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非劣效性研究中分析人群的选择:符合方案集还是意向性分析。

Choosing the analysis population in non-inferiority studies: per protocol or intent-to-treat.

作者信息

Matilde Sanchez M, Chen Xun

机构信息

Clinical Biostatistics and Research Decision Sciences, RY34-A316, Merck Research Laboratories, P.O. Box 2000, Rahway, NJ 07065, USA.

出版信息

Stat Med. 2006 Apr 15;25(7):1169-81. doi: 10.1002/sim.2244.

Abstract

For superiority trials, the intent-to-treat population (ITT) is considered the primary analysis population because it tends to avoid the over-optimistic estimates of efficacy that results from a per-protocol (PP) population. However, the roles of the ITT population and PP population in non-inferiority studies are not clearly defined as in superiority trials. In this paper, a simulation study is conducted to systematically investigate the impact of different types of missingness and protocol violations on the conservatism or anticonservatism of analyses based on the ITT and the PP population in non-inferiority trials. We find that conservatism or anticonservatism of the PP or ITT analysis depends on many factors, including the type of protocol deviation and missingness, the treatment trajectory (for longitudinal study) and the method of handling missing data in ITT population. The requirement that non-inferiority be shown for both PP and ITT populations does not necessarily guarantee the validity of a non-inferiority conclusion and a sufficiently powered PP analysis is not necessarily powered for ITT analysis. It is important to assess the potential types and rates of protocol deviation and missingness that might occur in a non-inferiority trial and to obtain some prior knowledge regarding the treatment trajectory of the test treatment versus the active control at the design stage so that a proper analysis plan and appropriate power estimation can be carried out. In general, for the types of protocol violations and missingness considered, we find that hybrid ITT/PP analysis, which excludes non-compliant patients as in the PP analysis and properly addresses the impact of non-trivial missing data as in the MLE-based ITT analysis, is more promising by way of providing reliable non-inferiority tests.

摘要

对于优效性试验,意向性分析人群(ITT)被视为主要分析人群,因为它往往能避免因符合方案(PP)人群而导致的疗效过度乐观估计。然而,ITT人群和PP人群在非劣效性研究中的作用并不像在优效性试验中那样明确界定。在本文中,进行了一项模拟研究,以系统地调查不同类型的缺失值和方案违背对非劣效性试验中基于ITT和PP人群分析的保守性或反保守性的影响。我们发现,PP或ITT分析的保守性或反保守性取决于许多因素,包括方案偏离和缺失值的类型、治疗轨迹(对于纵向研究)以及ITT人群中处理缺失数据的方法。要求在PP和ITT人群中均显示非劣效性并不一定能保证非劣效性结论的有效性,而且效能充足的PP分析对于ITT分析而言效能不一定充足。重要的是评估非劣效性试验中可能出现的方案偏离和缺失值的潜在类型和发生率,并在设计阶段获取有关试验治疗与活性对照的治疗轨迹的一些先验知识,以便能够实施适当的分析计划和进行适当的效能估计。一般来说,对于所考虑的方案违背和缺失值类型,我们发现混合ITT/PP分析,即像PP分析那样排除不依从患者,并像基于最大似然估计的ITT分析那样妥善处理非平凡缺失数据的影响,通过提供可靠的非劣效性检验更具前景。

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