Soulakova Julia N, Sampson Allan R
Department of Statistics, University of Nebraska-Lincoln, 340 Hardin Hall-North, Lincoln, NE 68583-0963 (E-mail:
Stat Biopharm Res. 2009;1(1):39-47. doi: 10.1198/sbr.2009.0004.
To determine that a combination drug is effective, the FDA requires demonstration that the combination itself is effective and that each component makes a contribution to the claimed effect. In a study with at least one component known to be effective at the considered doses, these regulatory requirements can be satisfied by showing that the combination is superior to each component. We term such a combination an efficacious combination. In a dose-response study involving combination drugs, one of which is known to be effective, we are interested in detecting those combinations which are efficacious, and for which no lower dose combination is also efficacious. We term these combinations the minimum efficacious dose set and our goal is to estimate this set. Our procedure requires first identifying all possible minimum efficacious dose sets and the corresponding hypotheses for a given design. Next, the proper testing order based on a graph representation is established and the hypotheses are tested using the "average" test under the closed testing principle. This procedure is shown to have strong control of overall error rate. The power of this procedure is studied by simulation.
为确定复方药物是否有效，美国食品药品监督管理局（FDA）要求证明该复方本身有效，且各成分对所宣称的效果有贡献。在一项研究中，若至少有一种成分在所考虑的剂量下已知有效，那么通过证明该复方优于各成分，即可满足这些监管要求。我们将这样的复方称为有效复方。在一项涉及复方药物的剂量反应研究中，其中一种成分已知有效，我们感兴趣的是检测出那些有效且不存在更低剂量复方也有效的复方。我们将这些复方称为最小有效剂量组，我们的目标是估计这个组。我们的程序首先需要针对给定设计识别所有可能的最小有效剂量组及相应假设。接下来，基于图形表示建立适当的测试顺序，并根据封闭测试原则使用“平均”检验对假设进行检验。结果表明，该程序能有效控制总体错误率。通过模拟研究了该程序的功效。
