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

PLoS ONE ◽  
2021 ◽  
Vol 16 (1) ◽  
pp. e0245111
Author(s):  
Adeniyi Francis Fagbamigbe ◽  
Karolina Karlsson ◽  
Jan Derks ◽  
Max Petzold
Keyword(s):  
Survival Data ◽  
Regression Models ◽  
Dental Restorations ◽  
Implant Complications ◽  
Flexible Parametric Model ◽  
Parametric Survival Model ◽  
Parametric Survival ◽  
Single Crowns ◽  
Swedish Cohort ◽  
Survival Regression

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<0.001) and 2 times (aHR = 2.338; 95% CI: 1.553–3.519, p<0.001) higher among patients with full- and partial-jaw restorations than those with single crowns. Flexible parametric survival model with frailty are the most suitable for modelling implant complications among the studied patients.

scholarly journals A bivariate power generalized Weibull distribution: A flexible parametric model for survival analysis

2019 ◽  
Vol 29 (8) ◽  
pp. 2295-2306 ◽  
Author(s):  
MC Jones ◽  
Angela Noufaily ◽  
Kevin Burke
Keyword(s):  
Survival Analysis ◽  
Weibull Distribution ◽  
Survival Data ◽  
Frailty Model ◽  
Weibull Model ◽  
Flexible Parametric Model ◽  
Shared Frailty Model ◽  
Shared Frailty ◽  
Power Variance ◽  
Parametric Survival

We are concerned with the flexible parametric analysis of bivariate survival data. Elsewhere, we argued in favour of an adapted form of the ‘power generalized Weibull’ distribution as an attractive vehicle for univariate parametric survival analysis. Here, we additionally observe a frailty relationship between a power generalized Weibull distribution with one value of the parameter which controls distributional choice within the family and a power generalized Weibull distribution with a smaller value of that parameter. We exploit this relationship to propose a bivariate shared frailty model with power generalized Weibull marginal distributions linked by the BB9 or ‘power variance function’ copula, then change it to have adapted power generalized Weibull marginals in the obvious way. The particular choice of copula is, therefore, natural in the current context, and the corresponding bivariate adapted power generalized Weibull model a novel combination of pre-existing components. We provide a number of theoretical properties of the models. We also show the potential of the bivariate adapted power generalized Weibull model for practical work via an illustrative example involving a well-known retinopathy dataset, for which the analysis proves to be straightforward to implement and informative in its outcomes.

scholarly journals Factors Determining Birth Intervals: A Multilevel Mixed Effect Parametric Survival Approach

2021 ◽  
Vol 28 (2) ◽  
pp. 29-35
Author(s):  
O.I. Adeniyi ◽  
I.R. Olonijolu ◽  
A.A. Akinrefon
Keyword(s):  
Economic Status ◽  
Random Effect ◽  
Survival Models ◽  
Age At First Birth ◽  
Birth Intervals ◽  
Mixed Effect ◽  
Flexible Parametric Model ◽  
Parametric Survival Model ◽  
Effect Parameter ◽  
Parametric Survival

Interval between births plays an important role in maternal health as well as child health. This study applies the methodology of Flexible parametric survival models to data on successive births among Nigeria women using the dataset from 2018 National Demographic Health survey. The flexible parametric survival model with Weibull baseline distribution was found to be the best among other fitted baseline distributions. The factors, zone of residence, educational qualification, religion, economic status and age at first birth were found to be significant in predicting the birth intervals. It was found that random effect parameter indicates that the interval between successive births is similar from the same woman. Keywords: Birth intervals, Baseline hazard, Mixed effect, Flexible parametric model, AIC. 

scholarly journals Different approaches to quantify years of life lost from COVID-19

2021 ◽  
Author(s):  
Tamás Ferenci
Keyword(s):  
Years Of Life Lost ◽  
Expected Number ◽  
Long Term Conditions ◽  
Developed Country ◽  
Individual Patient Level ◽  
Level Data ◽  
Parametric Survival Model ◽  
Epidemiologic Risk ◽  
Parametric Survival

AbstractThe burden of an epidemic is often characterized by death counts, but this can be misleading as it fails to acknowledge the age of the deceased patients. Years of life lost is therefore widely used as a more relevant metric, however, such calculations in the context of COVID-19 are all biased upwards: patients dying from COVID-19 are typically multimorbid, having far worse life expectation than the general population. These questions are quantitatively investigated using a unique Hungarian dataset that contains individual patient level data on comorbidities for all COVID-19 deaths in the country. To account for the comorbidities of the patients, a parametric survival model using 11 important long-term conditions was used to estimate a more realistic years of life lost. As of 12 May, 2021, Hungary reported a total of 27,837 deaths from COVID-19 in patients above 50 years of age. The usual calculation indicates 10.5 years of life lost for each death, which decreases to 9.2 years per death after adjusting for 11 comorbidities. The expected number of years lost implied by the life table, reflecting the mortality of a developed country just before the pandemic is 11.1 years. The years of life lost due to COVID-19 in Hungary is therefore 12% or 1.3 years per death lower when accounting for the comorbidities and is below its expected value, but how this should be interpreted is still a matter of debate. Further research is warranted on how to optimally integrate this information into epidemiologic risk assessments during a pandemic.

Sustainability Time and Its Determinant Factors of Small and Medium-scale Enterprises in East Gojjam Zone: Parametric Survival Regression Model

2021 ◽  
pp. 097215092098865
Author(s):  
Amare Wubishet Ayele ◽  
Abebaw Bizuayehu Derseh
Keyword(s):  
Regression Model ◽  
Marketing Channel ◽  
Educational Status ◽  
Weibull Regression ◽  
Service Sectors ◽  
Weibull Regression Model ◽  
Parametric Survival ◽  
Prospective Study Design ◽  
Significant Factors ◽  
Survival Regression

The contributions of small and medium-sized enterprises (SMEs) to socio-economic development are generally recognized, but they have faced several obstacles that impede their sustainability. This manuscript seeks to identify factors for the survival of SMEs in the East Gojjam Zone, Ethiopia. The prospective study design was employed. Both descriptive and inferential statistics, particularly families of parametric survival regression models, have been used. Of the 650 enterprises included in this study, 330 (50.8%) were censored (sustained enterprises) and the remaining 320 (49.2%) were events or withdrawn enterprises. The findings of this study revealed that the incidence of termination or withdrawal of SMEs in the study area is relatively common. The results from multivariable Weibull regression model revealed that woreda, sector, manger profile (gender, age, educational status, experience (in year) and source of experience), working place, marketing channel and profitability district status of enterprise were found to be statistically significant factors for the sustainability of enterprises in the study area. The bodies concerned, in particular the enterprise administrative offices at various levels, should work with collaborative organizations to develop a strong marketing platform (network), should be able to make workplaces accessible with the required infrastructure at minimal rental costs, and should prioritize the type of sector that has the highest customer needs at the onset, for instance, agriculture and service sectors.

scholarly journals Dental restoration longevity among geriatric and adult special needs patients

2017 ◽  
Author(s):  
D. J. Caplan ◽  
Y. Li ◽  
W. Wang ◽  
S. Kang ◽  
L. Marchini ◽  
...  
Keyword(s):  
Special Needs ◽  
Regression Models ◽  
Cox Regression ◽  
Dental Treatment ◽  
Treatment Options ◽  
Dental Restoration ◽  
University Of Iowa ◽  
Restorative Treatment ◽  
Dental Restorations ◽  
Iowa College

AbstractThis study aimed to describe the survival trajectory of dental restorations placed in an outpatient population of geriatric and adult special needs patients over a 15-year span, with particular interest in longevity of subsequent restorations in teeth that received multiple restorations over time. Dental restorations of different types and sizes in patients age ≥65 years treated between 2000-14 at the University of Iowa, College of Dentistry were followed until they incurred an event (i.e., restoration replacement, extraction of the tooth, or endodontic treatment of the tooth). Survival analysis and extended Cox regression models were used to generate hazards ratios for selected predictor variables. A total of 9184 restorations were followed in 1551 unique patients. During the follow-up period, 28.7% of these restorations incurred an event; and overall the restorations had a median lifespan of 6.25 years. In multivariable regression models, after controlling for gender and age, composite restorations and greater number of restoration surfaces were associated with higher risks of failure; and the initial restoration recorded in the database for each subject tended to have lower risk of failure than restorations placed later that included any of those same surfaces. This information potentially could be helpful to elderly patients considering various restorative treatment options during the dental treatment planning and informed consent process.

Sign in / Sign up

Export Citation Format

Share Document