Fluorescence devices for the detection of dental caries.

backgroundCaries is one of the most prevalent and preventable conditions worldwide. If identified early enough then non-invasive techniques can be applied, and therefore this review focusses on early caries involving the enamel surface of the tooth. The cornerstone of caries detection is a visual and tactile dental examination, however alternative methods of detection are available, and these include fluorescence-based devices. There are three categories of fluorescence-based device each primarily defined by the different wavelengths they exploit; we have labelled these groups as red, blue, and green fluorescence. These devices could support the visual examination for the detection and diagnosis of caries at an early stage of decay.

objectivesOur primary objectives were to estimate the diagnostic test accuracy of fluorescence-based devices for the detection and diagnosis of enamel caries in children or adults. We planned to investigate the following potential sources of heterogeneity: tooth surface (occlusal, proximal, smooth surface or adjacent to a restoration); single point measurement devices versus imaging or surface assessment devices; and the prevalence of more severe disease in each study sample, at the level of caries into dentine. SEARCH

methodsCochrane Oral Health's Information Specialist undertook a search of the following databases: MEDLINE Ovid (1946 to 30 May 2019); Embase Ovid (1980 to 30 May 2019); US National Institutes of Health Ongoing Trials Register (ClinicalTrials.gov, to 30 May 2019); and the World Health Organization International Clinical Trials Registry Platform (to 30 May 2019). We studied reference lists as well as published systematic review articles. SELECTION CRITERIA: We included diagnostic accuracy study designs that compared a fluorescence-based device with a reference standard. This included prospective studies that evaluated the diagnostic accuracy of single index tests and studies that directly compared two or more index tests. Studies that explicitly recruited participants with caries into dentine or frank cavitation were excluded. DATA COLLECTION AND ANALYSIS: Two review authors extracted data independently using a piloted study data extraction form based on the Quality Assessment of Diagnostic Accuracy Studies 2 (QUADAS-2). Sensitivity and specificity with 95% confidence intervals (CIs) were reported for each study. This information has been displayed as coupled forest plots and summary receiver operating characteristic (SROC) plots, displaying the sensitivity-specificity points for each study. We estimated diagnostic accuracy using hierarchical summary receiver operating characteristic (HSROC) methods. We reported sensitivities at fixed values of specificity (median 0.78, upper quartile 0.90). MAIN

resultsWe included a total of 133 studies, 55 did not report data in the 2 x 2 format and could not be included in the meta-analysis. 79 studies which provided 114 datasets and evaluated 21,283 tooth surfaces were included in the meta-analysis. There was a high risk of bias for the participant selection domain. The index test, reference standard, and flow and timing domains all showed a high proportion of studies to be at low risk of bias. Concerns regarding the applicability of the evidence were high or unclear for all domains, the highest proportion being seen in participant selection. Selective participant recruitment, poorly defined diagnostic thresholds, and in vitro studies being non-generalisable to the clinical scenario of a routine dental examination were the main reasons for these findings. The dominance of in vitro studies also means that the information on how the results of these devices are used to support diagnosis, as opposed to pure detection, was extremely limited. There was substantial variability in the results which could not be explained by the different devices or dentition or other sources of heterogeneity that we investigated. The diagnostic odds ratio (DOR) was 14.12 (95% CI 11.17 to 17.84). The estimated sensitivity, at a fixed median specificity of 0.78, was 0.70 (95% CI 0.64 to 0.75). In a hypothetical cohort of 1000 tooth sites or surfaces, with a prevalence of enamel caries of 57%, obtained from the included studies, the estimated sensitivity of 0.70 and specificity of 0.78 would result in 171 missed tooth sites or surfaces with enamel caries (false negatives) and 95 incorrectly classed as having early caries (false positives). We used meta-regression to compare the accuracy of the different devices for red fluorescence (84 datasets, 14,514 tooth sites), blue fluorescence (21 datasets, 3429 tooth sites), and green fluorescence (9 datasets, 3340 tooth sites) devices. Initially, we allowed threshold, shape, and accuracy to vary according to device type by including covariates in the model. Allowing consistency of shape, removal of the covariates for accuracy had only a negligible effect (Chi AUTHORS'

conclusionsThere is considerable variation in the performance of these fluorescence-based devices that could not be explained by the different wavelengths of the devices assessed, participant, or study characteristics. Blue and green fluorescence-based devices appeared to outperform red fluorescence-based devices but this difference was not supported by the results of a formal statistical comparison. The evidence base was considerable, but we were only able to include 79 studies out of 133 in the meta-analysis as estimates of sensitivity or specificity values or both could not be extracted or derived. In terms of applicability, any future studies should be carried out in a clinical setting, where difficulties of caries assessment within the oral cavity include plaque, staining, and restorations. Other considerations include the potential of fluorescence devices to be used in combination with other technologies and comparative diagnostic accuracy studies.