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CA153 in Breast Secretions as a Potential Molecular Marker for Diagnosing Breast Cancer: A Meta Analysis
- Source :
- PLoS ONE, Vol 11, Iss 9, p e0163030 (2016), PLoS ONE
- Publication Year :
- 2016
- Publisher :
- Public Library of Science (PLoS), 2016.
-
Abstract
- Purpose Many 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. Methods Related 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. Results This 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. Conclusions CA153 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.
- Subjects :
- 0301 basic medicine
Oncology
Pathology
Physiology
lcsh:Medicine
Cochrane Library
Biochemistry
Diagnostic Radiology
Mathematical and Statistical Techniques
0302 clinical medicine
Breast Tumors
Medicine and Health Sciences
Medicine
lcsh:Science
Prospective cohort study
Alcohol Consumption
Multidisciplinary
Radiology and Imaging
Area under the curve
030220 oncology & carcinogenesis
Meta-analysis
Physical Sciences
Female
Statistics (Mathematics)
Research Article
Mammography
medicine.medical_specialty
Imaging Techniques
Breast Neoplasms
Research and Analysis Methods
Sensitivity and Specificity
03 medical and health sciences
Breast cancer
Antigens, Neoplasm
Diagnostic Medicine
Internal medicine
Breast Cancer
Biomarkers, Tumor
Cancer Detection and Diagnosis
Humans
Statistical Methods
Secretion
Nutrition
business.industry
lcsh:R
Case-control study
Biology and Life Sciences
Cancers and Neoplasms
medicine.disease
Confidence interval
Diet
030104 developmental biology
Case-Control Studies
Diagnostic odds ratio
lcsh:Q
Physiological Processes
business
Mathematics
Biomarkers
Meta-Analysis
Subjects
Details
- ISSN :
- 19326203
- Volume :
- 11
- Database :
- OpenAIRE
- Journal :
- PLOS ONE
- Accession number :
- edsair.doi.dedup.....fa9f65125a388f2cb19ad44994d38507