Statistics in medicine
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Statistics in medicine · Jan 2004
ReviewThe evaluation of disease modifying therapies in Alzheimer's disease: a regulatory viewpoint.
Several drugs have received marketing approval in this country for the treatment of dementia of the Alzheimer's type. Their approval has been based on clinical trial designs that do not permit a distinction to be made between an effect of the drug on the symptoms of that disease, and an effect on the pathophysiological mechanisms that underlie that disorder. The latter effect has been referred to as 'disease-modifying.'In recent years there has been considerable interest in developing disease-modifying treatments for Alzheimer's disease (AD), using either specific clinical designs, or surrogate markers, such as brain imaging modalities. This paper outlines the regulatory framework governing how the Food and Drug Administration addresses new drug claims, the current basis for approving drugs for the treatment of AD, clinical trial designs that have been proposed as a means of demonstrating disease-modifying effects, a general and regulatory background to the use of surrogate markers in drug development, and, finally, views about the possible role of surrogate markers, especially brain imaging, as outcome measures in clinical trials intended to produce disease-modifying effects in Alzheimer's Disease.
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Statistics in medicine · Jul 2000
Review Comparative StudyHeterogeneity and statistical significance in meta-analysis: an empirical study of 125 meta-analyses.
For meta-analysis, substantial uncertainty remains about the most appropriate statistical methods for combining the results of separate trials. An important issue for meta-analysis is how to incorporate heterogeneity, defined as variation among the results of individual trials beyond that expected from chance, into summary estimates of treatment effect. Another consideration is which 'metric' to use to measure treatment effect; for trials with binary outcomes, there are several possible metrics, including the odds ratio (a relative measure) and risk difference (an absolute measure). ⋯ We present two exceptions to these observations, which derive from the weights assigned to individual trial estimates. We discuss the implications of these findings for selection of a metric for meta-analysis and incorporation of heterogeneity into summary estimates. Published in 2000 by John Wiley & Sons, Ltd.
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Statistics in medicine · Apr 2000
Review Comparative StudyStrategies for comparing treatments on a binary response with multi-centre data.
This paper surveys methods for comparing treatments on a binary response when observations occur for several strata. A common application is multi-centre clinical trials, in which the strata refer to a sample of centres or sites of some type. Questions of interest include how one should summarize the difference between the treatments, how one should make inferential comparisons, how one should investigate whether treatment-by-centre interaction exists, how one should describe effects when interaction exists, whether one should treat centres and centre-specific treatment effects as fixed or random, and whether centres that have either 0 successes or 0 failures should contribute to the analysis. This article discusses these matters in the context of various strategies for analysing such data, in particular focusing on special problems presented by sparse data.
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Statistics in medicine · Apr 1998
ReviewKappa-like indices of observer agreement viewed from a latent class perspective.
It is common practice to assess consistency of diagnostic ratings in terms of 'agreement beyond chance'. To explore the interpretation of such a term we consider relevant statistical techniques such as Cohen's kappa and log-linear models for agreement on nominal ratings. ⋯ As a result it is shown that Cohen's kappa may be an inadequate and biased index of chance-corrected agreement in studies of intra-observer as well as inter-observer consistency. We suggest a more critical use and interpretation of measures gauging observer reliability by the amount of agreement beyond chance.
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Statistics in medicine · Nov 1997
ReviewMethods of correcting for multiple testing: operating characteristics.
We examine the operating characteristics of 17 methods for correcting p-values for multiple testing on synthetic data with known statistical properties. These methods are derived p-values only and not the raw data. With the test cases, we systematically varied the number of p-values, the proportion of false null hypotheses, the probability that a false null hypothesis would result in a p-value less than 5 per cent and the degree of correlation between p-values. ⋯ Unfortunately, however, a uniformly best method of those examined does not exist. A suggested strategy for examining corrections uses a succession of methods that are increasingly lax in family-wise error. A computer program for these corrections is available.