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Clinical Trial Details — Status: Completed

Administrative data

NCT number NCT04129957
Other study ID # 2018.376
Secondary ID
Status Completed
Phase
First received
Last updated
Start date December 10, 2018
Est. completion date August 15, 2019

Study information

Verified date October 2019
Source Academic Centre for Dentistry in Amsterdam
Contact n/a
Is FDA regulated No
Health authority
Study type Observational

Clinical Trial Summary

The aim of the study is to identify predictors in patient profiles and implant characteristics and to develop and calibrate a prediction model for failure of implants. Patients` demographic characteristics, lifestyle habits, general health, dental health, and implant characteristics were regarded as potential predictors. The failure of implants and the follow-up time in days of implants were considered the outcome. Multivariate Cox proportional hazards regression analysis is used to find out the important risk factors for failure of dental implants and to develop the model for prediction of failure of dental implants at follow-up. The performance and clinical values of the model is determined.


Description:

During the past decades, dental implant therapy has developed into a successful treatment option for patients confronted with both partial and complete edentulism. Based on the literature, the survival rate of dental implants, which is defined that the dental implants are still in the mouth after insertion, is around 95% in the 5-year follow-up and around 90% in the 10-year follow-up. The success rate of dental implants, which is defined as dental implants in function, with good hard and soft tissue physiology and user satisfaction ranges from 85.2% to 88.7% in the follow-up of up to 20 years. This indicates that both the success rate and survival rate of dental implants is high. However, both survival rates and success rates vary across patients with different profiles. The expense of dental implant treatment is high and implant placement is a surgical procedure which is invasive and thus risky for the patients' health. Once the failure of dental implants occurs, it may cause some severe negative consequences for patients. For example, the failure will cause a financial loss for patients and a possible shock concerning both mental and physical aspects. To reduce these risks it is important and necessary for clinicians to be able to predict the risk of the failure of dental implants of individual patients before they undergo dental implant treatment.

Aim:

The aim of the project is to find out the possible risk factors for failure of dental implants and to develop a prediction model for the failure of dental implants at follow-up as a tool for clinicians to establish patients individual risk profile.

Methods:

The study is a retrospective design. The clinical data of the adult patients who were referred to the Department of Oral Implantology and Prosthetic Dentistry, Academic Centre for Dentistry Amsterdam (ACTA) for placement of dental implants from September 2009 to September 2013 are collected retrospectively from the clinical data management system of ACTA in the study.

The potential predictors include five domains: patients` demographic characteristics, lifestyle habits, general health, dental health, and implant characteristics. These predictors are pre-screened by international experts in dental implantology based their clinical knowledge and experience.

The outcomes included the follow-up time of implants and whether the failure of the implants was observed at the follow-up. The follow-up time is defined as the difference in time between implant placement and implant failure, or the date of the last follow-up time point if the dental implant is in an acceptable state. The failure of implants is defined as the presence of peri-implantitis, presence of mobility of implants, or removal of the implants for any reasons, for instance, unacceptable performance in aspects of function, tissue physiology, esthetics, and patients' satisfaction after placement of suprastructure.

The Multivariate Cox proportional hazards regression analysis will be used to find out the important risk factors and to develop the model. The performance of the model, in aspects of calibration and discrimination, is assessed. The clinical added values of the model is assessed. Then, the model is transformed into a score chart and a line chart, which is easy-to-use to the clinicians for the prediction.


Recruitment information / eligibility

Status Completed
Enrollment 337
Est. completion date August 15, 2019
Est. primary completion date June 30, 2019
Accepts healthy volunteers No
Gender All
Age group 18 Years and older
Eligibility Inclusion Criteria:

- patients were over 18 years old at baseline;

- patients underwent the placement of at least one implant;

- patients were followed up for the implants at least one time after placement of implants;

- patients provided their informed consent.

Exclusion Criteria:

- patients were <18 years old at baseline;

- patients were not followed up;

- patients did not provide the informed consent.

Study Design


Related Conditions & MeSH terms


Intervention

Procedure:
Placement of dental implants
All the included patients underwent the placement of at least one implant in either upper jaw, or lower jaw, or both.

Locations

Country Name City State
Netherlands Academic Centre for Dentistry in Amsterdam Amsterdam Noord-Holland

Sponsors (1)

Lead Sponsor Collaborator
Academic Centre for Dentistry in Amsterdam

Country where clinical trial is conducted

Netherlands, 

References & Publications (6)

Jung RE, Zembic A, Pjetursson BE, Zwahlen M, Thoma DS. Systematic review of the survival rate and the incidence of biological, technical, and aesthetic complications of single crowns on implants reported in longitudinal studies with a mean follow-up of 5 years. Clin Oral Implants Res. 2012 Oct;23 Suppl 6:2-21. doi: 10.1111/j.1600-0501.2012.02547.x. Review. — View Citation

Krebs M, Schmenger K, Neumann K, Weigl P, Moser W, Nentwig GH. Long-term evaluation of ANKYLOS® dental implants, part i: 20-year life table analysis of a longitudinal study of more than 12,500 implants. Clin Implant Dent Relat Res. 2015 Jan;17 Suppl 1:e275-86. doi: 10.1111/cid.12154. Epub 2013 Sep 17. — View Citation

Lekholm U, Gröndahl K, Jemt T. Outcome of oral implant treatment in partially edentulous jaws followed 20 years in clinical function. Clin Implant Dent Relat Res. 2006;8(4):178-86. — View Citation

Östman PO, Hellman M, Sennerby L. Ten years later. Results from a prospective single-centre clinical study on 121 oxidized (TiUniteā„¢) Brånemark implants in 46 patients. Clin Implant Dent Relat Res. 2012 Dec;14(6):852-60. doi: 10.1111/j.1708-8208.2012.00453.x. Epub 2012 May 29. — View Citation

Pjetursson BE, Asgeirsson AG, Zwahlen M, Sailer I. Improvements in implant dentistry over the last decade: comparison of survival and complication rates in older and newer publications. Int J Oral Maxillofac Implants. 2014;29 Suppl:308-24. doi: 10.11607/jomi.2014suppl.g5.2. Review. — View Citation

Pjetursson BE, Thoma D, Jung R, Zwahlen M, Zembic A. A systematic review of the survival and complication rates of implant-supported fixed dental prostheses (FDPs) after a mean observation period of at least 5 years. Clin Oral Implants Res. 2012 Oct;23 Suppl 6:22-38. doi: 10.1111/j.1600-0501.2012.02546.x. Review. — View Citation

Outcome

Type Measure Description Time frame Safety issue
Primary Failure of dental implants The failure of implants was defined as the presence of peri-implantitis, presence of mobility of implants, or removal of the implants for any reasons, for instance, unacceptable performance in aspects of function, tissue physiology, esthetics, and patients' satisfaction after placement of suprastructure. up to 5 years follow-up
Primary Follow-up time The follow-up time is defined as the difference in time between implant placement and implant failure, or the date of the last follow-up time point if the dental implant is in an acceptable state. up to 5 years follow-up
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