what aspirin can tell us about the value of antidepressants

There’s a nice post on Science-Based Medicine by Harriet Hall pushing back (kind of) against the increasingly popular idea that antidepressants don’t work. For context, there have been a couple of large recent meta-analyses that used comprehensive FDA data on clinical trials of antidepressants (rather than only published studies, which are biased towards larger, statistically significant, effects) to argue that antidepressants are of little or no use in mild or moderately-depressed people, and achieve a clinically meaningful benefit only in the severely depressed.

Hall points out that whether you think antidepressants have a clinically meaningful benefit or not depends on how you define clinically meaningful (okay, this sounds vacuous, but bear with me). Most meta-analyses of antidepressant efficacy reveal an effect size of somewhere between 0.3 and 0.5 standard deviations. Historically, psychologists consider effect sizes of 0.2, 0.5, and 0.8 standard deviations to be small, medium, and large, respectively. But as Hall points out:

The psychologist who proposed these landmarks [Jacob Cohen] admitted that he had picked them arbitrarily and that they had “no more reliable a basis than my own intuition.“ Later, without providing any justification, the UK’s National Institute for Health and Clinical Excellence (NICE) decided to turn the 0.5 landmark (why not the 0.2 or the 0.8 value?) into a one-size-fits-all cut-off for clinical significance.

She goes on to explain why this ultimately leaves the efficacy of antidepressants open to interpretation:

In an editorial published in the British Medical Journal (BMJ), Turner explains with an elegant metaphor: journal articles had sold us a glass of juice advertised to contain 0.41 liters (0.41 being the effect size Turner, et al. derived from the journal articles); but the truth was that the “glass“ of efficacy contained only 0.31 liters. Because these amounts were lower than the (arbitrary) 0.5 liter cut-off, NICE standards (and Kirsch) consider the glass to be empty. Turner correctly concludes that the glass is far from full, but it is also far from empty. He also points out that patients’ responses are not all-or-none and that partial responses can be meaningful.

I think this pretty much hits the nail on the head; no one really doubts that antidepressants work at this point; the question is whether they work well enough to justify their side effects and the social and economic costs they impose. I don’t have much to add to Hall’s argument, except that I think she doesn’t sufficiently emphasize how big a role scale plays when trying to evaluate the utility of antidepressants (or any other treatment). At the level of a single individual, a change of one-third of a standard deviation may not seem very big (then again, if you’re currently depressed, it might!). But on a societal scale, even canonically ‘small’ effects can have very large effects in the aggregate.

The example I’m most fond of here is Robert Rosenthal’s famous illustration of the effects of aspirin on heart attack. The correlation between taking aspirin daily and decreased risk of heart attack is, at best, .03 (I say at best because the estimate is based on a large 1988 study, but my understanding is that more recent studies have moderated even this small effect). In most domains of psychology, a correlation of .03 is so small as to be completely uninteresting. Most psychologists would never seriously contemplate running a study to try to detect an effect of that size. And yet, at a population level, even an r of .03 can have serious implications. Cast in a different light, what this effect means is that 3% of people who would be expected to have a heart attack without aspirin would be saved from that heart attack given a daily aspirin regimen. Needless to say, this isn’t trivial. It amounts to a potentially life-saving intervention for 30 out of every 1,000 people. At a public policy level, you’d be crazy to ignore something like that (which is why, for a long time, many doctors recommended that people take an aspirin a day). And yet, by the standards of experimental psychology, this is a tiny, tiny effect that probably isn’t worth getting out of bed for.

The point of course is that when you consider how many people are currently on antidepressants (millions), even small effects–and certainly an effect of one-third of a standard deviation–are going to be compounded many times over. Given that antidepressants demonstrably reduce the risk of suicide (according to Hall, by about 20%), there’s little doubt that tens of thousands of lives have been saved by antidepressants. That doesn’t necessarily justify their routine use, of course, because the side effects and costs also scale up to the societal level (just imagine how many millions of bouts of nausea could be prevented by eliminating antidepressants from the market!). The point is that just that, if you think the benefits of antidepressants outweigh their costs even slightly at the level of the average depressed individual, you’re probably committing yourself to thinking that they have a hugely beneficial impact at a societal level–and that holds true irrespective of whether the effects are ‘clinically meaningful’ by conventional standards.

5 thoughts on “what aspirin can tell us about the value of antidepressants”

  1. Tal,

    some good points here.

    The issue (for me, at least) is that SSRI’s have been so widely prescribed due to lobbying and time constraints on doctors that the majority of the people who take them are not really deriving any benefit over and above what they would gain from placebo. Depression itself is extremely placebo responsive, and I think that we probably need to move towards a model where side effects are the primary effect for cases of mild to moderate depression. To be honest, psychotherapy is probably the best treatment here, as its relatively effective and has very few side effects. Given its expense though, I can’t see that happening anytime soon.

  2. disgruntledphd,

    I challenge your assertion that psychotherapy has “very few side effects.” As someone who has has psychotherapy with many different therapists and who is currently taking antidepressant medication, I can tell you that the side effects from therapy can be really nasty. Antidepressants are a walk in the park.

    In psychotherapy you give someone permission to mess with your head because you accept that *their judgement is better than yours.* If you complain about the side effects you are brightly told that it’s proof the psychotherapy is working, that you’re doing great work, that maybe you should come in more frequently? In contrast, when you complain about the side effects of medication your doctor is likely to tweak or change your prescription.

    I have a long rant about psychotherapy side effects, but I’ll spare you. Suffice it to say today I have a psychotherapist who I see occasionally for top-ups, but if I had to choose I’d pick medication. It’s safer because I’m more in control.

    So don’t be so smug.

  3. disgruntledphd,

    Yeah, I agree with that. I’m not saying the use of antidepressants is anywhere near optimal, just that, on balance, at a societal scale, they’ve probably done much more good than harm. Now if you could get doctors to only prescribe antidepressants to severe cases, and use other treatments (e.g., psychotherapy) for milder cases, that would presumably be even better. But like you say, there are other logistical issues that arise there.

  4. There are a number of problems with comparing antidepressants and asprin. First is that antidepressants have tons of side effects. A lot of people go sexually numb, have huge weight swings, and memory problems. In young adults they can cause suicidal thoughts. They are extremely powerful drugs compared to asprin, which can save lives without any substantial adverse effects. Secondly, their cost to society is huge. They cost (billions and billions of dollars) to both individuals and tax payers, and seem to be major drug fueling big pharma, which heavily lobbies to make sure that they are used in any and all cases of depression There is even some evidence that the clinical trials are not really accurate due to data manipulation (David Healy).

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