Detection of mammagloblin by RT-PCR as a biomarker for lymph node metastasis in breast cancer patients: A systematic review and meta-analysis

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Background This meta-analysis presents evidence regarding the diagnostic accuracy of mammaglobin detected using the RT-PCR technique, related to the presence of sentinel node metastasis in breast cancer patients. Methods The following databases were consulted: Cochrane, Lilacs, Scielo, Hinary, PubMed, Elsevier, Embase, ProQuest, the Universidad del Rosario´s Centro de Recursos Para el Apren-dizaje y la Investigación (CRAI-UR) [Resource Center for Learning and Research], and the Google Scholar search engine. The quality of the studies was assessed using the QUADAS-2 and CASpe tools. The selected studies presented the necessary data to calculate diagnostic validity index of mammaglobin detection using RT-PCR, compared with the reference standard test. Global values for the sensitivity, specificity, positive predictive value, negative predictive value, probability ratios, diagnostic ORs, and summary ROC curves of this meta-analysis were obtained using the Meta-DiSc 1.4 program. Results Initially, 731 articles were obtained; but only 25 were included in the meta-analysis. Sensitivity was 84% (95% CI: 83% - 86%), and specificity was 92% (95% CI: 91% - 93%). Positive and negative predictive values were 9.26 (95% CI: 6.47–13.26) and 0.17 (95% CI: 0.13–0.23), respectively. The diagnostic OR was 66.34 (95% CI: 42.52–103.52). The predictive area under the sROC curve was 94.78 (Q = 0.8876). Conclusions The evaluated diagnostic index showed that the expression of the mammaglobin biomarker has diagnostic prediction for detecting lymph node metastasis in breast cancer patients, when analyzed using RT-PCR, although more than 50% heterogeneity was found.

Translated title of the contributionDetección de mammagloblin por RT-PCR como un biomarcador para metástasis en ganglios linfáticos en pacientes con cáncer de mama: una revisión sistemática y metaanálisis
Original languageEnglish
Article numbere0216989
Pages (from-to)1-16
Number of pages16
Issue number5
StatePublished - May 23 2019

All Science Journal Classification (ASJC) codes

  • General Biochemistry, Genetics and Molecular Biology
  • General Agricultural and Biological Sciences
  • General


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