Accuracy of Raman spectroscopy in discrimination of nasopharyngeal carcinoma from normal samples: a systematic review and meta-analysis

J Cancer Res Clin Oncol. 2019 Jul;145(7):1811-1821. doi: 10.1007/s00432-019-02934-y. Epub 2019 May 14.

Abstract

Objectives: The aim of this review was to systematically evaluate the diagnostic accuracy of Raman spectroscopy (RS) in the identification of nasopharyngeal carcinomas from normal nasopharyngeal tissue.

Methods: We searched six databases (PubMed, Embase, Cochrane Library, Web of Science, Scopus and CNKI) up to September 2018 for all published studies that assessed the diagnostic accuracy of RS in the detection of nasopharyngeal carcinomas. Non-qualifying studies were screened out in accordance with the specified exclusion criteria and relevant information about the diagnostic performance of RS extracted. A random effects model was adopted to calculate the pooled sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR, respectively), diagnostic threshold and diagnostic odds ratio (DOR). Additionally, we conducted a summary receiver-operating characteristic (SROC) curve analysis and threshold analysis, reporting area under the curve (AUC) to evaluate the overall performance of RS.

Results: Three studies examined RS analysis in vivo, the pooled sensitivity and specificity of RS of which were 0.90 and 0.91, respectively, with an AUC of 0.9617. Eighteen studies assessed ex vivo samples, for which RS exhibited particularly high accuracy for the analysis of blood plasma.

Conclusions: RS was demonstrated to be a reliable technique for the detection of nasopharyngeal carcinoma with high accuracy, but additional studies are required to improve its performance and expand its application in ex vivo detection.

Keywords: Diagnosis; Meta-analysis; Nasopharyngeal Carcinoma; Raman spectroscopy.

Publication types

  • Meta-Analysis
  • Systematic Review

MeSH terms

  • Databases, Factual
  • Humans
  • Nasopharyngeal Carcinoma / diagnosis*
  • Nasopharyngeal Neoplasms / diagnosis*
  • Spectrum Analysis, Raman / methods*