Evidence map›Paper›PMID 38063322›Full record

ArticleJournal of clinical laboratory analysis2023

Chinese expert consensus statement on the clinical application of AFP/AFP-L3%/DCP using GALAD and GALAD-like algorithm in HCC.

Chenjun Huang, Xiao Xiao, Lin Zhou, Fuxiang Chen, Jianyi Wang, Xiaobo Hu, Chunfang Gao, Clinical Laboratory Society of Chinese Rehabilitation Medicine Association, Molecular Diagnostics Society of Shanghai Medical Association, Tumor Immunology Branch of Shanghai Society for Immunology

Open access · goldAbstract readConsensus Statement
In one paragraph

Article in Journal of clinical laboratory analysis, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
1.6field-weighted citation impact, top 15% 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

7 citing papers in PubMed, 8 citations in OpenAlex.

  1. Article
  2. Article
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  4. Article
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  6. Blood biomarkers of hepatocellular carcinoma: a critical review.Frontiers in cell and developmental biology · 2024
    Review
  7. 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 5 institutions in 1 country.

Chenjun HuangDepartment of Clinical Laboratory Medicine Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.ORCID https://orcid.org/0000-0003-3836-6262
Xiao XiaoDepartment of Clinical Laboratory Medicine Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.ORCID https://orcid.org/0000-0002-9260-4519
Lin ZhouDepartment of Laboratory Medicine, Shanghai Changzheng Hospital, Shanghai, China.
Fuxiang ChenDepartment of Laboratory Medicine, Shanghai Ninth People's Hospital, Shanghai JiaoTong University School of Medicine, Shanghai, China.
Jianyi WangDepartment of Liver Diseases, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.
Xiaobo HuShanghai Clinical Laboratory Center, Shanghai, China.
Chunfang GaoDepartment of Clinical Laboratory Medicine Center, Yueyang Hospital of Integrated Traditional Chinese and Western Medicine, Shanghai University of Traditional Chinese Medicine, Shanghai, China.ORCID https://orcid.org/0000-0002-4891-2944
Clinical Laboratory Society of Chinese Rehabilitation Medicine Association, Molecular Diagnostics Society of Shanghai Medical Association, Tumor Immunology Branch of Shanghai Society for Immunology
Shanghai University of Traditional Chinese Medicine · CNSecond Military Medical University · CNShanghai Changzheng Hospital · CNShanghai Clinical Research Center · CNShanghai Jiao Tong University · CN

Funding

China National Key Projects for Infectious Disease 2018ZX10302205-003Innovation Group Project of Shanghai Municipal Health Commission 2019CXJQ03
6 · The paper itself

Abstract

backgroundPrimary hepatocellular carcinoma (HCC) is one of the most prevalent world-wide malignancies. Half of the newly developed HCC occurs in China. Optimizing the strategies for high-risk surveillance and early diagnosis are pivotal for improving 5-year survival. Constructing the scientific non-invasive detection technologies feasible for medical and healthcare institutions is among the key routes for elevating the efficacies of HCC identification and follow-up.

resultsBased on the Chinese and international guidelines, expert consensus statements, literatures and evidence-based clinical practice experiences, this consensus statement puts forward the clinical implications, application subjects, detection techniques and results interpretations of the triple-biomarker (AFP, AFP-L3%, DCP) based GALAD, GALAD like models for liver cancer.

conclusionsThe compile of this consensus statement aims to address and push the reasonable application of the triple-biomarker (AFP, AFP-L3%, DCP) detections thus to maximize the clinical benefits and help improving the high risk surveillance, early diagnosis and prognosis of HCC.

Indexed as

Carcinoma, HepatocellularLiver NeoplasmsAlgorithmsalpha-FetoproteinsBiomarkersBiomarkers, TumorHumansProtein PrecursorsProthrombinSensitivity and Specificityalpha-FetoproteinsBiomarkersBiomarkers, TumorProtein PrecursorsProthrombinalpha-fetoprotein (AFP)alpha-fetoprotein-L3% (AFP-L3%)des-gamma-carboxyprothrombin (DCP)gender-age-AFP-L3%-AFP-DCP (GALAD) modelhepatocellular carcinoma (HCC)

Identifiers

PMID38063322
PMCPMC10756949
OpenAlexW4389478316

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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.