Department of Geriatric Medicine/Nijmegen Alzheimer Centre, Donders Institute for Brain, Cognition and Behaviour, Radboud University Nijmegen Medical Centre, The Netherlands.
Eval Health Prof. 2011 Jun;34(2):151-63. doi: 10.1177/0163278710361925. Epub 2010 May 10.
While designing a trial to evaluate a complex intervention, one may be confronted with the dilemma that randomization at the level of the individual patient risks contamination bias, whereas cluster randomization risks incomparability of study arms and recruitment problems. Literature provides only few solutions to this dilemma and these are not always feasible. As an alternative solution for this dilemma, we developed a new two-stage randomization method called pseudo cluster randomization. In the first stage, the clusters (e.g., recruiting physicians) are randomized into two groups: one group of clusters in which the majority of the participants (e.g., 80%) will receive the experimental treatment; one group of clusters in which the majority will receive the control condition. Following this, the second stage of the randomization involves randomly assigning participants within clusters in the proportions determined by the first stage. This has important advantages. Compared with cluster randomization the potential occurrence of baseline incomparability of treatment arms and poor recruitment is reduced, because the physicians who recruit the participants are unable to know in advance which treatment condition the next participant they recruit will be assigned to. Limiting the exposure of half of the physicians to the innovative intervention lowers risk of contamination bias. When this type of contamination bias is present, pseudo cluster randomization can be more efficient than individual or cluster randomization in that smaller number of study participants is needed to achieve a predefined power.
在设计一项评估复杂干预措施的试验时，可能会面临这样的困境：在个体患者层面进行随机分组可能会导致污染偏倚，而整群随机分组则可能导致研究组之间不可比和招募问题。文献中仅提供了少数几种解决这一困境的方法，但并非总是可行。作为解决这一困境的替代方案，我们开发了一种新的两阶段随机化方法，称为伪整群随机化。在第一阶段，将群组（例如，招募医生）随机分为两组：一组群组中，大多数参与者（例如 80%）将接受实验性治疗；另一组群组中，大多数参与者将接受对照条件。在此之后，第二阶段的随机化涉及按照第一阶段确定的比例在群组内随机分配参与者。这种方法具有重要的优势。与整群随机化相比，这种方法降低了治疗组基线不可比和招募不佳的潜在风险，因为招募参与者的医生无法提前知道他们接下来招募的参与者将被分配到哪种治疗条件。限制一半医生接触创新干预措施可以降低污染偏倚的风险。当存在这种类型的污染偏倚时，伪整群随机化可能比个体或整群随机化更有效，因为需要较少的研究参与者即可达到预定的效力。
