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Diagnostic accuracy of calretinin for malignant mesothelioma in serous effusions: a meta-analysis.

Abstract
Numerous studies have investigated the utility of calretinin in differentiating malignant mesothelioma (MM) from metastatic carcinoma (MC) in serous effusions. However, the results remain controversial. The aim of this study is to determine the overall accuracy of calretinin in serous effusions for MM through a meta-analysis of published studies. Publications addressing the accuracy of calretinin in the diagnosis of MM were selected from the Medline (Ovid), PubMed, the Cochrane Library Database and the Web of Science. Data from selected studies were pooled to yield summary sensitivity, specificity, positive and negative likelihood ratio (LR), diagnostic odds ratio (DOR), and receiver operating characteristic (SROC) curve. Statistical analysis was performed by Meta-Disc 1.4 and STATA 12.0 softwares. 18 studies met the inclusion criteria and the summary estimating for calretinin in the diagnosis of MM were: sensitivity 0.91 (95%CI: 0.87-0.94), specificity 0.96 (95%CI: 0.95-0.96), positive likelihood ratio (PLR) 14.42 (95%CI: 7.92-26.26), negative likelihood ratio (NLR) 0.1 (95%CI: 0.05-0.2) and diagnostic odds ratio 163.03 (95%CI: 54.62-486.63). The SROC curve indicated that the maximum joint sensitivity and specificity (Q-value) was 0.92; the area under the curve was 0.97. Our findings suggest that calretinin may be a useful diagnostic tool for confirming MM in serous effusions.
AuthorsDiandian Li, Bo Wang, Hongyu Long, Fuqiang Wen
JournalScientific reports (Sci Rep) Vol. 5 Pg. 9507 (Mar 30 2015) ISSN: 2045-2322 [Electronic] England
PMID25821016 (Publication Type: Journal Article, Meta-Analysis)
Chemical References
  • Biomarkers, Tumor
  • Calbindins
Topics
  • Biomarkers, Tumor
  • Calbindins (metabolism)
  • Humans
  • Lung Neoplasms (diagnosis, metabolism)
  • Mesothelioma (diagnosis, metabolism)
  • Mesothelioma, Malignant
  • Pleural Effusion, Malignant (metabolism)
  • Publication Bias
  • ROC Curve
  • Reproducibility of Results
  • Sensitivity and Specificity

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