Evidence map›Paper›PMID 31423434›Full record

ArticleWorld journal of clinical cases2019

Performance of common imaging techniques

Xue-Ying Xu, Wu-Sheng Wang, Qi-Meng Zhang, Jun-Ling Li, Jin-Bin Sun, Tian-Tian Qin, Hong-Bo Liu

Open access · diamondAbstract read
In one paragraph

Article in World journal of clinical cases, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 24 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
24citing papers in PubMed, 1 pooled it
4.0field-weighted citation impact, top 6% 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

24 citing papers in PubMed, 1 synthesis or guideline pooled it, 40 citations in OpenAlex.

  1. Pooled it
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  3. Review
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  5. Review
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  7. Article
  8. Advances in laboratory medicine · 2024
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  9. Serum biomarkers for liver fibrosis assessment.Advances in laboratory medicine · 2024
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  10. Article
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  12. Liver fibrosis assessment: MR and US elastography.Abdominal radiology (New York) · 2022
    Review
  13. Article
  14. Article
  15. Review
  16. Liver fibrosis quantification.Abdominal radiology (New York) · 2022
    Review
  17. Article
  18. Article
  19. Article
  20. Article
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

7 authors at 1 institution in 1 country.

Xue-Ying XuDepartment of Epidemiology and Health Statistics, School of Public Health, China Medical University, Shenyang 110122, Liaoning Province, China.
Wu-Sheng WangDepartment of Epidemiology and Health Statistics, School of Public Health, China Medical University, Shenyang 110122, Liaoning Province, China.
Qi-Meng ZhangDepartment of Epidemiology and Health Statistics, School of Public Health, China Medical University, Shenyang 110122, Liaoning Province, China.
Jun-Ling LiDepartment of Epidemiology and Health Statistics, School of Public Health, China Medical University, Shenyang 110122, Liaoning Province, China.
Jin-Bin SunDepartment of Epidemiology and Health Statistics, School of Public Health, China Medical University, Shenyang 110122, Liaoning Province, China.
Tian-Tian QinDepartment of Epidemiology and Health Statistics, School of Public Health, China Medical University, Shenyang 110122, Liaoning Province, China.
Hong-Bo LiuDepartment of Epidemiology and Health Statistics, School of Public Health, China Medical University, Shenyang 110122, Liaoning Province, China. hbliu@cmu.edu.cn.
China Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundNoninvasive biomarkers have been developed to predict hepatitis B virus (HBV) related fibrosis owing to the significant limitations of liver biopsy. Both serum biomarkers and imaging techniques have shown promising results and may improve the evaluation of liver fibrosis. However, most of the previous studies focused on the diagnostic effects of various imaging techniques on fibrosis in all chronic liver diseases.

aimTo compare the performance of common imaging methods and serum biomarkers for prediction of significant fibrosis caused only by HBV infection.

methodsA systematic review was conducted on the records available in PubMed, EMBASE, and the Cochrane Library electronic databases until December 2018. We systematically assessed the effectiveness of two serum biomarkers and three imagine techniques in predicting significant fibrosis solely caused by HBV infection. The serum biomarkers included aspartate aminotransferase-to-platelet ratio index (APRI) and fibrosis index based on the 4 factors (FIB-4). The three imaging techniques included acoustic radiation force impulse (ARFI), FibroScan, and magnetic resonance elastography (MRE). Three parameters, the area under the summary receiver operating characteristic curve (AUSROC), the summary diagnostic odds ratio, and the summary sensitivity and specificity, were used to examine the accuracy of all tests for liver fibrosis.

resultsOut of 2831 articles evaluated for eligibility, 204 satisfied the predetermined inclusion criteria for this current meta-analysis. Eventually, our final data contained 81 studies. The AUSROCs of serum biomarkers of APRI and FIB-4 were both 0.75. For imaging techniques (ARFI, FibroScan, and MRE), the areas were 0.89, 0.83, and 0.97, respectively. The heterogeneities of ARFI and FibroScan were statistically significant (

conclusionThese five methods have attained an acceptable level of diagnostic accuracy. Imaging techniques, MRE in particular, demonstrate significant advantages in accurately predicting HBV-related significant fibrosis, while serum biomarkers are admissible methods.

Indexed as

Diagnostic testHepatitis B virusImaging technologyLiver fibrosisMeta-analysis

Identifiers

PMID31423434
PMCPMC6695542
OpenAlexW2964652198

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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.