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RESEARCH PRODUCT

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

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The pioneering attempt to characterize the response to periodontal treatment of patients undergoing periodontal maintenance (PM) (Wasserman & Hirschfeld 1988) was soon followed by the first studies on periodontal prognosis (McGuire 1991, McGuire & Nunn 1996a,b, McLeod et al. 1998). Two main conclusions were drawn, which remain generally accepted: establishing a periodontal prognosis is the basis of any treatment plan, and actual knowledge of the predictors of tooth loss (TL) is very limited. An extensive review on the subject noted the heterogeneity of the studies and the scarce information that could be drawn from them (Chambrone et al. 2010). Several statistical models analysing the predictors of TL during PM were capable of explaining the variance in TL to a limited extent: 19% (Tonetti et al. 1998), 12% (Konig et al. 2002) and 14% (Faggion et al. 2007). The variances can be interpreted as the percentage of improvement in the prediction, compared to the alternative of not considering any information provided by prognostic variables (Faggion et al. 2007). This lack of knowledge based on evidence is consistent with the discouraging observation that clinicians are able to predict good prognosis accurately (McGuire 1991). However, the accuracy of the remaining prognostic categories has been compared to a coin toss (McGuire & Nunn 1996a). Almost two decades after this illustrative comparison, we are far from improving on this scenario. Searching for additional information some authors wonder whether possible missing data on unknown or less studied prognostic factors could be involved (Tonetti et al. 1998, Konig et al. 2002). The aim of explaining TL through the analysis of up to twenty patient‐related factors (PRFs) and tooth‐related factors (TRFs), as previously described (McGuire 1991), would require a strict study design. Insofar as analyses have been performed on overall tooth loss (OTL) we might obtain misleading results. OTL includes TL due to periodontal disease (TLPD) plus, as reviewed, a 35% (Al‐Shammari et al. 2005) to 37% (Chambrone et al. 2010) rate of TL due to other reasons (TLOR) including caries, endodontic problems, root fractures and even strategic extractions, in some instances of periodontally stable teeth. The main suspected PRFs (age, severity, smoking, and compliance with PM) have been found to be statistically associated with TL with rather low consistency, in 40% to 80% of trials (McGuire & Nunn 1996b, 1999, Tonetti et al. 1998, Matthews et al. 2001, Checchi et al. 2002, Konig et al. 2002, Fardal et al. 2004, Chambrone & Chambrone 2006, Miyamoyo et al. 2006 Muzzi et al. 2006, Carnevale et al. 2007, Faggion et al. 2007, Eickholz et al. 2008, Jansson & Lagervall 2008, Pretzl et al. 2008, Tsami et al. 2009, Leininger et al. 2010, Martin et al. 2010, Baumer et al. 2011a,b, Graetz et al. 2011, Ng et al. 2011, Lu et al. 2013, Costa et al. 2014, Kim et al. 2014, Salvi et al. 2014, Saminsky et al. 2015, Seirafi et al. 2014) and this association has occurred in a seemingly mutual exclusive pattern, so that, for instance, either age or severity is significant, but not both. The few studies identifying both variables simultaneously utilized different criteria: number of teeth lost (Eickholz et al. 2008) or TL > 2 teeth, in a sub‐sample (Tonetti et al. 1998), rather than analysing TL as a dichotomous variable. Therefore, the statistical analysis may have influenced the results. In parallel, a masking or obscuring effect of some TRFs on PRFs has been described (McGuire & Nunn 1999, Pretzl et al. 2008). The present research attempted to overcome some limitations of the previous research. This was a retrospective case series of 500 patients undergoing PM that aimed to assess the simultaneous impact of PRFs and TRFs on TLPD.