Evidence map›Paper›PMID 27636552›Full record

SynthesisPloS one2016

CA153 in Breast Secretions as a Potential Molecular Marker for Diagnosing Breast Cancer: A Meta Analysis.

Shifu Tang, Lili Wei, Yifan Sun, Fang Zhou, Shengbo Zhu, Renqi Yang, Yiyong Huang, Hongyu Zhang, Hong Xu, Jianqing Yang

Abstract readMeta-Analysis
In one paragraph

Synthesis in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
19citing papers in PubMed, 2 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

19 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Effect of exosome biomarkers for diagnosis and prognosis of breast cancer patients.Clinical & translational oncology : official publication of the Federation of Spanish Oncology Societies and of the National Cancer Institute of Mexico · 2018
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  11. Cells · 2022
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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

10 authors.

Shifu TangDepartment of Laboratory Medicine, the Third Affiliated Hospital of Guangxi University of Chinese Medicine, Guangxi, China.
Lili WeiDepartment of Internal Medicine, the Third Affiliated Hospital of Guangxi University of Chinese Medicine, Guangxi, China.
Yifan SunDepartment of Laboratory Medicine, the Third Affiliated Hospital of Guangxi University of Chinese Medicine, Guangxi, China.
Fang ZhouDepartment of Rheumatology, the Fourth Affiliated Hospital of Guangxi Medical University, Guangxi, China.
Shengbo ZhuDepartment of Laboratory Medicine, the Third Affiliated Hospital of Guangxi University of Chinese Medicine, Guangxi, China.
Renqi YangDepartment of Laboratory Medicine, the Third Affiliated Hospital of Guangxi University of Chinese Medicine, Guangxi, China.
Yiyong HuangDepartment of Laboratory Medicine, the Third Affiliated Hospital of Guangxi University of Chinese Medicine, Guangxi, China.
Hongyu ZhangDepartment of Laboratory Medicine, the Third Affiliated Hospital of Guangxi University of Chinese Medicine, Guangxi, China.
Hong XuDepartment of Internal Medicine, the Third Affiliated Hospital of Guangxi University of Chinese Medicine, Guangxi, China.
Jianqing YangDepartment of General Surgery, the Third Affiliated Hospital of Guangxi University of Chinese Medicine, Guangxi, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeMany studies have reported that carbohydrate antigen 153 (CA153) in breast secretions (BS) can discriminate breast cancer (BC) patients from healthy individuals, indicating CA153 in BS as a potential index for BC. This meta-analysis aimed to evaluate the actual diagnostic value of CA153 in BS.

methodsRelated papers were obtained from Pubmed, Embase, Scopus, Ovid, Sciverse, the Cochrane library, Chinese Biomedical literature Database (CBM), Technology of Chongqing (VIP), Wan Fang Data, and Chinese National Knowledge Infrastructure (CNKI). Pooled sensitivity, specificity, and diagnostic odds ratio (DOR) of CA153 in BS for BC diagnosis were analyzed with the random effect model. SROC and the area under the curve (AUC) were applied to assess overall diagnostic efficiency.

resultsThis meta-analysis included five studies with a total of 329 BC patients and 381 healthy subjects. For CA153 in BS, the summary sensitivity, specificity, and DOR to diagnose BC were 0.63 (95% confidence interval (CI): 0.57∼0.68), 0.82 (95% CI: 0.78∼0.86), and 9.18 (95% CI: 4.22∼19.95), respectively. Furthermore, the AUC of BS CA153 in the diagnosis of BC was 0.8614.

conclusionsCA153 in BS is a valuable molecular marker in diagnosing BC and should be applied in standard clinical practices of BC screening upon confirmation of our findings in a larger prospective study.

Indexed as

Antigens, NeoplasmBiomarkers, TumorBreast NeoplasmsCase-Control StudiesFemaleHumansSensitivity and SpecificityAntigens, NeoplasmBiomarkers, TumorCA153 protein, human

Identifiers

PMID27636552
PMCPMC5026335

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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.