Michael E. DeBakey VA Medical Center Stroke Program and the Department of Neurology, Baylor College of Medicine, Houston, Texas, USA.
Stroke. 2010 Apr;41(4):765-70. doi: 10.1161/STROKEAHA.109.574103. Epub 2010 Feb 18.
Outcome from stroke is highly dependent on baseline conditions. Patients with stroke have a wide range of severities, ages, and etiologies and it has proven difficult to achieve randomization of key variables in clinical trials. We present a new post hoc approach to achieve balance among selected variables. To illustrate the approach, we rebalanced the National Institute of Neurological Diseases and Stroke Recombinant Tissue Plasminogen Activator trial, in which the contribution of baseline imbalances continues to be debated.
We selected baseline stroke severity (National Institutes of Health Stroke Scale), age, and glucose as matching criteria. The closest matched placebo and treated subjects were identified based on nearness to each other in 3-dimensional Euclidean space. Matching was performed within the quintiles of National Institutes of Health Stroke Scale that have been previously used to assess balance. Subjects who could not be matched were eliminated. Outcomes were assessed using the original specified National Institute of Neurological Diseases and Stroke trial measures.
We successfully matched the 2 arms resulting in nearly identical baseline characteristics and distribution among quintiles. Despite fewer subjects after outlier elimination, the primary outcome measures remained significantly improved. After rebalancing, the magnitude of benefit was reduced by 13% to 23%. Benefit was apparent mostly in the large vessel occlusion subtype.
This study demonstrated the feasibility of rebalancing individual subjects within a randomized trial. After rebalancing and outlier elimination, recombinant tissue plasminogen activator continued to demonstrate improved outcome. That the apparent treatment effect was reduced suggests that imbalances contributed to the magnitude of the original National Institute of Neurological Diseases and Stroke outcomes. This method could in theory be applied to any data set to find matched subjects for outcome or other analyses.
脑卒中的预后高度取决于基线情况。脑卒中患者的严重程度、年龄和病因差异较大，临床试验中很难实现关键变量的随机化。我们提出了一种新的事后分析方法，以实现选定变量之间的平衡。为了说明该方法，我们重新平衡了国家神经疾病和卒中研究所重组组织型纤溶酶原激活剂试验，该试验中基线失衡的影响仍存在争议。
我们选择基线脑卒中严重程度（国立卫生研究院脑卒中量表）、年龄和血糖作为匹配标准。根据彼此在三维欧几里得空间中的接近程度，确定最接近的安慰剂和治疗组匹配对象。匹配是在先前用于评估平衡的国立卫生研究院脑卒中量表五分位数内进行的。无法匹配的对象被排除。使用原始指定的国立神经疾病和卒中研究所试验措施评估结果。
我们成功地平衡了两个治疗组，导致基线特征几乎完全相同，五分位数分布也相似。尽管排除离群值后样本量减少，但主要结局指标仍显著改善。重新平衡后，获益幅度降低了 13%至 23%。获益主要见于大血管闭塞亚型。
本研究证明了在随机试验中对个体进行重新平衡的可行性。重新平衡和离群值排除后，重组组织型纤溶酶原激活剂继续显示出改善的结局。治疗效果的明显降低表明，失衡对原始国立神经疾病和卒中研究所结果的幅度有影响。该方法理论上可应用于任何数据集，以找到匹配的对象进行结局或其他分析。
