Prediction of Failure of Dental Implants

Sponsor
Academic Centre for Dentistry in Amsterdam (Other)
Overall Status
Completed
CT.gov ID
NCT04129957
Collaborator
(none)
337
1
8.1
41.4

Study Details

Study Description

Brief 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.

Condition or Disease Intervention/Treatment Phase
  • Procedure: Placement of dental implants

Detailed 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.

Study Design

Study Type:
Observational
Actual Enrollment :
337 participants
Observational Model:
Cohort
Time Perspective:
Retrospective
Official Title:
The Prediction of Failure Rate of Dental Implants
Actual Study Start Date :
Dec 10, 2018
Actual Primary Completion Date :
Jun 30, 2019
Actual Study Completion Date :
Aug 15, 2019

Arms and Interventions

Arm Intervention/Treatment
Patients who underwent placement of dental implants

The study only includes one cohort. That is the patients who underwent placement of dental implants at baseline.

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.
Other Names:
  • No other intervention
  • Outcome Measures

    Primary Outcome Measures

    1. Failure of dental implants [up to 5 years follow-up]

      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.

    2. Follow-up time [up to 5 years 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.

    Eligibility Criteria

    Criteria

    Ages Eligible for Study:
    18 Years and Older
    Sexes Eligible for Study:
    All
    Accepts Healthy Volunteers:
    No
    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.

    Contacts and Locations

    Locations

    Site City State Country Postal Code
    1 Academic Centre for Dentistry in Amsterdam Amsterdam Noord-Holland Netherlands 1081LA

    Sponsors and Collaborators

    • Academic Centre for Dentistry in Amsterdam

    Investigators

    • Study Chair: Geert van der Heijden, Prof. dr., Academic Centre for Dentistry Amsterdam

    Study Documents (Full-Text)

    More Information

    Publications

    Responsible Party:
    Naichuan Su, Principal Investigator, Academic Centre for Dentistry in Amsterdam
    ClinicalTrials.gov Identifier:
    NCT04129957
    Other Study ID Numbers:
    • 2018.376
    First Posted:
    Oct 17, 2019
    Last Update Posted:
    Oct 21, 2019
    Last Verified:
    Oct 1, 2019
    Individual Participant Data (IPD) Sharing Statement:
    Yes
    Plan to Share IPD:
    Yes
    Studies a U.S. FDA-regulated Drug Product:
    No
    Studies a U.S. FDA-regulated Device Product:
    No
    Keywords provided by Naichuan Su, Principal Investigator, Academic Centre for Dentistry in Amsterdam
    Additional relevant MeSH terms:

    Study Results

    No Results Posted as of Oct 21, 2019