Accuracy of Raman spectroscopy in the assisted diagnosis of colon cancer: a meta-analysis_Chinese Journal of Evidence-Based Medicine

Authors：

LI Chenxi ¹ , CHEN Cheng ² , LV Xiaoyi ² ,  GONG Zhongcheng ¹

1. Oncological Department of Oral and Maxillofacial Surgery, the First Affiliated Hospital of Xinjiang Medical University, School / Hospital of Stomatology, Stomatological Research Institute of Xinjiang Uygur Autonomous Region, Urumqi 830054, P. R. China;
2. College of Software Engineering, Xinjiang University, Urumqi 830046, P. R. China;

Corresponding author：

GONG Zhongcheng, Email: gump0904@aliyun.com

Keywords：

Raman spectroscopy; Colon cancer; Diagnosis; Screening; Systematic review; Meta-analysis

DOI：

10.7507/1672-2531.202112098

Video：

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Objective To systematically review the clinical significance of Raman spectroscopy (RS) in the auxiliary diagnosis of colon cancer (CC). Methods PubMed, Web of Science, The Cochrane Library, CNKI, VIP and WanFang Data databases were electronically searched to collect diagnostic tests related to RS in the auxiliary diagnosis of CC from inception to October 1^st, 2021. Two reviewers independently screened the literature, extracted data and assessed the risk of bias of the included studies. Meta-analysis was then performed using Stata 12.0 and Meta-Disc 1.4 software. Results A total of 21 studies involving 1 419 patients were included. The pooled sensitivity, specificity, positive likelihood ratio (PLR), negative likelihood ratio (NLR), diagnostic odds ratio (DOR) and positive posttest probability (PPP) for CC screening applying RS were 0.94 (95%CI 0.93 to 0.95), 0.91 (95%CI 0.90 to 0.92), 157.50 (95%CI 74.44 to 333.21), 10.40 (95%CI 6.62 to 16.33), 0.08 (95%CI 0.05 to 0.12) and 77%, respectively. The area under the curve (AUC) of summary receiver operating characteristic (SROC) curve was 0.98 (95%CI 0.96 to 0.99). Conclusion Current evidence shows that RS is a potentially useful tool for CC screening. Due to the limited quality and quantity of the included studies, more high-quality studies are needed to verify the above conclusion.

Citation： LI Chenxi, CHEN Cheng, LV Xiaoyi, GONG Zhongcheng. Accuracy of Raman spectroscopy in the assisted diagnosis of colon cancer: a meta-analysis. Chinese Journal of Evidence-Based Medicine, 2022, 22(6): 649-654. doi: 10.7507/1672-2531.202112098 Copy

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2.	Rembacken B, Hassan C, Riemann JF, et al. Quality in screening colonoscopy: position statement of the European Society of Gastrointestinal Endoscopy (ESGE). Endoscopy, 2012, 44(10): 957-968.
3.	李梦雅, 夏珂, 和海妍, 等. 拉曼光谱技术在检验医学中的研究进展及应用. 中华检验医学杂志, 2021, 44(1): 70-74.
4.	Ito H, Uragami N, Miyazaki T, et al. Highly accurate colorectal cancer prediction model based on Raman spectroscopy using patient serum. World J Gastrointest Oncol, 2020, 12(11): 1311-1324.
5.	Liu W, Wang H, Du J, et al. Raman microspectroscopy of nucleus and cytoplasm for human colon cancer diagnosis. Biosens Bioelectron, 2017, 97: 70-74.
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11.	罗舒文, 陈长水, CHENWei-dong. 基于拉曼光谱和多元统计分析技术的结肠癌早期诊断. 发光学报, 2013, 34(11): 1544-1549.
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17.	Bergholt MS, Zheng W, Lin K, et al. Characterizing variability of in vivo Raman spectroscopic properties of different anatomical sites of normal colorectal tissue towards cancer diagnosis at colonoscopy. Anal Chem, 2015, 87(2): 960-966.
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20.	Lopes PC, Moreira JA, Almeida A, et al. Discriminating adenocarcinoma from normal colonic mucosa through deconvolution of Raman spectra. J Biomed Opt, 2011, 16(12): 127001.
21.	Li P, Chen C, Deng X, et al. Drop coating deposition Raman spectroscopy of blood plasma for the detection of colorectal cancer. J Biomed Opt, 2015, 20(3): 037004.
22.	Lin D, Huang H, Qiu S, et al. Diagnostic potential of polarized surface enhanced Raman spectroscopy technology for colorectal cancer detection. Opt Express, 2016, 24(3): 2222-2234.
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24.	Chen Y, Chen G, Feng S, et al. Label-free serum ribonucleic acid analysis for colorectal cancer detection by surface-enhanced Raman spectroscopy and multivariate analysis. J Biomed Opt, 2012, 17(6): 067003.
25.	Feng S, Wang W, Tai IT, et al. Label-free surface-enhanced Raman spectroscopy for detection of colorectal cancer and precursor lesions using blood plasma. Biomed Opt Express, 2015, 6(9): 3494-3502.
26.	Ashok PC, Praveen BB, Bellini N, et al. Multi-modal approach using Raman spectroscopy and optical coherence tomography for the discrimination of colonic adenocarcinoma from normal colon. Biomed Opt Express, 2013, 4(10): 2179-2186.
27.	Petersen D, Naveed P, Ragheb A, et al. Raman fiber-optical method for colon cancer detection: Cross-validation and outlier identification approach. Spectrochim Acta A Mol Biomol Spectrosc, 2017, 181: 270-275.
28.	欧阳欢. 利用拉曼光谱技术快速诊断胃癌的Meta分析. 合肥: 安徽医科大学, 2016.
29.	赵倩妤. 拉曼光谱在癌症组织学诊断中的研究进展. 实用肿瘤学杂志, 2018, 32(1): 92-96.
30.	Leon-Sarmiento FE, Rizzo-Sierra CV, Leon-Ariza JS, et al. A new neurometric dissection of the area-under-curve-associated jiggle of the motor evoked potential induced by transcranial magnetic stimulation. Physiol Behav, 2015, 141: 111-119.
31.	Glas AS, Lijmer JG, Prins MH, et al. The diagnostic odds ratio: a single indicator of test performance. J Clin Epidemiol, 2003, 56(11): 1129-1135.
32.	Hillis SL. Equivalence of binormal likelihood-ratio and bi-chi-squared ROC curve models. Stat Med, 2016, 35(12): 2031-2057.

1. Depciuch J, Klębowski B, Stec M, et al. Similarities in the general chemical composition of colon cancer cells and their microvesicles investigated by spectroscopic methods-potential clinical relevance. Int J Mol Sci, 2020, 21(5): 1826.
2. Rembacken B, Hassan C, Riemann JF, et al. Quality in screening colonoscopy: position statement of the European Society of Gastrointestinal Endoscopy (ESGE). Endoscopy, 2012, 44(10): 957-968.
3. 李梦雅, 夏珂, 和海妍, 等. 拉曼光谱技术在检验医学中的研究进展及应用. 中华检验医学杂志, 2021, 44(1): 70-74.
4. Ito H, Uragami N, Miyazaki T, et al. Highly accurate colorectal cancer prediction model based on Raman spectroscopy using patient serum. World J Gastrointest Oncol, 2020, 12(11): 1311-1324.
5. Liu W, Wang H, Du J, et al. Raman microspectroscopy of nucleus and cytoplasm for human colon cancer diagnosis. Biosens Bioelectron, 2017, 97: 70-74.
6. Whiting PF, Rutjes AW, Westwood ME, et al. QUADAS-2: a revised tool for the quality assessment of diagnostic accuracy studies. Ann Intern Med, 2011, 155(8): 529-536.
7. 熊洋, 张德清, 高飞, 等. NIR-SERS技术结合统计分析结直肠癌氧合血红蛋白. 激光生物学报, 2016, 25(1): 33-40.
8. 刘燕玲. 表面增强拉曼光谱在胃肠道肿瘤血清检测中的应用研究. 广州: 南方医科大学, 2018.
9. 邹皇军. 共聚焦拉曼光谱技术对结直肠癌的诊断价值. 广州: 南方医科大学, 2019.
10. 林筱茜. 基于表面增强拉曼光谱技术的结肠癌和胃癌患者血液研究. 福州: 福建师范大学, 2013.
11. 罗舒文, 陈长水, CHENWei-dong. 基于拉曼光谱和多元统计分析技术的结肠癌早期诊断. 发光学报, 2013, 34(11): 1544-1549.
12. 王静. 基于膜电泳技术的血清蛋白表面增强拉曼光谱研究. 福州: 福建师范大学, 2014.
13. 林多. 结直肠癌患者血液表面增强拉曼光谱研究. 福州: 福建师范大学, 2012.
14. 覃业军. 散发性结直肠癌的β-Catenin基因突变及表达和单细胞拉曼光谱研究. 上海: 复旦大学, 2006.
15. 徐朝贤. 消化系统癌症患者血清蛋白表面增强拉曼光谱研究. 福州: 福建师范大学, 2016.
16. 李晓, 杨天月. 正常人和结直肠癌患者血清的拉曼光谱探测与区别. 光散射学报, 2011, 23(2): 138-141.
17. Bergholt MS, Zheng W, Lin K, et al. Characterizing variability of in vivo Raman spectroscopic properties of different anatomical sites of normal colorectal tissue towards cancer diagnosis at colonoscopy. Anal Chem, 2015, 87(2): 960-966.
18. Widjaja E, Zheng W, Huang Z. Classification of colonic tissues using near-infrared Raman spectroscopy and support vector machines. Int J Oncol, 2008, 32(3): 653-662.
19. Molckovsky A, Song LM, Shim MG, et al. Diagnostic potential of near-infrared Raman spectroscopy in the colon: differentiating adenomatous from hyperplastic polyps. Gastrointest Endosc, 2003, 57(3): 396-402.
20. Lopes PC, Moreira JA, Almeida A, et al. Discriminating adenocarcinoma from normal colonic mucosa through deconvolution of Raman spectra. J Biomed Opt, 2011, 16(12): 127001.
21. Li P, Chen C, Deng X, et al. Drop coating deposition Raman spectroscopy of blood plasma for the detection of colorectal cancer. J Biomed Opt, 2015, 20(3): 037004.
22. Lin D, Huang H, Qiu S, et al. Diagnostic potential of polarized surface enhanced Raman spectroscopy technology for colorectal cancer detection. Opt Express, 2016, 24(3): 2222-2234.
23. Wood JJ, Kendall C, Hutchings J, et al. Evaluation of a confocal Raman probe for pathological diagnosis during colonoscopy. Colorectal Dis, 2014, 16(9): 732-738.
24. Chen Y, Chen G, Feng S, et al. Label-free serum ribonucleic acid analysis for colorectal cancer detection by surface-enhanced Raman spectroscopy and multivariate analysis. J Biomed Opt, 2012, 17(6): 067003.
25. Feng S, Wang W, Tai IT, et al. Label-free surface-enhanced Raman spectroscopy for detection of colorectal cancer and precursor lesions using blood plasma. Biomed Opt Express, 2015, 6(9): 3494-3502.
26. Ashok PC, Praveen BB, Bellini N, et al. Multi-modal approach using Raman spectroscopy and optical coherence tomography for the discrimination of colonic adenocarcinoma from normal colon. Biomed Opt Express, 2013, 4(10): 2179-2186.
27. Petersen D, Naveed P, Ragheb A, et al. Raman fiber-optical method for colon cancer detection: Cross-validation and outlier identification approach. Spectrochim Acta A Mol Biomol Spectrosc, 2017, 181: 270-275.
28. 欧阳欢. 利用拉曼光谱技术快速诊断胃癌的Meta分析. 合肥: 安徽医科大学, 2016.
29. 赵倩妤. 拉曼光谱在癌症组织学诊断中的研究进展. 实用肿瘤学杂志, 2018, 32(1): 92-96.
30. Leon-Sarmiento FE, Rizzo-Sierra CV, Leon-Ariza JS, et al. A new neurometric dissection of the area-under-curve-associated jiggle of the motor evoked potential induced by transcranial magnetic stimulation. Physiol Behav, 2015, 141: 111-119.
31. Glas AS, Lijmer JG, Prins MH, et al. The diagnostic odds ratio: a single indicator of test performance. J Clin Epidemiol, 2003, 56(11): 1129-1135.
32. Hillis SL. Equivalence of binormal likelihood-ratio and bi-chi-squared ROC curve models. Stat Med, 2016, 35(12): 2031-2057.

Chinese Journal of Evidence-Based Medicine

Accuracy of Raman spectroscopy in the assisted diagnosis of colon cancer: a meta-analysis

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