on the limitations of psychiatry, or why bad drugs can be good too

The Neuroskeptic offers a scathing indictment of the notion, editoralized in Nature this week, that the next decade is going to revolutionize the understanding and treatment of psychiatric disorders:

The 2010s is not the decade for psychiatric disorders. Clinically, that decade was the 1950s. The 50s was when the first generation of psychiatric drugs were discovered – neuroleptics for psychosis (1952), MAOis (1952) and tricyclics (1957) for depression, and lithium for mania (1949, although it took a while to catch on).

Since then, there have been plenty of new drugs invented, but not a single one has proven more effective than those available in 1959. New antidepressants like Prozac are safer in overdose, and have milder side effects, than older ones. New “atypical” antipsychotics have different side effects to older ones. But they work no better. Compared to lithium, newer “mood stabilizers” probably aren’t even as good. (The only exception is clozapine, a powerful antipsychotic, but dangerous side-effects limit its use.)

Those are pretty strong claims–especially the assertion that not a single psychiatric drug has proven more effective than those available in 1959. Are they true? I’m not in a position to know for certain, having had only fleeting contacts here and there with psychiatric research. But I guess I’d be surprised if many basic researchers in psychiatry concurred with that assessment. (I’m sure many clinicians wouldn’t, but that wouldn’t be very surprising.) Still, even if you suppose that present-day drugs are no more effective than those available in 1959 on the average (which may or may not be true), it doesn’t follow that there haven’t been major advances in psychiatric treatment. For one thing, the side effects of many modern drugs do tend to be less severe. The Neuroskeptic is right that atypical antipsychotics aren’t as side effect-free as was once hoped; but consider, in contrast, drugs like lamotrigine or valproate–anticonvulsants nowadays widely prescribed for bipolar disorder–which are undeniably less toxic than lithium (though also no more, and possibly less, effective). If you’re diagnosed with bipolar disorder in 2010, there’s still a good chance that you’ll eventually end up being prescribed with lithium;, but (in most cases) it’s unlikely that that’ll be the first line of treatment. And on the bright side, you could end up with a well-managed case of bipolar disorder that never requires you to take drugs with frequent and severe side effects–something that frankly wouldn’t have been an option for almost anyone in 1959.

That last point gets to what I think is the bigger reason for optimism: choice. Even if new drugs aren’t any better than old drugs on average, they’re probably going to work for different groups of people. One of the things that’s problematic about the way the results of clinical trials are typically interpreted is that if a new drug doesn’t outperform an old one, it’s often dismissed as unhelpful. The trouble with this worldview is that even if drug A helps 60% of people on average and drug B helps 54% of people on average (and the difference is statistically and clinically significant), it may well be that drug B helps people who don’t benefit from drug A. The unfortunate reality is that even relatively stable psychiatric patients usually take a while to find an effective treatment regime; most patients try several treatments before settling on one that works. Simply in virtue of there being dozens more drugs available in 2009 than in 1959, it follows that psychiatric patients are much better off living today than fifty years ago. If an atypical antipsychotic controls your schizophrenia without causing motor symptoms or metabolic syndrome, you never have to try a typical antipsychotic; if valproate works well for your bipolar disorder, there’s no reason for you to ever go on lithium. These aren’t small advances; when you’re talking about millions of people who suffer from each of these disorders worldwide, the introduction of any drug that might help even just a fraction of patients who weren’t helped by older medication is a big deal, translating into huge improvements in quality of life and many tens of thousands of lives saved. That’s not to say we shouldn’t strive to develop drugs that aren’t also better on average than the older treatments; it’s just that it shouldn’t be the only (and perhaps not even the main) criterion we use to gauge efficacy.

Having said that, I do agree with the Neuroskeptic’s assessment as to why psychiatric research and treatment seems to proceed more slowly than research in other areas of neuroscience or medicine:

Why? That’s an excellent question. But if you ask me, and judging by the academic literature I’m not alone, the answer is: diagnosis. The weak link in psychiatry research is the diagnoses we are forced to use: “major depressive disorder”, “schizophrenia”, etc.

There are all sorts of methodological reasons why it’s not a great idea to use discrete diagnostic categories when studying (or developing treatments for) mental health disorders. But perhaps the biggest one is that, in cases where a disorder has multiple contributing factors (which is to say, virtually always), drawing a distinction between people with the disorder and those without it severely restricts the range of expression of various related phenotypes, and may even assign people with positive symptomatology to the wrong half of the divide simply because they don’t have some other (relatively) arbitrary symptoms.

For example, take bipolar disorder. If you classify the population into people with bipolar disorder and people without it, you’re doing two rather unfortunate things. One is that you’re lumping together a group of people who have only a partial overlap of symptomatology, and treating them as though they have identical status. One person’s disorder might be characterized by persistent severe depression punctuated by short-lived bouts of mania every few months; another person might cycle rapidly between a variety of moods multiple times per month, week, or even day. Assigning both people the same diagnosis in a clinical study is potentially problematic in that there may be very different underlying organic disorders, which means you’re basically averaging over multiple discrete mechanisms in your analysis, resulting in a loss of both sensitivity and specificity.

The other problem, which I think is less widely appreciated, is that you’ll invariably have many “control” subjects who don’t receive the diagnosis but share many features with people who do. This problem is analogous to the injunction against using median splits: you almost never want to turn an interval-level variable into an ordinal one if you don’t have to, because you lose a tremendous amount of information. When you contrast a sample of people with a bipolar diagnosis with a group of “healthy” controls, you’re inadvertently weakening your comparison by including in the control group people who would be best characterizing as falling somewhere in between the extremes of pathological and healthy. For example, most of us probably know people who we would characterize as “functionally manic” (sometimes also known as “extraverts”)–that is, people who seem to reap the benefits of the stereotypical bipolar syndrome in the manic phase (high energy, confidence, and activity level) but have none of the downside of the depressive phase. And we certainly know people who seem to have trouble regulating their moods, and oscillate between periods of highs and lows–but perhaps just not to quite the extent necessary to obtain a DSM-IV diagnosis. We do ourselves a tremendous disservice if we call these people “controls”. Sure, they might be controls for some aspects of bipolar symptomatology (e.g., people who are consistently energetic serve as a good contrast to the dysphoria of the depressive phase); but in other respects, they may actually closer to the prototypical patient than to most other people.

From a methodological standpoint, there’s no question we’d be much better off focusing on symptoms rather than classifications. If you want to understand the many different factors that contribute to bipolar disorder or schizophrenia, you shouldn’t start from the diagnosis and work backwards; you should start by asking what symptom constellations are associated with specific mechanisms. And those symptoms may well be present (to varying extents) both in people with and without the disorder in question. That’s precisely the motivation behind the current “endophenotype” movement, where the rationale is that you’re better off trying to figure out what biological and (eventually) behavioral changes a given genetic polymorphism is associated with, and then using that information to reshape taxonomies of mental health disorders, than trying to go directly from diagnosis to genetic mechanisms.

Of course, it’s easy to talk about the problems associated with the way psychiatric diagnoses are applied, and not so easy to fix them. Part of the problem is that, while researchers in the lab have the luxury of using large samples that are defined on the basis of symptomatology rather than classification (a luxury that, as the Neuroskeptic and others have astutely observed, many researchers fail to take advantage of), clinicians generally don’t. When you see a patient come in complain of dsyphoria and mood swings, it’s not particularly useful to say “you seem to be in the 96th percentile for negative affect, and have unusual trouble controlling your mood; let’s study this some more, mmmkay?” What you need is some systematic way of going from symptoms to treatment, and the DSM-IV offers a relatively straightforward (though wildly imperfect) way to do that. And then too, the reality is that most clinicians (at least, the ones I’ve talked to) don’t just rely on some algorithmic scheme for picking out drugs; they instead rely on a mix of professional guidelines, implicit theories, and (occasionally) scientific literature when making decisions about what types of symptom constellations have, in their experience, benefited more or less from specific drugs. The problem is that those decisions often fail to achieve their intended goal, and so you end up with a process of trial-and-error, where most patients might try half a dozen medications before they find one that works (if they’re lucky). But that only takes us back to why it’s actually a good thing that we have so many more medications in 2009 than 1959, even if they’re not necessary individually more effective. So, yes, psychiatric research has some major failings compared to other areas of biomedical research–though I do think that’s partly (though certainly not entirely) because the problems are harder. But I don’t think it’s fair to suggest we haven’t made any solid advances in the treatment or understanding of psychiatric disorders in the last half-century. We have; it’s just that we could do much better.

2 thoughts on “on the limitations of psychiatry, or why bad drugs can be good too”

  1. Hey,

    “Those are pretty strong claims–especially the assertion that not a single psychiatric drug has proven more effective than those available in 1959. Are they true?”

    Unfortunately, it is. Taking antidepressants as an example (as that’s my area), this Cochrane Review concluded that amitriptyline (available: 1961) is more effective than any other antidepressant, including all of the newer ones. If you look at other Cochrane Reviews examining antidepressants in depression, they either find tricyclics to be better than newer ones, or that they’re all the same.

    As you say, the fact that newer drugs are safer and better tolerated, and the sheer amount of choice that we now have, is nothing to sniff at. Certainly I agree that as a psychiatric patient you are better off today than 40 years ago. But from a scientific point of view the progress has been disappointing – we haven’t been able to use basic science to develop any better drugs. We haven’t, for example, found any biomarkers which predict who will respond to which drug, which was what a lot of the work from the 60s and 70s was aiming at. To use an analogy, in the 50s we were driving around in cars, which was OK, but we’d expected to be flying around in spaceships by the 21st century. In fact all we have are cars, we just have a wider choice of models, and they have nicer seats.

    As for diagnosis, I think you’ve nailed the problem when you point out that our diagnoses are useful for clinicians, but are then (inappropriately) used for research as well. For example, I would not want a clinician to go around diagnosing depression on the basis of sleep EEG abnormalities because that’s not been shown to be clinically useful, but I’d encourage researchers to so. By only including patients whose sleep EEG parameters (or whatever else) are a certain % outside the normal range you’d decrease the number of patients you’d be able to recruit, but you’d (hopefully) increase their biological homogeneity. If you found anything, it would only refer to that subset of people, but that’s better than finding nothing about depressives as a whole.

  2. It’s certainly not my area of expertise, but based on a lit search it seems like there’s a fair amount of work identifying biomarkers that predict antidepressant efficacy… There’s a Kato & Serretti (2008) meta-analysis suggesting that a number of polymorphisms predict either efficacy or prevalence of side effects. While I don’t doubt that some of those effects will turn out to be grossly inflated and/or outright false positives, it seems pretty unlikely that there’s nothing to any of that work. And these are still early days for pharmacogenetics; I’d be surprised if the pace of similar discoveries doesn’t pick up rapidly in the next decade.

    That said, my real objection wasn’t to the idea that drugs are no more effective today than 50 years ago, it was more with the characterization. I don’t think it’s fair to say there haven’t been major advances in treatment or understanding. I think there have been plenty of major advances, though I also agree that we’re probably not where you would have expected us to be by now 50 years ago.

    I think the the car analogy is actually an apt one. It’s true we’re not flying around Jetson-style; but I don’t think it’s fair to say there haven’t been major advances in car engineering. Electric/hybrid engines, engine control units, fuel injection, anti-lock braking systems, airbags, traction control, etc… these all seem like pretty important developments. Some of these technologies are very old, and others are new, but none were widely deployed until the last couple of decades, and they’ve dramatically improved comfort, safety, and/or performance. To me they fall squarely in the category of major advances–just as knowledge of the heritability of psychiatric disorders, identification of genetic and environmental risk factors, structural brain correlates, widespread availability of dozens of psychiatric drugs, etc.,do. But maybe we’re just having a semantic dispute over the definition of “major advance”. 😉

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