Assessing the surveillance use of 2018 EFP/AAP classification of periodontitis: A validation study and clustering analysis

聚类分析 牙周炎 一致性 医学 逻辑回归 牙周病学 人口 接收机工作特性 人工智能 牙科 内科学 计算机科学 环境卫生
作者
Mi Du,Yuanqiu Mo,An Li,Shaohua Ge,Marco Aurélio Peres
出处
期刊:Journal of Periodontology [Wiley]
卷期号:94 (10): 1254-1265 被引量:15
标识
DOI:10.1002/jper.23-0088
摘要

Abstract Background The performance of the 2018 European Federation of Periodontology/American Academy of Periodontology (EFP/AAP) classification of periodontitis for epidemiology surveillance purposes remains to be investigated. This study assessed the surveillance use of the 2018 EFP/AAP classification and its agreement with the unsupervised clustering method compared with the 2012 Centers for Disease Control and Prevention(CDC)/AAP case definition. Methods Participants ( n = 9424) in the National Health and Nutrition Examination Survey (NHANES) were staged by the 2018 EFP/AAP classification and classified into subgroups via k‐medoids clustering. Concordance levels between periodontitis definitions and the clustering method were evaluated through the multiclass area under the receiver operating characteristic curve (multiclass AUC) among “periodontitis cases” and the general population, respectively. The multiclass AUC of the 2012 CDC/AAP definition versus clustering was used as a reference. The associations of periodontitis with chronic diseases were estimated using multivariable logistic regression. Results All the participants were identified as “periodontitis cases” by the 2018 EFP/AAP classification, and the prevalence of stage III–IV was 30%. The optimal numbers of clusters were three and four. The 2012 CDC/AAP definition versus clustering yielded a multiclass AUC of 0.82 and 0.85 among the general population and “periodontitis cases,” respectively. The multiclass AUC of the 2018 EFP/AAP classification versus clustering was 0.77 and 0.78 for different target populations. Similar patterns prevailed in associations with chronic diseases between the 2018 EFP/AAP classification and clustering. Conclusions The validity of the 2018 EFP/AAP classification was verified by the unsupervised clustering method, which performed better in distinguishing “periodontitis cases” than classifying the general population. For surveillance purposes, the 2012 CDC/AAP definition showed a higher agreement level with the clustering method than the 2018 EFP/AAP classification.
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