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

Author:

Du Mi1ORCID,Mo Yuanqiu2,Li An3ORCID,Ge Shaohua1ORCID,Peres Marco A.45

Affiliation:

1. Department of Periodontology, School and Hospital of Stomatology, Cheeloo College of Medicine Shandong University & Shandong Key Laboratory of Oral Tissue Regeneration & Shandong Engineering Laboratory for Dental Materials and Oral Tissue Regeneration & Shandong Provincial Clinical Research Center for Oral Diseases Jinan China

2. Department of System Science, School of Mathematics Southeast University Nanjing China

3. Department of Periodontology, Stomatological Hospital, School of Stomatology Southern Medical University Guangzhou China

4. National Dental Research Institute Singapore National Dental Centre Singapore Singapore

5. Oral Health ACP, Health Service and Systems Research Programme Duke‐NUS Medical School Singapore

Abstract

AbstractBackgroundThe 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.MethodsParticipants (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.ResultsAll 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.ConclusionsThe 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.

Funder

Natural Science Foundation of Zhejiang Province

Natural Science Foundation of Shandong Province

National Natural Science Foundation of China

Publisher

Wiley

Subject

Periodontics,General Medicine

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