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Wednesday, February 06, 2013

Drug Companies: Stop Hiding Your Data

In one of the harsher comments to my earlier post on the use of "mystery placebos" in drug-company (and other) research, a post that got well over 32,000 visits, someone took me to task for alleging that pharmaceutical companies are evil, even though that's not what I said in the post. All I was trying to do with that post was call for a move toward standards for placebos, and also call for disclosure (by drug companies) of the ingredients of the placebos they manufacture for their own use, especially active placebos. The way things are now, nobody knows what's in a placebo except the drug companies, who aren't saying.

If I really wanted to show the pharma giants as evil, I'd have done a lot more than just write about lack of placebo standards. I'd have started by pointing to the disturbing pattern of research-hiding that characterizes drug-company research (the subject of today's post). Then I'd follow up with posts on defective protocol designs (this is practically a book), such as allowing test subjects to continue to take anxiolytics and other psychoactive drugs, on the side, while participating in SSRI efficacy research. (Or testing individuals for placebo-sensitivity and then removing sensitive individuals from studies before they begin.) Then I might talk about the completely bizarre practice of pooling results from different studies (studies that differ in the number of subjects, subject demographics, length of study, and other parameters), something FDA actually allows companies to do. I'd look at how GlaxoSmithKline suppressed suicide data on Paxil. Then I'd talk about illegal marketing of mood stabilizers and antipsychotics by Abbott and Johnson & Johnson, respectively. I'd talk about recent meta-studies that have shown that SSRIs like Prozac have no more efficacy than placebo, and less efficacy than certain older drugs, despite years of blatantly misleading propaganda to the contrary by Eli Lilly and others. (There's also the fact that SSRI studies have notoriously high drop-out rates, and most of the people who drop out do so either because the drugs didn't do anything or caused them to get worse. The drop-outs represent data that doesn't get reported.) And on and on.

But let's limit the discussion, today, to selective publication of research.

There is no doubt whatsoever that the major drug companies have engaged in a systematic practice of "hiding bad results." There is also a tendency of companies to spin-doctor research to show poor results in a favorable light.

In a 2010 study by researchers from the American University in Washington, D.C., the authors found:
Meta-analyses of FDA trials suggest that antidepressants are only marginally efficacious compared to placebos and document profound publication bias that inflates their apparent efficacy. These meta-analyses also document a second form of bias in which researchers fail to report the negative results for the prespecified primary outcome measure submitted to the FDA, while highlighting in published studies positive results from a secondary or even a new measure as though it was their primary measure of interest.
See "Efficacy and Effectiveness of Antidepressants: Current Status of Research,"  Psychotherapy and Psychosomatics 2010;79:267–279, full PDF here.
A German study (published in 2010) found that company-funded trials are four times more likely to find evidence in favor of the trial drug than studies funded by other sponsors.

Another study, published in 2003, found: "Studies sponsored by pharmaceutical companies were more likely to have outcomes favouring the sponsor than were studies with other sponsors (odds ratio 4.05; 95% confidence interval 2.98 to 5.51; 18 comparisons)."

In 2008, Erick Turner, M.D. and colleagues looked at 74 studies on antidepressants submitted to the FDA. They found that only half the studies were positive (showing good efficacy results). The unfavorable studies either weren't published (22 studies) or were spin-doctored to portray the results positively (11 studies) even though the results were actually poor. See "Selective Publication of Antidepressant Trials and Its Influence on Apparent Efficacy" (New England Journal of Medicine 2008; 358:252-260).

The Turner study found that if you looked only at published literature, you'd get the impression that 94% of trials conducted were positive. But if you take into account unpublished as well as published studies, only 51% of all studies are positive (for the 74 studies they looked at, on a variety of antidepressant drugs).

In 2004, then-NY-Attorney-General Eliot Spitzer filed suit against GlaxoSmithKline, saying the firm committed fraud by withholding negative information and misrepresenting data on its antidepressant Paxil. Last July, the suit was settled for $3 billion, the largest drug-company settlement in history.   It's important to note that GlaxoSmithKline didn't just cut a settlement deal. They actually pled guilty to the charges.

In 2007, FDA visited GlaxoSmithKline's Research Triangle Park (North Carolina) offices after reports in the New England Journal of Medicine showed that Avandia, GSK’s popular diabetes drug, increased patients' rate of heart attack by 43 percent. FDA found that GSK failed to report information on nine studies related to Avandia. FDA subsequently forced the company to respond with a plan to ensure that all relevant studies are reported to the government in the future. (See news account here.)

Meanwhile the Ottawa Hospital Research Institute, in conjunction with researchers from Canada, France and England, found that major drug companies routinely hid negative clinical trial information about 50 percent of the time

Is there a pattern here? I think so.

It's clear that FDA needs to make available all drug company studies (after they've been submitted to FDA) online, on its web site, as a public service. This would effectively cause all studies, good and bad, to be published (to the Web). We shouldn't have to rely on a subculture of drug injury lawyers to dig up, and air out, pharma research through expensive deposition and discovery processes. Nor should it be necessary for anyone to file a Freedom of Information Act request to get drug-company-submitted research out of the Food and Drug Administration. This is information that needs to be exposed, not hidden.

It's very simple. What the drug companies need to do is report their findings -- 100 percent of the findings 100 percent of the time. If they won't do it, FDA should do it for them. Otherwise consumers and legitimate scientists alike are being misled. Bamboozled. Not by accident but deliberately. That's what the data show.


  1. Anonymous11:35 AM

    Selective publication of research, or 'publication bias', is indeed a major issue in clinical medicine. But it is becoming an increasingly recognised problem and steps are being taken to tackle it. You highlight that the FDA should make available all studies conducted to the public, regardless of whether they have a positive or negative outcome. A variation of this concept has been attempted before where drug companies and academics who do clinical research publish were encouraged to 'sign-up' their trial/study to an online register. The major downside of this particular approach was that it was voluntary. Alternatively, you need to question why journal are the best medium for distribution of research. Are there other mechanisms which perhaps bypass the pressure of publishing only positive papers? In the end, publication bias is a complex issue to deal with, and requires multiple approaches to the tacle it.

    While I am here, I also will attempt to answer why, as you put, study results are 'pooled' from different studies. This type of data analysis is called a 'meta-analysis' and follows on from conducting a 'systematic review'. It is a cornerstone in evidence-based practice, even though it may appear bizarre. Initally, you perform the systematic review, which sets out exactly what you did to search for data in a particular area of medicine (search terms used, databases used etc). Using the collected data, you then pool it into what is called a meta-analysis (think giant spreadsheet of data from all the trials you used). Finally, and most importantly, you do analysis on the data as a whole to get one most accurate information on your clinical question. Further, you can conduct a cumalative meta-analysis which shows the 'summary results' if a meta-analysis was performed earlier in time. It's a difficult concept to explain, so I'll cut and paste an exerpt from Bad Pharma (book by Ben Goldacre) as to why they are so important (he uses the example of streptokinase);

    "So what’s that on the right? It’s something called a cumulative meta-analysis. If you look at the list of studies on the left of the diagram, you can see that they are arranged in order of date. The cumulative meta-analysis on the right adds in each new trial’s results, as they arrived over history, to the previous trials’ results. This gives the best possible running estimate, each year, of how the evidence would have looked at that time, if anyone had bothered to do a meta-analysis on all the data available to them. From this cumulative blobbogram you can see that the horizontal lines, the ‘summary effects’, narrow over time as more and more data is collected, and the estimate of the overall benefit of this treatment becomes more accurate. You can also see that these horizontal lines stopped touching the vertical line of no effect a very long time ago – and crucially, they do so a long time before we started giving streptokinase to everyone with a heart attack."

    Link to diagram:

    Institutes such as the Cochrane library do this type of analysis and because of the benefits to practice, the FDA and other regulatory bodies allow it.

  2. This clarity with your post is superb and that i may think you’re a guru for this issue.
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