Evidence map›Paper›PMID 24648972›Full record

ArticleBiomedical reports2013

Neutrophil gelatinase-associated lipocalin protein as a biomarker in the diagnosis of breast cancer: A meta-analysis.

Yu Wang, Tingting Zeng

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Biomedical reports, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Review
  3. Article
  4. Review
  5. The role of lipocalin-2 serum levels in the diagnostics of endometrial cancer.Cancer biomarkers : section A of Disease markers · 2019
    Article
  6. Article
  7. Article
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  9. Review
  10. 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

2 authors.

Yu WangLaboratory of Molecular Diagnosis of Cancer, State Key Laboratory of Biotherapy and Cancer Center, West China Hospital, Sichuan University, Chengdu, Sichuan 610041;
Tingting ZengAdverse Drug Reaction Monitoring Center of Chengdu, High-Tech District, Chengdu, Sichuan 610042, P.R. China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Neutrophil gelatinase-associated lipocalin (NGAL) has been thought to play an important role in breast cancer tumorigenesis and progression. Various studies have focused on the association between NGAL and breast cancer. The aim of this meta-analysis was to establish the overall accuracy of the NGAL test in the diagnosis of breast cancer. A comprehensive search of the literature was conducted using PubMed, OVID, ScienceDirect and the China National Knowledge Infrastructure (CNKI) databases, and our screening covered all published papers until November 2012. The relevant papers were selected according to stringent inclusion criteria. Essential data were abstracted from the included papers and further analysed by a systematic meta-analysis. The present meta-analysis included four study papers. The summary estimate was 64% (95% CI, 0.59-0.69) for sensitivity and 87% (95% CI, 0.81-0.92) for specificity. The positive likelihood (PLR), negative likelihood (NLR) and diagnostic odds (DOR) ratios were 5.63 (95% CI, 3.63-8.74), 0.32 (95% CI, 0.14-0.71) and 18.02 (95% CI, 9.84-32.98), respectively. The area under the summary ROC curve (AUC) for the diagnosis of breast cancer was 0.9008. Thus, NGAL is a potential biomarker for the diagnosis of breast cancer.

Indexed as

breast cancerdiagnosislipocalin-2meta-analysisneutrophil gelatinase-associated lipocalin

Identifiers

PMID24648972
PMCPMC3917029

What OpenQuestion holds

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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.