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Table 6. Area under the ROC curve, optimum sensitivity and specificity and corresponding ICDAS-II threshold used, for each examiner at each diagnostic threshold (D1, D3 and ERK 2–3) D1 diagnostic threshold AUC (SE) CI opt. sens. D3 diagnostic threshold opt. spec. ICDAS cut-off AUC (SE) CI opt. sens. opt. spec. ICDAS cut-off Examiner 1 0.85 (0.05) 0.75–0.94 0.71 0.91 1–2 0.88 (0.04) 0.81–0.96 0.79 0.90 2–3 Examiner 2 0.86 (0.05) 0.77–0.94 0.73 0.83 1–2 0.87 (0.04) 0.80–0.95 0.69 0.90 2–3 Examiner 3 0.73 (0.06) 0.62–0.84 0.59 0.78 1–2 0.87 (0.04) 0.80–0.94 0.48 0.94 2–3 Examiner 4 0.80 (0.05) 0.70–0.90 0.73 0.74 1–2 0.88 (0.04) 0.80–0.95 0.83 0.82 2–3 AUC = Area under the curve; SE = standard error; CI = 95% confidence interval; opt. sens. = optimum sensitivity; opt. spec. = optimum specificity. shows the Spearman’s correlation coefficient for ICDAS- II visual examination for each examiner, for both Downer and ERK histological scores. It is generally accepted that a correlation coefficient of 0.7 or above represents a strong relationship between two variables. Table 6 shows the area under the curve for each examiner, the optimum sensitivity and specificity and the ICDAS-II cut-off that resulted in this outcome, for the D1, D3 and ERK 2–3 diagnostic thresholds. At the D1 diagnostic threshold the optimum sensitivity and specificity for each examiner was obtained using ICDAS-II cut-off 1–2. To correctly reflect the D1 diagnostic threshold all lesions including those with an ICDAS-II code 1 should have been classed as caries. However, when this was done, sensitivity was high (mean = 0.89, min. = 0.76, max. = 0.96), but specificity was low (mean = 0.52, min. = 0.39, max. = 0.61). The D3 diagnostic threshold used the enamel-dentine junction to differentiate sound and caries, whereas the ERK 2–3 diagnostic threshold was deeper, between the outer third of dentine and middle third of dentine and yet the same ICDAS-II cut-off gave the optimum sensitivity and specificity. If a higher ICDAS-II cut-off of 3–4 was used to reflect this increased severity of lesion when validated with the ERK 2–3 histological threshold a mean sensitivity of 0.60 (min. = 0.56, max. = 0.64) and mean specificity of 0.90 (min. 0.84, max. 0.94) were obtained. Discussion Occlusal caries accounts for the majority of new lesions in the permanent dentition of children, adolescents and young adults. Whilst one of the most readily accessible tooth surfaces, it has a complex invaginated anatomy, which makes caries detection more difficult. There are numerous treatment options for occlusal caries and ultimately the aim is to link detection, diagnosis and appropriate treatment and this study addresses the first step in this process. To date little has been published on the visual ICDAS- II system, but other similar scoring systems have previously been used. In one study an interexaminer kappa value of 0.91 and intra-examiner kappa value of 0.9 was found between 2 examiners using an eight-point scoring system for diagnosing occlusal caries [Ekstrand et al., 1995]. Using a five-point scoring system, kappa values of 0.54–0.69 were found for interexaminer reproducibility of 3 examiners and 0.73–0.89 for intra-examiner agreement [Ekstrand et al., 1997]. In another study using the same system, kappa values of 0.47–0.61 between 3 examiners and 0.56–0.68 for intra-examiner reproducibility were achieved [Reis et al., 2004]. A recent study which also used a four-point system for 8 examiners [Souza- Zaroni et al., 2006], found kappa values of 0.35–0.5 for interexaminer and 0.81–0.85 for intra-examiner reproducibility. The reproducibility achieved with the ICDAS-II seven-point scoring system in this study compared favourably with those cited. However, it is likely that the cited studies reported unweighted kappa values, like Ekstrand [1997], since they did not mention weighting. If we compare the unweighted kappas from the present study (interexaminer 0.32–0.61; intra-examiner 0.54–0.65), the differences disappear. Although intra-examiner kappa values could not be calculated for the reference examiner, this examiner had used the ICDAS-II system extensively and achieved acceptable intra-examiner kappa values in a previously published 84 Caries Res 2008;42:79–87 Jablonski-Momeni /Stachniss /Ricketts / Heinzel-Gutenbrunner /Pieper
ERK 2–3 diagnostic threshold AUC (SE) CI opt. sens. opt. spec. ICDAS cut-off 0.84 (0.04) 0.76–0.93 0.84 0.75 2–3 0.84 (0.05) 0.75–0.93 0.80 0.79 2–3 0.86 (0.04) 0.78–0.94 0.64 0.90 2–3 0.84 (0.04) 0.76–0.92 0.88 0.68 2–3 study [Ekstrand et al., 1997] using comparable visual criteria. Interexaminer kappa values between the reference examiner and 3 trained examiners were also acceptable ( table 3 ). Histological validation of caries and in particular occlusal caries is notoriously difficult as preparing thin sections entails tooth tissue loss. Simply hemisecting a tooth through the lesion may not pass through the deepest aspect of the lesion in question. Taking a single section through an investigation site is also problematic if only one side of the section is examined as the depth of a lesion will vary from one side of a section to another [Ricketts et al., 1998]. Whilst only one side of the section was viewed in this study because of the mounting technique used, the sections were serial and the side viewed on one section corresponded to the side not viewed on the preceding section. These problems arise because of the three-dimensional nature of the spread of caries dictated by the complex anatomy of the occlusal surface. A lesion may originate at one site on the surface of the tooth but spread obliquely and non-symmetrically beneath the tooth surface. To overcome this problem and to record the deepest aspect of the lesion from where it originated at the investigation site, 1–4 sections were used depending on the severity of the lesion. The use of the coordinate system ensured accurate location of each section and thus that the lesion on the section originated from the investigation site in question. Because of the mode of spread alluded to above, it could be argued that the appearance at one site may influence the decision at another. For example, if one site was obviously carious, the likelihood of an adjacent site also being carious and recorded as such is much higher. The data collected at multiple sites cannot therefore be regarded as independent. To overcome this problem one investigation site per tooth was randomly selected for analysis. In previous studies comparing both visual classification systems and histological classification systems of increasing lesion severity, the relationships between the two variables have been strong, with Spearman correlation coefficients of 0.87 for an eight-point visual scale [Ekstrand et al., 1995] and 0.87–0.93 for a five-point visual scale [Ekstrand et al., 1997]. In this study the relationship between the ICDAS-II visual classification system and either histological classification system was not as strong (r s = 0.48–0.72 using Downer histology and 0.43–0.68 for ERK histology). For comparison with other studies using similar visual classification systems or different novel technologies, the Downer histology was used in the ROC analyses for each examiner at the D1 and D3 diagnostic threshold and the ERK histology was used similarly at the 2–3 threshold. For all examiners the ICDAS-II system produced areas under the ROC curves in excess of 0.7. At the D1 diagnostic threshold the mean sensitivity and specificity of the ICDAS-II were 0.69 and 0.82, respectively ( table 6 ). The sensitivity was found to be higher than that reported in a previous study using a different eight-point visual scale and three groups of examiners [Fyffe et al., 2000b] where sensitivity ranged between 0.46 and 0.5. The specificity in this study was similar to that reported by Fyffe et al. [2000b], who found specificities of 0.66–0.86. However, in this study optimum sensitivity and specificity were achieved at the ICDAS-II cut-off 1–2 and not 0–1, which would have been consistent with the D1 diagnostic threshold. When the 0–1 cut-off was used, sensitivity was high (mean = 0.89), but specificity was low (mean = 0.52). This means that a large number of sound sites were incorrectly scored as carious and this may have been due to stained sites, areas of fluorosis or developmental defects being incorrectly scored as caries. It is important to question what impact this would have clinically. From table 4 it can be seen that the sound sites that were incorrectly scored as carious were given a low ICDAS-II score which would not require operative treatment. The worse clinical outcome would therefore be giving prevention to a sound site, which in a high-risk patient would be of benefit. In this study, at the D3 diagnostic threshold mean sensitivity was 0.70 and specificity was 0.89 using ICDAS-II scores 2–3 to differentiate sound sites from those with dentine caries ( table 6 ). These are similar to those reported by Downer [1989], who in a review of the literature found that trained and experienced examiners using a Reproducibility/Accuracy of a Method for Caries Detection Caries Res 2008;42:79–87 85
Page 1 and 2: Original Paper Caries Res 2008;42:7
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