Evidence map›Paper›PMID 33977353›Full record

ArticleAbdominal radiology (New York)2021

Combining hepatic surface nodularity and serum tests better predicts hepatic fibrosis stages in chronic liver disease.

Hyo Jung Cho, Jaewon Choi, Bohyun Kim, JeongGil Ko, Joon-Il Choi, Jimi Huh, Jei Hee Lee, Jai Keun Kim

Abstract read
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In one paragraph

Article in Abdominal radiology (New York), 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.5field-weighted citation impact, top 36% 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

1 citing paper in PubMed, 5 citations in OpenAlex.

  1. 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

8 authors at 3 institutions in 2 countries.

Hyo Jung Cho *Department of Gastroenterology, Ajou University Hospital, Ajou University School of Medicine, Suwon, Republic of Korea.ORCID http://orcid.org/0000-0003-4792-8335
Jaewon Choi *School of Integrated Technology, College of Engineering, Yonsei University, Incheon, Republic of Korea.ORCID http://orcid.org/0000-0002-7696-3140
Bohyun KimDepartment of Radiology, Ajou University Hospital, Ajou University School of Medicine, Suwon, Republic of Korea. kbh@catholic.ac.kr.ORCID http://orcid.org/0000-0003-1157-415X
JeongGil KoSchool of Integrated Technology, College of Engineering, Yonsei University, Incheon, Republic of Korea.ORCID http://orcid.org/0000-0003-0799-4039
Joon-Il ChoiDepartment of Radiology, Seoul St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea.ORCID http://orcid.org/0000-0003-0018-8712
Jimi HuhDepartment of Radiology, Ajou University Hospital, Ajou University School of Medicine, Suwon, Republic of Korea.ORCID http://orcid.org/0000-0002-8832-6165
Jei Hee LeeDepartment of Radiology, Ajou University Hospital, Ajou University School of Medicine, Suwon, Republic of Korea.ORCID http://orcid.org/0000-0002-2231-820X
Jai Keun KimDepartment of Radiology, Ajou University Hospital, Ajou University School of Medicine, Suwon, Republic of Korea.ORCID http://orcid.org/0000-0003-0767-6655
Ajou University Hospital · KRYonsei University · KRSt. Mary's Hospital · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeHepatic surface nodularity quantified on CT images has shown promising results in staging hepatic fibrosis in chronic hepatitis C. The aim of this study was to evaluate hepatic surface nodularity, serum fibrosis indices, and a linear combination of them for staging fibrosis in chronic liver disease, mainly chronic hepatitis B.

methodsWe developed a semiautomated software quantifying hepatic surface nodularity on CT images. Hepatic surface nodularity and serum fibrosis indices were assessed in the development group of 125 patients to generate 3 linear models combining hepatic surface nodularity with the aspartate aminotransferase to platelet ratio index, fibrosis-4 index, or platelet count in reference to the METAVIR scoring system. The models were validated in 183 patients.

resultsHepatic surface nodularity and serum fibrosis indices all significantly correlated with fibrosis stages. For binary classifications into cirrhosis (F4), advanced fibrosis (≥ F3), and significant fibrosis (≥ F2), hepatic surface nodularity was significantly different across categories. The areas under the curve (AUCs) of the best model were 0.901, 0.872, and 0.794 for cirrhosis, advanced fibrosis, and significant fibrosis, respectively, higher than serum fibrosis indices alone (0.797-0.802, 0.799-0.818, and 0.761-0.773). In the validation group, the same model likewise showed higher AUCs (0.872, 0.831, and 0.850) compared to serum fibrosis indices (0.722-0.776, 0.692-0.768, and 0.695-0.769; p < 0.001 for F4).

conclusionHepatic surface nodularity combined with serum blood test could be a practical method to predict cirrhosis, advanced fibrosis, and significant fibrosis in chronic liver disease patients, providing higher accuracy than using serum fibrosis indices alone.

Indexed as

Hepatitis C, ChronicLiver CirrhosisHumansLiverRetrospective StudiesROC CurveChronic hepatitis BComputed tomographyHepatic surface nodularityLiver fibrosisSerum markers

Identifiers

PMID33977353
OpenAlexW3160748851

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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.