Joint modelling of multivariate longitudinal and time-to-event data

Invited presentation by the Statistics Research Group at the Department of Mathematical Sciences, University of Durha

Joint modelling of multivariate longitudinal and time-to-event data

Invited presentation by the Statistics Research Group at the Department of Mathematical Sciences, University of Durha

UK Heart Surgery: What Patients Can Expect from their Surgeons

This report presents selected findings from the National Adult Cardiac Surgery Audit for heart operations that took place between 2001/2 and 2010/11, alongside other information about cardiac surgery in the UK

Joint models of longitudinal and time-to-event data with more than one event time outcome: a review

Methodological development and clinical application of joint models of longitudinal and time-to-event outcomes have grown substantially over the past two decades. However, much of this research has concentrated on a single longitudinal outcome and a single event time outcome. In clinical and public health research, patients who are followed up over time may often experience multiple, recurrent, or a succession of clinical events. Models that utilise such multivariate event time outcomes are quite valuable in clinical decision-making. We comprehensively review the literature for implementation of joint models involving more than a single event time per subject. We consider the distributional and modelling assumptions, including the association structure, estimation approaches, software implementations, and clinical applications. Research into this area is proving highly promising, but to-date remains in its infancy

Statistical primer: performing repeated-measures analysis

Longitudinal data arise when repeated measurements are taken on the same individuals over time. Inference about between-group differences of within-subject change is usually of interest. This statistical primer for cardiothoracic and vascular surgeons aims to provide a short and practical introduction of biostatistical methods on how to analyse repeated-measures data. Several methodological approaches for analysing repeated measures will be introduced, ranging from simple approaches to advanced regression modelling. Design considerations of studies involving repeated measures are discussed, and the methods are illustrated with a data set measuring coronary sinus potassium in dogs after occlusion. Cardiothoracic and vascular surgeons should be aware of the myriad approaches available to them for analysing repeated-measures data, including the relative merits and disadvantages of each. It is important to present effective graphical displays of the data and to avoid arbitrary cross-sectional statistical comparisons

Minimally invasive versus conventional aortic valve replacement: a propensity-matched study from the UK National Data

Minimally invasive aortic valve replacement (MIAVR) has been demonstrated as a safe and effective option but remains underused. We aimed to evaluate outcomes of isolated MIAVR compared with conventional aortic valve replacement (CAVR).Data from The National Institute for Cardiovascular Outcomes Research (NICOR) were analyzed at seven volunteer centers (2006-2012). Primary outcomes were in-hospital mortality and midterm survival. Secondary outcomes were postoperative length of stay as well as cumulative bypass and cross-clamp times. Propensity modeling with matched cohort analysis was used.Of 307 consecutive MIAVR patients, 151 (49%) were performed during the last 2 years of study with a continued increase in numbers. The 307 MIAVR patients were matched on a 1:1 ratio. In the matched CAVR group, there was no statistically significant difference in in-hospital mortality [MIAVR, 4/307,(1.3%); 95% confidence interval (CI), 0.4%-3.4% vs CAVR, 6/307 (2.0%); 95% CI, 0.8%-4.3%; P = 0.752]. One-year survival rates in the MIAVR and CAVR groups were 94.4% and 94.6%, respectively. There was no statistically significant difference in midterm survival (P = 0.677; hazard ratio, 0.90; 95% CI, 0.56-1.46). Median postoperative length of stay was lower in the MIAVR patients by 1 day (P = 0.009). The mean cumulative bypass time (94.8 vs 91.3 minutes; P = 0.333) and cross-clamp time (74.6 vs 68.4 minutes; P = 0.006) were longer in the MIAVR group; however, this was significant only in the cross-clamp time comparison.Minimally invasive aortic valve replacement is a safe alternative to CAVR with respect to operative and 1-year mortality and is associated with a shorter postoperative stay. Further studies are required in high-risk (logistic EuroSCORE > 10) patients to define the role of MIAVR