Kernan W N, Viscoli C M, Makuch R W, Brass L M, Horwitz R I
Department of Internal Medicine, Yale University School of Medicine, New Haven, Connecticut, USA.
J Clin Epidemiol. 1999 Jan;52(1):19-26. doi: 10.1016/s0895-4356(98)00138-3.
Trialists argue about the usefulness of stratified randomization. For investigators designing trials and readers who use them, the argument has created uncertainty regarding the importance of stratification. In this paper, we review stratified randomization to summarize its purpose, indications, accomplishments, and alternatives. In order to identify research papers, we performed a Medline search for 1966-1997. The search yielded 33 articles that included original research on stratification or included stratification as the major focus. Additional resources included textbooks. Stratified randomization prevents imbalance between treatment groups for known factors that influence prognosis or treatment responsiveness. As a result, stratification may prevent type I error and improve power for small trials (<400 patients), but only when the stratification factors have a large effect on prognosis. Stratification has an important effect on sample size for active control equivalence trials, but not for superiority trials. Theoretical benefits include facilitation of subgroup analysis and interim analysis. The maximum desirable number of strata is unknown, but experts argue for keeping it small. Stratified randomization is important only for small trials in which treatment outcome may be affected by known clinical factors that have a large effect on prognosis, large trials when interim analyses are planned with small numbers of patients, and trials designed to show the equivalence of two therapies. Once the decision to stratify is made, investigators need to chose factors carefully and account for them in the analysis.
试验者们对分层随机化的效用存在争议。对于设计试验的研究者以及使用试验结果的读者而言，这场争论引发了关于分层重要性的不确定性。在本文中，我们回顾分层随机化以总结其目的、适用情况、成果及替代方法。为了识别研究论文，我们对1966年至1997年期间的医学文献数据库（Medline）进行了检索。检索得到33篇文章，这些文章包含关于分层的原创研究或以分层为主要关注点。其他参考资料包括教科书。分层随机化可防止已知影响预后或治疗反应性的因素在治疗组间出现不均衡。因此，分层可能预防I类错误并提高小型试验（<400例患者）的检验效能，但仅当分层因素对预后来有较大影响时才会如此。分层对活性对照等效性试验的样本量有重要影响，但对优效性试验则不然。理论上的益处包括便于进行亚组分析和期中分析。理想的最大分层数尚不清楚，但专家们主张将其控制在较小范围。分层随机化仅对以下情况很重要：治疗结果可能受已知且对预后来有较大影响的临床因素影响的小型试验、计划对少量患者进行期中分析的大型试验以及旨在证明两种疗法等效性的试验。一旦做出分层的决定，研究者需要仔细选择分层因素并在分析中加以考虑。
