Are The Effects of Medications Mainly Due to Placebo?

According to the authors of a recent paper, “the placebo response in clinical trials has four components: regression to the mean (RTM), measurement artefacts, natural tendency (NT) of the disease, and the genuine placebo effect”. The objective of their analysis was to determine what contributes to the size of the placebo effect in clinical drug trials by meta-regressions of randomized placebo-controlled clinical trials.

The authors identified 5 diseases where data on the rates of NT were available to search for a sample of n=150 (5×30) RCTs. They extracted various study descriptors and performed meta-regressions to predict improvement in treatment and placebo groups. The investigators sampled 30 trials each from the following diagnoses:

• osteoarthritis of the knee,
• irritable bowel syndrome,
• depression,
• sleep disorders,
• migraine,

and extracted relevant information. They estimated the effects due to RTM and NT and analyzed the improvement in the placebo and treatment groups by fitting two regression models. Both models were highly significant, explaining 72% of the variance. Improvement in the placebo group can be significantly predicted by improvement in the treatment group (beta= .84), whether a study was analyzed according to intention to treat (beta= -.10) or was a multicenter study (beta= .12). Improvement in the treatment group can be explained by the improvement in the placebo group (beta= .83), whether a study was a multi-center trial (beta = -.16), and by RTM (beta= -.18). The treatment effect is smaller in sleep studies (beta= -.17).

The authors concluded that the high correlation of r= .73 between placebo improvement and treatment improvement rates is genuine and not explainable by study or disease characteristics. We conclude from our data that the placebo-effect is the major driver of treatment effects in clinical trials that alone explains 69% of the variance. This leaves only limited space for effects due to pharmacological substances. Context effects are more important than pharmacological ones in the conditions studied by us.

Walach (senior author of the paper) offers the following explanation for the findings:

“The design of a clinical study, with blinding and randomisation, fulfils the formal criteria necessary to establish a generalised entanglement correlation [6-8]. This would mean: part of the therapeutic effect of a pharmacological substance is also found in the control group; but only because an entanglement correlation was generated by the blinding and randomisation. To put it another way: it is not really possible to draw any conclusions about the true effects of verum interventions based on such studies. Rather, one would have to use very different study types and extract the effect by combining the different data, as we once proposed. If one were to take these effects really seriously, the methodological canon would crumble quite quickly. But they are also the reason why, in interventions where the specific effects may be very small, it is not possible to separate ‘real’ from ‘fake’ effects by means of blinded, placebo-controlled studies.”

I might suggest an alternative explanation:

SLOPPY SCIENCE.

Let me explain:

• The authors lumped together trials of various drugs as though they are a homogeneous entity in terms of effectiveness beyond placebo (which, of course, they are not).
• The placebo response is the measured improvement of a patient in a clinical trial after receiving a sham treatment. Yet, the authors claim “the placebo response in clinical trials has four components: regression to the mean (RTM), measurement artefacts, natural tendency (NT) of the disease, and the genuine placebo effect”. This is nonsense, and I even fear that the authors know it.
• The paper’s ‘highlight’ claims that contextual factors like expectations and doctor-patient interactions drive healing. Yet, these phenomena are seperate from the placebo-effect and were not the subject of this investigation.
• Correlation is not causation.

I am surprised that the Journal of Clinical Epidemiology published this rubbish!