Long term comparison of the prognostic performance of PerioRisk, periodontal risk assessment, periodontal risk calculator, and staging and grading systems

Background Clinicians predominantly use personal judgment for risk assessment. Periodontal risk assessment tools (PRATs) provide an effective and logical system to stratify patients based on their individual treatment needs. This retrospective longitudinal study aimed to validate the association of different risk categories of four PRATs (Staging and grading; Periodontal Risk Assessment (PRA); Periodontal Risk Calculator; and PerioRisk) with periodontal related tooth loss (TLP), and to compare their prognostic performance. Methods Data on medical history, smoking status, and clinical periodontal parameters were retrieved from patients who received surgical and non-surgical periodontal treatment. A comparison of the rate of TLP and non-periodontal related tooth loss (TLO) within the risk tool classes were performed by means of Kruskal-Wallis test followed by post-hoc comparison with the Bonferroni test. Both univariate and multivariate Cox Proportional hazard regression models were built to analyze the prognostic significance for each single risk assessment tool class on TLP. Results A total of 167 patients with 4321 teeth followed up for a mean period of 26 years were assigned to four PRATs. PerioRisk class 5 had a hazard ratio of 18.43, Stage 4 had a hazard ratio of 7.99, and PRA class 3 had a hazard ratio of 6.13 compared with class/stage I. With respect to prognostic performance, PerioRisk tool demonstrated the best discrimination and model fit followed by PRA. Conclusion All PRATs displayed very good predictive capability of TLP. PerioRisk showed the best discrimination and model fit, followed by PRA.

Automated summary

This study validated the association of different periodontal risk assessment tools with periodontal related tooth loss and compared their prognostic performance. Results showed that all PRATs had very good predictive capability of TLP, with PerioRisk demonstrating the best discrimination and model fit.