Classification of periodontal diseases: history, present and future

Classification of periodontitis patients has been a challenge troughout the last 100 years. Historically, the classification of peridontal disease has been directly linked to the available knowledge about the clinical symptoms and the pathogenesis of the disease. Thus, throughout the years and paralel tot he development of knowledge, disease classification has evolved and has been updated several times. Currently, the internationally accepted classification system is the one proposed by Armitage (1999). However, also other disease clasification systems have been proposed aiming for an easier clinical applicability (Van der Velden 2000). Despit the efforts, classification remains an issue of controversy and all the different proposed systems present advantages and shortcomings. New knowledge of the disease etiology and pathobiology, as well as contemporary bioinformatics techniques, could contribute to the improvement of the current classification systems

Three periodontitis phenotypes: Bone loss patterns, antibiotic—surgical treatment and the new classification

Aim: To compare three periodontitis clusters (A, B and C) for alveolar bone loss (ABL) patterns, antibiotic prescriptions and surgeries and to relate them to the new classification of periodontitis. Materials and Methods: ABL patterns, prescription of systemic antibiotics and the number of surgeries were retrieved for all patients (n = 353) in the clusters. Comparisons and possible predictors for antibiotics were assessed, and results also evaluated in relation to the new classification. Results: Cluster A is characterized by angular defects often affecting the first molars and localized stage III/IV grade C periodontitis. Cluster B contains mainly localized or generalized stage III/IV, grade C patients. Cluster C contains mainly patients with generalized stage III/IV grade C periodontitis. Patients in cluster A received significantly more antibiotics compared to B and C (78% vs. 23% and 17%); the predictors for antibiotic prescription were young age and localized ABL. No differences in numbers of periodontal surgeries were observed between clusters (A = 1.0 ± 1.4, B = 1.3 ± 1.4 and C = 1.3 ± 1.5). Conclusions: Within stage III/IV grade C periodontitis, we could detect three clusters of patients. The distinct localized ABL pattern and younger age in cluster A presumably prompted clinicians to prescribe antibiotics

At least three phenotypes exist among periodontitis patients

Aim:To identify phenotypes of periodontitis patients by the use of an unsupervised modelling technique (clustering), based on pre-treatment radiographic and microbiological characteristics. Materials and methods: This retrospective study included data from 392 untreated periodontitis patients. Co-regularized spectral clustering algorithm was used to cluster the patients. The resulting clusters were subsequently characterized based on their demographics, radiographic bone loss patterns and microbial data. Results: The vast majority of patients fitted into one of the three main clusters (accuracy 90%). Cluster A (n = 18) was characterized by high prevalence and high proportions of Aggregatibacter actinomycetemcomitans, a trend for a more localized pattern of alveolar bone loss and young individuals. Clusters B (n = 200) and C (n = 135) differed clearly in disease severity patterns and smoking habits, but not in microbiological characteristics. Conclusion: On the basis of alveolar bone loss patterns and microbiological data, untreated periodontitis patients can be clustered into at least three phenotypes. These results should be validated in other cohorts, and the clinical utility needs to be explored on the basis of periodontal treatment outcomes and/or disease progression