Eastwood B J
Department of Statistics, University of Auckland, New Zealand.
Stat Med. 1996 Dec 15;15(23):2523-38. doi: 10.1002/(SICI)1097-0258(19961215)15:23<2523::AID-SIM378>3.0.CO;2-X.
Clinical trials with more than two groups are becoming increasingly common, especially trials with both active and placebo control groups. Equal allocation of subjects to each of the groups is the most common sample allocation, but in clinical trials where the purpose is to test hypotheses of relative risk, such as vaccine trials, equal allocation can be substantially sub-optimal. Optimal allocation for clinical trials has been considered previously, but not for trials with more than two groups. In this paper optimal sample allocation for relative risk trials is investigated in a variety of situations. The main results are as follows: (i) there are many situations where reductions of more than 20 per cent in sample size can be obtained by using optimal allocation instead of equal allocation; (ii) the optimal allocation for two group studies is not optimal in general; (iii) in many situations optimal allocation increases a subject's chances of being enrolled to a test treatment, and (iv) in most cases a grid search using the likelihood score asymptotic power function is the easiest method of finding an approximately optimal allocation. Extensions to situations more general than those covered here are sketched.
涉及超过两组的临床试验正变得越来越普遍,尤其是那些同时设有活性对照组和安慰剂对照组的试验。将受试者平均分配到各个组是最常见的样本分配方式,但在旨在检验相对风险假设的临床试验中,例如疫苗试验,平均分配可能在很大程度上并非最优。此前已经考虑过临床试验的最优分配,但未涉及超过两组的试验。本文研究了在各种情况下相对风险试验的最优样本分配。主要结果如下:(i)在许多情况下,使用最优分配而非平均分配可使样本量减少20%以上;(ii)两组研究的最优分配通常并非最优;(iii)在许多情况下,最优分配会增加受试者被纳入试验治疗组的机会;(iv)在大多数情况下,使用似然得分渐近功效函数进行网格搜索是找到近似最优分配的最简便方法。文中还简要介绍了比此处所涵盖情况更一般情形的扩展内容。