Dehbi Hakim-Moulay, Devlins Sean, Iasonos Alexia, Nankivell Matthew, Gilbert Duncan, O'Quigley John
Comprehensive Clinical Trials Unit, University College London, London, UK.
Memorial Sloan Kettering Cancer Centre, New York, NY, USA.
Stat Med. 2025 May;44(10-12):e70118. doi: 10.1002/sim.70118.
A dose optimization trial in oncology may be performed to compare an approved dose level of a given drug with a reduced dose level, testing the hypothesis that efficacy is maintained whilst reducing side effects and consequently improving adherence and quality-of-life. This is particularly relevant with modern therapeutic agents whose mechanisms of action imply that efficacy may not necessarily be linearly related to the dose. Using a conventional non-inferiority framework leads to large sample sizes that are often unfeasible in the phase IV setting. An alternative is to use a margin of practical non-inferiority, which we define in this paper and show how it can be exploited to justify a sample size. Whilst defining the extent of the margin, researchers also pre-specify the other dimensions of interest, such as receptor occupancy and/or side effects and quality-of-life, that will be used to establish practical non-inferiority if the observed efficacy of the reduced dose level lies within the margin. The comparison of efficacy is based on the observed difference between the reduced and the approved levels, instead of the confidence interval of this difference, leading to a reduction in sample size. The reduction in precision due to the smaller sample size is compensated by formally pre-specifying the additional dimensions to the decision process, allowing a more thorough assessment of the opportunity to reduce a dose in practice, with the many advantages that this may involve.
肿瘤学中的剂量优化试验可用于比较给定药物的批准剂量水平与降低后的剂量水平,检验在降低副作用从而提高依从性和生活质量的同时维持疗效的假设。这对于现代治疗药物尤为重要,因为其作用机制表明疗效不一定与剂量呈线性关系。使用传统的非劣效性框架会导致样本量过大,在IV期试验中往往不可行。另一种方法是使用实际非劣效性界值,我们在本文中对其进行了定义,并展示了如何利用它来确定样本量。在定义界值范围时,研究人员还预先指定其他感兴趣的维度,如受体占有率和/或副作用及生活质量,如果降低剂量水平的观察到的疗效在界值范围内,将用这些维度来确定实际非劣效性。疗效比较基于降低后的剂量水平与批准剂量水平之间观察到的差异,而不是该差异的置信区间,从而减少了样本量。由于样本量较小导致的精度降低通过在决策过程中正式预先指定额外维度得到补偿,从而能够更全面地评估在实际中降低剂量的机会及其可能带来的诸多优势。