Development of a nomogram for the prediction of periodontal tooth loss using the staging and grading system: A long‐term cohort study

Aim To develop and internally validate a nomogram built on a multivariate prediction model including parameters from the new classification of periodontal diseases, able to predict, at baseline, the occurrence of tooth loss due to periodontal reason (TLP). Materials and Methods A total of 315 indivi...

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Veröffentlicht in:Journal of clinical periodontology 2020-11, Vol.47 (11), p.1362-1370
Hauptverfasser: Ravidà, Andrea, Troiano, Giuseppe, Qazi, Musa, Saleh, Muhammad H.A., Lo Russo, Lucio, Greenwell, Henry, Giannobile, William V., Wang, Hom‐Lay
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Sprache:eng
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Zusammenfassung:Aim To develop and internally validate a nomogram built on a multivariate prediction model including parameters from the new classification of periodontal diseases, able to predict, at baseline, the occurrence of tooth loss due to periodontal reason (TLP). Materials and Methods A total of 315 individuals diagnosed with periodontal disease and receiving a minimum of one annual supportive periodontal therapy visit were included in the study. Patients were staged and graded based upon baseline data. The population was divided into a development (254 patients) and a validation (61 patients) cohort to allow subsequent temporal validation of the model. According to the TLP at the 10‐year follow‐up, patients were categorized as “low tooth loss” (≤ 1 TLP) or “high tooth loss” (≥ 2 TLP). Bootstrap internal validation was performed on the whole data set to calculate an optimism‐corrected estimate of performance. Results The generated nomogram showed a strong predictive capability (AUC = 0.81) and good calibration with an intercept = 0 and slope = 1. These findings were confirmed by internal validation using bootstrapping (average bootstrap AUC = 0.83). Conclusions The clinical implementation of the present nomogram guides the prediction of patients with high risk of disease progression and subsequent tooth loss for personalized care.
ISSN:0303-6979
1600-051X
DOI:10.1111/jcpe.13362