Validation of different Cariogram settings and factor combinations in preschool children from areas with high caries risk

Abstract

Background Caries risk assessment in preschool children has been limited validated. Aim To validate caries predictive ability of Cariogram using different combinations of factors and settings in preschool children from areas with high caries risk. Design Two to five years old children (N = 175) were examined for caries (cavitated and non‐cavitated lesions), at baseline and after 1 and 2 years. Mutans streptococci counts (MS) and saliva buffer capacity (SBC) were measured with chair side tests. Diet and oral health attitude were assessed through a parental questionnaire. Baseline caries risk was calculated using standard and high‐risk group variables in Cariogram either with nine factors or excluding MS and SBC. Poisson regression models, ROC analysis and information criteria (AIC and BIC), P < 0.05, were used to investigate the predictive ability of Cariograms and to quantify the associations. Results Accuracy of Cariogram was found limited. Cariograms with MS showed higher sensitivity but lower specificity than those without bacterial counts. Standard set Cariograms with MS counts performed slightly better than the other models, but the difference was not statistically significant. Caries prediction with standard and high set Cariograms was also found limited. Conclusions Cariogram with various factors and settings displayed suboptimal ability to predict caries in this population.

Oral health, caries risk profiles, and oral microbiome of pediatric patients with leukemia submitted to chemotherapy

“…The Cariogram, an interactive computer-based caries risk assessment programme, has developed rapidly in the past years, with many related studies and high evaluations. It has been used to evaluate the caries risk of various populations, including normal populations of different ages [12,42], patients undergoing oral treatment [43,44] and patients with systemic diseases [45]. Andreas et al compared the validity of three caries risk assessment tools and concluded that Cariogram displayed a higher validity in predicting caries increment [46].…”

“…Caries risk refers to the possibility of individuals to develop carious lesions over a certain period of time [12]. Assessing caries risk is an essential element in the planning of preventive and therapeutic strategies [13].…”

Prediction Models of Early Childhood Caries Based on Machine Learning Algorithms

“…The prediction of caries risk based on these risk factors is considered a cornerstone of clinical decision making and disease prevention in individual patients [14] and using comprehensive and standardized tools is recommended [15]. While many have attempted to evaluate the risk of dental caries in early childhood [16][17][18], none have developed a prediction model that uses large-scale, representative survey data from the Korea National Health and Nutrition Examination Survey (KNHANES).…”

Use of Cariogram as a Risk Assessment of Caries Lesions in the City of Arraial Do Cabo, Brazil / Uso Do Cariograma Como Avaliação De Risco De Lesões De Cárie Na Cidade De Arraial Do Cabo, Brasil

“…In this work the Cariogram used without salivary tests as a tool to interpret and map out a global risk of caries proved an accurate model, convenient to be used in clinical, low cost, teaching to the patient's motivation and easy interpretation, becoming thus an important ally in caries risk assessment, providing a more reliable diagnosis and treatment proposal, as corroborated by other authors. 7,8 The 10,11,12,13 When the ICDAS index was used to assess past / present experience, considering the initial stages of the lesion as an already established disease, an average of 11.9 was obtained in the general sample. This value is increased, as shown above, in relation to the CPOD/ceo-d of the same region, as well as also presented by SB Brasil 2010 in the State of Rio de Janeiro, a fact that can be explained due to this index providing early recognition of the disease while the DMFT / ceo-d index considers an installed disease only a cavity lesion already cavitated.…”