Addressing the issue of channeling bias in observational studies with propensity scores analysis.
Addressing the issue of channeling bias in observational studies with propensity scores analysis.
复制标题
DOI：
10.1016/j.sapharm.2005.12.001
复制
发表时间：
2006-03-01
期刊：
影响因子：
--
通讯作者：
Schommer, Jon C
中科院分区：
文献类型：
--
作者：
Lobo, Francis S;Wagner, Samuel;Schommer, Jon C
随机临床试验（RCT）仍然是确定药物效用的黄金标准，特别是从安全性和有效性的角度来看。然而，限制性的入选标准和严格的方案可能是将RCT结果推广到真实的世界实践和结果的障碍。观察性研究克服了RCT的这些局限性，因为它们代表了真实的世界人群和实践。尽管如此，归因因果关系仍然是观察性研究的主要局限性，因为受试者的治疗分配是非随机的。非随机分配可能导致被比较的组之间的风险因素不平衡，从而使治疗效果的估计发生偏倚。由于通道现象，非随机分配在比较来自相似治疗类别的较旧与较新药物的观察性研究中可能特别成问题。当具有相似适应症的药物治疗优先处方给具有不同基线疾病的患者组时，会发生重叠。在这篇手稿中，我们讨论了现象的通道和使用的统计技术称为倾向分数分析，可能调整通道的影响。在本文中，我们讨论了用于确定衍生倾向评分质量的测试，利用倾向评分的各种技术，以及这种技术的潜在局限性。随着越来越多的高质量的药物和医疗索赔数据用于观察性研究，必须给予更多的关注，以分析技术，调整最佳的非随机分配和由此产生的通道偏见。对于使用观察性研究设计的研究，倾向评分分析提供了一个合理的解决方案，以解决非随机分配的局限性，特别是当RCT过于昂贵，耗时或不符合伦理道德时。
Randomized Clinical Trials (RCTs) remain the gold standard for determining the utility of pharmaceuticals especially from a safety and efficacy standpoint. However, restrictive entry criteria and stringent protocols can be barriers to generalizing RCT findings to real world practices and outcomes. Observational studies overcome these limitations of RCTs since they are representative of real world populations and practices. Nonetheless, attributing causality remains a major limitation in observational studies, due to the non-random assignment of subjects to treatment. Non-random assignment can lead to imbalances in risk-factors between the groups being compared and thus bias the estimates of the treatment effect. Non-random assignment can be particularly problematic in observational studies comparing older versus newer pharmaceuticals from similar therapeutic classes due to the phenomenon of channeling. Channeling occurs when drug therapies with similar indications are preferentially prescribed to groups of patients with varying baseline prognoses. In this manuscript we discuss the phenomenon of channeling and the use of a statistical technique known an propensity scores analysis which potentially adjusts for the effects of channeling. During the course of this manuscript we discuss tests for determining the quality of the derived propensity score, various techniques for utilizing propensity scores, and also the potential limitations of this technique. With the increasing availability of high quality pharmaceutical and medical claims data for use in observational studies, increased attention must be given to analytic techniques that adjust optimally for non-random assignment and resulting channeling bias. For research studies using observational study designs, propensity score analysis offers a reasonable solution to address the limitation of non-random assignment, especially when RCTs are too costly, time-consuming or not ethically feasible.