A Perspective on the Scientific Registry of Transplant Recipients' Migration to Bayesian Methods

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/112268/1/ajt13354.pd

A weighted cumulative sum (WCUSUM) to monitor medical outcomes with dependent censoring

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/108011/1/sim6139.pd

Survival Benefit-Based Deceased-Donor Liver Allocation

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74806/1/j.1600-6143.2009.02571.x.pd

Semiparametric Analysis of Correlated Recurrent and Terminal Events

In clinical and observational studies, recurrent event data (e.g., hospitalization) with a terminal event (e.g., death) are often encountered. In many instances, the terminal event is strongly correlated with the recurrent event process. In this article, we propose a semiparametric method to jointly model the recurrent and terminal event processes. The dependence is modeled by a shared gamma frailty that is included in both the recurrent event rate and terminal event hazard function. Marginal models are used to estimate the regression effects on the terminal and recurrent event processes, and a Poisson model is used to estimate the dispersion of the frailty variable. A sandwich estimator is used to achieve additional robustness. An analysis of hospitalization data for patients in the peritoneal dialysis study is presented to illustrate the proposed method.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/66008/1/j.1541-0420.2006.00677.x.pd

Liver and Intestine Transplantation in the United States, 1995–2004

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/74804/1/j.1600-6143.2006.01273.x.pd

Influence of maternal and perinatal factors on subsequent hospitalisation for asthma in children: evidence from the Oxford record linkage study

Background: There is much interest in the possibility that perinatal factors may influence the risk of disease in later life. We investigated the influence of maternal and perinatal factors on subsequent hospital admission for asthma in children. Methods: Analysis of data from the Oxford record linkage study (ORLS) to generate a retrospective cohort of 248 612 records of births between 1970 and 1989, with follow-up to records of subsequent hospital admission for 4 017 children with asthma up to 1999. Results: Univariate analysis showed significant associations between an increased risk of admission for asthma and later years of birth (reflecting the increase in asthma in the 1970s and 1980s), low social class, asthma in the mother, unmarried mothers, maternal smoking in pregnancy, subsequent births compared with first-born, male sex, low birth weight, short gestational age, caesarean delivery, forceps delivery and not being breastfed. Multivariate analysis, identifying each risk factor that had a significant effect independently of other risk factors, confirmed associations with maternal asthma (odds ratio (OR) 3.1, 95% confidence interval 2.7-3.6), male sex (versus female, 1.8, 1.7-2.0), low birth weight (1000-2999 g versus 3000-3999 g, 1.2, 1.1-1.3), maternal smoking (1.1, 1.0-1.3) and delivery by caesarean section (1.2; 1.0-1.3). In those first admitted with asthma under two years old, there were associations with having siblings (e.g. second child compared with first-born, OR 1.3, 1.0-1.7) and short gestational age (24-37 weeks versus 38-41 weeks, 1.6, 1.2-2.2). Multivariate analysis confined to those admitted with asthma aged six years or more, showed associations with maternal asthma (OR 3.8, 3.1-4.7), age of mother (under 25 versus 25-34 at birth, OR 1.16, 1.03-1.31; over 35 versus 25-34, OR 1.4, 1.1-1.7); high social class was protective (1 and 2, compared with 3, 0.72; 0.63-0.82). Hospital admission for asthma in people aged over six was more common in males than females (1.4; 1.2-1.5); but, by the teenage years, the sex ratio reversed and admission was more common in females than males. Conclusion: Several maternal characteristics and perinatal factors are associated with an elevated risk of hospital admission for asthma in the child in later life. </p

Semiparametric Methods for Clustered Recurrent Event Data

In biomedical studies, the event of interest is often recurrent and within-subject events cannot usually be assumed independent. In addition, individuals within a cluster might not be independent; for example, in multi-center or familial studies, subjects from the same center or family might be correlated. We propose methods of estimating parameters in two semi-parametric proportional rates/means models for clustered recurrent event data. The first model contains a baseline rate function which is common across clusters, while the second model features cluster-specific baseline rates. Dependence structures for patients-within-cluster and events-within-patient are both unspecified. Estimating equations are derived for the regression parameters. For the common baseline model, an estimator of the baseline mean function is proposed. The asymptotic distributions of the model parameters are derived, while finite-sample properties are assessed through a simulation study. Using data from a national organ failure registry, the proposed methods are applied to the analysis of technique failures among Canadian dialysis patients.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/46817/1/10985_2005_Article_2970.pd

An Estimating Function Approach to the Analysis of Recurrent and Terminal Events

Summary In clinical and observational studies, the event of interest can often recur on the same subject. In a more complicated situation, there exists a terminal event (e.g., death) which stops the recurrent event process. In many such instances, the terminal event is strongly correlated with the recurrent event process. We consider the recurrent/terminal event setting and model the dependence through a shared gamma frailty that is included in both the recurrent event rate and terminal event hazard functions. Conditional on the frailty, a model is specified only for the marginal recurrent event process, hence avoiding the strong Poisson‐type assumptions traditionally used. Analysis is based on estimating functions that allow for estimation of covariate effects on the recurrent event rate and terminal event hazard. The method also permits estimation of the degree of association between the two processes. Closed‐form asymptotic variance estimators are proposed. The proposed method is evaluated through simulations to assess the applicability of the asymptotic results in finite samples and the sensitivity of the method to its underlying assumptions. The methods can be extended in straightforward ways to accommodate multiple types of recurrent and terminal events. Finally, the methods are illustrated in an analysis of hospitalization data for patients in an international multi‐center study of outcomes among dialysis patients.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/98766/1/biom12025.pdfhttp://deepblue.lib.umich.edu/bitstream/2027.42/98766/2/biom12025-sm-0001-SupMat.pd