文章基本信息

标题：Analysis of responder-based endpoints: improving power through utilising continuous components
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作者：James Wason ; Martina McMenamin ; Susanna Dodd 等
期刊名称：Trials
印刷版ISSN：1745-6215
电子版ISSN：1745-6215
出版年度：2020
卷号：21
期号：1
页码：427-432
DOI：10.1186/s13063-020-04353-8
出版社：BioMed Central
摘要：BACKGROUND :Clinical trials and other studies commonly assess the effectiveness of an intervention through the use of responder-based endpoints. These classify patients based on whether they meet a number of criteria which often involve continuous variables categorised as being above or below a threshold. The proportion of patients who are responders is estimated and, where relevant, compared between groups. An alternative method called the augmented binary method keeps the definition of the endpoint the same but utilises information contained within the continuous component to increase the power considerably (equivalent to increasing the sample size by > 30%). In this article we summarise the method and investigate the variety of clinical conditions that use endpoints to which it could be applied. METHODS :We reviewed a database of core outcome sets (COSs) that covered physiological and mortality trial endpoints recommended for collection in clinical trials of different disorders. We identified responder-based endpoints where the augmented binary method would be useful for increasing power. RESULTS :Out of the 287 COSs reviewed, we identified 67 new clinical areas where endpoints were used that would be more efficiently analysed using the augmented binary method. Clinical areas that had particularly high numbers were rheumatology (11 clinical disorders identified), non-solid tumour oncology (10 identified), neurology (9 identified) and cardiovascular (8 identified). CONCLUSIONS :The augmented binary method can potentially provide large benefits in a vast array of clinical areas. Further methodological development is needed to account for some types of endpoints.
关键词：Augmented binary method;Composite endpoint;Efficiency;Responder analysis;Statistical analysis