A predictive nomogram: a cross-sectional study on a simple-to-use model for screening 12-year-old children for severe caries in middle schools - Shaoying Duan; Meng Li; Jialiang Zhao; Huiyu Yang; Jinfeng He; Lei Lei; Ran Cheng; Tao Hu (BMC, 2021)
Abstract Background A nomogram is a tool that transforms complex regression equations into simple and visual graphs and enables clinicians and patients to conveniently compute output probabilities without needing medical knowledge and complex formulas. The aim of this study was to develop and validate a predictive nomogram to screen for severe caries among 12-year-old children based on risk factors in Sichuan Province, China. Methods A cross-sectional study of 4573 12-year-olds was conducted up to May 2016 in middle schools from three districts and three counties in Sichuan Province, China. All the children underwent oral examinations and completed questionnaires to assess general information, oral impacts on daily performance, dietary habits, subjective health conditions, history of dental trauma, frequency of toothache, dental visits, and knowledge, attitudes, and behaviours toward oral hygiene. Univariate analysis and multivariate logistic regression analysis were used to determine which variables were significantly associated with severe caries (operationalized as DMFT ≥ 3). A nomogram was developed and validated by using the 'rms' package and two cross-validation methods. Results Severe caries was found in 537 of the 4573 children (11.74%). Multivariate logistic regression analysis revealed that the following variables predicted a higher risk of severe caries: 'female' [odds ratio (OR) = 1.985, 95% confidence interval (95% CI): 1.63-2.411], 'urban' (OR = 2.389, 95% CI: 1.96-2.91), 'non-only child' (OR = 1.317, 95% CI: 1.07-1.625), 'very poor self-assessment of oral health status' (OR = 2.157, 95% CI: 1.34-3.467) and 'visited a dentist less than 6 months' (OR = 1.861, 95% CI: 1.38-2.505). Multivariate logistic regression analysis also indicated that the following variables predicted a lower risk of severe caries: 'middle level of urbanization' (OR = 0.395, 95% CI: 0.32-0.495) and 'high level of urbanization' (OR = 0.466, 95% CI: 0.37-0.596). Both the fivefold and leave-one-out cross-validation methods indicated that the nomogram model built by these 6 variables displayed good disease recognition ability. Conclusions The nomogram was a simple-to-use model to screen children for severe caries. This model was found to facilitate non-dental professionals in assessing risk values without oral examinations and making referrals to dental professionals.