scholarly journals Variable Selection in Cox Regression Models with Varying Coefficients

2012 ◽  
Author(s):  
Toshio Honda ◽  
Wolfgang K. HHrdle
Keyword(s):  
Variable Selection ◽  
Regression Models ◽  
Cox Regression ◽  
Varying Coefficients

Variable Selection via Generalized SELO-Penalized Cox Regression Models

2019 ◽  
Vol 32 (2) ◽  
pp. 709-736
Author(s):  
Yueyong Shi ◽  
Deyi Xu ◽  
Yongxiu Cao ◽  
Yuling Jiao
Keyword(s):  
Variable Selection ◽  
Regression Models ◽  
Cox Regression

scholarly journals Risk of infective endocarditis among patients with tetralogy of fallot

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
E Havers-Borgersen ◽  
J.H Butt ◽  
M Groening ◽  
M Smerup ◽  
G.H Gislason ◽  
...  
Keyword(s):  
Infective Endocarditis ◽  
Tetralogy Of Fallot ◽  
Valve Replacement ◽  
Pulmonary Valve ◽  
Cox Regression ◽  
Pulmonary Valve Replacement ◽  
Varying Coefficients ◽  
Background Population ◽  
Increased Risk

Abstract Introduction Patients with tetralogy of Fallot (ToF) are considered at high risk of infective endocarditis (IE) as a result of altered hemodynamics and multiple surgical and interventional procedures including pulmonary valve replacement (PVR). The overall survival of patients with ToF has increased in recent years. However, data on the risk of adverse outcomes including IE are sparse. Purpose To investigate the risk of IE in patients with ToF compared with controls from the background population. Methods In this nationwide observational cohort study, all patients with ToF born in 1977–2017 were identified using Danish nationwide registries and followed from date of birth until occurrence of an outcome of interest (i.e. first-time IE), death, or end of study (July 31, 2017). The comparative risk of IE among ToF patients versus age- and sex-matched controls from the background population was assessed. Results A total of 1,156 patients with ToF were identified and matched with 4,624 controls from the background population. Among patients with ToF, 266 (23.0%) underwent PVR during follow-up. During a median follow-up time of 20.4 years, 38 (3.3%) patients and 1 (0.03%) control were admitted with IE. The median time from date of birth to IE was 10.8 years (25th-75th percentile 2.8–20.9 years). The incidence rates of IE per 1,000 person-years were 2.2 (95% confidence interval (CI) 1.6–3.0) and 0.01 (95% CI 0.0001–0.1) among patients and controls, respectively. In multivariable Cox regression models, in which age, sex, pulmonary valve replacement, and relevant comorbidities (i.e. chronic renal failure, diabetes mellitus, presence of cardiac implantable electronic devices, other valve surgeries), were included as time-varying coefficients, the risk of IE was significantly higher among patients compared with controls (HR 171.5, 95% CI 23.2–1266.7). Moreover, PVR was associated with an increased risk of IE (HR 3.4, 95% CI 1.4–8.2). Conclusions Patients with ToF have a substantial risk of IE and the risk is significantly higher compared with the background population. In particular, PVR was associated with an increased risk of IE. With an increasing life-expectancy of these patients, intensified awareness, preventive measures, and surveillance of this patient group are advisable. Figure 1. Cumulative incidence of IE Funding Acknowledgement Type of funding source: None

scholarly journals Correction to: MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package

2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Matthew D. Koslovsky ◽  
Marina Vannucci
Keyword(s):  
Variable Selection ◽  
Regression Models ◽  
R Package ◽  
Bayesian Variable Selection ◽  
Multinomial Regression

An amendment to this paper has been published and can be accessed via the original article.

Female hormonal exposures and risk of rheumatoid arthritis in the French E3N-EPIC cohort study

Rheumatology ◽  
2021 ◽  
Author(s):  
Carine Salliot ◽  
Yann Nguyen ◽  
Gaëlle Gusto ◽  
Amandine Gelot ◽  
Juliette Gambaretti ◽  
...  
Keyword(s):  
Rheumatoid Arthritis ◽  
Prospective Cohort ◽  
Regression Models ◽  
Proportional Hazards ◽  
Cox Regression ◽  
Cox Proportional Hazards ◽  
Smoking History ◽  
Nulliparous Women ◽  
Hormonal Exposures ◽  
Incident Cases

Abstract Objective To assess the relationships between female hormonal exposures and risk of rheumatoid arthritis (RA), in a prospective cohort of French women. Methods E3N is an on-going French prospective cohort that included 98 995 women aged 40–65 years in 1990. Every 2–3 years, women completed mailed questionnaires on their lifestyles, reproductive factors, and health conditions. Cox proportional-hazards regression models were used to determine factors associated with risk of incident RA, with age as the time scale, adjusted for known risk factors of RA, and considering endogenous and exogenous hormonal factors. Hazard ratios (HRs) and 95% confidence intervals (CIs) were estimated. Effect modification by smoking history was investigated. Results A total of 698 incident cases of RA were ascertained among 78 452 women. In multivariable-adjusted Cox regression models, risk of RA was increased with early age at first pregnancy (<22 vs ≥27 years; HR = 1.34; 95%CI 1.0–1.7) and menopause (≤45 vs ≥53 years; HR = 1.40; 95%CI 1.0–1.9). For early menopause, the association was of similar magnitude in ever and never smokers, although the association was statistically significant only in ever smokers (HR = 1.54; 95%CI 1.0–2.3). We found a decreased risk in nulliparous women never exposed to smoking (HR = 0.44; 95%CI 0.2–0.8). Risk of RA was inversely associated with exposure to progestogen only in perimenopause (>24 vs 0 months; multi-adjusted HR = 0.77; 95%CI 0.6–0.9). Conclusions These results suggest an effect of both endogenous and exogenous hormonal exposures on RA risk and phenotype that deserves further investigation.

Scalable Bayesian variable selection regression models for count data

2020 ◽  
pp. 187-219 ◽  
Author(s):  
Yinsen Miao ◽  
Jeong Hwan Kook ◽  
Yadong Lu ◽  
Michele Guindani ◽  
Marina Vannucci
Keyword(s):  
Variable Selection ◽  
Count Data ◽  
Regression Models ◽  
Bayesian Variable Selection

Treatment Time or Convection Volume in HDF: What Drives the Reduced Mortality Risk?

2015 ◽  
Vol 40 (1) ◽  
pp. 53-58 ◽  
Author(s):  
Camiel L.M. de Roij van Zuijdewijn ◽  
Menso J. Nubé ◽  
Piet M. ter Wee ◽  
Peter J. Blankestijn ◽  
Renée Lévesque ◽  
...  
Keyword(s):  
Confidence Intervals ◽  
Mortality Risk ◽  
Survival Benefit ◽  
Regression Models ◽  
Cox Regression ◽  
Treatment Time ◽  
High Volume ◽  
P Values ◽  
Hazard Ratios

Background/Aims: Treatment time is associated with survival in hemodialysis (HD) patients and with convection volume in hemodiafiltration (HDF) patients. High-volume HDF is associated with improved survival. Therefore, we investigated whether this survival benefit is explained by treatment time. Methods: Participants were subdivided into four groups: HD and tertiles of convection volume in HDF. Three Cox regression models were fitted to calculate hazard ratios (HRs) for mortality of HDF subgroups versus HD: (1) crude, (2) adjusted for confounders, (3) model 2 plus mean treatment time. As the only difference between the latter models is treatment time, any change in HRs is due to this variable. Results: 114/700 analyzed individuals were treated with high-volume HDF. HRs of high-volume HDF are 0.61, 0.62 and 0.64 in the three models, respectively (p values <0.05). Confidence intervals of models 2 and 3 overlap. Conclusion: The survival benefit of high-volume HDF over HD is independent of treatment time.

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