Literature DB >> 17122171

Predicting clustered dental implant survival using frailty methods.

S-K Chuang1, T Cai.   

Abstract

The purpose of this study was to predict future implant survival using information on risk factors and on the survival status of an individual's existing implant(s). We considered a retrospective cohort study with 677 individuals having 2349 implants placed. We proposed to predict the survival probabilities using the Cox proportional hazards frailty model, with three important risk factors: smoking status, timing of placement, and implant staging. For a non-smoking individual with 2 implants placed, an immediate implant and in one stage, the marginal probability that 1 implant would survive 12 months was 85.8% (95%CI: 77%, 91.7%), and the predicted joint probability of surviving for 12 months was 75.1% (95%CI: 62.1%, 84.7%). If 1 implant was placed earlier and had survived for 12 months, then the second implant had an 87.5% (95%CI: 80.3%, 92.4%) chance of surviving 12 months. Such conditional and joint predictions can assist in clinical decision-making for individuals.

Mesh:

Substances:

Year:  2006        PMID: 17122171      PMCID: PMC2443684          DOI: 10.1177/154405910608501216

Source DB:  PubMed          Journal:  J Dent Res        ISSN: 0022-0345            Impact factor:   6.116


  20 in total

1.  Immediate postextraction implant placement with root-analog stepped implants: surgical procedure and statistical outcome after 6 years.

Authors:  G Gomez-Roman; M Kruppenbacher; H Weber; W Schulte
Journal:  Int J Oral Maxillofac Implants       Date:  2001 Jul-Aug       Impact factor: 2.804

2.  Predicting dental implant survival by use of the marginal approach of the semi-parametric survival methods for clustered observations.

Authors:  S K Chuang; L Tian; L J Wei; T B Dodson
Journal:  J Dent Res       Date:  2002-12       Impact factor: 6.116

3.  Risk factors affecting dental implant survival.

Authors:  Valerie A Vehemente; Sung-Kiang Chuang; Shadi Daher; Ali Muftu; Thomas B Dodson
Journal:  J Oral Implantol       Date:  2002       Impact factor: 1.779

4.  Risk factors for dental implant failure: a strategy for the analysis of clustered failure-time observations.

Authors:  S K Chuang; L J Wei; C W Douglass; T B Dodson
Journal:  J Dent Res       Date:  2002-08       Impact factor: 6.116

5.  Semiparametric estimation of random effects using the Cox model based on the EM algorithm.

Authors:  J P Klein
Journal:  Biometrics       Date:  1992-09       Impact factor: 2.571

6.  Bootstrap analysis of multivariate failure time data.

Authors:  Jane Monaco; Jianwen Cai; James Grizzle
Journal:  Stat Med       Date:  2005-11-30       Impact factor: 2.373

7.  A prospective multicenter clinical study of the Osseotite implant: four-year interim report.

Authors:  T Testori; L Wiseman; S Woolfe; S S Porter
Journal:  Int J Oral Maxillofac Implants       Date:  2001 Mar-Apr       Impact factor: 2.804

8.  Survival of the Brånemark implant in partially edentulous jaws: a 10-year prospective multicenter study.

Authors:  U Lekholm; J Gunne; P Henry; K Higuchi; U Lindén; C Bergström; D van Steenberghe
Journal:  Int J Oral Maxillofac Implants       Date:  1999 Sep-Oct       Impact factor: 2.804

9.  Cox regression analysis of multivariate failure time data: the marginal approach.

Authors:  D Y Lin
Journal:  Stat Med       Date:  1994-11-15       Impact factor: 2.373

10.  Five-year prospective follow-up report of the Astra tech standard dental implant in clinical treatment.

Authors:  G Weibrich; R S Buch; J Wegener; W Wagner
Journal:  Int J Oral Maxillofac Implants       Date:  2001 Jul-Aug       Impact factor: 2.804

View more
  2 in total

1.  Physicochemical Characterization and In Vivo Evaluation of Amorphous and Partially Crystalline Calcium Phosphate Coatings Fabricated on Ti-6Al-4V Implants by the Plasma Spray Method.

Authors:  Estevam A Bonfante; Lukasz Witek; Nick Tovar; Marcelo Suzuki; Charles Marin; Rodrigo Granato; Paulo G Coelho
Journal:  Int J Biomater       Date:  2012-08-27

2.  Nanometer scale titanium surface texturing are detected by signaling pathways involving transient FAK and Src activations.

Authors:  Willian F Zambuzzi; Estevam A Bonfante; Ryo Jimbo; Mariko Hayashi; Martin Andersson; Gutemberg Alves; Esther R Takamori; Paulo J Beltrão; Paulo G Coelho; José M Granjeiro
Journal:  PLoS One       Date:  2014-07-07       Impact factor: 3.240

  2 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.