Development of a nomogram for identifying periodontitis cases in Denmark.

Abstract

Although self-reported health outcomes are of importance, attempts to validate a clinical applicable instrument (e.g., nomogram) combining sociodemographic and self-reported information on periodontitis have yet to be performed to identify periodontitis cases. Clinical and self-reported periodontitis, along with sociodemographic data, were collected from 197 adults. Akaike information criterion models were developed to identify periodontitis, and nomograms developed based on its regression coefficients. The discriminatory capability was evaluated by receiver-operating characteristic curves. Decision curve analysis was performed. Smoking [OR 3.69 (95%CI 1.89, 7.21)], poor/fair self-rated oral health [OR 6.62 (95%CI 3.23, 13.56)], previous periodontal treatment [OR 9.47 (95%CI 4.02, 22.25)], and tooth loss [OR 4.96 (95%CI 2.47, 9.97)], determined higher probability of having "Moderate/Severe Periodontitis". Age [OR 1.08 (95%CI 1.05, 1.12)], low educational level [OR 1.65 (95%CI 1.34, 2.23)], poor/fair self-rated oral health [OR 3.57 (95%CI 1.82, 6.99)], and previous periodontal treatment [OR 6.66 (95%CI 2.83, 15.68)] determined higher probability for "Any Periodontitis". Both nomograms showed excellent discriminatory capability (AUC of 0.83 (95%CI 0.75, 0.91) and 0.81 (95% CI 0.74, 0.88), good calibration, and slight overestimation of high risk and underestimation of low risk. Hence, our nomograms could help identify periodontitis among adults in Denmark.