Oral Sciences Research Group, Department of Surgery and Medical Surgical Specialties, School of Medicine and Dentistry, Health Research Institute Foundation of Santiago (FIDIS), Universidade de Santiago de Compostela, Santiago de Compostela, Spain.
Periodontology Unit, Centre for Host Microbiome Interactions, Faculty of Dentistry, Oral and Craniofacial Sciences, King's College London, London, UK.
J Clin Periodontol. 2019 Dec;46(12):1166-1182. doi: 10.1111/jcpe.13188. Epub 2019 Oct 16.
To analyse, by means of a meta-analytical approach, the diagnostic accuracy of molecular biomarkers in gingival crevicular fluid (GCF) for the detection of periodontitis in systemically healthy subjects.
Studies on GCF molecular biomarkers providing a binary classification table (or sensitivity and specificity values and group sample sizes) in individuals with clinically diagnosed periodontitis were considered eligible. The search was performed using six electronic databases. The methodological quality of studies was assessed through the tool Quality Assessment of Diagnostic Studies. Meta-analyses were performed using the Hierarchical Summary Receiver Operating Characteristic, which adjusts classification data using random effects logistic regression.
The included papers identified 36 potential biomarkers for the detection of periodontitis and for four of them meta-analyses were performed. The median sensitivity and specificity were for MMP8, 76.7% and 92.0%; for elastase, 74.6% and 81.1%; for cathepsin, 72.8% and 67.3%, respectively. The worst estimates of sensitivity and specificity were for trypsin (71.3% and 66.1%, respectively).
MMP8 showed good sensitivity and excellent specificity, which resulted in this biomarker being clinically the most useful or effective for the diagnosis of periodontitis in systemically healthy subjects, regardless of smoking condition.
通过荟萃分析方法分析龈沟液（GCF）中分子生物标志物在检测系统健康受试者牙周炎中的诊断准确性。
研究对象为符合临床诊断牙周炎的个体，研究内容为提供龈沟液分子生物标志物的二项分类表（或敏感性和特异性值以及组样本量）。使用六个电子数据库进行搜索。通过诊断研究质量评估工具评估研究的方法学质量。使用层次综合接收者操作特征曲线进行荟萃分析，该曲线使用随机效应逻辑回归调整分类数据。
纳入的论文确定了 36 种用于检测牙周炎的潜在生物标志物，其中 4 种进行了荟萃分析。MMP8 的中位敏感性和特异性分别为 76.7%和 92.0%；弹性蛋白酶为 74.6%和 81.1%；组织蛋白酶为 72.8%和 67.3%。胰蛋白酶的敏感性和特异性最差，分别为 71.3%和 66.1%。
MMP8 具有良好的敏感性和极好的特异性，因此该生物标志物在诊断系统健康受试者的牙周炎方面最有用或最有效，无论吸烟状况如何。
