Evidence map›Paper›PMID 35158982›Full record

ArticleCancers2022

External Validation of the FSAC Model Using On-Therapy Changes in Noninvasive Fibrosis Markers in Patients with Chronic Hepatitis B: A Multicenter Study.

Jae Seung Lee, Hyun Woong Lee, Tae Seop Lim, In Kyung Min, Hye Won Lee, Seung Up Kim, Jun Yong Park, Do Young Kim, Sang Hoon Ahn, Beom Kyung Kim

Open access · goldAbstract read
In one paragraph

Article in Cancers, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
0.8field-weighted citation impact, top 30% 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

4 citing papers in PubMed, 5 citations in OpenAlex.

  1. Article
  2. Article
  3. Review
  4. 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

10 authors at 1 institution in 1 country.

Jae Seung LeeDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Korea.ORCID 0000-0002-2371-0967
Hyun Woong LeeDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Korea.
Tae Seop LimDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Korea.
In Kyung MinBiostatistics Collaboration Unit, Department of Biomedical Systems Informatics, Yonsei University College of Medicine, Seoul 03722, Korea.
Hye Won LeeDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Korea.ORCID 0000-0002-3552-3560
Seung Up KimDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Korea.ORCID 0000-0002-9658-8050
Jun Yong ParkDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Korea.ORCID 0000-0001-6324-2224
Do Young KimDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Korea.ORCID 0000-0002-8327-3439
Sang Hoon AhnDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Korea.
Beom Kyung KimDepartment of Internal Medicine, Yonsei University College of Medicine, Seoul 03722, Korea.
Yonsei University · KR

Funding

Korea Disease Control and Prevention Agency 2019ER510202
6 · The paper itself

Abstract

Antiviral therapy (AVT) induces the regression of non-invasive fibrosis markers (NFMs) and reduces hepatocellular carcinoma (HCC) risk among chronic hepatitis B (CHB) patients. We externally validated the predictive performance of the FSAC prediction model for HCC using on-therapy NFM responses. Our multicenter study consecutively recruited treatment-naïve CHB patients (

Indexed as

antiviral agentsarea under curvecalibrationcarcinomachronicdiscriminant analysishepatitis Bhepatocellularmodelsstatistical

Identifiers

PMID35158982
PMCPMC8833581
OpenAlexW4213069594

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.