Evidence map›Paper›PMID 31107735›Full record

ArticleEuropean journal of gastroenterology & hepatology2019

Noninvasive inflammatory markers for assessing liver fibrosis stage in autoimmune hepatitis patients.

Xiaoling Yuan, Sheng-Zhong Duan, Junying Cao, Nan Gao, Jie Xu, Lanjing Zhang

Abstract read
In one paragraph

Article in European journal of gastroenterology & hepatology, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed, 2 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, 2 syntheses or guidelines pooled it.

  1. Guideline
  2. Pooled it
  3. Article
  4. Article
  5. Deciphering the Role of Oroxylin A in Liver Fibrosis.Drug design, development and therapy · 2025
    Review
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Autoimmune Hepatitis and Fibrosis.Journal of clinical medicine · 2023
    Review
  13. Review
  14. Article
  15. Article
  16. Article
  17. Article
  18. Review
  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

6 authors.

Xiaoling YuanDepartment of Infectious Disease, Ninth People's Hospital.
Sheng-Zhong DuanLaboratory of Oral Microbiota and Systemic Diseases, School of Stomatology, Shanghai Ninth People's Hospital, Shanghai Jiao Tong University School of Medicine.
Junying CaoDepartment of Infectious Disease, Ninth People's Hospital.
Nan GaoDepartment of Biological Sciences, Rutgers University, Newark.
Jie XuDepartment of Infectious Disease, Ninth People's Hospital.
Lanjing ZhangDepartment of Pathology, Princeton Medical Center, Plainsboro.

Funding

Endosomal Control of Microbe-Host HomeostasisR01DK102934 · NIDDK · RUTGERS THE STATE UNIV OF NJ NEWARK · PI GAO, NAN · 2014 to 2018
$1.8M
NIDDK NIH HHS R01 DK102934
6 · The paper itself

Abstract

objectiveTo examine the accuracy of noninvasive inflammatory markers in predicting liver fibrosis stage in patients with autoimmune hepatitis (AIH). PATIENTS AND

methodsWe enrolled 55 patients with AIH and 60 healthy controls in this study, and divided them into three groups: F0 (control); F1-F3 (noncirrhotic fibrosis); and F4 (cirrhosis). The following markers were analyzed for all participants: lymphocyte-to-neutrophil ratio (LNR); lymphocyte-to-platelet ratio (LPR); lymphocyte-to-monocyte ratio (LMR); immunoglobulin-to-platelet ratio (IGPR); aminotransferase-to-platelet ratio index (APRI); aspartate aminotransferase-to-alanine aminotransferase ratio (AAR); and fibrosis-4 score (FIB-4). The predictive accuracy of these noninvasive markers was assessed using area under the receiver operating characteristic curve. Multivariate ordinal logistic regression models were used to analyze associations between the noninvasive markers and liver fibrosis stage.

resultsAAR, LPR, LMR, IGPR, APRI, and FIB-4 were linked to liver fibrosis-stage (P < 0.05), with correlation indices of - 0.219, 0.258, - 0.149, 0.647, 0.841, and 0.704, respectively, but not LNR (P = 0.093). area under the receiver operating characteristic curves of LPR, IGPR, AAR, LMR, APRI, and FIB-4 for detecting cirrhosis (F4 vs. F0-F3) were 0.936 (95% confidence interval: 0.870-1.000, P < 0.001), 0.939 (0.875-1.000, P < 0.001), 0.528 (0.319-0.738, P = 0.768), 0.555 (0.409-0.700, P = 0.568), 0.798 (0.694-0.902, P = 0.002), and 0.881 (0.796-0.967, P < 0.001). Our multivariate ordinal regression analysis showed that LPR and IGPR were associated independently with liver fibrosis stage, with a coefficient of 0.385 (95% confidence interval: 0.103-0.667, P = 0.007) and 14.903 (2.091-27.786, P = 0.023), respectively.

conclusionLPR and IGPR were associated independently with liver fibrosis stage in treatment-naive AIH, and were superior to APRI and FIB-4 in detecting cirrhosis.

Indexed as

Age FactorsAlanine TransaminaseAspartate AminotransferasesCase-Control StudiesFemaleHepatitis, AutoimmuneHumansImmunoglobulinsInflammationLeukocyte CountLiver CirrhosisLogistic ModelsLymphocyte CountMaleMiddle AgedMonocytesAlanine TransaminaseAspartate AminotransferasesImmunoglobulins

Identifiers

PMID31107735
PMCPMC7333545

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LicenceCC BY-NC-ND
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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.