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Establishing a Competing Risk Regression Nomogram Model for Survival Data
Published on: October 23, 2020
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Risk Factors for Dental Restoration Survival: A Practice-Based Study
M Laske1, N J M Opdam1, E M Bronkhorst1
11 Department of Dentistry, Radboud Institute for Health Sciences, Radboud University Medical Centre, Nijmegen, the Netherlands.
Journal of Dental Research
|February 21, 2019
Summary
Identifying patient risk factors is crucial for improving dental restoration survival. Factors like age, health, and habits significantly impact restoration longevity, guiding personalized dental care.
Area of Science:
- Dental biomaterials and restorative dentistry
- Clinical epidemiology and public health
Background:
- Direct class II restorations are common dental procedures.
- Identifying factors influencing restoration survival is key to improving patient outcomes and dental care quality.
Purpose of the Study:
- To investigate practice, patient, tooth, and restoration-level risk factors affecting the survival of direct class II restorations.
- To analyze the influence of these factors on restoration longevity and reintervention rates.
Main Methods:
- A practice-based cohort study analyzing 31,472 direct class II restorations from 11 Dutch dental practices.
- Kaplan-Meier survival analysis, calculation of annual failure rates (AFRs), and multivariable Cox regression analysis were employed.
Main Results:
- The mean 2-year annual failure rate (AFR) was 7.8%, with significant variation among operators (3.6%–11.4%).
- Patient factors like elderly age, medical compromise, periodontal issues, high caries risk, parafunctional habits, molar location, endodontic treatment, and multisurface restorations increased failure risk.
- Restorations for fractures failed more than those for caries; socioeconomic status became significant when patient factors were excluded.
Conclusions:
- Restoration survival is influenced by a complex interplay of practice, patient, and tooth-level factors.
- Identifying and recording patient-specific risk factors is essential for personalized dental care and improving restoration success.
- Further research should incorporate these patient risk factors into data collection and analysis.
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