Strategies to prevent the placebo effect from obscuring clinical trial results
“My baby had GERD, so I tied a red ribbon to her stroller and she was cured!”
“When I was diagnosed was Type 2 diabetes, I rubbed turmeric paste on the soles of my feet every night. Within a month, my blood sugar levels were normal!”
“If your knees hurt, keep a bowl of freshly ground rock salt in your room for 3 nights. Your pain will vanish.”
Do these claims sound like nonsense to you? Yet, for a few people, this medical advice will actually work, no matter how absurd it sounds. The reason---the mysterious placebo effect.
What is the placebo effect?
The placebo effect is when a person experiences a perceived improvement in their condition after receiving a treatment that has no therapeutic effect (i.e., placebos are physically and pharmacologically inert). More plainly put, people think that they are getting better even if they’re receiving an ineffective treatment or no treatment at all.
The placebo effect in clinical trials
Obviously, if someone is going to feel better in spite of receiving random or nonsensical treatments, what’s the use of the billions of dollars and years of hard work spent on rigorous, statistically sound clinical trials? The placebo effect can significantly influence the results of research on therapeutic interventions. Participants in clinical trials may show improvements simply because they believe they are receiving a beneficial treatment, even if they are actually receiving a placebo. This can make it difficult the true efficacy of the treatment being tested, making it crucial to account for placebo effects in study design and analysis.
How do we handle the placebo effect in clinical trials?
First of all, let’s understand how exactly a placebo is used in clinical trials. Researchers sometimes conduct a placebo-controlled trial: a trial in which one group of participants gets the active treatment while the other gets the placebo. Ideally, the researcher ensures that all other variables are the same between the two groups (e.g., disease status, age, comorbidities), so that any difference in trial outcomes between the two groups can be attributed to the active treatment.
Now obviously, it’s better if the participants DON’T know they’re receiving the intervention or a placebo, so that their own beliefs about their treatment don’t influence the results. That’s where we use blinding, to make sure participants don’t know whether they belong to the treatment group or the control group. And of course, it’s even more effective to use double-blinding, where neither the researchers nor the participants know who is in which group until the very end of the trial.
Other strategies to prevent the placebo effect from obscuring trial results
Over the years, researchers have developed various strategies to counter the placebo effect and thus obtain robust and reliable results. Researchers have tried out incorporating a “run-in period” into their trial design (e.g., Hui et al., 2021). This is a period at the start of the trial where EVERYONE gets a placebo, though they don’t know it’s a placebo. Those participants who report an improvement in the concerned symptoms (deemed “high placebo responders”) are then excluded from the actual clinical trial. However, this practice has been found not particularly effective (Davis et al., 1995; Laursen et al., 2019).
Another strategy to counter the placebo effect involves a two-phase, sequential parallel comparison trial design (see, for example, Mathew et al., 2017). In the first phase, participants are randomly assigned to receive either a placebo or an active treatment. Those who do not respond to the placebo proceed to the second phase, where they are once more randomized to receive either a placebo or an active treatment. The ultimate analysis incorporates combined data from both phases.
Evans et al. (2021) provide a comprehensive review of various other strategies to counter the placebo effect, which include modifications to messaging around intervention vs placebo and specific training to subjects on accurate responding.
Another very important aspect is power. If the study has a sufficiently large sample and adequate statistical power, the results are likely to be robust. In contrast, if the study has low power and very few participants in the intervention and control groups, even 1-2 persons experiencing the placebo effect can skew the results.
Conclusion
The placebo effect, though “a pain in the neck” to researchers, can’t be ignored altogether. Even if the placebo itself isn’t capable of doing anything, the placebo effect may elicit neuroendocrine responses, which can in turn interact with the autonomic nervous system and immune system (Wager & Atlas, 2015). It may not be possible to completely prevent the placebo effect from obscuring your study results. However, with a well-thought-out study design and adequate statistical power, you can be more confident about the quality of the evidence you’re generating.
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