Suissa S, Edwardes M D
Division of Clinical Epidemiology, Royal Victoria Hospital, Montréal, Québec, Canada.
Epidemiology. 1997 May;8(3):275-80. doi: 10.1097/00001648-199705000-00008.
Nonexperimental studies using computerized databases often give rise to missing or partially available information on confounders. A frequent situation occurs when data on exposure are available for all subjects of a case-control study, but data on confounders are available only for the cases but not for the controls. In that situation, the fact of confounding can be verified by assessing the association between exposure and a confounder in the cases, but the data are insufficient to produce an adjusted estimate of the relative risk if confounding is found to be present. We propose simple conditions under which an adjusted estimate of the relative risk can be obtained when data on a confounder are available only for the cases, and we derive formulae for the estimator and its confidence limits. The method requires an external estimate of the confounder prevalence or, additionally, of the confounder-exposure odds ratio. We illustrate the technique with data from a nested case-control study of the risk of acute cardiac death associated with the use of bronchodilator drugs within a cohort of 12,301 asthmatics, with smoking as the confounder of interest.
使用计算机化数据库进行的非实验性研究常常会导致混杂因素的信息缺失或部分可得。一种常见的情况是，在病例对照研究的所有受试者中都有暴露数据，但混杂因素的数据仅在病例组中可得，而对照组中没有。在这种情况下，可以通过评估病例组中暴露与混杂因素之间的关联来验证混杂的存在，但如果发现存在混杂，这些数据不足以得出相对风险的调整估计值。我们提出了一些简单的条件，在这些条件下，当混杂因素的数据仅在病例组中可得时，可以获得相对风险的调整估计值，并推导了估计量及其置信区间的公式。该方法需要对混杂因素的患病率进行外部估计，或者另外还需要对混杂因素-暴露比值比进行估计。我们用来自一项巢式病例对照研究的数据来说明该技术，该研究在一个由12301名哮喘患者组成的队列中，研究使用支气管扩张剂药物与急性心源性死亡风险之间的关联，吸烟是感兴趣的混杂因素。
