Literature DB >> 36138121

Diagnosis accuracy of Raman spectroscopy in the diagnosis of breast cancer: a meta-analysis.

Mei-Huan Wang1, Xiao Liu1, Qian Wang2,3, Hua-Wei Zhang4,5.   

Abstract

To investigate the diagnostic efficiency of Raman spectroscopy for the diagnosis of breast cancer, we searched PubMed, Web of Science, Cochrane Library, and Embase for articles published from the database establishment to May 20, 2022. Pooled sensitivity, specificity, diagnostic odds ratio, and area under the receiver pooled operating characteristic curve were derived for the included studies as outcome measures. The methodological quality was assessed according to the questionnaires and criteria suggested by the Diagnostic Accuracy Research Quality Assessment-2 tool. Sixteen studies were included in this meta-analysis. The pooled sensitivity and specificity of Raman spectroscopy for breast cancer diagnosis were 0.97 (95% CI, [0.92-0.99]) and 0.96 (95% CI, [0.91-0.98]). The diagnostic odds ratio was 720.89 (95% CI, [135.73-3828.88]) and the area under the curve of summary receiver operating characteristic curves was 0.99 (95% CI, [0.98-1]). Subgroup analysis revealed that all subgroup types in our analysis, including different races, sample types, diagnostic algorithms, number of spectra, instrument types, and laser wavelengths, turned out to have a sensitivity and specificity greater than 0.9. Significant heterogeneity was found between studies. Deeks' funnel plot demonstrated that publication bias was acceptable. This meta-analysis suggests that Raman spectroscopy may be an effective and accurate tool to differentiate breast cancer from normal breast tissue, which will help us diagnose and treat breast cancer.
© 2022. Springer-Verlag GmbH Germany, part of Springer Nature.

Entities:  

Keywords:  Breast cancer; Diagnostic efficiency; Meta-analysis; Raman spectroscopy

Mesh:

Year:  2022        PMID: 36138121     DOI: 10.1007/s00216-022-04326-7

Source DB:  PubMed          Journal:  Anal Bioanal Chem        ISSN: 1618-2642            Impact factor:   4.478


  34 in total

1.  Investigation of support vector machines and Raman spectroscopy for lymph node diagnostics.

Authors:  Martina Sattlecker; Conrad Bessant; Jennifer Smith; Nick Stone
Journal:  Analyst       Date:  2010-03-05       Impact factor: 4.616

2.  Label-Free Raman Spectroscopic Techniques with Morphological and Optical Characterization for Cancer Cell Analysis.

Authors:  Sanghwa Lee; Jun Ki Kim
Journal:  Adv Exp Med Biol       Date:  2021       Impact factor: 2.622

3.  Comparison of the performance of screening mammography, physical examination, and breast US and evaluation of factors that influence them: an analysis of 27,825 patient evaluations.

Authors:  Thomas M Kolb; Jacob Lichy; Jeffrey H Newhouse
Journal:  Radiology       Date:  2002-10       Impact factor: 11.105

4.  Raman spectroscopic sensing of carbonate intercalation in breast microcalcifications at stereotactic biopsy.

Authors:  R Sathyavathi; Anushree Saha; Jaqueline S Soares; Nicolas Spegazzini; Sasha McGee; Ramachandra Rao Dasari; Maryann Fitzmaurice; Ishan Barman
Journal:  Sci Rep       Date:  2015-04-30       Impact factor: 4.379

Review 5.  Tear fluid biomarkers in ocular and systemic disease: potential use for predictive, preventive and personalised medicine.

Authors:  Suzanne Hagan; Eilidh Martin; Amalia Enríquez-de-Salamanca
Journal:  EPMA J       Date:  2016-07-13       Impact factor: 6.543

6.  Molecular fingerprint of precancerous lesions in breast atypical hyperplasia.

Authors:  Chao Zheng; Hong Ying Jia; Li Yuan Liu; Qi Wang; Hong Chuan Jiang; Li Song Teng; Cui Zhi Geng; Feng Jin; Li Li Tang; Jian Guo Zhang; Xiang Wang; Shu Wang; Fernandez-Escobar Alejandro; Fei Wang; Li Xiang Yu; Fei Zhou; Yu Juan Xiang; Shu Ya Huang; Qin Ye Fu; Qiang Zhang; De Zong Gao; Zhong Bing Ma; Liang Li; Zhi Min Fan; Zhi Gang Yu
Journal:  J Int Med Res       Date:  2020-06       Impact factor: 1.671

7.  Monitoring glycosylation metabolism in brain and breast cancer by Raman imaging.

Authors:  M Kopec; A Imiela; H Abramczyk
Journal:  Sci Rep       Date:  2019-01-17       Impact factor: 4.379

8.  Efficacy of Raman spectroscopy in the diagnosis of bladder cancer: A systematic review and meta-analysis.

Authors:  Hongyu Jin; Tianhai Lin; Ping Han; Yijun Yao; Danxi Zheng; Jianqi Hao; Yiqing Hu; Rui Zeng
Journal:  Medicine (Baltimore)       Date:  2019-11       Impact factor: 1.817

9.  Efficacy of raman spectroscopy in the diagnosis of kidney cancer: A systematic review and meta-analysis.

Authors:  Hongyu Jin; Xiao He; Hui Zhou; Man Zhang; Qingqing Tang; Lede Lin; Jianqi Hao; Rui Zeng
Journal:  Medicine (Baltimore)       Date:  2020-07-02       Impact factor: 1.817

Review 10.  Accuracy of Raman spectroscopy for differentiating skin cancer from normal tissue.

Authors:  Jing Zhang; Yimeng Fan; Yanlin Song; Jianguo Xu
Journal:  Medicine (Baltimore)       Date:  2018-08       Impact factor: 1.817

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