Levintow Sara N, Nielson Carrie M, Hernandez Rohini K, Breskin Alexander, Pritchard David, Lash Timothy L, Rothman Kenneth J, Gilbertson David, Muntner Paul, Critchlow Cathy, Brookhart M Alan, Bradbury Brian D
Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, North Carolina, USA.
NoviSci, a Target RWE Company, Durham, North Carolina, USA.
Pharmacoepidemiol Drug Saf. 2023 Jun;32(6):599-606. doi: 10.1002/pds.5623. Epub 2023 Apr 4.
This narrative review describes the application of negative control outcome (NCO) methods to assess potential bias due to unmeasured or mismeasured confounders in non-randomized comparisons of drug effectiveness and safety. An NCO is assumed to have no causal relationship with a treatment under study while subject to the same confounding structure as the treatment and outcome of interest; an association between treatment and NCO then reflects the potential for uncontrolled confounding between treatment and outcome.
We focus on two recently completed NCO studies that assessed the comparability of outcome risk for patients initiating different osteoporosis medications and lipid-lowering therapies, illustrating several ways in which confounding may result. In these studies, NCO methods were implemented in claims-based data sources, with the results used to guide the decision to proceed with comparative effectiveness or safety analyses.
Based on this research, we provide recommendations for future NCO studies, including considerations for the identification of confounding mechanisms in the target patient population, the selection of NCOs expected to satisfy required assumptions, the interpretation of NCO effect estimates, and the mitigation of uncontrolled confounding detected in NCO analyses. We propose the use of NCO studies prior to initiating comparative effectiveness or safety research, providing information on the potential presence of uncontrolled confounding in those comparative analyses.
Given the increasing use of non-randomized designs for regulatory decision-making, the application of NCO methods will strengthen study design, analysis, and interpretation of real-world data and the credibility of the resulting real-world evidence.
本叙述性综述描述了阴性对照结局(NCO)方法在评估药物有效性和安全性的非随机比较中,由于未测量或测量错误的混杂因素导致的潜在偏倚时的应用。假定阴性对照结局与所研究的治疗方法没有因果关系,同时受到与感兴趣的治疗方法和结局相同的混杂结构影响;那么治疗方法与阴性对照结局之间的关联就反映了治疗方法与结局之间存在未控制混杂因素的可能性。
我们重点关注两项最近完成的阴性对照结局研究,这些研究评估了开始使用不同骨质疏松症药物和降脂疗法的患者结局风险的可比性,阐明了可能导致混杂的几种方式。在这些研究中,阴性对照结局方法应用于基于索赔的数据源,其结果用于指导进行比较有效性或安全性分析的决策。
基于这项研究,我们为未来的阴性对照结局研究提供了建议,包括对目标患者群体中混杂机制识别的考虑、预期满足所需假设的阴性对照结局的选择、阴性对照结局效应估计值的解释,以及减轻在阴性对照结局分析中检测到的未控制混杂因素。我们建议在开展比较有效性或安全性研究之前使用阴性对照结局研究,为那些比较分析中未控制混杂因素的潜在存在提供信息。
鉴于在监管决策中越来越多地使用非随机设计,阴性对照结局方法的应用将加强对真实世界数据的研究设计、分析和解释,以及由此产生的真实世界证据的可信度。