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A competing risk model for bond strength data analysis.

Antonin Tichy1, Marek Brabec2, Pavel Bradna3

  • 1Institute of Dental Medicine, First Faculty of Medicine of the Charles University and General University Hospital in Prague, Karlovo Namesti 32, Prague, 121 11, Czech Republic; Department of Cariology and Operative Dentistry, Graduate School of Medical and Dental Sciences, Tokyo Medical and Dental University, 1-5-45 Yushima, Bunkyo-ku, Tokyo 113-8510, Japan.

Dental Materials : Official Publication of the Academy of Dental Materials
|September 19, 2020
PubMed
Summary
This summary is machine-generated.

A competing risk (CR) model accurately estimates dental adhesive bond strength by distinguishing failure modes. This method avoids underestimation, especially when adhesive failures are infrequent, offering more reliable data analysis.

Keywords:
AdhesionCompeting risksFailure modeMicrotensile bond strengthWeibull analysis

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Area of Science:

  • Dental Materials Science
  • Biomaterials Engineering
  • Statistical Modeling in Dentistry

Background:

  • Micro-tensile bond strength (μTBS) testing is crucial for evaluating dental adhesives.
  • Conventional survival models often overlook distinct failure modes (adhesive, cohesive, mixed), potentially skewing results.
  • Accurate bond strength assessment is vital for predicting clinical longevity of dental restorations.

Purpose of the Study:

  • To compare a competing risk (CR) model with a conventional survival model for analyzing μTBS data.
  • To investigate the impact of distinguishing failure modes on bond strength estimations.
  • To assess the reliability of CR model parameters as indicators of internal validity.

Main Methods:

  • Fifty human molars were subjected to μTBS testing using five universal adhesives under varying aging conditions.
  • Fractographic analysis via scanning electron microscopy classified failure modes.
  • Weibull CR and conventional Weibull models were employed for survival analysis of μTBS data.

Main Results:

  • Competing risk model estimates for adhesive failures (scale and 10% probability strength) were higher than conventional model estimates, particularly with fewer adhesive failures.
  • CR model strength estimates for cohesive failures remained consistent across groups, irrespective of bond strength or failure distribution.
  • Conventional models may underestimate bond strength, especially when adhesive failures are less prevalent.

Conclusions:

  • Analyzing μTBS data with a competing risk model provides more accurate bond strength estimations than conventional methods.
  • Failure mode distinction is critical to prevent underestimation of bond strength, particularly in specific failure scenarios.
  • Cohesive failure strength estimates from the CR model can serve as a valuable internal validity check for the model's performance.