Early Development Biostatistics, Sanofi-Aventis, Bridgewater, NJ, 08807-0890, USA.
J Immunol Methods. 2011 Oct 28;373(1-2):200-8. doi: 10.1016/j.jim.2011.08.019. Epub 2011 Sep 1.
Most therapeutic proteins induce an unwanted immune response. Antibodies elicited by these therapeutic proteins may significantly alter drug safety and efficacy, highlighting the need for the strategic assessment of immunogenicity at various stages of clinical development. Immunogenicity testing is generally conducted by a multi-tiered approach whereby patient samples are initially screened for the presence of anti-drug antibodies in a screening assay. The screening assay cut point is statistically determined by evaluation of drug-naïve samples and is typically chosen to correspond to a false positive rate of 5%. While various statistical approaches for determination of this screening cut point have been commonly adopted and described in the immunogenicity literature, the performance of these approaches has not been fully evaluated. This paper reviews various statistical approaches for cut point calculation, evaluates the impact of sampling design and variability on the performance of each statistical approach, and highlights the difference between an 'average' or 'confidence-level' cut point in order to develop more specific recommendations regarding the statistical calculation of immunogenicity screening cut points.
大多数治疗性蛋白会引起不受欢迎的免疫反应。这些治疗性蛋白引起的抗体可能会显著改变药物的安全性和疗效，这凸显了在临床开发的各个阶段对免疫原性进行策略性评估的必要性。免疫原性测试通常采用多层次的方法进行，即通过筛选试验初步筛选患者样本中是否存在抗药物抗体。筛选试验的截止值通过对无药物治疗样本的评估进行统计学确定，通常选择对应于 5%的假阳性率。虽然免疫原性文献中经常采用和描述了各种用于确定这种筛选截止值的统计方法，但这些方法的性能尚未得到充分评估。本文回顾了各种用于计算截止值的统计方法，评估了采样设计和变异性对每种统计方法性能的影响，并强调了“平均”或“置信水平”截止值之间的差异，以便就免疫原性筛选截止值的统计计算提出更具体的建议。
