Healthy Skepticism Library item: 10881
Warning: This library includes all items relevant to health product marketing that we are aware of regardless of quality. Often we do not agree with all or part of the contents.
 
Publication type: Journal Article
Lobo FS, Wagner S, Gross CR, Schommer JC.
Addressing the issue of channeling bias in observational studies with propensity scores analysis.
Res Social Adm Pharm 2006 Mar; 2:(1):143-51
http://www.ncbi.nlm.nih.gov/sites/entrez?Db=pubmed&Cmd=ShowDetailView&TermToSearch=17138506&ordinalpos=1&itool=EntrezSystem2.PEntrez.Pubmed.Pubmed_ResultsPanel.Pubmed_RVDocSum
Abstract:
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.
Keywords:
Bias (Epidemiology)*
Causality
Confounding Factors (Epidemiology)
Data Interpretation, Statistical
Drug Therapy
Humans
Models, Statistical*
Population Surveillance*/methods
Randomized Controlled Trials
Research Design*
Treatment Outcome