But Marks points out that the FDA typically follows the advice of its independent advisory committees — and the one that evaluated MDMA in June overwhelmingly voted against approving the drug, citing problems with clinical trial design that the advisers felt made it difficult to determine the drug’s safety and efficacy. One concern was about the difficulty of conducting a true placebo-controlled study with a hallucinogen: around 90% of the participants in Lykos’s trials guessed correctly whether they had received the drug or a placebo, and the expectation that MDMA should have an effect might have coloured their perception of whether it treated their symptoms.
Another concern was about Lykos’s strategy of administering the drug alongside psychotherapy. Rick Doblin, founder of the Multidisciplinary Association for Psychedelic Studies (MAPS), the non-profit organization that created Lykos, has said that he thinks the drug’s effects are inseparable from guided therapy. MDMA is thought to help people with PTSD be more receptive and open to revisiting traumatic events with a therapist. But because the FDA doesn’t regulate psychotherapy, the agency and advisory panel struggled to evaluate this claim. “It was an attempt to fit a square peg into a round hole,” Marks says.
Yeah, that’s the thing with placebo. It’s surprisingly effective, and separating the psychological effect from actual chemistry can be very tricky. If most participants can correctly identify if they’re bing fed the real drug or a placebo, it makes it impossible to figure out how much each effect contributes to the end result. Ideally, you would only use effective medicine that does not need the placebo effect to actually work.
Imagine, if all medicine had lots of placebo effect in them. How would you treat patients who are in a coma or otherwise unconscious?
So, let’s just use an example of a pill that treats headaches so I can understand, because I’m kinda stupid.
It works super well, and most patients taking it in double blind trials find it relieves headache pain considerably. Why is it a bad thing, to the point of rejecting it as a treatment, that the patient feels that the pill is working very well and has concluded on their own that this is probably not a placebo?
I can understand a patient being misled by coincidence, but surely a measurable, verifiable, and repeatable benefit to the patient compared to pills without medicinal ingredients would warrant a different conclusion, wouldn’t it?
In your coma scenario, I’m sure there is a statistical analysis that can be performed to show with a degree of certainty that a specific medication has a higher likelihood of being effective than a placebo in a controlled experiment.
I commented on this same story a while ago when it first broke that it was likely to be rejected and I don’t think anyone explained it in the thread.
Statistical tests are very picky. They have been designed by mathematicians in a mathematical ideal vacuum void of all reality. The method works in those ideal conditions, but when you take that method and apply it in messy reality where everything is flawed, you may run into some trouble. In simple cases, it’s easy to abide by the assumptions of the statistical test, but as your experiment gets more and more complicated, there are more and more potholes for you to dodge. Best case scenario is, your messy data is just barely clean enough that you can be reasonably sure the statistical test still works well enough and you can sort of trust the result up to a certain point.
However, when you know for a fact that some of the underlying assumptions of the statistical test are clearly being violated, all bets are off. Sure, you get a result, but who in their right mind would ever trust that result?
If the test says that the medicine is works, there’s clearly financial incentive to believe it and start selling those pills. If it says that the medicine is no better than placebo, there’s similar incentive to reject the test result and demand more experiments. Most of that debate goes out the window if you can be reasonably sure that the data is good enough and the result of your statistical test is reliable enough.