Girman Cynthia J, Faries Douglas, Ryan Patrick, Rotelli Matt, Belger Mark, Binkowitz Bruce, O'Neill Robert
Comparative & Outcomes Evidence, Center for Observational & Real-world Evidence, Merck Sharp & Dohme, North Wales, PA 19454, USA.
J Comp Eff Res. 2014 May;3(3):259-70. doi: 10.2217/cer.14.16.
The use of healthcare databases for comparative effectiveness research (CER) is increasing exponentially despite its challenges. Researchers must understand their data source and whether outcomes, exposures and confounding factors are captured sufficiently to address the research question. They must also assess whether bias and confounding can be adequately minimized. Many study design characteristics may impact on the results; however, minimal if any sensitivity analyses are typically conducted, and those performed are post hoc. We propose pre-study steps for CER feasibility assessment and to identify sensitivity analyses that might be most important to pre-specify to help ensure that CER produces valid interpretable results.
尽管存在挑战,但医疗保健数据库在比较效果研究(CER)中的应用仍在呈指数级增长。研究人员必须了解其数据来源,以及结局、暴露因素和混杂因素是否得到充分记录,以解决研究问题。他们还必须评估是否可以充分减少偏倚和混杂因素。许多研究设计特征可能会影响结果;然而,通常很少进行敏感性分析,即便进行也多是事后分析。我们提出了CER可行性评估的预研究步骤,并确定可能最重要的预先指定的敏感性分析,以帮助确保CER产生有效的可解释结果。