Multi-Centre External Validation of a Nomogram for 10-Year Periodontal Tooth Loss Prediction.

Abstract

Aims: To externally validate the potential applicability of the 2018 classification of periodontal diseases as a risk assessment tool, through the use of a nomogram built on a multivariate predictor model.

Materials and methods: Data from 459 patients with periodontitis, across four cohorts (three in the United States, and one in the United Kingdom), were retrospectively analysed. After staging and grading periodontitis before active periodontal therapy (APT), patients were categorised by the model as having 'low tooth loss' (≤ 1 teeth lost due periodontal reasons [TLP]) or 'high tooth loss' (≥ 2 TLP) at a 10-year follow-up. Model discrimination was evaluated using the area under the receiver operating characteristic (AUC-ROC) curve. Calibration was assessed through calibration plots, calibration-in-the-large (CITL), calibration slope and the expected:observed (E:O) ratio. Recalibration methods, including Temperature Scaling, Isotonic Regression and Beta Calibration, were also tested.

Results: The original nomogram yielded an aggregate AUC-ROC 0.72 but showed poor calibration. Isotonic recalibration improved the AUC-ROC to 0.77 and enhanced calibration metrics, achieving an E-statistic of 1.00, CITL of 0.00 and a calibration slope of 1.00.

Conclusion: A nomogram based on the components of the 2018 periodontal disease classification can serve as a prognostic tool with cross-site applicability across clinical settings in industrialised countries, accurately predicting the 10-year risk of tooth loss due to periodontitis from the initial assessment conducted before the start of APT.