 12.8% (95%CI 8.6-17.0); HBeAg-negative immune-inactive phase: 32.4% (95%CI 0.0-100.0), 24.8% (95%CI 4.5-45.1), 3.0% (95%CI 0.0-8.3), and 0.0% (95%CI 0.0-1.0); and HBeAg-negative immune-reactive phase: 6.3% (95%CI 3.5-9.2), 50.3% (95%CI 38.9-61.7), 30.3% (95%CI 20.9-39.6), and 10.0% (95%CI 6.6-13.5), respectively. There was only one study for HBsAg-negative phase, thus not allowing further meta-analyses.

conclusionsFibrosis risk persists through CHB natural course. These data can support risk estimation in clinical practice and provide reference for noninvasive investigation.

Indexed as

Hepatitis B, ChronicAdultDNA, ViralFemaleHepatitis B e AntigensHepatitis B Surface AntigensHepatitis B virusHumansLiver CirrhosisMaleDNA, ViralHepatitis B e AntigensHepatitis B Surface AntigensChronic hepatitis B virus infectionImmune phasesLiver fibrosisMeta-analysisNatural historyPrevalence

Identifiers

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Registered trials

None linked

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.