Use of disease risk scores in pharmacoepidemiologic studies
Use of disease risk scores in pharmacoepidemiologic studies
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DOI：
10.1177/0962280208092347
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发表时间：
2009-02-01
影响因子：
2.3
通讯作者：
Ray, Wayne A.
中科院分区：
文献类型：
--
作者：
Arbogast, Patrick G.;Ray, Wayne A.
自动化数据库越来越多地用于药物流行病学研究。这些数据库包括处方药记录和与医疗保健提供者的接触记录，从中可以为药物暴露和潜在混杂因素的协变量构建非常详细的替代指标。通常可以跟踪这些变量的日常变化。然而，虽然这些信息通常对于研究成功至关重要，但其数量可能会给统计分析带来挑战。一种常见的方法是使用倾向得分。另一种方法是构建疾病风险评分。这类似于倾向得分，它根据协变量计算汇总度量。然而，疾病风险评分估计的是未暴露在油中的疾病发生的概率或发生率。然后根据疾病风险评分代替个体协变量来估计暴露与疾病之间的关联。这篇综述描述了疾病风险评分在药物流行病学研究中的使用，包括对其历史的简要讨论、对其构建和使用的更详细描述、比较其性能与传统模型的模拟研究的总结、其效用与倾向评分的比较，以及未来研究的一些进一步主题。
Automated databases are increasingly used in pharmacoepidemiologic studies. These databases include records of prescribed medications and encounters with medical care providers from which one can construct very detailed Surrogate measures for both drug exposure and covariates that are potential confounders. Often it is possible to track day-by-day changes in these variables. However, while this information is often critical for study success, its Volume can pose challenges for statistical analysis. One common approach is the use of propensity scores. An alternative approach is to construct a disease risk score. This is analogous to the propensity score in that it calculates a summary measure from the covariates. However, the disease risk score estimates the probability or rate of disease Occurrence conditional oil being unexposed. The association between exposure and disease is then estimated adjusting for the disease risk score in place of the individual covariates. This review describes the use of disease risk scores in phamacoepidemiologic studies, and includes a brief discussion of their history, a more detailed description of their construction and use, a summary of simulation Studies comparing their performance vis-a-vis traditional models, a comparison of their utility with that of propensity scores, and some further topics for future research.