Dehbi Hakim-Moulay, Hackshaw Allan
Comprehensive Clinical Trials Unit at University College London (UCL), 90 High Holborn, London, WC1V 6LJ, UK.
Cancer Research UK & UCL Cancer Trials Centre, 90 Tottenham Court Road, London, W1T 4TJ, UK.
Trials. 2020 Mar 30;21(1):301. doi: 10.1186/s13063-020-04248-8.
In rare cancers or subtypes of common cancers, a comparison of multiple promising treatments may be required. The selected treatment can then be assessed against the standard of care (if it exists) or used as a backbone for combinations with new, possibly targeted, agents. There could be different experimental therapies or different doses of the same therapy, and either can be done in combination with standard treatments. A 'pick-the-winner' design is often used, which focuses on efficacy to select the most promising treatment. However, a treatment with a slightly lower efficacy compared to another treatment may actually be preferred if it has a better toxicity or quality of life profile, is easier to administer, or cheaper.
By pre-defining a margin of practical equivalence in order to calculate the sample size, a more flexible assessment can be made of whether the treatments have very different effects or are sufficiently close so that other factors can be used to choose between them. Using exact binomial probabilities, we calculated the sample size for two- and three-arm randomised selection trials including a margin of practical equivalence with a variety of input parameters.
We explain conceptually the margin of practical equivalence in this paper, and provide a free user-friendly web application to calculate the required sample size for a variety of input parameters.
The web application should help promote the randomised selection design with a margin of practical equivalence, which provides greater flexibility than the 'pick-the-winner' approach in assessing the results of selection trials.
在罕见癌症或常见癌症的亚型中，可能需要对多种有前景的治疗方法进行比较。然后可以根据护理标准（如果存在）评估所选治疗方法，或将其用作与新的、可能是靶向的药物联合使用的基础。可能存在不同的实验性疗法或相同疗法的不同剂量，并且两者都可以与标准治疗联合使用。通常采用“选出优胜者”的设计，该设计侧重于疗效以选择最有前景的治疗方法。然而，如果一种治疗方法的毒性或生活质量更好、更易于给药或更便宜，那么与另一种治疗方法相比疗效略低的治疗方法实际上可能更受青睐。
通过预先定义实际等效性的界限来计算样本量，可以对治疗方法是否具有非常不同的效果或是否足够接近从而可以使用其他因素在它们之间进行选择进行更灵活的评估。使用精确的二项式概率，我们计算了双臂和三臂随机选择试验的样本量，包括具有各种输入参数的实际等效性界限。
我们在本文中从概念上解释了实际等效性界限，并提供了一个免费的用户友好型网络应用程序来计算各种输入参数所需的样本量。
该网络应用程序应有助于推广具有实际等效性界限的随机选择设计，这在评估选择试验结果时比“选出优胜者”方法提供了更大的灵活性。
