I take issue with the definition of evidence-based medicine implied.
Evidence based medicine recognizes a continuum of strength of inference
related to the strength of study design and conduct (as far as protection
against bias) that creates a hierarchy. It recognizes that clinicians
(because EBM is a clinical paradigm) need to determine what is the highest
level of evidence available to answer a specific clinical question. The
predominance of the RCT and the systematic review come from the predominance
of treatment clinical questions (and the availability of treatment studies)
in practice. It just takes a quick look at the Users Guides to the Medical
Literature series in JAMA or at the series on the Rational Cllinical
Examination to understand that the scope of EBM is not limited to any
specific question type or topic.
Consideration to a hierarchy of evidence is only one part of EBM (other
components include the incorporation of patient values and preferences, of
reality constraints, and expertise).
Thus, the methods David attributes to HTA are no different than those
involved in the clinical practice of EBM.
The need to make policy recommendations based on evidence and to incorporate
evidence in an explicit fashion has come associated with the need to have a
classification system for the evidence and a separate one for the
recommendations. I would suggest people look at a more modern approach of
this issue in the most recent ACCP Consensus on Antithrombotic treatment
(Chest, 2001). Again, this is different than the use of evidence at the
> -----Original Message-----
> From: Doggett, David [SMTP:[log in to unmask]]
> Sent: Friday, August 17, 2001 10:32 AM
> To: [log in to unmask]
> Subject: Re: Randomized versus non-randomized studies
> This question highlights the difference between evidence-based medicine
> it has been defined and practiced in systematic reviews) and technology
> assessment. EBM meta-analyses and systematic reviews have confined
> themselves almost exclusively to RCTs. Thus, the topics covered by EBM
> limited to questions addressed by RCTs. Technology assessment (TA) does
> have that luxury. We must present decision makers with the current state
> knowledge, regardless of the source; although, it is essential to
> analyze the reliability of the data.
> I recently gave a talk on meta-analysis of uncontrolled studies at the
> annual meeting of the International Society for Technology Assessment in
> Health Care that was here in Philadelphia in June. Our approach has been
> use an evidence hierarchy only to guide our literature searches and
> inclusion criteria, not to assign points by which to weight evidence.
> if there are a number of double-blind RCTs, we do a meta-analysis of
> Lesser designs (unblinded RCT, other controlled studies, uncontrolled
> studies) will then only be looked at for any additional evidence they may
> provide, such as on special patient groups, prognostic factors, etc. But
> there are no dbRCTs, we use whatever there is on the next level down the
> evidence hierarchy.
> In addition to the Ioannidis article cited by Sontheimer, there are other
> interesting articles on randomized versus nonrandomized studies. One is
> "Randomized, Controlled Trials, Observational Studies, and the Hierarchy
> Research Designs"
> Concato J, Sha N and Horwitz RI, N Engl J Med, 2000, 342:1887-92. This
> study found little difference in effect sizes in 55 RCTs and 44 controlled
> studies of five different medical topics.
> On the other hand, another study, "Assignment Methods in Experimentation:
> When Do Nonrandomized Experiments Approximate Answers From Randomized
> Experiments?" Heinsman DT and Shadish WR, Psych Meth, 1995, 1:154-69,
> substantial differences in effect sizes in 51 RCTs vs. 47 controlled
> of four topics in education research. These two contrasting findings show
> that the problem is topic specific. Furthermore, these latter authors
> on to do multiple regression analysis of various study design and
> variables in the studies. That is, they correlated the study variables to
> the effect size. What they found was that randomization was seventh in
> top ten ranking of study variables affecting the effect size. Knowing
> correlation coiefficeints, they were then able to adjust the study results
> for these variables. After adjustment there was little or no difference
> the effect sizes of the studies.
> Sometimes there are not any controlled trials, only uncontrolled case
> series. Then it is necessary to go to the literature and synthesize a
> historical control. This is also good practice for assessing the validity
> of active controls in RCTs without a no-treatment group. This procedure
> problematic and has been examined in the study "Randomized versus
> Controls for Clinical Trials" Sacks H, Chalmers TC, Smith H Jr; Am J Med,
> 1982, 72:233-40. These authors found that using historical controls
> frequently exagerates the effect size. While treatment group results were
> similar regardless of the comparison design, historical controls usually
> fared worse than parallel controls, thus accounting for the exageration in
> effect size. Because of this potential exageration, small or modest
> sizes found with historical controls are not very reliable; however, we
> seen some situations where the effect size with historical controls was so
> large and striking that the findings could not be ignored, and in fact
> strong evidence that there was no equipoise, and an RCT might be
> This raises a point that has always puzzled me. RCTs are only considered
> ethical if there is equipoise. But what can the evidence be for
> EBM only recognizes RCTs as valid evidence. As far as I know, EBM is
> on what the evidence must be for equipoise. Any thoughts anyone?
> David L. Doggett, Ph.D.
> Senior Medical Research Analyst
> Health Technology Assessment and Information Services
> ECRI, a non-profit health services research organization
> 5200 Butler Pike
> Plymouth Meeting, Pennsylvania 19462, U.S.A.
> Phone: (610) 825-6000 x5509
> FAX: (610) 834-1275
> e-mail: [log in to unmask]
> -----Original Message-----
> From: Sontheimer, Daniel MD [mailto:[log in to unmask]]
> Sent: Friday, August 17, 2001 8:30 AM
> To: [log in to unmask]
> I thought someone might have started kicking this one around, particularly
> with all the recent discussion on evidence grading. From JAMA,
> Ioannidis, J et al. "Comparison of Evidence of Treatment Effects in
> Randomized and Nonrandomized Studies"
> the authors state:
> "Although we perused several hundreds of meta-anlyses, the vast majority
> regarded the randomized design as a prerequisite for eligibility and most
> them did not even cite the nonrandomized studies. This is unfair for
> epidemiological research that may offer some complementary insights to
> provided by randomized trials. We propose that future systematic reviews
> and meta analyses should pay more attention to the available randomized
> data. It would be wrong to reduce the efforts to promote randomized
> so as to obtain easy answers from nonrandomized designs. However,
> nonrandomized evidence may also be useful and may be helpful in the
> interpretation of randomized results."
> I can see their point, but have a little trouble with using the term
> Limiting to randomized data provides a uniform framework for building a
> systematic review or meta-analysis. There is something to be said for
> keeping it simple. Perhaps, citing of nonrandomized trials that are
> discrepant would be helpful. Any other thoughts?
> Dan Sontheimer
> Assoc. Director Spartanburg Family Medicine Residency
> Spartanburg, SC USA
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