The Cipriani paper was a meta-analysis of trials comparing one drug against another. With a total of over 25,000 patients, it boasted an impressively large dataset, but I advised caution. Their method of crunching the numbers (indirect comparisons) was complex, and rested on a lot of assumptions.I wasn't the only skeptic. Cipriani et al has attracted plenty of comments in the medical literature, and they make for some fascinating reading. Indeed, they amount to crash-course in the controversies surrounding antidepressants today - a whole debate in microcosm. So here's the microcosm, in a nutshell:
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In The Lancet, the original paper was accompanied by glowing praise by one Sagar Parikh:
Free of any potential funding bias... Now, the clinician can identify the four best treatments... A new gold standard of reliable information has been compiled for patients to review.But critical comments swiftly appeared in the Lancet's letters pages. While not accusing Cipriani and colleagues themselves of bias or conflicts-of-interest, Tom Jefferson noted that way back in 2003, David Healy drew attention to:
documents that a communications agency acting on behalf of the makers of sertraline were forced to make available by a US court. Among them was a register of completed sertraline studies awaiting to be assigned to authors. This practice (rent-a-key-opinion-leader) is of unknown prevalence but it undermines any attempt at reviewing the evidence in a meaningful way.This is what's known as medical ghostwriting, and it is indeed a scandal. However, by itself, ghostwriting doesn't distort evidence as such. It's what's published - or not published - that counts. Almost all antidepressant trials are run and funded by drug companies. All too often, they just don't publish data showing their products in an unfavourable light. The fearsome John Ioannidis - known for writing papers with titles like Why most published research findings are false - pulled no punches in reminding readers of this, in his letter:
Among placebo controlled antidepressant trials registered with the US FDA, most negative results are unpublished or published as positive. Take sertraline, which Cipriani and colleagues recommend as the best ... of five FDA-registered trials, the only positive trial was published, one negative trial was published as positive, and three negative trials were unpublished. Head-to-head comparisons can suffer worse bias, since regulatory registration is uncommon. Meta-analysis of published plus industry-furnished data could spuriously suggest that the best drugs are those with the most shamelessly biased data ...Ioannidis also noted that Cipriani did not include placebo-controlled trials in their analysis. He helpfully provided a table showing that if you do include these trials, the ranking of antidepressants is very different:
Of course, Ioannidis was not saying that the drug-vs-placebo data is better than the drug-vs-drug trials. After all, he had just declared it to be biased. But neither is it necessarily worse, and there's no good reason not to consider it.Cipriani et al's response to their critics was a little light on detail. In response to concerns of industrial publication bias, they said that:
we contacted the original authors and pharmaceutical companies to obtain further data or to confirm reported figures.But of course the pharmaceutical companies were under no obligation to play ball. They could just have chosen not to reveal embarrassing data. Rather more reassuring is the fact that the original paper did look for correlations between the drug company running each trial, and the results of the trial; they didn't find any. Rather cheekily, Cipriani et al then went on to suggest that they were the ones who were sticking it to Big Pharma:
The standard thinking has become that most antidepressants are of similar average efficacy and tolerability ... In some ways, this is a comfortable position for industry and its hired academic opinion leaders—it sets a low threshold for the introduction of new agents which can initially be marketed on the basis of small differences in specific adverse effects rather than on clear advantages in terms of overall average efficacy and acceptability.They certainly have a point here. If aspiring antidepressants had to be proven better than existing ones in order to be sold, instead of just as good, there would probably have been no new antidepressants since Prozac in 1990. (And Prozac is only "better" than the drugs available in 1960 in that it's safer and has fewer side effects; it's no more effective.)
But this is not really relevant to whether the Cipriani analysis is valid. And in The Lancet letters, the authors did not address some of the criticisms, such as Ioannidis's point about including placebo-controlled trials, at all. They do point out that their raw data is available online for anyone to play around with.
The debate continued in the pages of Evidence Based Mental Health. In 2008, Gerald Gartlehner and Bradley Gaynes conducted a rather similar meta-analysis, but they reached very different conclusions. They declared that all post-1990 antidepressants are equally effective (or ineffective).
In their comments on the Cipriani paper, Gartlehner and Gaynes say that they were just more cautious in interpreting the results of a complex and problematic statistical process:
Ranking sertraline and escitalopram higher than other drugs conveys a precisionThey also accuse Cipriani et al of various technical shortcomings - and in a meta-analysis, such 'technicalities' can often greatly the skew the results:
and existence of clinically important differences that is not reflected in the body of evidence. ...for sertraline and escitalopram the range of probabilities actually extends from the first to the eighth rank for both efficacy and acceptability... the validity of results of indirect comparisons depends on various assumptions, some of which are unverifiable ... We simply took underlying uncertainties into greater consideration and interpreted findings more cautiously than Cipriani and colleagues.
they included studies with very different populations such as frail elderly, patients with accompanying anxiety and inpatients as well as outpatients ... the effect measure of choice was odds ratios rather than relative risks. Odds ratios have mathematical advantages that statisticians value. Practitioners, however, frequently overestimate their clinical importance...Cipriani et al respond to some of these technical criticisms, while admitting that their analysis has limitations. But, they say, even an imperfect ranking of antidepressants is better than none at all:
We have a choice. We may either make the best use of the available randomised evidence or we essentially ignore it. We believe that it is better to have a set of criteria based on the available evidence than to have no criteria at all... We believe that, despite the likely biases of the included trials, and the limitations of our approach, our analysis makes the best use of the randomised evidence, providing clinicians with evidence based criteria that can be used to guide treatment choices.
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What are we to make of all this? Here's my two cents. It's implausible that all antidepressants are truly equally effective. They affect the brain in different ways. The pharmacological differences between SSRIs such as Prozac, Zoloft and Lexapro are minimal at best but mirtazapine and reboxetine, say, target entirely different systems. They work differently, so it would be odd if they all worked equally well.The search phrase that most often leads people to this blog is "best antidepressant". People really want to know which antidepressant is most likely to help them. In truth, everyone responds differently to every drug, so there is no one best treatment. But Cipriani et al are quite right that even a roughly correct ranking could help improve the treatment of people with depression, even if the differences are tiny. If Drug X helps 1% more people than Drug Y on average, that's a lot of people when 30 million Americans take antidepressants every year.
So, what is the best antidepressant, on average? I don't know. But maybe it's escitalopram or sertraline. Stranger things have happened.
Gartlehner, G., & Gaynes, B. (2009). Are all antidepressants equal? Evidence-Based Mental Health, 12 (4), 98-100 DOI: 10.1136/ebmh.12.4.98
9 comments:
Whether one AD is better than another avoids the question of whether we have sufficiently precise tools to measure that outcome. After all, do we really believe that the BPI can tell us that?
What a disgrace - this "mouth for hire" business should be a sacking offence in any University, or the like. Indeed, anyone who is appointed or promoted based partly on a CV that includes papers that were "ghost written" by a drugs firm should be treated as guilty of embezzlement. It's about time some old-fashioned Presbyterian ethics were re-introduced into science and science-related disciplines, such as medicine. And into the financial world. And into politics. And into.....
reasonsformoving - That's certainly true. And scales could also falsely suggest differences. I reckon the only reason Cipriani ranked mirtazapine as most effective, is that it promotes sleep (very strongly) & increases appetite. And common depression scales (BDI,HAMD) include several Insomnia and Weight Loss items.
dearieme - Unfortunately if you did that half the senior medical faculty of most universities would get the boot.
Or maybe not unfortunately...
"half the senior medical faculty of most universities": seriously, some proportion approaching a half are as corrupt as that?
I agree with Cipriani's view. We must make the best of what we have. We live in a money driven world and this is the result in medical research. Of course there are individuals with their snouts in the trough. Why the indignant surprise? It's the same everywhere else. But that doesn't mean the information is useless. That, indeed, would be the negative abstraction of the depressive ;-)
There was an article in the BJPsych recently showing some interesting evidence of differential treatment effects of Nortriptyline and Escitalopram on different symptom dimensions in depression. http://bjp.rcpsych.org/cgi/content/abstract/194/3/252
Ultimately clinical depression is probably such a multitudinous entity at the biological level that it's hardly surprising the studies of antidepressants are so confusing.
you should rembember that depression isn´t a disease, it´s more of a heterogenous group of different synromes. So what is the best AD depends on what kind of symptoms the patient has. If you do a study about AD-s, you can get such a result as you like, just picking the right population to study.
As there isn´t a best antibiotic for infection, there is not a best AD for depression.
Jim: I agree with all of that. But it raises the question of how we should use the available data. Re: nortriptyline vs escitalopram there's just been another paper from the same group finding that a
"two-piece growth mixture model categorized participants into a majority (75%) following a gradual improvement trajectory and the remainder following a trajectory with rapid initial improvement. The rapid improvement trajectory was over-represented among nortriptyline-treated participants ... In contrast, conventional response and remission favoured escitalopram"...
I actually read some Ioannidis’ (one of the authors mentioned in the post) articles. The author is a Professor and Chairman of the Department of Hygiene and Epidemiology, University of Ioannina School of Medicine in Greece. University of Ioannina as I learned is only 5 years younger than the professor. The professor is not a psychiatrist and that shows in his calculations and reasoning.
So here I am, in my office, listening from thousands of patients how well SRI's work and how they improve their depression, and when stopped - symptoms come back, and when restarted symptoms go away, and how much easier and happier and normal their life became. And then a Greek professor does meta- analysis and statistically "proves" that placebo is as effective.
We learned, thanks to the chap with a calculator, that millions of people have been fooled by thousands of doctors. What if tomorrow he comes up with statistical data that bronchial asthma can be treated as effectively with short promenades as with albuterol? Or severe migraine will go away in a week or so if you do nothing? Meta-analysis said so…
Meta analysis is not sticking numbers in one’s PC, anyone can do that, but understanding the nature of the field of psychiatry, how different it is presently from other medical fields, and then apply appropriate thoughtful methods to get new understanding.
Briefly, almost all research of depression suffers from major limitations. Depression is a cyclical disorder, many symptoms are subjective and highly influenced by the interviewers, symptoms of depression are often confused with symptoms of demoralization and plain dysphoria, the dose of medications must carefully and individually titrated - studies can't possibly accomplish that.
Most studies are time limited - only studies that last a year or more should be valid because seasons are influencing mood for many (imagine comparing blind epidemiological pediatric asthma studies in winter and summer and insist that summer placebo works as well as medication in winter). There are also hormonal and age influences, pts selection, pressure to recruit, you name it.
It is very difficult, if not impossible, to design a study for heterogeneous disorder with unknown etiology and unpredictable response to medications when the natural course of the disorder(s) is poorly understood and even more poorly agreed on. The existing methodology is DEFICIENT and does not take in consideration all the variables.
Even with the most careful design it is almost impossible to demonstrate efficacy of a particular treatment modality in depression. Most studies do not recognize differences between typical and atypical depression, major depressive disorder and depressive personality disorder (which is not in latest DSM, btw), between complicated bereavement and depression of andropause, bipolar and unipolar depression, and plain dysphoria.
Without these distinctions and differentiations all studies are faulty. Meta-analysis only compounds the errors mathematically manipulating bad data. But some information can be used to demonstrate "somatic" safety and tolerability of the medications in various doses because human body is more consistent and uniformed than human brains when it comes to response to meds.
Professor ignored these influences and went ahead with his meta-analysis, I am not surprised by the results; if you ignore variables then everything turns into a mush.
SRI's work, let's figure out for whom and what type of depression, and hold back for a while on meta-analyses.
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