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Sample size requirements for separating out the effects of combination treatments: Randomised controlled trials of combination therapy vs. standard treatment compared to factorial designs for patients with tuberculous meningitis

机译:区分联合治疗效果的样本量要求:结核性脑膜炎患者联合治疗与标准治疗与因子设计比较的随机对照试验

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Background In certain diseases clinical experts may judge that the intervention with the best prospects is the addition of two treatments to the standard of care. This can either be tested with a simple randomized trial of combination versus standard treatment or with a 2 × 2 factorial design. Methods We compared the two approaches using the design of a new trial in tuberculous meningitis as an example. In that trial the combination of 2 drugs added to standard treatment is assumed to reduce the hazard of death by 30% and the sample size of the combination trial to achieve 80% power is 750 patients. We calculated the power of corresponding factorial designs with one- to sixteen-fold the sample size of the combination trial depending on the contribution of each individual drug to the combination treatment effect and the strength of an interaction between the two. Results In the absence of an interaction, an eight-fold increase in sample size for the factorial design as compared to the combination trial is required to get 80% power to jointly detect effects of both drugs if the contribution of the less potent treatment to the total effect is at least 35%. An eight-fold sample size increase also provides a power of 76% to detect a qualitative interaction at the one-sided 10% significance level if the individual effects of both drugs are equal. Factorial designs with a lower sample size have a high chance to be underpowered, to show significance of only one drug even if both are equally effective, and to miss important interactions. Conclusions Pragmatic combination trials of multiple interventions versus standard therapy are valuable in diseases with a limited patient pool if all interventions test the same treatment concept, it is considered likely that either both or none of the individual interventions are effective, and only moderate drug interactions are suspected. An adequately powered 2 × 2 factorial design to detect effects of individual drugs would require at least 8-fold the sample size of the combination trial. Trial registration Current Controlled Trials ISRCTN61649292
机译:背景技术在某些疾病中,临床专家可能会判断具有最佳前景的干预措施是在护理标准中增加两种治疗方法。既可以通过简单的随机试验将联合治疗与标准治疗进行比较,也可以通过2×2析因设计进行测试。方法我们以结核性脑膜炎的新试验设计为例,比较了两种方法。在该试验中,假定将两种药物加至标准治疗中可将死亡风险降低30%,并且达到80%功效的组合试验的样本量为750名患者。我们根据每种药物对联合治疗效果的贡献以及两者之间相互作用的强度,通过联合试验的样本规模的16倍至16倍来计算相应因子设计的功效。结果在没有相互作用的情况下,如果联合治疗的效果较差,则与联合试验相比,析因设计的样本量要增加八倍,才能获得80%的功效,以共同检测两种药物的作用。总效果至少为35%。如果两种药物的个体作用相同,则样本量增加8倍,还可以在单​​侧10%显着性水平上检测到定性相互作用的能力为76%。样本量较小的析因设计极有可能被低估,即使两种药物同样有效,也只能显示一种药物的重要性,并且会错过重要的相互作用。结论如果所有干预措施均测试相同的治疗方案,则多种干预措施与标准疗法的实用组合试验在患者人数有限的疾病中非常有价值,可以认为两种干预措施均无效或只有一种有效,并且只有中等程度的药物相互作用才有效。怀疑的。足够强大的2×2析因设计来检测单个药物的效果,至少需要联合试验样本大小的8倍。试用注册电流对照试验ISRCTN61649292

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