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Bayesian inference for an illness-death model for stroke with cognition as a latent time-dependent risk factor
Longitudinal data can be used to estimate the transition intensities between healthy and unhealthy states prior to death. An illness-death model for history of stroke is presented, where time-dependent transition intensities are regressed on a latent variable representing cognitive function. The change of this function over time is described by a linear growth model with random effects. Occasion-specific cognitive function is measured by an item response model for longitudinal scores on the Mini-Mental State Examination, a questionnaire used to screen for cognitive impairment. The illness-death model will be used to identi...
Source: Statistical Methods in Medical Research - November 26, 2015 Category: Statistics Authors: van den Hout, A., Fox, J.-P., Klein Entink, R. H. Tags: Articles Source Type: research

Change point detection in risk adjusted control charts
Precise identification of the time when a change in a clinical process has occurred enables experts to identify a potential special cause more effectively. In this article, we develop change point estimation methods for a clinical dichotomous process in the presence of case mix. We apply Bayesian hierarchical models to formulate the change point where there exists a step change in the odds ratio and logit of risk of a Bernoulli process. Markov Chain Monte Carlo is used to obtain posterior distributions of the change point parameters including location and magnitude of changes and also corresponding probabilistic intervals ...
Source: Statistical Methods in Medical Research - November 26, 2015 Category: Statistics Authors: Assareh, H., Smith, I., Mengersen, K. Tags: Articles Source Type: research

Piecewise mixed-effects models with skew distributions for evaluating viral load changes: A Bayesian approach
Studies of human immunodeficiency virus dynamics in acquired immuno deficiency syndrome (AIDS) research are very important in evaluating the effectiveness of antiretroviral (ARV) therapies. The potency of ARV agents in AIDS clinical trials can be assessed on the basis of a viral response such as viral decay rate or viral load change in plasma. Following ARV treatment, the profile of each subject's viral load tends to follow a ‘broken stick’-like dynamic trajectory, indicating multiple phases of decline and increase in viral loads. Such multiple-phases (change-points) can be described by a random change-point mo...
Source: Statistical Methods in Medical Research - November 26, 2015 Category: Statistics Authors: Huang, Y., Dagne, G. A., Zhou, S., Wang, Z. Tags: Articles Source Type: research

A joint model for the dependence between clustered times to tumour progression and deaths: A meta-analysis of chemotherapy in head and neck cancer
The observation of time to tumour progression (TTP) or progression-free survival (PFS) may be terminated by a terminal event. In this context, deaths may be due to tumour progression, and the time to the major failure event (death) may be correlated with the TTP. The usual assumption of independence between the TTP process and death, required by many commonly used statistical methods, can be violated. Furthermore, although the relationship between TTP and time to death is most relevant to the anti-cancer drug development or to evaluation of TTP as a surrogate endpoint, statistical models that try to describe the dependence...
Source: Statistical Methods in Medical Research - November 26, 2015 Category: Statistics Authors: Rondeau, V., Pignon, J.-P., Michiels, S., on behalf of the MACH-NC collaborative Group Tags: Articles Source Type: research

Impact of delayed diagnosis time in estimating progression rates to hepatitis C virus-related cirrhosis and death
Delay of the diagnosis of hepatitis C virus (HCV), and its treatment to avert cirrhosis, is often present sincethe early stage of HCV progression is latent. Current methods to determine the incubation time to HCV-related cirrhosis and the duration time from cirrhosis to subsequent events (e.g. complications or death) used to be based on the time of liver biopsy diagnosis and ignore this delay which led to an interval censoring for the first event time and a double censoring for the subsequent event time. To investigate the impact of this delay in estimating HCV progression rates and relevant estimating bias, we present a c...
Source: Statistical Methods in Medical Research - November 26, 2015 Category: Statistics Authors: Fu, B., Wang, W., Shi, X. Tags: Articles Source Type: research

Frailties in multi-state models: Are they identifiable? Do we need them?
The inclusion of latent frailties in survival models can serve two purposes: (1) the modelling of dependence in clustered data, (2) explaining lack of fit of univariate survival models, like deviation from the proportional hazards assumption. Multi-state models are somewhere between univariate data and clustered data. Frailty models can help in understanding the dependence in sequential transitions (like in clustered data) and can be useful in explaining some strange phenomena in the effect of covariates in competing risks models (like in univariate data). The (im)possibilities of frailty models will be exemplified on a da...
Source: Statistical Methods in Medical Research - November 26, 2015 Category: Statistics Authors: Putter, H., van Houwelingen, H. C. Tags: Articles Source Type: research

Assessing the sensitivity of methods for estimating principal causal effects
The framework of principal stratification provides a way to think about treatment effects conditional on post-randomization variables, such as level of compliance. In particular, the complier average causal effect (CACE) – the effect of the treatment for those individuals who would comply with their treatment assignment under either treatment condition – is often of substantive interest. However, estimation of the CACE is not always straightforward, with a variety of estimation procedures and underlying assumptions, but little advice to help researchers select between methods. In this article, we discuss and ex...
Source: Statistical Methods in Medical Research - November 26, 2015 Category: Statistics Authors: Stuart, E. A., Jo, B. Tags: Articles Source Type: research

A two-stage estimation for screening studies using two diagnostic tests with binary disease status verified in test positives only
This article considers the statistical estimation and inference for screening studies in which two binary tests are used for screening with a binary disease status verified only for those subjects with at least one positive test result. The challenge encountered in these studies is the non-identifiability because the disease rate is not identifiable for subjects with negative results from both tests without additional assumptions. Different homogeneous association models have been proposed in the literature to circumvent the non-identifiability problem, which were solved using numerical methods. We propose to formulate the...
Source: Statistical Methods in Medical Research - November 26, 2015 Category: Statistics Authors: Li, F., Chu, H., Nie, L. Tags: Articles Source Type: research

Probabilistic sensitivity analysis in health economics
The objective of this article is to review the problem of health economic assessment from the standpoint of Bayesian statistical decision theory with particular attention to the philosophy underlying the procedures for sensitivity analysis. (Source: Statistical Methods in Medical Research)
Source: Statistical Methods in Medical Research - November 26, 2015 Category: Statistics Authors: Baio, G., Dawid, A. P. Tags: Articles Source Type: research

Bayesian design for dichotomous repeated measurements with autocorrelation
In medicine and health sciences, binary outcomes are often measured repeatedly to study their change over time. A problem for such studies is that designs with an optimal efficiency for some parameter values may not be efficient for other values. To handle this problem, we propose Bayesian designs which formally account for the uncertainty in the parameter values for a mixed logistic model which allows quadratic changes over time. Bayesian D-optimal allocations of time points are computed for different priors, costs, covariance structures and values of the autocorrelation. Our results show that the optimal number of time p...
Source: Statistical Methods in Medical Research - October 9, 2015 Category: Statistics Authors: Abebe, H. T., Tan, F. E., van Breukelen, G. J., Berger, M. P. Tags: Articles Source Type: research

The effect of heterogeneous variance on efficiency and power of cluster randomized trials with a balanced 2 x 2 factorial design
Sample size calculation for cluster randomized trials (CRTs) with a 2x2 factorial design is complicated due to the combination of nesting (of individuals within clusters) with crossing (of two treatments). Typically, clusters and individuals are allocated across treatment conditions in a balanced fashion, which is optimal under homogeneity of variance. However, the variance is likely to be heterogeneous if there is a treatment effect. An unbalanced allocation is then more efficient, but impractical because the optimal allocation depends on the unknown variances. Focusing on CRTs with a 2x2 design, this paper addresses two ...
Source: Statistical Methods in Medical Research - October 9, 2015 Category: Statistics Authors: Lemme, F., van Breukelen, G. J., Candel, M. J., Berger, M. P. Tags: Articles Source Type: research

Sample size calculation for treatment effects in randomized trials with fixed cluster sizes and heterogeneous intraclass correlations and variances
When comparing two different kinds of group therapy or two individual treatments where patients within each arm are nested within care providers, clustering of observations may occur in both arms. The arms may differ in terms of (a) the intraclass correlation, (b) the outcome variance, (c) the cluster size, and (d) the number of clusters, and there may be some ideal group size or ideal caseload in case of care providers, fixing the cluster size. For this case, optimal cluster numbers are derived for a linear mixed model analysis of the treatment effect under cost constraints as well as under power constraints. To account f...
Source: Statistical Methods in Medical Research - October 9, 2015 Category: Statistics Authors: Candel, M. J., van Breukelen, G. J. Tags: Articles Source Type: research

Efficient design of cluster randomized and multicentre trials with unknown intraclass correlation
For cluster randomized and multicentre trials evaluating the effect of a treatment on persons nested within clusters, equations have been published to compute the optimal sample sizes at the cluster and person level as a function of sampling costs and intraclass correlation (ICC). Here, optimal means maximum power and precision for a given sampling budget, or minimum sampling costs for a given power and precision. However, the ICC is usually unknown, and the optimal sample sizes depend strongly on this ICC. To overcome this local optimality problem, this study presents Maximin designs (MMDs) based on relative efficiency (R...
Source: Statistical Methods in Medical Research - October 9, 2015 Category: Statistics Authors: van Breukelen, G. J., Candel, M. J. Tags: Articles Source Type: research

Optimal and maximin sample sizes for multicentre cost-effectiveness trials
This paper deals with the optimal sample sizes for a multicentre trial in which the cost-effectiveness of two treatments in terms of net monetary benefit is studied. A bivariate random-effects model, with the treatment-by-centre interaction effect being random and the main effect of centres fixed or random, is assumed to describe both costs and effects. The optimal sample sizes concern the number of centres and the number of individuals per centre in each of the treatment conditions. These numbers maximize the efficiency or power for given research costs or minimize the research costs at a desired level of efficiency or po...
Source: Statistical Methods in Medical Research - October 9, 2015 Category: Statistics Authors: Manju, M. A., Candel, M. J., Berger, M. P. Tags: Articles Source Type: research

Efficient treatment allocation in two-way nested designs
Cluster randomized and multicenter trials sometimes combine two treatments A and B in a factorial design, with conditions such as A, B, A and B, or none. This results in a two-way nested design. The usual issue of sample size and power now arises for various clinically relevant contrast hypotheses. Assuming a fixed total sample size at each level (number of clusters or centers, number of patients), we derive the optimal proportion of the total sample to be allocated to each treatment arm. We consider treatment assignment first at the highest level (cluster randomized trial) and then at the lowest level (multicenter trial)....
Source: Statistical Methods in Medical Research - October 9, 2015 Category: Statistics Authors: Lemme, F., van Breukelen, G. J., Berger, M. P. Tags: Articles Source Type: research