Robust Methods for Interval-Censored Life History Data

Interval censoring arises frequently in life history data, as individuals are often only observed at a sequence of assessment times. This leads to a situation where we do not know when an event of interest occurs, only that it occurred somewhere between two assessment times. Here, the focus will be on methods of estimation for recurrent event data, current status data, and multistate data, subject to interval censoring. With recurrent event data, the focus is often on estimating the rate and mean functions. Nonparametric estimates are readily available, but are not smooth. Methods based on local likelihood and the assumption of a Poisson process are developed to obtain smooth estimates of the rate and mean functions without specifying a parametric form. Covariates and extra-Poisson variation are accommodated by using a pseudo-profile local likelihood. The methods are assessed by simulations and applied to a number of datasets, including data from a psoriatic arthritis clinic. Current status data is an extreme form of interval censoring that occurs when each individual is observed at only one assessment time. If current status data arise in clusters, this must be taken into account in order to obtain valid conclusions. Copulas offer a convenient framework for modelling the association separately from the margins. Estimating equations are developed for estimating marginal parameters as well as association parameters. Efficiency and robustness to the choice of copula are examined for first and second order estimating equations. The methods are applied to data from an orthopedic surgery study as well as data on joint damage in psoriatic arthritis. Multistate models can be used to characterize the progression of a disease as individuals move through different states. Considerable attention is given to a three-state model to characterize the development of a back condition known as spondylitis in psoriatic arthritis, along with the associated risk of mortality. Robust estimates of the state occupancy probabilities are derived based on a difference in distribution functions of the entry times. A five-state model which differentiates between left-side and right-side spondylitis is also considered, which allows us to characterize what effect spondylitis on one side of the body has on the development of spondylitis on the other side. Covariate effects are considered through multiplicative time homogeneous Markov models. The robust state occupancy probabilities are also applied to data on CMV infection in patients with HIV

Predicting Time on Prolonged Benefits for Injured Workers with Acute Back Pain

Introduction Some workers with work-related compensated back pain (BP) experience a troubling course of disability. Factors associated with delayed recovery among workers with work-related compensated BP were explored. Methods This is a cohort study of workers with compensated BP in 2005 in Ontario, Canada. Follow up was 2æyears. Data was collected from employers, employees and health-care providers by the Workplace Safety and Insurance Board (WSIB). Exclusion criteria were: (1) no-lost-time claims, (2) \u3e30ædays between injury and claim filing, (3) 65æyears. Using proportional hazard models, we examined the prognostic value of information collected in the first 4æweeks after injury. Outcome measures were time on benefits during the first episode and time until recurrence after the first episode. Results Of 6,657 workers, 1,442 were still on full benefits after 4æweeks. Our final model containing age, physical demands, opioid prescription, union membership, availability of a return-to-work program, employer doubt about work-relatedness of injury, worker?s recovery expectations, participation in a rehabilitation program and communication of functional ability was able to identify prolonged claims to a fair degree [area under the curve (AUC)æ=æ.79, 95æ% confidence interval (CI) .74?.84]. A model containing age, sex, physical demands, opioid prescription and communication of functional ability was less successful at predicting time until recurrence (AUCæ=æ.61, 95æ% CI .57, .65). Conclusions Factors contained in information currently collected by the WSIB during the first 4æweeks on benefits can predict prolonged claims, but not recurrent claims. Electronic supplementary material The online version of this article (doi:10.1007/s10926-014-9534-5) contains supplementary material, which is available to authorized users

Interval estimation for response adaptive clinical trials

In this paper we examine a new method for constructing confidence intervals for the difference of success probabilities to analyze dependent data from response adaptive designs with binary responses. Specifically we investigate the feasibility of the Jeffreys-Perks procedure for interval estimation. Simulation results are derived to demonstrate the performance of the Jeffreys-Perks procedure compared with the profile likelihood method. It is found that both asymptotic methods perform well for small sample sizes despite being approximate procedures.Adaptive allocation Two-sample binomial Interval estimation Profile likelihood Randomized play-the-winner rule

MicroRNA-34a dependent regulation of AXL controls the activation of dendritic cells in inflammatory arthritis

Current treatments for rheumatoid arthritis (RA) do not reverse underlying aberrant immune function. A genetic predisposition to RA, such as HLA-DR4 positivity, indicates that dendritic cells (DC) are of crucial importance to pathogenesis by activating auto-reactive lymphocytes. Here we show that microRNA-34a provides homoeostatic control of CD1c+ DC activation via regulation of tyrosine kinase receptor AXL, an important inhibitory DC auto-regulator. This pathway is aberrant in CD1c+ DCs from patients with RA, with upregulation of miR-34a and lower levels of AXL compared to DC from healthy donors. Production of pro-inflammatory cytokines is reduced by ex vivo gene-silencing of miR-34a. miR-34a-deficient mice are resistant to collagen-induced arthritis and interaction of DCs and T cells from these mice are reduced and do not support the development of Th17 cells in vivo. Our findings therefore show that miR-34a is an epigenetic regulator of DC function that may contribute to RA