DSM-5: A Little Mix Up

Proposals in the upcoming DSM-5 psychiatric manual for diagnosing "mixed" mood states may be muddled, according to a new paper.

The mixed state - the name alluding to a mix between depression and mania - has traditionally been viewed (more or less) as combining the dysphoria of depression with the energy of mania. Anger, agitation, restlessness and so forth.

I've been depressed and I know only too well the difference between that "active" depression and the "inactive" kind; if I had to choose, I'd always go for the latter, because at least you're in less danger of doing or saying something you later regret.

However, in the proposals for DSM-5, "mixed" episodes as such will be abolished. Instead, a depressive episode will have "mixed features" if it is associated with at least 3 of 7 symptoms normally seen in (hypo)mania. But - and here's the key novelty - those 7 are only the "good" symptoms of mania. Not things like anger, irritability, insomnia or 'aimless' hyperactivity. (Edit: There are also separate criteria for "mixed" manic and hypomanic episodes).

What will this mean? In a new paper, psychiatrists Perlis, Cusin, and Fava tried to find out. The large STAR*D antidepressant trial recruited people with depression, but it gave everyone the Psychiatric Diagnosis Screening Questionnaire (PDSQ), amongst many other measures. This helpfully included six items on "mania symptoms", which correspond pretty closely to the DSM-V proposed "mixed" features.

Perlis et al found that depressed patients who reported experiencing these "mixed" items had a better response to antidepressant treatment. The more mixed symptoms, the more likely they were to get better on the common SSRI citalopram, even adjusting for other variables.

That's the exact opposite of what you'd expect from a measure of "mixed states", as these are thought to be less responsive to antidepressants - maybe even caused by them. There was no placebo group, so it's unclear why they got better, but either way, it's unexpected; the authors declare themselves "surprised". Hmm. What a mystery...

Or maybe not. These manic symptoms are all things that you're not when you're depressed. The 6 items actually make a good summary of what depression, even agitated depression (except maybe #6) isn't.

So, one interpretation of these results is that people who endorsed these items just weren't depressed, at some point in the 6 months prior to doing the PDSQ. Assuming they were depressed at other points that means their mood was variable over time.

People whose depression is variable might well be more likely to recover than the ones whose depression was unrelenting.

Now Perlis et al do consider this -

further models were fit incorporating the IDS-C30 pleasure and reactivity items; results were essentially unchanged indicating that they are unlikely to be confounded by mood variability per se...

But this assumes that the IDS-C30 questionnaire is a good measure of mood variability in this sample. Maybe it's not, and these data are telling us so. I'd have said that's more likely than the idea that these people were actually both cheerful and depressed at the same time, which seems like a contradiction in terms.

Maybe I'm wrong, and these people did feel that, but the problem is, we can't tell, because no-one actually sat down and asked these people what was going on, or heard their account of what they meant by ticking both the "depressed" and "manic" boxes.

Did they experience a strange mixed emotional state in which they simultaneously depressed and happy? Did their mood see-saw from one day to the next? Or weekly, monthly? Were they depressed in the day and happier in the evening? Were they depressed, then back to normal, leading them to see the normal as a 'high', by comparison with the lows? Were they depressed when sober and happy when drunk? Vice versa? Are they experiencing normal ups and downs and interpreting them as 'mood swings' because they've become convinced, for whatever reason, that they have a mood disorder? Did they just have a poor command of English and weren't really trying to say what the highly-educated investigators assume they were?

Who knows? No-one, because no-one asked. Rely on questionnaire 'measures' (as if emotions can be measured) as a replacement for understanding, and you'll end up where this paper does - with a 'result' that's impossible to understand.

Don't seek, and ye shan't find.

It's not great news for the DSM-5 proposals, either way, although defenders could hold out hope that the differences between those criteria and the PDSQ measure might mean the DSM-5 will perform better...

 Perlis, R., Cusin, C., and Fava, M. (2012). Proposed DSM-5 mixed features are associated with greater likelihood of remission in out-patients with major depressive disorder Psychological Medicine, 1-7 DOI: 10.1017/S0033291712000281

Ketamine - Magic Antidepressant, or Expensive Illusion?

Not one but two new papers have appeared from the Carlos Zarate group at NIMH reporting that a single injection of the drug ketamine has rapid, powerful antidepressant effects.

One placebo-controlled study found a benefit in depressed bipolar patients who were already on mood stabilizers. The other found benefits in treatment-resistant major depression, though ketamine wasn't compared to placebo that time. Here's the bipolar trial:

There have now been several studies finding dramatic antidepressant effects of ketamine, a compound that all journalists seem contractually bound to call either a or a "club drug" or a "horse-tranquilizer". Great news?

If you believe it. But hold your, er, horses... there's a problem. As I said almost 3 years ago about one of the earlier ketamine trials:

In theory, the trial was double blind - neither the patients nor the doctors knew whether they were getting ketamine or placebo. But you'll know when you've been injected with 0.5mg/kg ketamine. You get high. That's why people take it [recreationally]. The study can't really be called double blind.

To their credit, Zarate et al did acknowledge this, and suggested that in future ketamine could be compared to another drug which produces noticeable effects. But they really should have done that to begin with.

It's now 2012, and there have still not been any published studies comparing ketamine to an active comparator i.e. a different drug that produces noticable psychoactive effects, to avoid unblinding. This means it's 12 years since the initial pilot report on ketamine in depression, and 6 years since the first large trial appeared.

The authors of the 2006 paper themselves wrote that "limitations in preserving study blind may have biased patient reporting... One potential study design in future studies with ketamine might be to include an active comparator" and suggested amphetamine for the big role.

Good idea. But six years later, we're still waiting. Which is really a bit silly. There have been dozens of papers written about the possible antidepressant effects of ketamine, from human trials to mouse work. That's a lot of research dollars (and dead mice) on something that might just be an active placebo.

Looking at the registered ketamine research on clinicaltrials.gov, I found that four active-comparator ketamine trials are in the pipeline (1,2,3,4), plus one cancelled (5). Only one is for depression though. The others being for OCD, cocaine dependence and suicidal ideation.

In all of these trials a benzodiazepine is the active comparator. Is that a good idea? Well, it's certainly better than nothing, but I wonder.

An active comparator has to "make an impression" on the patient equal to that produced by the real drug.  The null hypothesis, remember, is that ketamine has no specific antidepressant effect. That means it produces improvement through a combination of a) the placebo effect (expectation) and b) non-specific psychoactive changes.

More on that second one: any psychoactive drug might relieve depression by "taking your mind off it" and a change in mental state, as provided by a drug, also provides a demonstration that "I won't always feel this way". By showing that states of consciousness are products of brain chemistry, almost any drug could therefore offer a "glimmer of hope" to the depressed. If all this sounds very subjective, it is, but that's the point. Psychiatry is.

Would a benzo make as big an impression as 0.5 mg/kg ketamine IV? It's impossible to predict, really; so we'd need to ask people about the subjective strength of the drug effect. Personally, I worry that a lot of people just get sleepy on benzos and don't really feel much, so I'd prefer they used something a bit more hard-hitting like amphetamine, but maybe that's just me.

There's a deeper problem though. Suppose our ketamine-benzo trial finds no difference between ketamine and benzo. A critic could say, ah, but maybe it was just a "failed trial", so it doesn't overturn the positive studies. The patients weren't properly diagnosed, or weren't depressed enough, or were too depressed, etc.

Nitpicking such differences between studies is a well-practiced art.

Critics could complain in other ways if the study did find a benefit of ketamine. As I see it, the only way to settle this once and for all is to do a three-way randomized controlled trial - inactive placebo vs. active comparator vs. ketamine.

That way, if it's a failed trial, we'd know: there'd be no difference between ketamine and the inactive placebo. If there was a difference, but the active comparator was just as good as ketamine, that means it was all about nonspecific effets. Finally, if ketamine was better than the other two conditions, we could be pretty confident it was really working.

Also important is the question of volunteer expertise; subjects shouldn't be able to tell what drug they're on, but people who'd taken ketamine and/or the comparator drug before might be able to do that, so you'd want naive volunteers.

In conclusion: It's possible that ketamine has no specific antidepressant effects. To find out we ideally need a three-way trial, with both active and inactive comparators, careful monitoring of subjective drug effects and patient knowledge and expectations. Until that happens, I will be skeptical of ketamine in depression.

This is not because I just think it's impossible. Ketamine profoundly affects the brain in ways that we don't understand. I've suffered depression and I know it can come and go in a matter of minutes. So I think it's entirely possible that it works - but it's also possible that it's a nonspecific effect.

Look. I really want to know the answer to this. Both as a neuroscientist, and as a depression sufferer, this is very important to me. That's why we urgently need a good trial.

Link: See also the discussion and the comments over at The Neurocritic and this Scientific American piece which is pretty good except that it doesn't cover the active placebo issue.


Zarate CA Jr, Brutsche NE, Ibrahim L, Franco-Chaves J, Diazgranados N, Cravchik A, Selter J, Marquardt CA, Liberty V, and Luckenbaugh DA (2012). Replication of Ketamine's Antidepressant Efficacy in Bipolar Depression: A Randomized Controlled Add-On Trial. Biological psychiatry PMID: 22297150

Ibrahim, L., et al. (2012). Course of Improvement in Depressive Symptoms to a Single Intravenous Infusion of Ketamine vs Add-on Riluzole: Results from a 4-Week, Double-Blind, Placebo-Controlled Study Neuropsychopharmacology DOI: 10.1038/npp.2011.338

Psychiatry's True Blood? Pt 1.

Imagine that there was a blood test that could detect depression. Wouldn't that be useful?

It depends.

Ridge Diagnostics are a US company who offer such a test. They've just published some results of the technology in Molecular Psychiatry. In two samples of patients with major depressive disorder (MDD), they report differences in the"MDDScore", between the patients and healthy controls.

The MDDScore is an aggregate value, calculated from the levels of 9 metabolites in blood serum. They're all well-known molecules, including hormones, such as cortisol and prolactin. The novelty is in how they're put together to make the MDDScore. We're given equations - but the key variables are not provided, because they're proprietary:

Long-term Neuroskeptic readers will recall that this "secret ingredients" approach to publishing science was also adopted by another company offering a different depression test.

Anyway, the performance of the test was impressive. In both the pilot and the replication samples, the MDDScore was significantly higher in the depressed people than in the controls. In both cases, the test had a sensitivity of over 91% and a specificity of over 81%, which is pretty good. Ridge Diagnostics are already offering the MDDScore clinically. For $745 a pop.

However...

Although there were two depressed patient groups (n=36 and 34), there was only one set of controls (n=43); both patient samples were compared to it. This means the second, "replication", test was not fully independent of the first one. If the first finding was a fluke caused by the control group having weird results by chance, for instance, then the second study would just repeat the fluke.

The patients were significantly older, and with a higher BMI, than the controls. They did control for these variables, which is good, but this raises the question of whether these folks differed in other ways, that they didn't measure, and hence couldn't control for.

In both samples, the patients had a very significantly higher MDDScore than the controls (p less than 0.0001, both times). But in both cases, the difference in levels of EGF (epidermal growth factor) was almost as strong: p=0.0003 and p less than 0.0001, respectively. Other metabolites weren't far behind. Testing for EGF would almost certainly be cheaper than getting an MDDScore.

Finally, all these data demonstrate is that the test can distinguish between people with MDD and entirely healthy people. But how often are doctors going to need to do that? More likely, they'll want to distinguish depression from other things that are often confused with it, such as: bipolar disorder, anxiety disorders, chronic fatigue syndrome, bereavement, "stress", and all manner of physical illnesses e.g. thyroid problems. Daniel Carlat said last year that

If the test cannot distinguish different psychiatric problems, then the MDDScore is simply a non-specific "biomarker" for emotional difficulties of all stripes, and would be essentially useless.

How disorder-specific is the MDDScore? This paper doesn't tell us. And to date, this is the only published paper mentioning the MDDScore. The website mentions some conference presentations, but none have yet appeared in a peer reviewed journal.

Ridge Diagnostics have an interesting history. But that's another story - stay tuned for Part 2.

Papakostas, G., Shelton, R., Kinrys, G., Henry, M., Bakow, B., Lipkin, S., Pi, B., Thurmond, L., and Bilello, J. (2011). Assessment of a multi-assay, serum-based biological diagnostic test for major depressive disorder: a Pilot and Replication Study Molecular Psychiatry DOI: 10.1038/mp.2011.166

The Trojan Horses of Medicine

Dodgy science is being smuggled into medical journals thanks to a loophole in the regulations, say Italian psychiatrists Barbui and Cipriani in an important article.

They focus on agomelatine, a recently-approved antidepressant. But their point applies to all of medicine, not just psychiatry.

Here's the problem. Nowadays, major medical journals have rules governing systematic reviews and meta-analyses of clinical trial data. If you want to review the evidence about how well a certain drug works, or its safety, you've got to do it properly. You have to consider all of the data, not just focus on the results that suit you. And so on.

However, these rules don't apply to "narrative" review papers, which is a broad term meaning any kind of article meant to give a discussion of the pharmacology, history, chemistry etc. behind a particular drug. For a narrative review, there are no rules.

In particular, you can write about the clinical trial data in such articles with no restrictions. Unlike in a proper systematic review, you can cherry-pick trials and so on to your heart's content. Some narrative reviews have so much clinical data in them that they end up being, in effect, a bad systematic review. One that would never have been deemed acceptable as a systematic review.

Barbui and Cipriani argue that narrative reviews are often used in this way, namely to paint drugs in a positive light. In the case of agomelatine, they mention a number of recent narrative reviews which were supposedly about the drug's mechanism of action, but which actually contained extensive (but biased) reviews of the clinical trial data.

It's not hard to see how pharmaceutical companies might take advantage of this process.

However, the problem is surely not limited to agomelatine. It's a loophole that affects every branch of medicine:

Most medical journals require adherence to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). It is an evidence-based minimum set of items for reporting in systematic reviews and meta-analyses. Adherence to PRISMA is not required in review articles dealing with basic science issues as these articles are not focused on clinical trials.

In practice, however, the agomelatine case indicates that clinical data are regularly included and reviewed with no reference to the rigorous requirements of the PRISMA approach. These articles have this way became a modern Trojan horse for reintroducing the brave old world of narrative-based medicine into medical journals.

How do we stop this? It's simple, the authors say: just make all references to clinical data subject to PRISMA, or other accepted regulations, whatever the supposed 'primary focus' of the paper:

We argue that medical journals should urgently apply this higher standard of reporting, which is already available, easy to implement and inexpensive, to any form of clinical data presentation.

Of course, there are plenty of good narrative reviews that really do cover the pharmacology or other science in a useful way. The problem is not narrative reviews as such, but the way they're used.

Barbui, C., and Cipriani, A. (2012). Agomelatine and the brave old world of narrative-based medicine Evidence-Based Mental Health, 15 (1), 2-3 DOI: 10.1136/ebmh.2011.100485

Challenging the Antidepressant Severity Dogma?

Regular readers will be familiar with the idea that "antidepressants only work in severe depression".

A number of recent studies have shown this. I've noted some important questions over how we ought to define "severe" in this context, and see the comments here for some other caveats, but I'm not aware of any studies that directly contradict this idea.

Until now. A new paper has just come out which seeks to challenge this dogma - not the author's term, but I think it's fair to say that the severity theory is becoming a dogma, even if it's an evidence-based one (but then, all dogmas start out seeming reasonable).

However, while the new paper is interesting, I think the dogma survives intact.

The authors went through the archives of all of the trials of antidepressants for depressive disorders conducted at the famous New York State Psychiatric Institute for the past 30 years. They excluded any patients who were severely depressed, and just looked at the milder cases. The drugs were mostly the older tricyclic antidepressants.

With a mean HAMD17 score of about 14, the patients they looked at were certainly mild. By comparison, most trials today have a mean of well over 20, and according to the main studies supporting the severity dogma, you need a score of about 25ish to benefit substantially:

So what happened? They reanalyzed 6 trials with over 800 patients. Overall there was a highly significant effect of antidepressants over placebo in mild depression, with an effect size d=0.52, or about 3.5 HAMD points. This is actually better than most other studies have found in "severe" depression. If valid, these results would torpedo the severity theory.

This seems very interesting... but. There's a big but (I cannot lie). Although the authors say they wanted to include all the relevant trials from the NYSPI, they only had access to the data from 6. There were another 6 projects, but they were "pharmaceutical company studies from which data were not released to the investigators."

This pretty much wrecks the whole deal. If those 6 studies all found no benefit of the drug, the overall average results would be much less impressive. We have no way of knowing what those studies found, but I'd wager that most of them were negative, because of publication bias - we know that drug companies tend to publish positive studies and bury negative ones. Or at least they did, at the time these studies took place (there are better regulations now).

By contrast, severity dogma classic Kirsch et al (2008) avoided publication bias by looking at unpublished data. Fournier et al (2010), the other major severity study, didn't but the data were very similar to Kirsch et al so it's not hard to believe them.

So in my view, until we know what happened in the other 6 trials, we can't really interpret these results, and the severity theory stands.

Stewart, J., Deliyannides, D., Hellerstein, D., McGrath, P., and Stewart, J. (2011). Can People With Nonsevere Major Depression Benefit From Antidepressant Medication? The Journal of Clinical Psychiatry DOI: 10.4088/JCP.10m06760

The Real Story On That "Antidepressant Surge"

Remember last week's story about how depression rates are soaring in Britain? It was all triggered by "new data" about an increase in antidepressant prescriptions.

At the time I was skeptical, not least because the data wasn't actually new, but I've done a bit more digging and it turns out the media coverage was even more misleading than I thought.

Here's some pretty graphs from the NHS Information Centre. I reiterate that all of these are freely available and have been for ages. Here's the one for antidepressants:

They've been rising strongly! In total prescription rates are about 60% higher now compared to in 2006. Oh dear.

What the papers didn't tell you is that pretty much every other class of drug has also increased over that period, by even more in some cases. Here's ADHD drugs, and dementia pills, which have increased by about 75% and 100% respectively:

There have also been steady increases in anticonvulsants and a 40% increase in meds for Parkinson's disease. All of the graphs are here.

So this suggests that there's been a general increase in prescriptions for brain drugs. But in fact it's even wider than that because if we look at the same data for cardiovascular system drugs, we find the same picture for most (although not all) kinds of these medications.

And for painkillers, we find over 50% increases in prescriptions of the stronger opioid drugs, a 20% increase in migraine drugs etc etc. I swear I'm not just copying and pasting the same graph.

Now clearly, all of these increased prescriptions don't mean that there are simultaneous explosions in rates of dementia, heart disease, pain, migraine, Parkinson's and ADHD, all in the past 5 years. We would have noticed if that were the case.

What's happened, clearly, is that doctors are just writing more prescriptions nowadays.

So it's misleading to say that there's been a spike in antidepressant prescriptions. Yes it's technically true but it ignores the context. The truth is that we seem to be experiencing a cultural shift in our relationship to medications - perhaps evidence of the creeping medicalization of life (although there are more prosaic explanations that need to be ruled out before we conclude that; this could be a bureaucratic change in the way prescriptions are counted.)

However, "Escalating Depression Crisis - Antidepressant Use Soars" is a better headline than "Possible Medicalization Gradually Continues For Sixth Year In Row".

The truth, sadly, has an inherent disadvantage in the battle for news coverage. If we find the truth boring, it's easy for someone to come along and make up something attention grabbing. But the only easy way to make the truth more interesting is to make it, well, less true.

Antidepressants: Bad Drugs... Or Bad Patients?

Why is it that modern trials of antidepressant drugs increasingly show no benefit of the drugs over placebo? This is the question asked by Cornell psychiatrists Brody et al in an American Journal of Psychiatry opinion piece.

They suggest that maybe it's the patients fault:

Participation that is induced by cash payments may lead subjects to exaggerate their symptoms [i.e. in order to get included into the trial]... Another contributing factor to high placebo response rates may be the extent to which the volunteers in antidepressant trials are really generalizable to patients in clinical practice.

Since the initial antidepressant trials in the 1960s, participants have gone from being patients who were recruited primarily from inpatient psychiatric populations to outpatient volunteers who are often recruited by advertisements. At times, these symptomatic volunteers have participated in other trials. When we contact potential participants to schedule screening, they often ask to be reminded which trial we are screening for or mistake our research trial for a different protocol in which they recently participated.

They then recount the tale of two "professional subjects" who claimed to be depressed and enrolled in two antidepressant trials simultaneously, without telling the researchers; it only came to light when someone involved in both studies spotted the duplicate names.

I've been the victim of such nonsense myself, as have many of colleagues - it's a perennial watercooler topic. A few years ago I was running a study recruiting people who'd recovered from psychiatric illness. The main source of volunteers was online adverts.

That study was a learning experience. What I learned is that House was right. We recruited about 20 people. No fewer than 3 turned out to have enrolled in other studies and lied about it. After I realized this I Googled the offender's names and two of them turned up in the court pages of the local newspaper pleading guilty to various petty crimes.

Another volunteer was left handed and, upon realizing that I was only recruiting right-handed people, discretely switched his pen to his right hand and then took 5 minutes trying to fill out a form with his off hand. He didn't make it in, but if I hadn't been paying attention he would have.

So yes, it is a problem. However, it would have to be taking place on a massive scale for it to be having a significant effect on antidepressant trial results and this really seems pretty unlikely.

In my view, the authors miss out on the real problem with recruiting depressed people through adverts:  depressed people don't tend to respond to adverts, because depressed people don't do anything. That's why they call it depression.

Getting recruited into a modern clinical trial is actually quite a challenge. There are many pieces of paper to fill in, calls to return, appointments to attend. Turn up late to the screening visit, or otherwise make life difficult for the study staff, and you'll be marked down as "unreliable" and they'll find someone who plays by the rules. Modern trials are very expensive. The last thing a study sponsor wants is a volunteer who will end up forgetting to take their pills on time.

Depression, unfortunately, makes you bad at doing things. You procrastinate, you forget, you put things off until too late, you have a change of heart and decide not to, you get cold feet, you can't be bothered... That goes for things as simple as cooking dinner in severe cases, let alone something as complicated as taking part in a trial.

So while you wouldn't go looking for aquaphobic people in a swimming pool, I'm not sure we should be looking for depressed people through adverts.

Brody B, Leon AC, and Kocsis JH (2011). Antidepressant clinical trials and subject recruitment: just who are symptomatic volunteers? The American journal of psychiatry, 168 (12), 1245-7 PMID: 22193668

Britain - the Prozac Nation? Not So Fast...

Oh no! The stress of the recession has turned us into a nation of antidepressant addicts, according to every single British newspaper this morning.

The media coverage has been predictable with lots of scary, context-free statistics, and boilerplate quotes from the usual suspects. No doubt tomorrow we'll see a selection of moralistic op-eds about this.

But not one of the many nigh-identical articles provided a link to the original data, or even a useful description of where one might find it. After contacting one of the NHS organizations named as the source, I managed to track the numbers down.

It turns out that the key figures have been publicly available since April 2011, so I'm not sure why this story appeared in British "news"papers at all. Also, it would have been easy for journalists to link to the source, if they respected the intelligence of their readers enough to do that. I just did it and it wasn't terribly hard to click "Add Link".

On that note, I actually read a bizarre article today criticizing British journalists for providing too many links to their source data... if only.

Anyway, the data. Ben Goldacre has already written an excellent piece on this (in fact, he wrote it back in April 2011, curiously enough...see above), but here's some more detail.

First off, the data are all about antidepressants, not depression. A crucial distinction, there, because nowadays, antidepressants are widely used for all kinds of other things. Everything from other psychiatric disorders like anxiety and OCD, to non-psychiatric stuff like back and joint pain, premature ejaculation, and menopausal hot flushes.

We can't tell how much of the antidepressant use was for depression. But there are clues suggesting that a lot of it wasn't. It turns out that the second most popular antidepressant (after citalopram) was the very old drug amitriptyline, with nearly 9 million prescriptions per year - or 20% of the total.

Nowadays amitriptyline is rarely used for depression, because newer, less toxic alternatives are available. However it is used, in low doses, to treat chronic pain. So I suspect that pain accounts for a large % of amitriptyline use. That would also explain why the cost to the NHS per prescription of amitryptiline was by far the lowest of all antidepressants: low doses are cheap.

How about the increase over time?

The newspapers are correct that antidepressant use rose from 33.9 million prescriptions in the year 2007/8, to 43 million in 2010/2011. That's a 28% rise over 3 years. However, if we go 3 years further back to the equivalent 2004/5 Prescription Cost Analysis, we find that antidepressant prescriptions were 28.9 million. So they rose 17% in the 3 years before 2007/8, long before the recession was on the horizon.

The recent 28% rise, in other words, is unlikely to be related to the recession, at least not entirely.

We also know(1,2) that the number of antidepressant prescriptions per person has been rising over the past several years in the UK. So the increase in prescriptions might not even mean more antidepressant users - it might just mean that the same number of users are using more each. (And that could mean anything, including that bureaucracies are saving money by prescribing for shorter periods).

One study found that there was no increase in the number of people taking antidepressants for depression from 1993 to 2005, with all of the rise in prescriptions over that period being a product of more prescriptions per person.

Another study did find a true rise in users from 1995 to 2007, albeit lower than the raw figures would suggest, but those figures were limited to a particular part of Scotland and it wasn't just about depression - it included all other uses of these drugs as well.

Overall, it's just impossible to know, from these data, whether there's been a true increase in antidepressant use for depression in recent years. The most we can say is that there might have been one, and if so it might have something to do with the economy.

Do Antidepressants Make Some People Worse?

Antidepressants may help depression in some people but make it worse for others, according to a new paper.

This is a tough one so bear with me.

Gueorguieva, Mallinckrodt and Krystal re-analysed the data from a number of trials of duloxetine (Cymbalta) vs placebo. Most of the trials also had another antidepressant (an SSRI) as well. And the SSRIs and duloxetine seemed to be indistinguishable so from now on I'll just call it antidepressants vs. placebo as the authors did.

People on placebo got, on average, moderately better over 8 weeks.

People on antidepressants fell into two classes. The largest class got, on average, a lot better. But about 25% did poorly, staying just as depressed as before. This "nonresponder" group did much worse than the placebo group - again on average. Here you can see the mean "trajectories" of depression symptoms (HAMD scores) in the three groups:

This raises the scary possibility that while antidepressants are helping some people, they're harming others. But hang on. It's complicated.

First off, maybe this is all a statistical illusion. When the authors say that the people on drug fell into two classes, what they mean is that when you try to model the data according to a certain mathematical model, assuming either 1, 2, 3 or 4 underlying classes, the 2 class solution was the best fit. While for placebo a 1 class solution was best.

We considered linear, quadratic, and cubic trends over time, with between 1 and 4 trajectory classes. We also considered piecewise models with a change point at 2 weeks, linear change before week 2, and quadratic change after week 2. The selection of the best model was based on the Schwartz-Bayesian information criterion and on the Lo-Mendell-Rubin (LMR) likelihood ratio test...

That's nice... but they don't present the raw data. They don't tell us whether, looking at the individual trajectories of people on antidepressants, you'd actually see two classes. What I want is a graph of how likely people are to get better by a certain amount. If Gueorguieva et al are right, I want it to look like this i.e. bimodal -

We're not shown this graph. I'll eat my hat if it does look like that, frankly, because if it did people would have noticed the bimodality in antidepressant trials ages ago.

True, statistical models can tell us things that aren't obvious by inspection, so even if this isn't what the data look like, they might still be right. It could be that the two "peaks" are so broad, and there's so much random noise, that they blur into one.

However, it's also true that you can fit an infinite number of models to any set of data and at some point you have to step back and say - am I making this more complicated than it needs to be?

It could be that a 2-class model is better than a 1-class model for the people on antidepressants, but only because they're both crap, and really, every patient has a different, unpredictable trajectory which is poorly captured by such models.

Let's assume however that this is true. What would it mean?

Firstly, the fact that one class of people on antidepressants does worse than people on placebo doesn't mean that antidepressants are harming them. The authors miss this point, when they say

there are 2 trajectories for patients treated with antidepressants and 1 trajectory for patients treated with placebo [so] some patients would seem to be more effectively treated with placebo than with a serotonergic antidepressant.

But that's fallacious. It treats a purely statistical entity as representing individual people. Suppose that what antidepressants do is to take people who, on placebo, would have improved a bit, and make them improve a bit more than they otherwise would have. You'd then end up with more people doing well, but also fewer people doing moderately because they'd have been "moved up" out of the middle ground.

That "nudging people off the fence" could lead to a bimodal distribution and two distinct classes. But in this case the people doing badly would have done badly either way. The drug didn't make them do badly, it just made doing-badly into a class. On the other hand it's consistent with antidepressants doing real harm. We can't tell.

We do know that other randomized controlled trials show very convincingly that in a small minority of people, mostly but not exclusively young people, antidepressants do worsen suicidal thoughts and behaviours. So it's plausible. But we just don't know yet.

What worries me is that this paper is the latest in a series of attempts  to use, well, creative statistical approaches to antidepressant trial data. This one is nowhere near as dodgy as the Cherrypicker's Manifesto I discussed last year, but it cites that paper and others by the same group. The first sentence of the Abstract of this paper makes the intention clear:

The high percentage of failed clinical trials in depression may be due to high placebo response rates and the failure of standard statistical approaches to capture heterogeneity in treatment response.

In other words, the reason clinical trials of new antidepressants often fail to show a benefit over placebo is not because the drugs are crap but because the statistics aren't subtle enough. And you can see where this is going: if only we could use statistical models to find the people who do benefit from antidepressants, and compare them to placebo, there'd be no problem...

Gueorguieva R, Mallinckrodt C, and Krystal JH (2011). Trajectories of depression severity in clinical trials of duloxetine: insights into antidepressant and placebo responses. Archives of General Psychiatry, 68 (12), 1227-37 PMID: 22147842

A Psychedelic Tale of Two Neurotransmitters

An unexpected interaction between neurotransmitter systems may explain psychosis and hallucinations, according to a fascinating new paper.

Serotonin (5HT) and glutamate are two neurotransmitters. Up until now, it was thought that they acted independently. A given neuron might have receptors for both serotonin and glutamate, but they didn't interact: serotonin would never affect the glutamate receptors, and vice versa.

The new research overturns that view. Authors Miguel Fribourg and colleagues of Mount Sinai School of Medicine show, in a series of elegant experiments in mice, that different receptors can cluster together, forming a complex. The two receptors, serotonin's 5HT2A and glutamate's mGluR2, can talk to each other.

However, this doesn't seem to happen under normal conditions. Serotonin and glutamate don't seem to trigger the receptor interaction, or at least not very much. Only certain drugs can do it. And this is where it gets really interesting.

Psychedelic drugs, like LSD, have long been thought of as 5HT2A agonists, binding to the receptor and activating it. It turns out that this was only half right. They also inhibit mGluR2 transmission via the receptor complex. Serotonin itself is a 5HT2A agonist, but it doesn't do that. So psychedelics seem to be a kind of (for want of a better word) "superagonist".

It also works in reverse. The antipsychotic drugs clozapine and risperidone are known as 5HT2A antagonists. But Fribourg et al show that they also activate the mGluR2 receptor.

And the cross-talk can go in the other direction. Certain molecules that act on mGluR2 can either inhibit or promote 5HT2A. Unlike psychedelics and antipsychotics, these mGluR2 drugs have not been tested in humans yet. But these data predict that they will have psychedelic-like or antipsychotic-like effects, depending which way they work.

The interaction turns out to be all about G proteins, which are part of the chain of transmitter substances that convey signals within the cell, in response to neurotransmitters outside it. Here's a chart showing the effects of various drugs on the balance between different G proteins: the LSD-like psychedelic DOI has the opposite effect from the antipsychotics clozapine and risperidone.

This paper builds on a previous one from the same team showing that psychedelic 5HT2A "agonists" (like LSD and DOI) have different effects on G proteins from other, non-psychedelic agonists. That was interesting in itself but by adding glutamate to the picture, this new paper is really ground-breaking.

This goes a long way to explaining one of the mysteries of serotonin which is this:  if 5HT2A agonists like LSD are psychedelic, why aren't antidepressants the same? Almost all antidepressants work by increasing extracellular 5HT levels. That ought to mean that they activate 5HT2A receptors (indirectly). This explains why not - 5HT alone doesn't promote the crucial 5HT2A-mGluR2 interaction.

Taken together, these interesting results show clearly that 5HT2A and mGluR2 are hooking up and doing something exciting. Certainly in terms of how hallucinogens work.

I'm less convinced that this can directly explain antipsychotic effects though. The problem is that while newer "atypical" antipsychotics act on 5HT2A, the older antipsychotics don't, and atypicals are at best only slightly more effective on average.

What we don't yet know is whether this kind of complex receptor interactions can happen with other receptors. I'd have thought it unlikely that these two receptors were the only ones that could ever do it. The synapse looks like it's more complex than we could have imagined.

Fribourg M, et al. (2011). Decoding the Signaling of a GPCR Heteromeric Complex Reveals a Unifying Mechanism of Action of Antipsychotic Drugs. Cell, 147 (5), 1011-23 PMID: 22118459

Cognitive Behavioural Therapy vs. Psychoanalysis

Clinical trials of cognitive behavioural psychotherapy (CBT) for depression are often of poor quality - and are no better than trials of the rival psychodynamic school.

So says a new American Journal of Psychiatry paper that could prove controversial.

CBT is widely perceived as having a better evidence base than other therapies. The "creation myth" of CBT (at least as I was taught it) is that it was invented by a psychoanalyst who got annoyed at the unscientific nature of psychodynamic i.e. Freudian-influenced therapy. CBT has always looked on clinical trials more favorably than the dynamic school.

However, the authors of this meta-analysis found that while there are certainly lots of published CBT trials for depression, they're actually no better quality than the psychodynamic trials.

"Surprisingly" (their word), they found no difference between the CBT for depression trials, and the psychodynamic trials, on a rating score of trial methodology.

Trials got better over time, but the two groups improved equally (see above). The mean score was 25.5 for CBT and 25.1 for dynamic, on a scale that goes from 0 to 48. Anything over 24 points is deemed acceptable but this is clearly an arbitrary cut-off.

The RCTP-QRS scale is relatively new and it was developed by the people who wrote this paper (albeit with the input of other experts.) There's 24 items and each gets a score from 0 (bad) to 2 (good). Items are things like "Adaquate sample size", "Patients randomly assigned to group", etc.

Worryingly, better CBT trials tended to find smaller benefits of CBT over the comparison treatment. The overall results showed that while CBT was clearly better than doing nothing, it was pretty much the same as antidepressants, and other psychotherapies, in adults with depression:

The article follows one from the same group, Gerber et al, who reviewed the evidence for psychodynamic therapy in more detail. And last year, another team reported evidence of publication bias in psychotherapy trials. In this study, the authors report possible publication bias, but they don't go into detail.

Overall this is interesting stuff, and a reminder that while CBT has the most evidence of any psychotherapy, this is not the same thing as saying that it has the best evidence...

Nathan C. Thoma et al (2011). A Quality-Based Review of Randomized Controlled Trials of Cognitive-Behavioral Therapy for Depression: An Assessment and Metaregression American Journal of Psychiatry

A Dangerous Truth about Antidepressants

An opinion piece by veteran psychiatrist and antidepressant drug researcher Sheldon Preskorn contains a remarkable historical note -

“A dangerous idea!” That was the response after a presentation I gave to a small group of academic leaders with an interest in psychopharmacology [over 15 years ago].

What evoked such a response? The acknowledgment that most currently available antidepressants specifically treat only one out of four patients with major depression based on the bulk of clinical trials data.

There was no argument about the accuracy of this statement, but...some claim it is “dangerous” to admit that the specific response rate to most antidepressants is 20%–30% because such an acknowledgment might undermine the value of antidepressant treatment.

By the "specific" response rate Preskorn means the number of depressed people who'll get better on antidepressants and who wouldn't have done so well on placebo. This rate is fairly low because, while most people get better on antidepressants, most of those improve on placebo as well.

Preskorn rejects the view that it's dangerous to acknowledge this:

...there are several problems with this reaction. First, it is hard to deny reality. The “placebo” response rate in antidepressant trials is arguably the most reproducible finding in psychiatry. Moreover, if available antidepressants were magic bullets, then polypharmacy would not be so common. Second, this reaction ignores the fact that antidepressants are tremendously valuable to the patients who specifically benefit from them...

Every treatment in every area of medicine has limitations. Acknowledging that fact should galvanize us to action. Denial on the other hand perpetuates the status quo.

Unfortunately, we're not told who these academic leaders were. I wonder if they included amongst their ranks some of the "key opinion leaders" in the field whose leadership proved rather less than ideal. The column is actually adapted from a 1996 article by Preskorn.

Preskorn is right, of course, that denying the fact that antidepressants are only substantially better than placebo in a fraction of people who get diagnosed with "depression" is wrong, and also misses the point: because hundreds of millions of Americans have diagnosable depression (due to the loose definition of "depression"), even if they only helped 1% of them, they'd still help over a million people.

But he doesn't mention that this approach was ultimately self-defeating. As a result of the failure to acknowledge that antidepressants are only helpful in some cases of depression (namely "severe" depression), these drugs became very widely used and - oh dear - people started saying that the drugs are being overused, and don't work in most people who take them.

Whoever could have seen that coming.

This has "devalued" antidepressants - and psychiatry itself - more than anything else has.

Preskorn SH (2011). What Do the Terms "Drug-Specific Response/Remission Rate" and "Placebo" Really Mean? Journal of psychiatric practice, 17 (6), 420-424 PMID: 22108399

Does MRI Make You Happy?

A startling new paper from Tehran claims Antidepressant effects of magnetic resonance imaging-based stimulation on major depressive disorder.

Yes, this study says that having an MRI scan has a powerful antidepressant effect.

They took 51 depressed patients, and gave them all either an MRI scan or a placebo sham scan. The sham was a "scan" in a decommissioned scanner. The magnet was off but they played recorded scannerish sounds to make it believable. Patients were blinded to group.

They found that people in the scanner group improved much more than those in the sham group over two weeks. Actually there were two different kinds of scans, T1 structural MRI and EPI functional MRI, but they were the same:

Now, if this is true, it's huge. Obviously. For one thing, it would undermine the whole premise of functional MRI, which is that it's a method of recording brain activity. If it's also stimulating the brain in some way at the same time, then it would make it hard to interpret those activations. In particular it would cast all the studies using fMRI in depression into doubt.

So is it true? I can't see any obvious flaws in the design. Assuming that the authors are right when they say that "patients could not distinguish the difference between the actual and sham MRI scan", i.e. assuming that the blind was truly blind, then the methodology was sound.

But let's look at the statistics. The paper is full of very impressive p values less than 0.001 but those turn out to all be referring to the changes within each group, and those changes are fairly meaningless. What matters is the differences in the groups and

Changes in BDI scores (between baseline and day 14) were significantly different among the three studied groups (F=5.48, p=0.007 overall) using ANOVA, and between the DWI group vs. Sham and T1 vs. Sham (p<0.05) using post hoc tests. Changes in HAMD24 scores (between baseline and day 14) were also compared among the 3 groups using ANOVA but the level of significance was slightly above the significance threshold (F=2.89, p=0.06).

Which is rather less convincing. There was a close-to-significant group difference in the HAMD24, and a significant but only just effect on the BDI. Remember that there were only 17 people in each group.

I'm inclined to think that this is one of the 5% of experiments which will produce a nominally significant result even assuming everything goes to plan and there are no confounds. My suspicion is that everyone in the trial got better (they were all on antidepressants, plus there's the placebo effect and the effect of time) - except a small number of people who didn't improve. And by chance they were all in the sham group.

The reason I'm skeptical is that I just can't see a plausible mechanism. The authors suggest that MRI scans might stimulate the brain in a similar way to TMS and that this could have antidepressant effects.

But there's a lot of problems with this: 1) the evidence is questionable whether TMS even works for depression 2) the magnetic stimulation of the brain generated during MRI is much weaker than in the case of TMS and 3) if MRI really stimulated the brain like TMS, then, like TMS, it would have a risk of triggering seizures in people with epilepsy. But it doesn't.

Vaziri-Bozorg SM, et al (2011). Antidepressant effects of magnetic resonance imaging-based stimulation on major depressive disorder: a double-blind randomized clinical trial. Brain imaging and behavior PMID: 22069111

Another Antidepressant Bites The Dust

Yet another up-and-coming antidepressant has flopped.

A paper just out reveals that the snappily-named GSK372475 doesn't work and has lots of side effects. It's a report of two clinicals trials in which Glaxo's contender was pitched against placebo and against older antidepressants in the treatment of depression.

GSK372475 failed to improve depression any better than placebo, even though the trials were large (393 and 504 patients respectively) and twice as long as most antidepressant trials (10 weeks whereas 4 or 6 is more usual)which ought to have given it plenty of room to shine.

The comparison drugs, the widely used venlafaxine and paroxetine, did work. A bit.

One of the trials even used the Bech "Melancholia Subscale" as an outcome measure, which Neuroskeptic readers may remember as I've praised it before. Venlafaxine worked on that, GSK's new pill didn't. If anything, the new drug was worse than placebo, in that patients improved slower.

In terms of side effects it caused dry mouth, insomnia, and nausea serious enough to make many people quit the study early. But even worse, it raised heart rate by almost 10 beats per minute on average, which is really never a good sign.

So, overall, it was an utter flop. In one sense this is not surprising. New "antidepressants" that don't work in trials have been all too common recently. Just last week we learned about the failure of "Serdaxin" in a Phase II trial. Actually Serdaxin isn't a new drug but an old antibiotic called clavulanic acid that a company was trying to rebrand as a mood lifter.

However the failure of GSK372475 is a bit of a mystery. The drug is a potent triple reuptake inhibitor (TRI) which acts on the neurotransmitters serotonin, noradrenaline and dopamine. By contrast, venlafaxine is a double reuptake inhibitor which doesn't hit dopamine, and paroxetine only targets serotonin. I've written about other TRIs before.

Now it seems surprising that venlafaxine worked, but a TRI didn't, in the same trial. That would imply that blocking the reuptake of dopamine makes you more depressed, enough to cancel out the other actions which are shared with venlafaxine. Which is not what I'd have predicted.

There are other differences between the drugs though. Venlafaxine has a very short half-life - it's broken down in the body in a matter of hours. But GSK372475 has a halflife of 8-10 days. Could this be the problem?

Learned S, Graff O, Roychowdhury S, Moate R, Krishnan KR, Archer G, Modell JG, Alexander R, Zamuner S, Evoniuk G, & Ratti E (2011). Efficacy, safety, and tolerability of a triple reuptake inhibitor GSK372475 in the treatment of patients with major depressive disorder: two randomized, placebo- and active-controlled clinical trials. Journal of psychopharmacology (Oxford, England) PMID: 22048884