Todd Jim, Carpenter Lucy, Li Xianbin, Nakiyingi Jessica, Gray Ron, Hayes Richard
London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK.
Int J Epidemiol. 2003 Oct;32(5):755-62. doi: 10.1093/ije/dyg150.
Randomized intervention trials in which the community is the unit of randomization are increasingly being used to evaluate the impact of public health interventions. In the design of community randomized trials (CRT), the power of the study is likely to be affected by two issues: the matching or stratification of communities, and the number and size of the communities to be randomized.
Data from three East African community intervention trials, designed to evaluate the impact of interventions to reduce human immunodeficiency virus (HIV) incidence, are used to compare the efficiency of different trial designs.
Compared with an unmatched design, stratification reduced the between-community variation in the Mwanza trial (from 0.51 to 0.24) and in the Masaka trial (from 0.38 to 0.28). The reduction was smaller in the Rakai trial where the selected communities were more homogeneous (from 0.15 to 0.11). For all trials, individual matching of communities produced estimates of between-community variation similar to those from the stratified designs. The linear association between HIV prevalence and incidence was strong in the Mwanza trial (correlation coefficient R = 0.83) and the Masaka trial (R = 0.83), but weak in the Rakai trial (R = 0.28). Unmatched study designs that use smaller communities tend to increase between-community variation, but reduce the design effect and improve study power.
These empirical data suggest that selection of homogeneous communities, or stratification of communities prior to randomization, may improve the power of CRT.
以社区作为随机化单位的随机干预试验越来越多地用于评估公共卫生干预措施的影响。在社区随机试验(CRT)的设计中,研究效能可能受到两个问题的影响:社区的匹配或分层,以及要随机化的社区数量和规模。
来自三项东非社区干预试验的数据用于比较不同试验设计的效率,这些试验旨在评估降低人类免疫缺陷病毒(HIV)发病率的干预措施的影响。
与非匹配设计相比,分层降低了姆万扎试验(从0.51降至0.24)和马萨卡试验(从0.38降至0.28)中社区间的变异。在拉凯试验中,由于所选社区更为同质化,这种降低幅度较小(从0.15降至0.11)。对于所有试验,社区的个体匹配产生的社区间变异估计值与分层设计的估计值相似。HIV患病率与发病率之间的线性关联在姆万扎试验(相关系数R = 0.83)和马萨卡试验(R = 0.83)中很强,但在拉凯试验中较弱(R = 0.28)。使用较小社区的非匹配研究设计往往会增加社区间变异,但会降低设计效应并提高研究效能。
这些实证数据表明,选择同质化社区或在随机化之前对社区进行分层,可能会提高社区随机试验的效能。