135
Views
0
CrossRef citations to date
0
Altmetric
Review Article

Diagnostic accuracy of MALDI-TOF mass spectrometry for non-small cell lung cancer: a meta-analysis

, , &
Pages 245-252 | Received 22 Aug 2017, Accepted 20 Dec 2017, Published online: 12 Jan 2018
 

Abstract

Objective: To assess the overall accuracy of matrix-assisted laser desorption/ionization time-of-flight mass spectrometry (MALDI-TOF MS) in identifying non-small cell lung cancer (NSCLC).

Methods: A comprehensive search of PubMed, EMBASE and CNKI databases as well as the reference lists from relevant articles was performed prior to July 2017. Two authors independently screened articles based on inclusion and exclusion criteria and assessed the quality of each study using the Quality Assessment of Diagnostic Accuracy Studies 2 (QADAS-2) tool. Meta-disc 1.4 and Stata12.0 software programs were used for the statistical analysis.

Results: Eleven eligible articles comprising 16 studies and representing 935 subjects were included in this meta-analysis. The pooled sensitivity and specificity were 0.84 (95% CI: 0.80–0.87) and 0.77 (95% CI: 0.74–0.80), respectively. The overall diagnostic performance as measured by the area under the curve (AUC) for the summary receiver-operating characteristic (SROC) curve was 0.9380.

Conclusions: MALDI-TOF MS has a high diagnostic accuracy for NSCLC.

Disclosure statement

The authors declare no conflicts of interest.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 65.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 527.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.