Inclusion of unexposed subjects improves the precision and power of self-controlled case series method

The self-controlled case series is an important method in the studies of the safety of biopharmaceutical products. It uses the conditional Poisson model to make comparison within persons. In models without adjustment for age (or other time-varying covariates), cases who are never exposed to the product do not contribute any information to the estimation. We provide analytic proof and simulation results that the inclusion of unexposed cases in the conditional Poisson model with age adjustment reduces the asymptotic variance of the estimator of the exposure effect and increases power. We re-analysed a vaccine safety dataset to illustrate.

自身对照病例系列研究（self-controlled case series）是生物制药产品安全性研究中的重要方法。该方法采用条件泊松模型开展个体内比较。在未针对年龄（或其他时变协变量）进行校正的模型中，从未接触受试产品的病例不会为参数估计提供任何有效信息。本研究通过解析推导与模拟实验证实，在经年龄校正的条件泊松模型中纳入未暴露病例，可降低暴露效应估计量的渐近方差并提升检验效能。我们通过重新分析一项疫苗安全性数据集对上述结论进行了演示说明。