Sensitivity analysis for correlated survival models

In this thesis we introduce a model for informative censoring. We assume that the joint distribution of the failure and the censored times depends on a parameter δ, which is actually a measure of the possible dependence, and a bias function B(t,θ). Knowledge of δ means that the joint distribution is fully specified, while B(t,θ) can be any function of the failure times. Being unable to draw inferences about δ, we perform a sensitivity analysis on the parameters of interest for small values of δ, based on a first order approximation. This will give us an idea of how robust our estimates are in the presence of small dependencies, and whether the ignorability assumption can lead to misleading results. Initially we propose the model for the general parametric case. This is the simplest possible case and we explore the different choices for the standardized bias function. After choosing a suitable function for B(t,θ) we explore the potential interpretation of δ through it's relation to the correlation between quantities of the failure and the censoring processes. Generalizing our parametric model we propose a proportional hazards structure, allowing the presence of covariates. At this stage we present a data set from a leukemia study in which the knowledge, under some certain assumptions, of the censored and the death times of a number of patients allows us to explore the impact of informative censoring to our estimates. Following the analysis of the above data we introduce an extension to Cox's partial likelihood, which will call "modified Cox's partial likelihood", based on the assumptions that censored times do contribute information about the parameters of interest. Finally we perform parametric bootstraps to assess the validity of our model and to explore up to what values of parameter δ our approximation holds

Does preservation of the sub-valvular apparatus during mitral valve replacement affect long-term survival and quality of life? A Microsimulation Study

RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are.Abstract Background Techniques to preserve the sub-valvular apparatus in order to reduce morbidity and mortality following mitral valve replacement have been frequently reported. However, it is uncertain what impact sub-valvular apparatus preservation techniques have on long-term outcomes following mitral valve replacement. This study investigated the effect of sub-valvular apparatus preservation on long-term survival and quality of life following mitral valve replacement. Methods A microsimulation model was used to compare long-term survival and quality-adjusted life years following mitral valve replacement after conventional valve replacement and sub-valvular apparatus preservation. Probabilistic sensitivity analysis and alternative analysis were performed to investigate uncertainty associated with the results. Results Our Analysis suggests that patients survive longer if the sub-valvular apparatus are preserved (65.7% SD 1.5%, compared with 58.1% SD 1.6% at 10 years). The quality adjusted life years gained over a 10 year period where also greater after sub-valvular apparatus preservation. (6.54 QALY SD 0.07 QALY, compared with 5.61 QALY, SD 0.07 QALY). The superiority of preservation techniques was insensitive to patient age, parameter or model uncertainty. Conclusion This study suggests that long-term outcomes may be improved when the sub-valvular apparatus are preserved. Given the lack of empirical data further research is needed to investigate health-related quality of life after mitral valve replacement, and to establish whether outcomes differ between preservation techniques.Published versio

Two-stage meta-analysis of survival data from individual participants using percentile ratios

Methods for individual participant data meta-analysis of survival outcomes commonly focus on the hazard ratio as a measure of treatment effect. Recently, Siannis et al. (2010, Statistics in Medicine 29:3030–3045) proposed the use of percentile ratios as an alternative to hazard ratios. We describe a novel two-stage method for the meta-analysis of percentile ratios that avoids distributional assumptions at the study level. Copyright © 2012 John Wiley & Sons, Ltd

Cumulative probability distribution of incremental QALY payoffs for SAP compared to conventional MVR

<p><b>Copyright information:</b></p><p>Taken from "Does preservation of the sub-valvular apparatus during mitral valve replacement affect long-term survival and quality of life? A Microsimulation Study"</p><p>http://www.cardiothoracicsurgery.org/content/3/1/17</p><p>Journal of Cardiothoracic Surgery 2008;3():17-17.</p><p>Published online 23 Apr 2008</p><p>PMCID:PMC2374780.</p><p></p

10-year survival curves illustrating survival following SAP and conventional MVR

<p><b>Copyright information:</b></p><p>Taken from "Does preservation of the sub-valvular apparatus during mitral valve replacement affect long-term survival and quality of life? A Microsimulation Study"</p><p>http://www.cardiothoracicsurgery.org/content/3/1/17</p><p>Journal of Cardiothoracic Surgery 2008;3():17-17.</p><p>Published online 23 Apr 2008</p><p>PMCID:PMC2374780.</p><p></p