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<p><strong>You Are Here:</strong> <span class="crumb_link"><a href="/" class="crumb_link">AHRQ Archive Home</a> > <a href="/research/resarch.htm" class="crumb_link"><em>Research Activities</em> Archive</a> > <a href="." class="crumb_link">January 2004</a> </span></p>
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<td><h1><a name="h1" id="h1"></a>Pharmaceutical Research </h1>
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<p>This information is for reference purposes only. It was current when produced and may now be outdated. Archive material is no longer maintained, and some links may not work. Persons with disabilities having difficulty accessing this information should contact us at: <a href="https://info.ahrq.gov/">https://info.ahrq.gov</a>. Let us know the nature of the problem, the Web address of what you want, and your contact information. </p>
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<h2>Confounding factors may be the reason that randomized controlled trials of HRT conflict with observational studies </h2>
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<p>Recent clinical trials demonstrating that hormone replacement therapy (HRT) does not prevent coronary heart disease in women have raised doubts concerning observational studies that had shown a cardioprotective effect of HRT. Much of the explanation likely lies in what has been called the "healthy user" effect. Most women who decided to use HRT probably had a more favorable cardiovascular risk factor profile than nonusers, and these differences were due to factors not measured in many of the observational studies, explains Wayne A. Ray, Ph.D., of Vanderbilt University Medical Center, in a recent article. </p>
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<p>Dr. Ray points out that another contributing factor may be that most of the observational studies included women who had been taking HRT for some time before study followup began (prevalent users). This practice can cause two types of bias, both of which plausibly may have contributed to the discrepancy in findings between the observational and randomized studies of HRT. </p>
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<p>First, prevalent users are "survivors" of the early period of medication, which can introduce substantial bias if risk varies with time, just as in studies of operative procedures that enroll patients after they have survived surgery. Second, covariates for drug users at study entry often are plausibly affected by the drug itself. Investigators often do not adjust for these factors on the causal pathway, which may introduce confounding. A new-user design, which eliminates these biases by restricting the analysis to people under observation at the start of the current course of treatment, should be used more frequently in pharmacoepidemiology research, concludes Dr. Ray. Dr. Ray's work was supported in part by the Agency for Healthcare Research and Quality through a cooperative agreement (HS10384) as part of the Agency's <a href="http://certs.hhs.gov/about/certsovr.htm">Centers for Education and Research on Therapeutics</a> (CERTs) initiative. </p>
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<p>See "Evaluating medication effects outside of clinical trials: New-user designs," by Dr. Ray, in the <em>American Journal of Epidemiology</em> 158(9), pp. 915-920, 2003.</p>
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<p><strong>Editor's Note:</strong> In a related study, Dr. Ray discusses the limitations of post-marketing studies of drug safety, which are usually observational studies of patients who receive drugs in the course of clinical practice. For details, see Ray, W.A. (2003, October). "Population-based studies of adverse drug effects." (AHRQ grant HS10384). <em>New England Journal of Medicine</em> 349(17), pp. 1592-1594. </p>
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