Modelling time-varying risk factors of tooth loss: Results from joint model compared with extended Cox regression model.
J Clin Periodontol
; 51(2): 110-117, 2024 02.
Article
en En
| MEDLINE
| ID: mdl-37846605
ABSTRACT
AIM:
To illustrate the use of joint models (JMs) for longitudinal and survival data in estimating risk factors of tooth loss as a function of time-varying endogenous periodontal biomarkers (probing pocket depth [PPD], alveolar bone loss [ABL] and mobility [MOB]). MATERIALS ANDMETHODS:
We used data from the Veterans Affairs Dental Longitudinal Study, a longitudinal cohort study of over 30 years of follow-up. We compared the results from the JM with those from the extended Cox regression model which assumes that the time-varying covariates are exogenous.RESULTS:
Our results showed that PPD is an important risk factor of tooth loss, but each model produced different estimates of the hazard. In the tooth-level analysis, based on the JM, the hazard of tooth loss increased by 4.57 (95% confidence interval [CI] 2.13-8.50) times for a 1-mm increase in maximum PPD, whereas based on the extended Cox model, the hazard of tooth loss increased by 1.60 (95% CI 1.37-1.87) times.CONCLUSIONS:
JMs can incorporate time-varying periodontal biomarkers to estimate the hazard of tooth loss. As JMs are not commonly used in oral health research, we provide a comprehensive set of R codes and an example dataset to implement the method.Palabras clave
Texto completo:
1
Banco de datos:
MEDLINE
Asunto principal:
Pérdida de Hueso Alveolar
/
Pérdida de Diente
Límite:
Humans
Idioma:
En
Año:
2024
Tipo del documento:
Article