Kong L, Kohberger R C, Koch G G
Department of Biostatistics, Graduate School of Public Health, University of Pittsburgh, Pennsylvania 15261, USA.
J Biopharm Stat. 2006;16(4):555-72. doi: 10.1080/10543400600721596.
Immunogenicity trials that study the immune responses to vaccination are often used in the vaccine development process as alternatives to clinical efficacy trials. The comparisons of immune responses among various treatment groups are conducted in a non-inferiority or equivalence framework. When there exists a level of immune response that correlates with protection against disease, it is of interest to compare the proportion of responders as defined as response above a specific level or as a predefined increase in immune levels for post-vaccination levels above pre-vaccination levels. Since vaccines often contain several antigens, the correlations between the immune responses need to be taken into account in the analysis. In this paper, we describe appropriate testing methods for demonstrating the non-inferioritylequivalence of two treatments on each of the binomial endpoints. We conduct a comprehensive simulation study to shed light on how the Type I error and power are affected and to what extent when correlated multiple binomial endpoints are present in the vaccine trials. We also illustrate the computation of power for assessment of non-inferioritylequivalence in real studies.
在疫苗研发过程中，研究疫苗接种免疫反应的免疫原性试验常被用作临床疗效试验的替代方法。各治疗组间免疫反应的比较是在非劣效性或等效性框架下进行的。当存在与疾病防护相关的免疫反应水平时，比较达到特定水平以上反应者的比例，或比较接种后相对于接种前免疫水平有预定义升高的反应者比例，是很有意义的。由于疫苗通常包含多种抗原，分析时需要考虑免疫反应之间的相关性。在本文中，我们描述了用于证明两种治疗方法在每个二项式终点上非劣效性/等效性的适当测试方法。我们进行了一项全面的模拟研究，以阐明当疫苗试验中存在相关的多个二项式终点时，I型错误和检验效能是如何受到影响以及受影响的程度。我们还说明了在实际研究中评估非劣效性/等效性时检验效能的计算方法。
