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The accuracy of Raman spectroscopy in the detection and diagnosis of oral cancer: A systematic review and meta‐analysis
Author(s) -
Zhan Qi,
Li Yuan,
Yuan Yihang,
Liu Jinchi,
Li Yi
Publication year - 2020
Publication title -
journal of raman spectroscopy
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.748
H-Index - 110
eISSN - 1097-4555
pISSN - 0377-0486
DOI - 10.1002/jrs.5940
Subject(s) - medicine , receiver operating characteristic , diagnostic odds ratio , meta analysis , cancer , likelihood ratios in diagnostic testing , area under the curve , pathology , subgroup analysis , diagnostic accuracy , odds ratio , oral cancers , oncology
Purpose The aim of this study was to systematically review and assess the diagnostic accuracy of Raman spectroscopy (RS) for oral cancer tissue, oral precancerous lesions, and normal oral tissue. Methods PubMed, Embase, Web of Science, the China National Knowledge Infrastructure, and gray literature were searched for all relevant articles published before July 2019. We used the Quality Assessment of Diagnostic Accuracy Studies tool to assess the quality of the included studies. We estimated the pooled sensitivity, specificity, positive and negative likelihood ratios (PLR and NLR), diagnostic odds ratio (DOR), and established summary receiver operating characteristic (SROC) curves to identify the diagnostic accuracy of RS for oral cancer tissue, oral precancerous lesions, and normal oral tissue. In addition, the area under the curve (AUC) was reported to estimate the overall effectiveness of RS. Results A total of 41 articles were eligible for this meta‐analysis. The coalescent sensitivity and specificity of RS in diagnosing oral cancer in vivo were 0.91 and 0.85. The positive likelihood ratio, the negative likelihood ratio, and the area under the curve were 8.01, 0.10, and 0.9284. The frozen tissue subgroup in vitro oral cancer group showed improved diagnostic accuracy with an AUC of 0.9968. The in vitro frozen tissue group also showed better diagnostic accuracy in distinguishing between oral precancerous lesions and normal oral tissues. Conclusions RS has the advantages of being noninvasive and able to provide real‐time and in situ results, so it deserves to be studied and improved further to better serve clinical work.