Introduction of a prediction model to assigning periodontal prognosis based on survival rates

Abstract

Aims

To develop a prediction model for tooth loss due to periodontal disease (TLPD) in patients following periodontal maintenance (PM), and assess its performance using a multicentre approach.

Material and methods

A multilevel analysis of eleven predictors of TLPD in 500 patients following PM was carried out to calculate the probability of TLPD. This algorithm was applied to three different TLPD samples (369 teeth) gathered retrospectively by nine periodontist, associating several intervals of probability with the corresponding survival rates, based on significant differences in the mean survival rates. The reproducibility of these associations was assessed in each sample (One-way ANOVA and pair-wise comparison with Bonferroni corrections).

Results

The model presented high specificity and moderate sensitivity, with optimal calibration and discrimination measurements. Seven intervals of probability were associated with seven survival rates and these associations contained close to 80% of the cases: the probability predicted the survival rate at this percentage. The model performed well in the three samples, since the mean survival rates of each association were significantly different within each sample, while no significant differences between the samples were found in pair-wise comparisons of means.

Conclusions

This model might be useful for predicting survival rates in different TLPD samples

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