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

Adult patients with respiratory syncytial virus infection: impact of solid organ and hematopoietic stem cell transplantation on outcomes

BackgroundRespiratory syncytial virus (RSV) is a common community‐acquired pathogen responsible for a substantial disease burden in adults. We investigated the outcomes after RSV infection in hospitalized adults over a 3‐year period.MethodsThis single‐center, retrospective study identified 174 patients hospitalized with RSV upper or lower respiratory tract infection (LRTI) between January 1, 2009 and June 30, 2012. Clinical data were extracted from medical records. The primary outcome analyzed was all‐cause mortality, defined as death during the index hospital admission. Subjects were divided into 3 groups for comparison: hematopoietic stem cell transplant (HSCT) patients, solid organ transplant (SOT) patients, and non‐transplant patients.ResultsIn our study, 41/174 (23.6%) were HSCT recipients and 28/174 (16.1%) were SOT recipients. Twelve of 174 (6.9%) died. Death occurred in 2/41 (4.9%) HSCT and 3/28 (10.7%) SOT recipients, compared to 7/106 (6.6%) non‐transplant patients. When compared to the non‐transplant cohort, HSCT and SOT were not found to be significant risk factors for mortality (P = 0.685 and 0.645, respectively). In multivariate logistic regression, age >60 was associated with mortality (P = 0.019), while lymphopenia on admission trended toward an association with death (P = 0.054). HSCT patients were less likely to be admitted to an intensive care unit (odds ratio [OR] 0.26, P = 0.04), but were significantly more likely to receive ribavirin therapy (OR 11.62, P 60 or with lymphopenia on admission. This study did not identify any significant increased mortality or morbidity associated with RSV infection in immune suppressed transplant recipients vs. patients who had not received a transplant.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/113135/1/tid12409.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

Additive and multiplicative hazards modeling for recurrent event data analysis

<p>Abstract</p> <p>Background</p> <p>Sequentially ordered multivariate failure time or recurrent event duration data are commonly observed in biomedical longitudinal studies. In general, standard hazard regression methods cannot be applied because of correlation between recurrent failure times within a subject and induced dependent censoring. Multiplicative and additive hazards models provide the two principal frameworks for studying the association between risk factors and recurrent event durations for the analysis of multivariate failure time data.</p> <p>Methods</p> <p>Using emergency department visits data, we illustrated and compared the additive and multiplicative hazards models for analysis of recurrent event durations under (i) a varying baseline with a common coefficient effect and (ii) a varying baseline with an order-specific coefficient effect.</p> <p>Results</p> <p>The analysis showed that both additive and multiplicative hazards models, with varying baseline and common coefficient effects, gave similar results with regard to covariates selected to remain in the model of our real dataset. The confidence intervals of the multiplicative hazards model were wider than the additive hazards model for each of the recurrent events. In addition, in both models, the confidence interval gets wider as the revisit order increased because the risk set decreased as the order of visit increased.</p> <p>Conclusions</p> <p>Due to the frequency of multiple failure times or recurrent event duration data in clinical and epidemiologic studies, the multiplicative and additive hazards models are widely applicable and present different information. Hence, it seems desirable to use them, not as alternatives to each other, but together as complementary methods, to provide a more comprehensive understanding of data.</p

Solving the Organ Shortage Crisis: The 7th Annual American Society of Transplant Surgeons’ State-of-the-Art Winter Symposium

Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/73036/1/j.1600-6143.2007.02146.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