Statistics in medicine
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Statistics in medicine · May 2012
Competing risks and the clinical community: irrelevance or ignorance?
Life expectancy has dramatically increased in industrialized nations over the last 200 hundred years. The aging of populations carries over to clinical research and leads to an increasing representation of elderly and multimorbid individuals in study populations. Clinical research in these populations is complicated by the fact that individuals are likely to experience several potential disease endpoints that prevent some disease-specific endpoint of interest from occurrence. ⋯ We then discuss the importance of agreement between the competing risks methodology and the study aim, in particular the distinction between etiologic and prognostic research questions. In a review of 50 clinical studies performed in individuals susceptible to competing risks published in high-impact clinical journals, we found competing risks issues in 70% of all articles. Better recognition of issues related to competing risks and of statistical methods that deal with competing risks in accordance with the aim of the study is needed.
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Statistics in medicine · May 2012
Bayesian adaptive clinical trials: a dream for statisticians only?
Adaptive or 'flexible' designs have emerged, mostly within frequentist frameworks, as an effective way to speed up the therapeutic evaluation process. Because of their flexibility, Bayesian methods have also been proposed for Phase I through Phase III adaptive trials; however, it has been reported that they are poorly used in practice. We aim to describe the international scientific production of Bayesian clinical trials by investigating the actual development and use of Bayesian 'adaptive' methods in the setting of clinical trials. ⋯ The spread and use of these articles depended heavily on their topic, with 3.1% of the biostatistical articles accumulating at least 25 citations within 5 years of their publication compared with 15% of the reviews and 32% of the clinical articles. We also examined the reasons for the limited use of Bayesian adaptive design methods in clinical trials and the areas of current and future research to address these challenges. Efforts to promote Bayesian approaches among statisticians and clinicians appear necessary.