Association, prediction, generalizability: Cross-center validity of predicting tooth loss in periodontitis patients

F Schwendicke; L T Arsiwala; J Krois; A Bäumer; B Pretzl; P Eickholz; H Petsos; T Kocher; B Holtfreter; C Graetz

doi:10.1016/j.jdent.2021.103662

Association, prediction, generalizability: Cross-center validity of predicting tooth loss in periodontitis patients

J Dent. 2021 Jun:109:103662. doi: 10.1016/j.jdent.2021.103662. Epub 2021 Apr 12.

Authors

F Schwendicke¹, L T Arsiwala², J Krois², A Bäumer³, B Pretzl⁴, P Eickholz⁵, H Petsos⁵, T Kocher⁶, B Holtfreter⁶, C Graetz⁷

Affiliations

¹ Department of Oral Diagnostics, Digital Health and Health Services Research, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany. Electronic address: falk.schwendicke@charite.de.
² Department of Oral Diagnostics, Digital Health and Health Services Research, Charité- Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Germany.
³ Section of Periodontology, Department of Conservative Dentistry, Clinic for Oral, Dental and Maxillofacial Diseases, University Hospital Heidelberg, Heidelberg, Germany; Private Practice, Bielefeld, Germany.
⁴ Section of Periodontology, Department of Conservative Dentistry, Clinic for Oral, Dental and Maxillofacial Diseases, University Hospital Heidelberg, Heidelberg, Germany.
⁵ Department of Periodontology, Center of Dentistry and Oral Medicine (Carolinum), Johann Wolfgang Goethe-University Frankfurt/Main, Frankfurt/Main, Germany.
⁶ Department of Restorative Dentistry, Periodontology, Endodontology, and Preventive and Pediatric Dentistry, University Medicine Greifswald, Greifswald, Germany.
⁷ Clinic of Conservative Dentistry and Periodontology, University of Kiel, Kiel, Germany.

PMID: 33857544
DOI: 10.1016/j.jdent.2021.103662

Abstract

Objectives: To predict patients' tooth loss during supportive periodontal therapy across four German university centers.

Methods: Tooth loss in 897 patients in four centers (Kiel (KI) n = 391; Greifswald (GW) n = 282; Heidelberg (HD) n = 175; Frankfurt/Main (F) n = 49) during supportive periodontal therapy (SPT) was assessed. Our outcome was annualized tooth loss per patient. Multivariable linear regression models were built on data of 75 % of patients from one center and used for predictions on the remaining 25 % of this center and 100 % of data from the other three centers. The prediction error was assessed as root-mean-squared-error (RMSE), i.e., the deviation of predicted from actually lost teeth per patient and year.

Results: Annualized tooth loss/patient differed significantly between centers (between median 0.00 (interquartile interval: 0.00, 0.17) in GW and 0.09 (0.00, 0.19) in F, p = 0.001). Age, smoking status and number of teeth before SPT were significantly associated with tooth loss (p < 0.03). Prediction within centers showed RMSE of 0.14-0.30, and cross-center RMSE was 0.15-0.31. Predictions were more accurate in F and KI than in HD and GW, while the center on which the model was trained had a less consistent impact. No model showed useful predictive values.

Conclusion: While covariates were significantly associated with tooth loss in linear regression models, a clinically useful prediction was not possible with any of the models and generalizability was not given. Predictions were more accurate for certain centers.

Clinical relevance: Association should not be confused with predictive value: Despite significant associations of covariates with tooth loss, none of our models was useful for prediction. Usually, model accuracy was even lower when tested across centers, indicating low generalizability.

Keywords: Accuracy; Modelling; Periodontitis; Supportive periodontal therapy; Tooth loss.

MeSH terms

Humans
Periodontitis*
Retrospective Studies
Smoking
Tooth Loss*
Treatment Outcome