Evidence map›Paper›PMID 25873748›Full record

SynthesisDisease markers2015

The diagnostic accuracy of HE4 in lung cancer: a meta-analysis.

Daye Cheng, Ying Sun, Hu He

Open access · hybridAbstract readMeta-AnalysisSystematic Review
In one paragraph

Synthesis in Disease markers, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
14citing papers in PubMed, 2 pooled it
2.6field-weighted citation impact, top 10% 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

14 citing papers in PubMed, 2 syntheses or guidelines pooled it, 23 citations in OpenAlex.

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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

3 authors at 2 institutions in 1 country.

Daye ChengDepartment of Transfusion, First Hospital of China Medical University, Shenyang 110001, China.
Ying SunDepartment of Transfusion, First Hospital of China Medical University, Shenyang 110001, China.
Hu HeDepartment of Transfusion, First Hospital of China Medical University, Shenyang 110001, China.
First Hospital of China Medical University · CNChina Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The diagnostic value of serum HE4 in patients with lung cancer remains controversial. Thus, we performed a systematic review and meta-analysis to assess the diagnostic accuracy of serum HE4 for lung cancer. We conducted a comprehensive literature search in PubMed, EMBASE, Chinese National Knowledge Infrastructure (CNKI), and WANFANG databases between Jan. 1966 and Nov. 2014. The diagnostic sensitivity (SEN), specificity (SPE), positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR), and summary receiver operating characteristic curve (SROC) were pooled by Meta-DiSc 1.4 software. A total of seven articles including 715 cases and 549 controls were included for analysis. The summary estimates for serum HE4 in the diagnosis of lung cancer in these studies were pooled SEN 0.72 (95% CI: 0.68-0.75), SPE 0.85 (95% CI: 0.81-0.88), PLR 4.68 (95% CI: 3.23-6.78), NLR 0.31 (95% CI: 0.24-0.39), and DOR 17.14 (95% CI: 9.72-30.20), and the area under the curve (AUC) was 0.8557. This meta-analysis indicated that serum HE4 is a potential tool in the diagnosis of lung cancer. In addition, considering the high heterogeneity and potential publication bias, further studies with rigorous design and large sample size are needed in the future.

Indexed as

Biomarkers, TumorCase-Control StudiesHumansLung NeoplasmsProteinsSensitivity and SpecificityWAP Four-Disulfide Core Domain Protein 2Biomarkers, TumorProteinsWAP Four-Disulfide Core Domain Protein 2WFDC2 protein, human

Identifiers

PMID25873748
PMCPMC4383439
OpenAlexW2044638794

What OpenQuestion holds

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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.