Hemmelmann Claudia, El Galta Rachid, Wang Jessie, Schmitt Susanne, Arani Ramin
Hexal AG, Industriestr. 25, D-83607 Holzkirchen, Germany.
Sandoz Inc., 100 College Road West, Princeton, NJ 08540, USA.
Pharmaceuticals (Basel). 2025 Feb 20;18(3):285. doi: 10.3390/ph18030285.
: To derive the equivalence margin (EQM), typically, a "classical" meta-analysis on direct within-trial estimation of the effect size of the reference drug compared to the placebo or standard of care is performed: a certain factor of the 95% confidence interval for the pooled treatment effect compared to placebo is used. However, treatment regimens in many indications are becoming more complex (e.g., combination treatments), and for most of these clinical study data, direct comparisons are not available. On the other hand, data for the comparison of the common treatment to the reference treatment in one study and to the placebo in another study are available in some situations. : In such situations, an anchor-based indirect comparison can be applied to estimate the treatment effect of Reference vs. Placebo. This treatment effect (Reference vs. Placebo) can be estimated by calculating the difference of the two treatment effects and the variance as the sum of both variances. The 95% confidence interval of this estimated treatment effect can then be used to derive the EQM. To alleviate any concerns about the underlying assumptions of transitivity and consistency, multiple sensitivity analyses can be performed. : We present a case study for deriving the EQM using the anchor-based indirect comparison along with sensitivity analyses (i.e., direct comparison against similar reference drug, the impact of variation of treatment effect on Comparator, and effect size Reference vs. Placebo, including trial data with slightly different population characteristics) for a planned efficacy trial in the biosimilar setting. : An anchor-based indirect comparison for EQM derivation is an approach health authorities can agree to if sufficiently supported through other means, e.g., relevant sensitivity analyses.
为了得出等效性界值（EQM），通常会对参考药物与安慰剂或对照标准之间的效应大小进行直接的试验内估计，进行一项“经典”的荟萃分析：使用与安慰剂相比的合并治疗效应的95%置信区间的某个因子。然而，许多适应症的治疗方案正变得越来越复杂（例如联合治疗），对于大多数这些临床研究数据，无法进行直接比较。另一方面，在某些情况下，可以获得一项研究中常用治疗与参考治疗比较的数据以及另一项研究中与安慰剂比较的数据。
在这种情况下，可以应用基于锚定的间接比较来估计参考药物与安慰剂之间的治疗效果。这种治疗效果（参考药物与安慰剂之间）可以通过计算两种治疗效果的差异并将方差作为两者方差之和来估计。然后可以使用该估计治疗效果的95%置信区间来得出等效性界值。为了减轻对传递性和一致性等潜在假设的任何担忧，可以进行多次敏感性分析。
我们展示了一个案例研究，该研究针对生物类似药环境下的一项计划疗效试验，使用基于锚定的间接比较以及敏感性分析（即与类似参考药物的直接比较、治疗效果变化对对照药的影响以及参考药物与安慰剂的效应大小，包括具有略有不同人群特征的试验数据）来得出等效性界值。
如果通过其他方式（例如相关的敏感性分析）获得充分支持，基于锚定的间接比较来推导等效性界值是卫生当局可以认可的一种方法。
