WestCHEM, Department of Pure and Applied Chemistry, Glasgow, UK.
Clinical Research Unit, Royal Alexandra Hospital, NHS Greater Glasgow and Clyde, Paisley, UK.
BJS Open. 2020 Aug;4(4):554-562. doi: 10.1002/bjs5.50289. Epub 2020 May 19.
Vibrational spectroscopy (VS) is a minimally invasive tool for analysing biological material to detect disease. This study aimed to review its application to human blood for cancer diagnosis.
A systematic review was undertaken using a keyword electronic database search (MEDLINE, Embase, PubMed, TRIP and Cochrane Library), with all original English-language manuscripts examining the use of vibrational spectral analysis of human blood for cancer detection. Studies involving fewer than 75 patients in the cancer or control group, animal studies, or where the primary analyte was not blood were excluded.
From 1446 results, six studies (published in 2010-2018) examining brain, bladder, oral, breast, oesophageal and hepatic cancer met the criteria for inclusion, with a total population of 2392 (1316 cancer, 1076 control; 1476 men, 916 women). For cancer detection, reported mean sensitivities in each included study ranged from 79·3 to 98 per cent, with specificities of 82·8-95 per cent and accuracies between 81·1 and 97·1 per cent. Heterogeneity in reporting strategies, methods and outcome measures made meta-analysis inappropriate.
VS shows high potential for cancer diagnosis, but until there is agreement on uniform standard reporting methods and studies with adequate sample size for valid classification models have been performed, its value in clinical practice will remain uncertain.
振动光谱(VS)是一种用于分析生物材料以检测疾病的微创工具。本研究旨在综述其在人类血液中用于癌症诊断的应用。
使用关键字电子数据库搜索(MEDLINE、Embase、PubMed、TRIP 和 Cochrane Library)进行系统综述,纳入所有检查人类血液振动光谱分析用于癌症检测的原始英文手稿。排除癌症或对照组患者少于 75 例、动物研究或主要分析物不是血液的研究。
从 1446 项结果中,有 6 项研究(发表于 2010-2018 年)符合纳入标准,研究对象包括脑癌、膀胱癌、口腔癌、乳腺癌、食道癌和肝癌,总人群为 2392 人(癌症 1316 人,对照组 1076 人;男性 1476 人,女性 916 人)。对于癌症检测,每个纳入研究报告的平均敏感性范围为 79.3%至 98%,特异性为 82.8%至 95%,准确性为 81.1%至 97.1%。由于报告策略、方法和结果测量的异质性,使得荟萃分析不适用。
VS 显示出癌症诊断的巨大潜力,但在达成统一的标准报告方法的共识并进行具有足够样本量的有效分类模型研究之前,其在临床实践中的价值仍不确定。