Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts, USA.
Pharmacoepidemiol Drug Saf. 2019 May;28(5):665-670. doi: 10.1002/pds.4729. Epub 2019 Feb 20.
Implementing a cohort study in longitudinal healthcare databases requires looking back over some covariate assessment period (CAP) preceding cohort entry to measure confounders. We used simulations to compare fixed-duration versus all-available CAPs for confounder adjustment in the presence of differences in available baseline time between exposure groups.
We simulated cohorts of 10 000 patients with binary variables for a single confounder, exposure, and outcome. Baseline time was simulated based on the observed distribution in a claims-based comparison of statin users versus nonusers. We compared bias after measuring confounders using fixed-duration and all-available CAPs, both when exposure groups had similar and discrepant amounts of available baseline time.
When the comparison groups had similar amounts of baseline time, an all-available CAP was less biased than a fixed-duration CAP. When baseline time differed between comparison groups, the preferable CAP approach depended on the direction of confounding and which exposure group had higher covariate sensitivity. These findings were consistent in direction across sensitivity analyses.
In certain settings of differential available baseline time between exposure groups, the all-available CAP was more biased than the fixed-duration CAP. The relative directions and strengths of confounding and misclassification biases are an important consideration when choosing between a fixed-duration or all-available CAP, but they are often unknown. Therefore, we recommend comparing the amount of available baseline time between exposure groups. When there is a large discrepancy, despite appropriate design choices, we recommend a fixed-duration approach to avoid potential increases in bias because of differential data availability.
在纵向医疗保健数据库中实施队列研究需要回顾队列入组前的一段时间（CAP），以测量混杂因素。我们使用模拟比较了在暴露组之间可用基线时间存在差异的情况下，固定时长和所有可用 CAP 用于混杂因素调整的效果。
我们模拟了 10000 名患者的队列，其中包含一个混杂因素、暴露和结局的二分类变量。根据他汀类药物使用者与非使用者的索赔比较中观察到的分布，模拟了基线时间。我们比较了使用固定时长和所有可用 CAP 测量混杂因素后的偏倚，同时比较了暴露组具有相似和不同可用基线时间的情况。
当比较组具有相似的基线时间时，所有可用 CAP 比固定时长 CAP 的偏倚更小。当比较组的基线时间存在差异时，首选的 CAP 方法取决于混杂的方向以及哪个暴露组具有更高的协变量敏感性。这些发现在敏感性分析中具有一致的方向。
在暴露组之间可用基线时间存在差异的某些情况下，所有可用 CAP 比固定时长 CAP 的偏倚更大。混杂和分类错误偏倚的相对方向和强度是在固定时长或所有可用 CAP 之间选择时的重要考虑因素，但通常是未知的。因此，我们建议比较暴露组之间的可用基线时间。当存在很大差异时，尽管进行了适当的设计选择，我们建议采用固定时长方法，以避免因数据可用性差异而导致潜在的偏倚增加。
