Hernández-Díaz Sonia, Bateman Brian T, Palmsten Kristin, Schneeweiss Sebastian, Huybrechts Krista F
Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, Massachusetts.
Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, Massachusetts.
Pharmacoepidemiol Drug Saf. 2020 Sep;29(9):1151-1158. doi: 10.1002/pds.4946. Epub 2019 Dec 20.
To evaluate the use of data from population-based surveys such as the National Health and Nutrition Examination Survey (NHANES) for external adjustment for confounders imperfectly measured in health care databases in the United States.
Our example study used Medicaid Analytic eXtract (MAX) data to estimate the relative risk (RR) for prenatal serotonin-norepinephrine reuptake inhibitors (SNRIs) exposure and cardiac defects. Smoking and obesity are known confounders poorly captured in databases. NHANES collects information on lifestyle factors, depression, and prescription medications. External adjustment requires information on the prevalence of confounders and their association with SNRI use; which was obtained from the NHANES. It also requires estimates of their association with the outcome, which were based on the literature and allowed us to correct the RR using sensitivity analyses.
In MAX, the RR for the association between prenatal SNRI exposure and cardiac defects was 1.51 unadjusted and 1.20 adjusted for measured confounders and restricted to women with depression. In NHANES, among women of childbearing age with depression, the prevalence of smoking was 60.2% (95% Confidence Interval 43.2, 74.3) for SNRI users and 44.1% (39.6, 48.8) for nonusers of antidepressants. The corresponding estimates for obesity were 59.2% (43.2, 74.3) and 40.5% (35.9, 45.0), respectively. If the associations between smoking and obesity with cardiac defects are independent from each other and from other measured confounders, additional adjustment for smoking and obesity would move the RR from 1.20 to around 1.10.
National surveys like NHANES are readily available sources of information on potential confounders and they can be used to assess and improve the validity of RR estimates from observational studies missing data on known risk factors.
评估使用基于人群调查的数据，如美国国家健康与营养检查调查（NHANES），对美国医疗保健数据库中测量不完美的混杂因素进行外部调整。
我们的示例研究使用医疗补助分析提取物（MAX）数据来估计产前血清素 - 去甲肾上腺素再摄取抑制剂（SNRI）暴露与心脏缺陷的相对风险（RR）。吸烟和肥胖是已知在数据库中捕捉不佳的混杂因素。NHANES收集生活方式因素、抑郁症和处方药的信息。外部调整需要关于混杂因素的患病率及其与SNRI使用的关联信息，这些信息从NHANES获得。它还需要估计它们与结局的关联，这基于文献，并使我们能够通过敏感性分析校正RR。
在MAX中，产前SNRI暴露与心脏缺陷之间关联的RR未经调整为1.51，经测量的混杂因素调整后为1.20，并仅限于患有抑郁症的女性。在NHANES中，在患有抑郁症的育龄女性中，SNRI使用者的吸烟患病率为60.2%（95%置信区间43.2, 74.3），非抗抑郁药使用者为44.1%（39.6, 48.8）。肥胖的相应估计分别为59.2%（43.2, 74.3）和40.5%（35.9, 45.0）。如果吸烟和肥胖与心脏缺陷之间的关联彼此独立且与其他测量的混杂因素独立，对吸烟和肥胖进行额外调整会使RR从1.20降至约1.10。
像NHANES这样的全国性调查是关于潜在混杂因素的现成信息来源，它们可用于评估和提高来自观察性研究的RR估计值的有效性，这些研究缺少已知风险因素的数据。
