The primary criticism of observational studies is that there is no way to know the extent of unmeasured confounding.
Randomized controlled trials (RCTs) have their own limitations. They often exclude patients with co-morbid conditions and select the most adherent patients using a pre-randomization run-in phase.
However, there is another problem with RCTs, one that is not widely recognized. Quoting myself in a forthcoming paper (link to abstract (email me for reprint)):
In RCTs patients have uncertainty about what treatment they are receiving. A patient receiving an active drug or therapy might falsely believe that they are receiving the placebo or sham therapy. Outside of the RCT environment, a patient who is prescribed a drug by their physician will be sure that they are receiving the active drug. We would expect placebo effects to be stronger if patients were unaware that they might be given a placebo. Similarly, we might expect active treatments to be more effective if there was no uncertainty about treatment receipt. While there has been great emphasis about the importance of concealing treatment assignment, this concealment creates uncertainty within the patient about treatment assignment.
Treatment uncertainty could affect subjects’ behavior (such as adherence) and subjective well being. Given the evidence about placebo effects, it’s not unreasonable to speculate that these uncertainty effects could be substantial. Further, treatment uncertainty also might also affect who is willing to participate in the studies. For example, patients’ who want the newest therapy might be unwilling to risk getting randomized to placebo.
In the next post, I will formalize these ideas. In the final post of this series, I will propose a solution.