James D Beck1,2, Kevin L Moss2, Thiago Morelli2,3, Steven Offenbacher2,3. 1. Department of Dental Ecology, School of Dentistry, University of North Carolina at Chapel Hill, Chapel Hill, NC. 2. Center for Oral and Systemic Diseases, School of Dentistry, University of North Carolina at Chapel Hill. 3. Department of Periodontology, School of Dentistry, University of North Carolina at Chapel Hill.
Abstract
BACKGROUND: This paper focuses on Periodontal Profile Class (PPC), a component of the Periodontal Profile Phenotype (P3 ) System that may be more representative of the periodontitis phenotype than current case definitions of periodontitis. Data illustrate the unique aspects of the PPC compared with other commonly used periodontal classification indices. METHODS: Latent Class Analysis (LCA) identified discrete classes of individuals grouped by tooth-level clinical parameters. The analysis defined seven distinct periodontal profile classes (PPC A through G) and seven distinct tooth profile classes (TPC A through G). This LCA classification was an entirely data-derived agnostic process without any preconceived presumptions of what constituted disease. RESULTS: Comparing the PPC with the Centers for Disease Control/American Academy of Periodontology (CDC/AAP) and European indices, the PPC is unique in that it contains four disease classes not traditionally used. Less than half of individuals classified as Healthy by both the CDC/AAP and European indices were Healthy using the PPC. About 25% of those classified as Severe by CDC/AAP and European indices were PPC-Severe. The remainder spread out over the High Gingival Index, Posterior Disease, Tooth Loss, and Severe Tooth Loss phenotypes. CONCLUSIONS: The PPC classification provides a significant departure from the traditional clinical case status indices that have been used, but has resulted in clinical phenotypes that are quite familiar to most clinicians who take notice of the distribution of missing teeth, areas of recession, diminished periodontal support, and other aspects of the dentition while conducting a periodontal examination. The mutually exclusive categories provided by the PPC system provide periodontal clinical summaries that can be an important component of precision dentistry.
BACKGROUND: This paper focuses on Periodontal Profile Class (PPC), a component of the Periodontal Profile Phenotype (P3 ) System that may be more representative of the periodontitis phenotype than current case definitions of periodontitis. Data illustrate the unique aspects of the PPC compared with other commonly used periodontal classification indices. METHODS: Latent Class Analysis (LCA) identified discrete classes of individuals grouped by tooth-level clinical parameters. The analysis defined seven distinct periodontal profile classes (PPC A through G) and seven distinct tooth profile classes (TPC A through G). This LCA classification was an entirely data-derived agnostic process without any preconceived presumptions of what constituted disease. RESULTS: Comparing the PPC with the Centers for Disease Control/American Academy of Periodontology (CDC/AAP) and European indices, the PPC is unique in that it contains four disease classes not traditionally used. Less than half of individuals classified as Healthy by both the CDC/AAP and European indices were Healthy using the PPC. About 25% of those classified as Severe by CDC/AAP and European indices were PPC-Severe. The remainder spread out over the High Gingival Index, Posterior Disease, Tooth Loss, and Severe Tooth Loss phenotypes. CONCLUSIONS: The PPC classification provides a significant departure from the traditional clinical case status indices that have been used, but has resulted in clinical phenotypes that are quite familiar to most clinicians who take notice of the distribution of missing teeth, areas of recession, diminished periodontal support, and other aspects of the dentition while conducting a periodontal examination. The mutually exclusive categories provided by the PPC system provide periodontal clinical summaries that can be an important component of precision dentistry.
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Authors: Ryan T Demmer; Faye L Norby; Kamakshi Lakshminarayan; Keenan A Walker; James S Pankow; Aaron R Folsom; Thomas Mosley; Jim Beck; Pamela L Lutsey Journal: Neurology Date: 2020-07-29 Impact factor: 9.910
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Authors: Julie T Marchesan; Mustafa Saadat Girnary; Kevin Moss; Eugenia Timofeev Monaghan; Grant Joseph Egnatz; Yizu Jiao; Shaoping Zhang; Jim Beck; Karen V Swanson Journal: Periodontol 2000 Date: 2020-02 Impact factor: 7.589