>> The bigger problem is “depression” is not reproducibly measurable, because it has no falsifiable or biomedical marker.
That's something I like to point out using SSRIs as an example. The claim is that they increase levels of serotonin and that the cause of the depression is reduced serotonin. The thing is, nobody actually checks your serotonin levels and says "oh that's low take this." Then there's the problem of why ones serotonin is low when it wasn't always that way. There are probably many causes of depression and quite possibly some that don't lower serotonin.
If mdma makes you friendlier, does that mean that people who are shy are suffering from friendliness deficit disorder and can I get a prescription for it.
Hmm... I question a meta study that says it has finally solved the issue and put it to rest, when there are plenty of other studies saying the exact opposite.
"SSRIs might have statistically significant effects on depressive symptoms, but all trials were at high risk of bias and the clinical significance seems questionable. SSRIs significantly increase the risk of both serious and non-serious adverse events. The potential small beneficial effects seem to be outweighed by harmful effects."
All the major meta-analyses come to roughly the same conclusion, which is that anti-depressants have modest positive effects. The paper you linked to finds exactly this, but argues that the effect size they found is insignificant because of the high risk of bias. Other studies have gone to extraordinary lengths to control for potential biases and come up with a very similar effect size. Reasoning about the data is quite challenging, because we're talking about relatively small shifts in a relatively broad statistical distribution.
"Number needed to treat" is a useful epidemiological concept in this case. A perfect drug that cures every single patient has an NNT of one - for each patient you treat, one patient is successfully treated. When you translate the results of SSRI meta-analyses, you get an NNT of about seven - for every seven patients who take SSRIs, one more patient will recover than if those patients were given a placebo.
It's hard to know what to do with that information. Is it worth prescribing antidepressants to 1,000,000 people to treat 142,000 of them? On a pure cost-benefit analysis, the answer is a resounding yes. Antidepressants are relatively cheap and safe. Are you willing to take a pill every day to get a one-in-seven chance of an effective treatment? Maybe. If you're in the throes of a deep depression, you might be willing to give anything a try. If you're just feeling a bit blue, maybe not. By the same token, if you're taking antidepressants and you don't think that they're helping, you're probably right.
As a layman, I find it surprising that SSRIs were clinically approved for treatment based on a 1 in 7 chance of demonstrating positive effects. Are other medications anywhere near as ineffective? Whether antibiotics, Tylenol, or Viagra, I can't imagine any of those being effective in less than, say, 5 out of 7 cases.
>Are other medications anywhere near as ineffective?
Yes. Reviews suggest that statins have an NNT of between 50 and 200 depending on the patient's underlying risk for cardiovascular disease. Coronary stents are probably useless. Reviews of antibiotics, antivirals and corticosteroids show a wide range of NNTs and often show no positive effect.
The drug approval system has a relatively high bar for safety, but a relatively low bar for efficacy. A drug manufacturer only has to prove that their drug is effective for one particular cohort of patients with a particular disease, but doctors are then free to prescribe the drug to any patient with any disease. Many surgical interventions are never subject to a randomised controlled trial.
Good point. I think stents, and to some extent, statins, are starting to be exposed as often misused tools. Yet, for some reason, it feels politically incorrect to ask the same questions if SSRIs.
We don't really know how antidepressants work. We don't know how a lot of drugs work. Nobody knows why acetaminophen (paracetamol) cures your headache. Knowing how a drug works is useful but not essential; modern medicine relies on hundreds of drugs with unknown mechanisms of action.
The bigger problem is “depression” is not reproducibly measurable, because it has no falsifiable or biomedical marker.