Predictors of tooth loss due to periodontal disease in patients following long‐term periodontal maintenance

Abstract

AimTo analyse patient‐related factors (PRFs) and tooth‐related factors (TRFs) associated with tooth loss due to periodontal disease (TLPD) in patients undergoing periodontal maintenance (PM).Material and MethodsThe sample consisted of 500 patients (mean follow‐up of 20 years). The impact of PRFs on TLPD was analysed with Poisson regression and multivariate logistic regression. The simultaneous impact of PRFs and TRFs was analysed with multilevel logistic regression and Cox regression.ResultsTooth loss due to periodontal disease was 515 (mean 0.05 patient/year). The significant PRFs were severe periodontitis (p < 0.001), aggressive periodontitis (p < 0.001), smoking (p = 0.018), bruxism (p = 0.022) and baseline number of teeth (p = 0.001). These PRFs allowed characterizing patients losing more teeth. The whole TRFs analysed were significant, depending on the type of tooth and the category of each factor (e.g. mobility 0, 1, 2, and 3). The significant PRFs increased the risk of TLPD by 2 to 3 times while TRFs increased the risk to a higher extent. Mobility was the main TRF.ConclusionsSevere periodontitis, aggressive periodontitis, smoking, bruxism and baseline number of teeth, as well as the whole TRFs analysed, were associated with TLPD.

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

“…The ideal approach to assessing the accuracy of the prediction is the prospective longitudinal approach. However, it does not seem to be practical, as TLPD usually takes place in the long term as half of the teeth are lost between 10 and 20 years of observation (Martinez‐Canut, ). The already described alternative retrospective approach enables an immediate assessment of the accuracy of the prediction.…”

A comprehensive approach to assigning periodontal prognosis

“…The variable of crown‐to‐root ratio was already incorporated in the algorithm of the prediction model to calculate the probability of TLPD, with a certain increase in the probability of TLPD (Odds ratio 3.3 for non‐molars) (Martinez‐Canut, 2015). However, its actual role might be much more relevant than was revealed with the statistical analysis and perhaps root length itself might be more relevant than crown‐to‐root ratio.…”

“…Despite all efforts to increase this subsample, the actual prevalence of patients concentrating higher rates of TLPD is certainly low. A baseline sample of 500 patients was required (Martinez‐Canut, 2015) for a final sample of 22 LTO index 4 and 5. Interestingly, these 22 patients would represent 4.4% of our baseline sample of 500 patients, which is consistent with the actual percentage of patients experiencing higher TLPD rates reported in the literature, with the use of genuine TLPD samples instead of overall tooth loss samples (Chambrone & Chambrone, 2006; Checchi et al., 2002; Fardal et al., 2004; Lü et al., 2013; Muzzi et al., 2006).…”

“…Treatment rendered and periodontal maintenance programme has been previously described (Martinez‐Canut, 2015; Martinez‐Canut, Llobell & Romero, 2017). In brief, these patients received similar treatment and complied with PM every 4 months.…”

“…The first approach attempted to characterize the baseline status of patients that lose more teeth during PM (Fardal, Grytten, Martin, Houlihan, & Heasman, 2016; Martinez‐Canut, 2015; Martinez‐Canut, Llobell, & Romero, 2017; Tonetti, Muller‐Campanile, & Lang, 1998; Wasserman & Hirschfeld, 1988); the second approach focused on assessing the risk of disease progression and the resulting tooth loss (Lang & Tonetti, 2003; Lindskog et al., 2010; Page et al., 2002; Page, Krall, Martin, Mancl, & Garcia, 2002). The tools developed for this purpose have been assessed in longitudinal studies, their capability to identify patients with different levels of risk being demonstrated (Lang, Suvan, & Tonetti, 2015).…”