Predictors of clinical outcomes after periodontal treatment of aggressive periodontitis: 12-month randomized trial

Abstract

Little is known about the factors that may be used in clinical practice to predict the therapeutic response of aggressive periodontitis patients. The aim of this study was to determine predictors of clinical outcomes after non-surgical treatment of aggressive periodontitis. A total of 24 patients (aged 13-26 years) received oral hygiene instructions, as well as subgingival scaling and root planing. Twelve subjects received systemic azithromycin at random. Clinical variables were assessed at baseline, 3, 6, 9, and 12 months. Baseline microbiological assessment was performed by checkerboard DNA-DNA hybridization. Multivariable models used generalized estimating equations. There were significant improvements in the entire sample in regard to pocket depth, clinical attachment level and bleeding on probing. Significant predictors of a reduction in mean pocket depth were: use of azithromycin, non-molar teeth, generalized disease and baseline pocket depth. Absence of plaque predicted a 0.22 mm higher attachment gain, whereas a baseline pocket depth ≥7 mm predicted a 1.36 mm higher attachment loss. Azithromycin, plaque, and baseline pocket depth were significant predictors of bleeding on probing. The concomitant presence of all three red complex species predicted a 0.78 mm higher attachment loss. It may be concluded that dental plaque, tooth type, disease extent, baseline pocket depth, and use of azithromycin were significant predictors of the clinical response to treatment for aggressive periodontitis in young individuals. Moreover, the presence of multiple periodontal pathogens may predict challenges in achieving a favorable outcome for aggressive periodontitis.

Local IL‐10 level as a predictive factor in generalized aggressive periodontitis treatment response

“…Despite the interesting clinical observation and risk assessment, this study included only clinical aspects in determining which variable represents a long‐term success predictor. Some other studies have also suggested the calprotectin levels in GCF, LPS response pattern and the presence of red complex pathogens in the subgingival biofilm as predictive factors of clinical response and future periodontal breakdown in GAgP patients . However, considering the complexity of the GAgP etiopathogenesis, evaluating the microbiological and immunological patterns in conjunction with clinical parameters is essential for risk assessment in that population.…”

“…According to the authors, the inclusion of different parameters (such as probing depth ≥6 mm, bleeding index count ≥2, and different bone loss calculations) could be useful to modify the original PRA and better identify GAgP subjects with higher or lower‐risk for future tooth loss and periodontal destruction. Haas et al reported that patient and tooth factors could predict a better or worse response to treatment of localized and generalized aggressive periodontitis. Molars, absence of systemic antibiotic (azithromycin), localized aggressive periodontitis, infrabony defects and higher probing pocket depth resulted in a worse clinical response to non‐surgical therapy …”

“…Haas et al reported that patient and tooth factors could predict a better or worse response to treatment of localized and generalized aggressive periodontitis. Molars, absence of systemic antibiotic (azithromycin), localized aggressive periodontitis, infrabony defects and higher probing pocket depth resulted in a worse clinical response to non‐surgical therapy …”

“…Moreover, more advanced open‐ended molecular techniques have been associating GAgP with a higher presence of Selenomonas spp , Filifactor alocis and other bacterial phyla . Furthermore, there is some evidence that subgingival microbiota can influence GAgP response to non‐surgical therapy …”

“…Molars, absence of systemic antibiotic (azithromycin), localized aggressive periodontitis, infrabony defects and higher probing pocket depth resulted in a worse clinical response to non-surgical therapy. 15,16 Thus, many aspects should be considered in predictive analysis in the GAgP population. First, clinicians should decide, within different protocols, the most predictable therapeutic approach, once GAgP patients present a reduced response to non-surgical mechanical therapy.…”