Caries Research · 2012 · 77 citations · 27 references
DentistryOral Health SciencesPeriodontologyOral DiagnosisPediatric Dental CariesRisk Assessment In DentistryCaries DetectionCaries DiagnosisCaries PreventionCaries ProgressionCaries Risk AssessmentOral Health IndicatorsCaries MeasurementCaries Risk Assessment ModelsCaries Risk IndicatorsCarious Risk AssessmentDental Caries IncidenceDietary Sugar IntakeReceiver Operating Characteristic AnalysisSugar Frequency
The validity of Cariogram in relation to caries increment over a 2-year period was evaluated. In 2007, the caries risk profile in a group of Sardinian schoolchildren (957) aged 7-9 years was assessed using the Cariogram software. A re-examination using the same criteria was performed 2 years later on 861 individuals from the original sample (drop-out 10.0%). The possible correlated variables were analyzed using the principal component analysis (PCA). The performances of Cariogram in predicting caries increment were evaluated by receiver operating characteristic (ROC) analysis. At follow-up examination, 54.4% of the sample had developed new carious lesions (mean DFS 1.6, 95% CI 1.5-1.8). The mean caries increment (ΔDFS) was 0.5, 95% CI 0.4-0.5. PCA showed that Cariogram, gingival status and dietary sugar frequency, both at baseline and at follow-up, tend to form a separate cluster (goodness of fit ≥0.75). Sensitivity and specificity measured by ROC analysis were 0.83 and 0.85, respectively, so the gain in certainty was 1.68, while the area under the ROC curve was 0.93. A strong correlation between caries risk profiles at baseline and caries incidence in the permanent teeth after 2 years was found. The validity of Cariogram was confirmed, the software fulfilling the criteria for a good risk assessment model: precision, accuracy and ease of use.
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Absence of bleeding on probing An indicator of periodontal stability
Niklaus P. Lang, Rolf Adler, Andreas Joss et al. · Journal Of Clinical Periodontology · 1990 · 661 citations