Kundt G, Glass A
University of Rostock, School of Medicine, Institute of Biostatistics and Informatics in Medicine and Ageing Research, Ernst-Heydemann-Str. 8, 18057 Rostock, Germany.
Methods Inf Med. 2012;51(1):55-62. doi: 10.3414/ME10-01-0078. Epub 2011 Jul 26.
If in a clinical trial prognostic factors are known in advance, it is often recommended that randomization of patients should be stratified. The best-known method is permuted-block randomization within strata. But it suffers from the disadvantage that imbalance still occurs in the trial as a whole if there are a large number of strata, or/and the block sizes are too large for the number of patients. The results of Hallstrom and Davis are appropriate for evaluating the risk of such a troubled situation by using two special cases of their general variance formula. But it is merely generally argued for whichever practical situations these special cases are valid. Consequently, additional investigations are required to reveal the conditions for correct application.
We investigated the range of validity of special cases by performing computer simulations, varying a number of trial characteristics, and discuss the application of results for practical situations.
The validity of special cases is not given in each situation. Depending on block size, a binomial distribution model is valid for a permitted average maximum number of patients per stratum between 36% and 57% of considered block sizes, whereas the uniform distribution model works adequately from at least 70%. In an intermediate range of invalidity, implementation of a simulation study is necessary to compute the probability distribution of differences.
Our results are important if choosing the stratified permuted-block randomization to estimate the risk for an intolerable overall imbalance when planning a trial.
在临床试验中,如果预先知道预后因素,通常建议对患者进行分层随机分组。最著名的方法是在各层内进行排列分组随机化。但它有一个缺点,即如果层数很多,和/或对于患者数量而言区组大小太大,那么在整个试验中仍会出现不平衡。霍尔斯特伦和戴维斯的结果适用于通过使用其一般方差公式的两个特殊情况来评估这种困境的风险。但对于这些特殊情况在哪些实际情形中有效,只是进行了一般性的论证。因此,需要进一步研究以揭示正确应用的条件。
我们通过进行计算机模拟、改变一些试验特征来研究特殊情况的有效性范围,并讨论结果在实际情形中的应用。
特殊情况并非在每种情形下都有效。根据区组大小,二项分布模型对于每层允许的平均最大患者数在考虑的区组大小的36%至57%之间时有效,而均匀分布模型至少在70%时能充分发挥作用。在无效的中间范围内,有必要进行模拟研究来计算差异的概率分布。
在规划试验时,如果选择分层排列分组随机化来估计不可容忍的总体不平衡风险,我们的结果很重要。