Performance evaluation of survival regression models in analysing Swedish dental implant complication data with frailty

Adeniyi Francis Fagbamigbe, Karolina Karlsson, Jan Derks and Max Petzold

PLOS ONE, 2021, vol. 16, issue 1, 1-16

Abstract: The use of inappropriate methods for estimating the effects of covariates in survival data with frailty leads to erroneous conclusions in medical research. This study evaluated the performance of 13 survival regression models in assessing the factors associated with the timing of complications in implant-supported dental restorations in a Swedish cohort. Data were obtained from randomly selected cohort (n = 596) of Swedish patients provided with dental restorations supported in 2003. Patients were evaluated over 9 years of implant loss, peri-implantitis or technical complications. Best Model was identified using goodness, AIC and BIC. The loglikelihood, the AIC and BIC were consistently lower in flexible parametric model with frailty (df = 2) than other models. Adjusted hazard of implant complications was 45% (adjusted Hazard Ratio (aHR) = 1.449; 95% Confidence Interval (CI): 1.153–1.821, p = 0.001) higher among patients with periodontitis. While controlling for other variables, the hazard of implant complications was about 5 times (aHR = 4.641; 95% CI: 2.911–7.401, p

Date: 2021
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Persistent link: https://EconPapers.repec.org/RePEc:plo:pone00:0245111

DOI: 10.1371/journal.pone.0245111

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