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首页> 外文期刊>Pharmacoepidemiology and drug safety >Supplementary data collection with case-cohort analysis to address potential confounding in a cohort study of thromboembolism in oral contraceptive initiators matched on claims-based propensity scores.
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Supplementary data collection with case-cohort analysis to address potential confounding in a cohort study of thromboembolism in oral contraceptive initiators matched on claims-based propensity scores.

机译:具有病例群分析的补充数据收集,以解决与基于声明的倾向得分相匹配的口服避孕药引发剂血栓栓塞的队列研究中的潜在混淆。

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PURPOSE: Residual confounding is a potential limitation of pharmacoepidemiologic studies, and in particular, studies based on administrative claims data that do not capture lifestyle and clinical confounders. We describe an application of the case-cohort design to assess residual confounding by thromboembolic risk factors (e.g., smoking and obesity) not captured in claims data in a claims-based cohort study of thromboembolism among matched oral contraceptive (OC) initiators. METHODS: This study was conducted using the Ingenix Research Data Mart, a database containing medical claims for approximately 12 million members of a large health plan of the United States. We randomly sampled 701 OC initiators from cohorts of ethinyl estradiol/drospirenone (n = 22,429) and other OC initiators (n = 44,858) identified in the years 2001-2004 and matched by propensity score in a claims-based cohort study. Supplementary data on risk factors not measured in the cohort study were collected from medical records for the sample. We estimated the risk ratio of thromboembolism adjusted for the supplementary variables using Cox regression modified for a case-cohort design, and compared it to the rate ratio from the cohort study. RESULTS: The risk ratio adjusted for the supplementary variables was 0.90 (95 per cent (%) confidence interval (CI): 0.49, 1.68) which was similar to the rate ratio (0.92; 95%CI: 0.50, 1.63), indicating negligible confounding by the supplementary variables in the cohort study. CONCLUSIONS: Case-cohort methods were used to assess residual confounding in a claims-based cohort study. This approach adds to a growing number of methods to evaluate residual confounding in cohort studies.
机译:目的:残留混杂是药物流行病学研究的一个潜在局限性,特别是基于行政声明数据的研究不能捕获生活方式和临床混杂因素。我们描述了案例队列设计的应用,以评估基于权利的基于队列的队列研究中匹配的口服避孕药(OC)引发剂之间未在索赔数据中捕获的血栓栓塞危险因素(例如吸烟和肥胖)造成的残留混杂。方法:本研究是使用Ingenix研究数据集市进行的,该数据库包含美国大约1200万大型医疗计划成员的医疗索赔。我们从乙炔雌二醇/屈螺酮(n = 22,429)和其他OC引发剂(n = 44,858)的队列中随机抽取了701个OC引发剂,并在基于索赔的队列研究中与倾向评分相匹配。从队列的医疗记录中收集了队列研究中未测量的危险因素的补充数据。我们使用针对病例队列设计进行修正的Cox回归估计了针对补充变量调整后的血栓栓塞的风险比率,并将其与队列研究的比率进行了比较。结果:针对补充变量调整后的风险比为0.90(95%(%)置信区间(CI):0.49、1.68),与比率(0.92; 95%CI:0.50、1.63)相似,表明可以忽略不计在队列研究中被补充变量混淆。结论:案例队列方法被用于评估基于索赔的队列研究中的残留混杂因素。这种方法增加了越来越多的方法来评估队列研究中的残留混杂因素。

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