This Article Full Text Full Text (PDF) Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Similar articles in PubMed Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Chuang, S.K. Articles by Dodson, T.B. Search for Related Content PubMed PubMed Citation Articles by Chuang, S.K. Articles by Dodson, T.B. Social Bookmarking                         What's this?

Frailty Approach for the Analysis of Clustered Failure Time Observations in Dental Research

¹ Department of Oral and Maxillofacial Surgery, Massachusetts General Hospital and Harvard School of Dental Medicine, 55 Fruit Street, Warren 1201, Boston, MA 02114, USA, and Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA;
^2,4 Department of Biostatistics, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA;
³ Department of Oral Health Policy and Epidemiology, Harvard School of Dental Medicine, 188 Longwood Ave., Boston, MA;
⁵ Department of Oral and Maxillofacial Surgery, Harvard School of Dental Medicine, and Massachusetts General Hospital, 55 Fruit Street, Warren 1201, Boston, MA;

Correspondence: ^* corresponding author, schuang{at}hsph.harvard.edu, PO Box 67376, Chestnut Hill Station, Chestnut Hill, MA 02467, USA

Because dental implant failure patterns tend to cluster within subjects, we hypothesized that the risk of implant failure varies among subjects. To address this hypothesis in the setting of clustered, correlated observations, we considered a retrospective cohort study where we identified a cohort having at least one implant placed. The cohort was composed of 677 patients who had 2349 implants placed. To test the hypothesis, we applied an innovative analytic method, i.e., the Cox proportional hazards model with frailty, to account for correlation within subjects and the heterogeneity of risk, i.e., frailty, among subjects for implant failure. Consistent with our hypothesis, risk for implant failure among subjects varied to a statistically significantly degree (p = 0.041). In addition, the risk for implant failure is significantly associated with several factors, including tobacco use, implant length, immediate implant placement, staging, well size, and proximity of adjacent implants or teeth.

Key Words: survival analysis • dental implants • risk factors • follow-up study • Cox regression analysis • clustered survival data • frailty approach • gamma distribution

Journal of Dental Research, Vol. 84, No. 1, 54-58 (2005)
DOI: 10.1177/154405910508400109


CiteULike    Complore    Connotea    Del.icio.us    Digg    Reddit    Technorati    Twitter    What's this?