Berry D A, Fox T L
Stat Med. 1983 Jul-Sep;2(3):331-43. doi: 10.1002/sim.4780020305.
Suppression of premature ventricular contractions (PVCs) is one of the goals of antiarrhythmic therapy. In a clinical trial, however, it may be difficult to distinguish antiarrhythmic drug effect from spontaneous variation in PVCs. We propose the application of linear regression to PVC histories to ascertain drug effect in individual patients. The model determines which variables are important in explaining a patient's PVCs. One such variable indicates the presence or absence of the drug; the model determines whether the drug has an effect on the patient's PVCs, while compensating for the other explanatory variables. In addition to determining the statistical significance of any drug effect, the model estimates the strength of the effect for each patient. We demonstrate the method with data from a three-day clinical trial which used 24-hour Holter monitoring. The method is flexible and can be modified to apply to any clinical study design. It allows for inferences concerning populations and subpopulations of patients.
抑制室性早搏（PVCs）是抗心律失常治疗的目标之一。然而，在一项临床试验中，可能难以将抗心律失常药物的效果与PVCs的自发变化区分开来。我们建议应用线性回归分析PVCs病史，以确定个体患者的药物疗效。该模型确定哪些变量对于解释患者的PVCs很重要。其中一个这样的变量表明药物的存在与否；该模型在补偿其他解释变量的同时，确定药物是否对患者的PVCs有影响。除了确定任何药物效果的统计学显著性外，该模型还估计每位患者的效果强度。我们用一项为期三天的临床试验数据来演示该方法，该试验使用了24小时动态心电图监测。该方法灵活，可修改以适用于任何临床研究设计。它允许对患者群体和亚群体进行推断。
