Statistics in medicine
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Statistics in medicine · Dec 2007
Comparative StudyA competing risks analysis of bloodstream infection after stem-cell transplantation using subdistribution hazards and cause-specific hazards.
After peripheral blood stem-cell transplantation, patients treated for severe haematologic diseases enter a critical phase (neutropenia). Analysis of bloodstream infection during neutropenia has to account for competing risks. ⋯ Proportional subdistribution hazards modelling of the subdistribution of the CIF is establishing itself as an interpretation-friendly alternative. We apply both methods and discuss their relative merits.
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Statistics in medicine · Dec 2007
The analysis of continuous outcomes in multi-centre trials with small centre sizes.
The standard analysis of clinical trials stratified by centre is to include centres as fixed effects, but if many centres contribute small numbers of patients, this approach results in a loss of power. Assuming no treatment by centre interaction, we used simulation to examine power and coverage of confidence intervals from three approaches to the analysis of continuous outcome in multi-centre trials: ignoring centres, including centres as fixed effects, and including them as random effects. The simulation incorporated eight sizes of centre effects; randomization in blocks of size 2 or 4; and two sample sizes, namely 100 and 200 patients per treatment arm in a parallel groups design. ⋯ Fixed effects analysis was less powerful, particularly when centre effects were small. Incorporating block randomization with larger block size increased non-orthogonality in the design, contributing to loss of power. Where centre effects are small and recruitment in many centres is low, the approaches of ignoring centres or incorporating them as random effects have better performance than the traditional fixed effects analysis.
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The number needed to treat (NNT) is a popular measure to describe the absolute effect of a new treatment compared with a standard treatment or placebo in clinical trials with binary outcome. For use of NNT measures in epidemiology to compare exposed and unexposed subjects, the terms 'number needed to be exposed' (NNE) and 'exposure impact number' (EIN) have been proposed. Additionally, in the framework of logistic regression a method was derived to perform point and interval estimation of NNT measures with adjustment for confounding by using the adjusted odds ratio (OR approach). ⋯ NNE is the average number of unexposed persons needed to be exposed to observe one extra case; EIN is the average number of exposed persons among one case can be attributed to the exposure. By means of simulations it is shown that the ARD approach is better than the OR approach in terms of bias and coverage probability, especially if the confounder distribution is wide. The proposed method is illustrated by application to data of a cohort study investigating the effect of smoking on coronary heart disease.
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Statistics in medicine · Dec 2007
Frequentist evaluation of group sequential clinical trial designs.
Group sequential stopping rules are often used as guidelines in the monitoring of clinical trials in order to address the ethical and efficiency issues inherent in human testing of a new treatment or preventive agent for disease. Such stopping rules have been proposed based on a variety of different criteria, both scientific (e.g. estimates of treatment effect) and statistical (e.g. frequentist type I error, Bayesian posterior probabilities, stochastic curtailment). ⋯ Thus, the basis used to initially define a stopping rule is relatively unimportant so long as the operating characteristics of the stopping rule are fully investigated. In this paper we describe how the frequentist operating characteristics of a particular stopping rule might be evaluated to ensure that the selected clinical trial design satisfies the constraints imposed by the many different disciplines represented by the clinical trial collaborators.