The Vioxx Hit Squad

"We may need to seek them out and destroy them where they live." The words of a Merck employee regarding people who dared to criticize its bestkilling, er, bestselling painkiller/heart attack inducer Vioxx.

According to The Australian , Merck

...made a hit list of doctors who had to be "neutralised" or discredited because they criticised the anti-arthritis drug the pharmaceutical giant produced. Staff at US company Merck & Co emailed each other about the list of doctors - mainly researchers and academics - who had been negative about the drug Vioxx or Merck and a recommended course of action.

The email, which came out in the Federal Court in Melbourne yesterday as part of a class action against the drug company, included the words "neutralise", "neutralised" or "discredit" against some of the doctors' names.

More about this and similar tales of evil at Before You Take That Pill. You might recall that the superhero team in videos used to train Vioxx sales reps was known as the V-Squad. Perhaps the V-Squad was sent out to "destroy them where they live?" Check out the V-Squad videos here and decide for yourself.

Seroquel, Weight Gain, And the Pursuit of GAD and Depression Indications

Jim Edwards at BNET dug through the Seroquel documents and found many instances of AZ employees noting that Seroquel causes weight gain. Yet the company seemed bent on keeping this information hidden. As I mentioned last week, this sure seems a lot like Zyprexa redux, except with more sex scandals and perhaps more buried data. I suggest that everyone head over to BNET and see the details.

Despite all the bad news, AZ is pressing onward with its application for FDA approval for Seroquel in both generalized anxiety disorder and depression. Yikes. I broke the story earlier this week about the "scientific literature" claiming that Seroquel worked better than Haldol in the treatment of schizophrenia, yet internal company data showed Haldol as superior to Seroquel in reducing schizophrenia symptoms. Between discrepant data, the apparent hiding of negative clinical trials and trying to keep doctors distracted from data indicating that Seroquel caused weight gain, I think that Seroquel's luck may have ran out -- my bet is that the FDA won't approve the drug for depression or GAD. But I've been wrong before; the FDA did approve Abilify as an add-on treatment for depression based on pretty flimsy evidence.

Treatment Guidelines and GSK's Open Disclosure

Last week, I noted that a recently published article had found that studies favoring GSK's "mood stabilizer" Lamictal tended to get published in medical journals while articles reaching less favorable conclusions tended to remained unpublished. I wrote that "GSK worked the system expertly and it paid off." A reader commented that he thought my characterization of GSK as hiding negative data on Lamictal was inaccurate. I appreciate his well-written critical comments, which are linked here and are partially reproduced below:

Acute Depression - All of the acute depression studies (there were 5 not 3 as you reported) were presented at scientific meetings over the years and were recently published in Bipolar Disorders (Calabrese et al. 2008). Why so long to publish? The paper was rejected twice and took 3 years to get accepted because journal reviewers did not find the data of interest.

I responded via comment that, if his history is accurate, then the reviewers should be flogged. He added that GSK had provided negative Lamictal data to numerous authors who wrote review articles on Lamictal. In some cases, this appears to be true. However, in at least one notable case, either GSK failed to provide the data or the authors completely ignored the negative data. The data here appeared in a 2004 "academic highlight" (i.e., lowlight) in the Journal of Clinical Psychiatry. Of relevance, the article was funded by an "unrestricted educational grant" from GSK. The article bashes antidepressant treatment in bipolar as unsupported by evidence. Then the expert panel of authors/key opinion leaders put together their guidelines for treating bipolar disorder.

The article begins by discussing bipolar depression. Lithium is discussed first and receives a positive review. Then comes Lamictal, GSK's mood stabilizer. They discuss, in detail, the positive results from Calabrese et al. The authors then discuss some positive long-term findings for lamotrigine before moving on to olanzapine and olanzapine/fluoxetine. They conclude that lithium and Lamictal have the best evidence for treating bipolar depression as can be seen here:

Category 1 evidence is the best evidence, so hooray for lamotrigine/Lamictal! But what don't they discuss in their "expert" review of the data? How about two negative studies -- SCA40910 (completed in 2002) and SCAB2001 (completed in 1997) -- GSK titles of studies that both showed negative results for Lamictal in treating depression in bipolar disorder. A reader tracked these down and sent them -- you can find them if you head to GSK's clinical trial registry. Given that these "International Consensus Guidelines" were published in February of 2004, you'd think the authors would have included data from both of GSK's unpublished studies unless:
A. They didn't know about their existence (and why would they unless GSK told them)
B. They knew about them but opted to not include them in this "expert review"

Given that a GSK employee has told me how open and honest GSK has been with their data, I'd be interested in seeing his response as to which of the above he believes took place. Keep in mind that the Journal of Clinical Psychiatry, in which this so-called "academic highlight" appeared is a very widely read journal. According to Google Scholar, this piece has been cited 46 times, many of which have doubtlessly recycled the inaccurate claim that Lamictal is an effective treatment for acute bipolar depression.

The same pattern as usual: Company conducts research, selectively publishes positive results, funds "educational" pieces such as "academic highlights" to paint an overly rosy picture of treatment effectiveness and/or safety, and physicians, based upon the "evidence base" delude themselves into thinking that they are writing prescriptions based on the best scientific data.

Antidepressants: Meet the New News, Same as the Old News

A recent meta-analysis from Irving Kirsch and colleagues (available here in PLoS Medicine) indicated that for the great majority of depressed people, the advantage of antidepressants over placebo was small. No kidding. For the most part, this study actually says nothing new. In fact, the same authors did a very similar study not once, but twice, showing that antidepressants were mostly hype (1, 2). So we've known for years that there is a good deal of publication bias (i.e., burying negative results) and that the difference between antidepressants and placebos is quite modest. Wait, you didn't know that? Ah, therein lies the problem. News such as this survives for one to two media cycles then vanishes, as the media attends to more important matters, such as Britney's latest bout of trouble, who won an Oscar, and the like. I mean no disrespect to Kirsch and his colleagues -- their work is tremendously important -- but shouldn't the media make damn sure that the public is aware that the collection of published and unpublished data from clinical trials indicates that antidepressants give only a small benefit over placebo? Or should we learn more about K-Fed, Michael Jackson, and various other trivia?

Note that there is, indeed, a small benefit for drug over placebo. Is the small benefit worth the side effects? Well, that's a different question... An even better question is "Please define the term 'small benefit'..." The benefits for medication over placebo appear to be an underwhelming 1.8 points on the Hamilton Depression Rating Scale. Considering that it is a 52-point scale, with many of those points being determined by ratings of sleep and anxiety, any advantage for a drug relative to a placebo might be unrelated to the core symptoms of depression.

What this study adds is that the most severely depressed patients appear to show somewhat more benefit on antidepressants relative to placebo. Their analyses indicate that the placebo response tends to decline among the most severe cases of depression while the antidepressant effect remains about the same. But most people who take antidepressants are not severely depressed. And, shock of all shocks, Kirsch and colleagues found that data from some trials showing no advantage for drug over placebo were simply not available.

Warning: This paragraph is a bit wonky, so you might want to skip ahead. The authors adopted a standard that anything under an effect size of .50 is not clinically significant, which is a standard adopted by the National Institute of Clinical Excellence (NICE) in the UK. According to conventional criteria (e.g., Cohen), an effect size of .50 translates to a moderate effect and an effect size of .20 translates into a small effect. The average effect in this analysis for drug over placebo was .32. Such an effect is certainly not impressive, but should not be confused with no effect. The problem (as noted above) is we don't really know what a small effect means -- on what items on the rating scale was there typically a difference between drug and placebo? Were these items relevant to depression? In any individual study, one can cherry pick items from a rating scale and show a difference favoring a drug, but I'd be more interested in what a large meta-analysis such as Kirsch's most recent study would show on the individual items of the HAM-D or other rating scales. One more thing: The effect for antidepressants really looks bad at the lowest end of severity. Go to Table 1 in the study and look at the effect sizes for the studies where the baseline depression rating is under 24. My own back of the envelope calculations, factoring in sample size, gives an effect size of about .10, which equates to about nothing for the least depressed folks.

Fortunately, the Independent has a nice little story on the topic, though the headline is a little obnoxious. I quote as follows:

Alternative treatments for depression, such as counselling or physical exercise, should be tried first, Professor Kirsch said. The pharmaceutical companies had withheld data that was available to the licensing authorities so that doctors and patients did not understand the true efficacy, or lack of it, of the drugs.

"This has been the frustration. It has made it very difficult to answer the question of whether the drugs work. The pharmaceutical companies should be obliged when they get a drug licensed to make all the data available to the public. When you analyse all the trials of these SSRIs, both published and unpublished, it leads you to more sober conclusions," he said.

Tim Kendall, deputy director of the Royal College of Psychiatrists' research unit, said the findings, if proved true, would not be surprising. As head of the National Collaborating Centre for Nice guidelines on mental health, he said it had proved impossible to get access to unpublished trials in the past.

"The companies have this data but they will not release it. When we were drawing up the guidelines on prescribing antidepressants to children [in 2004] we wrote to all the companies asking for it but they said no. The Government pledged in its manifesto to compel the drug companies to give access to their data but that commitment has not been met."

But, to be fair and balanced, here are the critiques of the pharma companies, which provide the usual nonspecific and bogus mumbo-jumbo

GlaxoSmithKline, makers of Seroxat, said the authors of the study had "failed to acknowledge" the very positive benefits of SSRIs and their conclusions were "at odds with the very positive benefits seen in actual clinical practice." A spokesperson added: "This one study should not be used to cause unnecessary alarm for patients."

Lilly said in a statement: "Extensive scientific and medical experience has demonstrated that fluoxetine [Prozac] is an effective antidepressant.

Wyeth said: "We recognise the need for both pharmacological and non-pharmacological treatments for depression."

If there is such "extensive" evidence about the "very positive" effects of these medications, why wouldn't a single one of these companies cite a single study? Oh, right, because Kirsch already examined the relevant studies. This study, in combination with the recent study in the New England Journal of Medicine that showed how every single drug company with an antidepressant on the market twisted their data regarding the efficacy of antidepressants, should serve as a wakeup call for those who have not been paying attention to the issues of mediocre antidepressant efficacy and how inconvenient data are buried. Overplay the positive data, hide or lie about the negative data. As for depressed patients: Let Them Eat Prozac.

Also see discussion at Furious Seasons.

Key Opinion Leaders and Information Laundering: The Case of Paxil

Joseph Glenmullen’s testimony regarding GlaxoSmithKline’s burial of suicide data related to Paxil, which was discussed briefly across the blogosphere last week (Pharmalot, Furious Seasons, for example), was quite interesting in many respects.

One important aspect that needs public airing is how key opinion leaders in psychiatry were used by GSK to help allay fears that Paxil might induce suicidal thoughts and/or behaviors. When GSK issues statements indicating that Paxil is not linked to increased suicide risk, many people will think “Gee, of course GSK will say Paxil is not linked to suicide – it’s their product, after all.” But when purportedly independent academic researchers make the same claims regarding the alleged safety of Paxil, then people tend to think “Well, if these big-name researchers say it’s safe, then I suppose that there’s no risk.” But what if GSK simply hands these big-name researchers (aka “key opinion leaders") charts with data, and then the “independent” researchers go about stating that Paxil is safe? Mind you, the researchers in question don’t see the actual raw data – just tables handed to them from GSK – in other words, they simply take GSK’s word that the data is accurate. In essence, these researchers are serving as information conduits for GSK.

But wait a second, what if the charts and data tables handed to them by GSK are not an accurate representation of the raw data; what if GSK is lying? Well, of course, it turns out that GSK was lying in a big way for several years. This post will not go into depth on the suicide data, as it has been covered elsewhere (1, 2, 3 ) -- even GSK now admits that Paxil is related to an increased risk of suicidality.

My main question in this post is how we are supposed to trust our "key opinion leaders" in psychiatry if they are willing to simply look at data tables from GSK (and others), then make pronouncements regarding the benefits and safety of medication without ever examining the raw data. To put this in layman's terms, suppose an election occurs and candidate A wins 70% of votes while candidate B wins 30% of votes. As the vote counter, I then rig the results to say that candidate B won the election by a 55% to 45% margin. Suppose that the election certification board shows up later and I show them a spreadsheet that I created which backs up my 55% vote tally for candidate A. The election board is satisfied and walks away, not knowing that the vote counting was a sham. Obviously, the election board should have checked the ballots (the raw data) rather than simply examining the spreadsheet (the data table). In much the same way, these so-called thought leaders in psychiatry should have checked the raw data before issuing statements about Paxil.

What did these key opinion leaders say about Paxil? Some quotes from Glenmullen's testimony follows, based upon documents he obtained in GSK's archive. Here's what David Dunner (University of Washington) and Geoffrey Dunbar (of GSK) reportedly said at a conference

Suicides and suicide attempts occurred less frequently with Paxil than with either placebo or active controls.

John Mann of Columbia University, regarding how data were collected:

We spent quite a bit of time gathering data from various drug companies and formulating it into the publication of the committee's findings

The committee he references is a committee from the American College of Neuropsychopharmacology, the same organization that issued a dubious report blessing the use of antidepressants in kids.

More from Mann, after being asked if he saw raw data or just data summarized in tables:

To be perfectly honest, I can't recall how much of the statistical raw data we received at the time that we put these numbers together...No, I think we all went through the tables of data that were provided at the time.

To use the analogy from above, the election board did not actually see the ballots. Stuart Montgomery is next. He was an author, along with Dunner and Dunbar, on a paper in the journal European Neuropsychopharmacology that stated:

Consistent reduction in suicides, attempted suicides, and suicidal thoughts, and protection against emergent suicidal thoughts suggest that Paxil has advantages in treating the potentially suicidal client.

Did Dunner see any raw data?

Dunner: I didn't see the raw data in the case report forms. I did see the tables. I work with the tables. The tables came before any draft, as I recall. We -- we created the paper from the tables.

Attorney: And -- and you never questioned, did you, or did you not question the validity of the data in Table 8?

Dunner: No

The above-mentioned paper that gave a clean slate to Paxil? According to a GSK document examined by Glenmullen, it was used by GSK to help convince physicians that they need not worry about Paxil inducing suicidality.

If you are an academic researcher, and you simply take data tables from drug companies then reproduce them in a report and/or publication, you are not doing research -- you are laundering information. People think that you have closely examined the data, but you have not, and you are thus doing the public a disservice.

I am unaware of any of the above researchers ever issuing a public apology. I can respect the context of the times; researchers may not have been aware of how pharmaceutical companies fool around with data in the early 90's. So if anyone wants to issue a mea culpa, I'd respect such an apology, but I have a feeling that not a single one of the above named individuals (nor this guy) will make an apology. Instead, it will be more business as usual, as these key opinion leaders, knowing who butters their bread, will continue to launder information and tell the public that everything will be fine and dandy if they just take their Paxil, Seroquel, or whatever hot drug of the moment is burning up the sales charts.

Antidepressants: Hiding and Spinning Negative Data

As I alluded to yesterday, a whopper of a study has just appeared in the New England Journal of Medicine. It tracked each study antidepressant submitted to the FDA, comparing the results as seen by the FDA in comparison with the data published in the medical literature. The FDA uses raw data from the submitting drug companies for each study. This makes great sense, as the FDA statisticians can then compare their analyses to the analyses from drug companies, in order to make sure that the drug companies were analyzing their data accurately.

After studies are submitted to the FDA, drug companies then have the option of submitting data from their trials for publication in medical journals. Unlike the FDA, journals are not checking raw data. Thus, it is possible that drug companies could selectively report their data. An example of selective data reporting would be to assess depression using four measures. Suppose that two of the four measures yield statistically significant results in favor of the drug. In such a case, it is possible that the two measures that did not show an advantage for the drug would simply not be reported when the paper was submitted for publication. This is called "burying data," "data suppression," "selective reporting," or other less euphemistic terms. In this example, the reader of the final report in the journal would assume that the drug was highly effective because it was superior to placebo on two of two depression measures, left completely unaware that on two other measures the drug had no advantage over a sugar pill. Sadly, we know from prior research that data are often suppressed in such a manner. In less severe cases, one might just switch the emphasis placed on various outcome measures. If a measure shows a positive result, allocate a lot of text to discussing that result and barely mention the negative results.

But wait, there's an even better way to suppress data. Suppose that a negative study is submitted to the FDA. There is no commercial value in presenting negative results on a product. Indeed, it makes no sense from a commercial vantage point to submit a clinical trial that shows no advantage for one's drug for publication in a medical journal. While it earns a bit of good PR for being honest, it would of course hurt sales for the drug, which would not please shareholders. From an amoral, purely financial view, there is no reason to publish negative trial results.

On the other hand, there is science. One of the first things that any medical student hopefully learns is that scientists should report all of their results so that other scientists, physicians, the media, and the general public have an up-to-date and comprehensive understanding of all scientific findings. Yes, this may sound naive, but this is how science is supposed to work in an ideal world.

Back to the NEJM study. Were manufacturers of antidepressants playing by the rules of science or the rules of the almighty dollar? Take a look at this table excerpted from the study...

The FDA concluded that 38 studies yielded positive results. 37 of these 38 studies were published. The FDA found mixed or "questionable" results in 12 studies. Of these 12 studies, six were not published, and six others were published as if they were positive findings. Of the 24 studies that the FDA concluded were negative, three were published accurately, five were published as if they were positive findings, and 16 were not published. To summarize, positive studies were nearly always reported while mixed and negative studies were nearly always either not published or published in a manner that spun the results unreasonably. How does one turn a questionable or negative finding into a positive one? As mentioned above, report the results that are favorable to your product and sweep the remaining results under the rug.

Overall, how do the statistics for this group as prepared by the FDA compare to the statistics in medical journal publications? Remember, physicians are trained to highly value medical journals, as they are the storehouse for "evidence-based medicine." I'll borrow a quote from the study authors:

For each drug, the effect-size value based on published literature was higher than the effect-size value based on FDA data, with increases ranging from 11 to 69%

Well, that's not very reassuring. Effect size refers to the magnitude of the difference between the drug and placebo. Note that for every single drug, the effect size as reported in the medical literature (the foundation for "evidence based medicine) was greater than the effect size calculated from the FDA's data. Remember, the FDA's data is based on raw data submitted by drug companies, and is thus much less subject to bias than data that the drug companies manipulate prior to submitting for publication in a medical journal. Other highlights from the authors:

Not only were positive results more likely to be published, but studies that were not positive, in our opinion, were often published in a way that conveyed a positive outcome... we found that the efficacy of this drug class is less than would be gleaned from an examination of the published literature alone. According to the published literature, the results of nearly all of the trials of antidepressants were positive. In contrast, FDA analysis of the trial data showed that roughly half of the trials had positive results. The statistical significance of a study’s results was strongly associated with whether and how they were reported, and the association was independent of sample size.

I'll say it one more time: Every single drug had an inflated effect size in the medical literature in comparison with the data held by the FDA. To move into layman's terms for a moment, manufacturers of every single drug appear to have cheated. This is not some pie in the sky statistics review -- this is the medical literature (the foundation of "evidence-based medicine") being much more optimistic about the effects of antidepressants than is accurate. This is marketing trumping science.

The drugs that were found to have increased their effects as a result of selective publication and/or data manipulation:

• Bupropion (Wellbutrin)
• Citalopram (Celexa)
• Duloxetine (Cymbalta)
• Escitalopram (Lexapro)
• Fluoxetine (Prozac)
• Mirtazapine (Remeron)
• Nefazodone (Serzone)
• Paroxetine (Paxil)
• Sertraline (Zoloft)
• Venlafaxine (Effexor)

That is every single drug approved by the FDA for depression between 1987 and 2004. Just a few of many tales of data suppression and/or spinning can be found below:

• Data reported on only 1 of 15 participants in an Abilify study
• Data hidden for about 10 years on a negative Zoloft for PTSD study
• Suicide attempts vanishing from a Prozac study
• Long delay in reporting negative results from an Effexor for youth depression study
• Data from Abilify study spun in dizzying fashion. Proverbial lipstick on a pig.
• A trove of questionable practices involving a key opinion leader
• Corcept heavily spins its negative antidepressant trial results

Props to the Wall Street Journal (David Armstrong and Keith Winstein in particular) and the New York Times (Benedict Carey) for quickly getting on this important story.

There are some people who seem unmoved by this story. Indeed, some people are crying that this is an unfair portrayal of the drug industry. More on their curious take on the situation coming later.

I'll close with a question: What does this say about the key opinion leaders whose names appear as authors on most of these published clinical trials in which the data is reported inaccurately?

Antidepressants: You Dropped a Bomb on Me

According to a hot-off-the-press article in the New England Journal of Medicine, publication bias in antidepressants has been quite quite substantial. Much as I've documented in a recent post, the researchers found a great deal of misinterpreted research and buried studies.

Hats off to the researchers for their impressive and thorough analysis. Unfortunately, I have no time to comment on the study in more depth now. In the meantime, read David Armstrong's excellent piece in the Wall Street Journal. I plan to offer my take on this sordid tale in the near future.

If you've read my blog for long, you are aware that I am qualified to say "TOLD YOU SO!" on this topic. I hope that the bomb dropped on the drug industry from this study's results is heard loudly and clearly across the world.

Zetia: Just the Latest Chapter in Hiding Data

There have been many interesting posts written about how data regarding Zetia were buried for quite some time. One of the main storylines in this saga is that it took about two years after the study was completed to analyze and release the data. The most disappointing aspect of this story is that few if any outlets are noting that this is not a fluke event.

Clinical trials are a huge part of how drugs are marketed. After examining clinical trial data, physicians who prescribe their drug believe they are engaging in evidence-based medicine. Granted, most physicians have little training in actually understanding statistics or research design, which are key in understanding clinical trial evidence. But that's not the point of this post...

The point is that Zetia is just the latest chapter in a lengthy volume of hidden clinical trial data. Here's one study in which it appears that data were reported on 1 of 15 participants. There was also a study examining Zoloft for PTSD in which data were reported about 10 years after the end of the study. How about suicide attempts apparently vanishing from a study report on Prozac? And a 5-6 year delay in reporting results on Effexor for depression in youth?

The above reports on hiding data were all based on studies I encountered randomly. I did not go fishing to find studies which published their data many years after it was collected or only reported a partial picture of their results. I was just looking through journals and happened to run across the studies mentioned above. Publication bias does not just occur when negative results are simply not published (which seems a fairly common practice), but it also occurs when negative results are published after a long delay. Delaying negative data means raking in more cash before the negative data reduces prescriptions for a product.

So you can be outraged by the Zetia story if you'd like, but please don't act surprised. Similar events will happen again and again and again.

Update: Welcome to those of you who have clicked the link from the Wall Street Journal. Please take a look around to find a series of documented incidents where science has been overrun by marketing. Add comments as you deem appropriate.

Changes?

Alex Chernavsky has written many thoughtful comments on this blog, which I greatly appreciate. His latest comment is about the potential Zetia coverup, but it could have been written in response to many other topics and been just as apropos. I wish I could disagree with him, but I think he has a point...

What strikes me in these cases is just how little progress we are making. I've been following this stuff for the last 12 years or so, and I see a lot of exposés -- but not a lot of substantial changes that result from those exposés.

For example, if you look back to 2000-2001, you'll see that David Willman -- a reporter for the Los Angeles Times -- won the Pulitzer prize for a series of articles about corruption in the pharmaceutical industry. His articles are first-rate and are still worth reading today:

http://www.pulitzer.org/year/2001/investigative-reporting/works/

But that was seven years ago. Are we in a better position today? Maybe I'm being overly harsh, but I just don't see a lot of progress made. Big Pharma has corrupted medicine -- and especially psychiatry -- and now has its sights set on psychologists.

Zetia: But Why Would We Show You the Scary Data?

Alex Berenson has potentially unearthed another December Surprise for a major drug company. You may recall that last December, Berenson started writing on the Zyprexa mess (1, 2), which everyone can now read about through accessing the now-infamous Zyprexa documents over at Furious Seasons.

It now appears that there have been at least three unpublished studies regarding the health effects of Merck/Schering Plough's anticholesterol drug Zetia that point to the drug causing liver problems. Read the full article at the New York Times. Only time and a little sunshine on these studies will reveal whether this is a big story, but it is important to note that this is not particularly surprising -- on this modest blog, I have documented several incidents of data pointing to poor efficacy and/or drug risks being buried (1, 2, 3, 4, 5, 6 are just a few examples). Many other blogs, newspapers, and other sources have also documented such problems. Hiding data is an everyday occurrence. For whatever new medication is approved, the public dissemination of risks and benefits are managed by the sponsoring company and what would be the company's motivation to provide data that paint a scary picture of their new drug?

You REALLY Don't Wanna Publish That, Right?

Due to a lot of hits on a post from March over the past few days, I am providing a link to it since it is apparently becoming a hot commodity. The post is about Zyprexa, and the email of one Lilly employee in which different ways to suppress the study's results were discussed. Naughty. Very naughty.

And Lilly is painting David Egilman as the bad guy for his role in disseminating the now-infamous Zyprexa documents? Gimme a friggin' break! Oh, and did I mention the aforementioned post is based on one of those documents?

Yous-A-Don't Wanna Publish That, Right?

When a company funds a study that finds unfavorable results, they can always deep-six it. But what if someone else conducts the study -- someone you did not fund? Well, a Lilly employee had some interesting thoughts on the matter.

A study was conducted, then presented at a conference. A Lilly employee found out about it, noted that it pointed toward negative safety implications for olanzapine (Zyprexa) and then had some ideas [bold in original, color highlights added]...

If we work on the assumption that this poster WILL be published as a full manuscript soon, our attention needs to turn to how we can minimise its impact on both the global and local level... Where will this paper be published?... Can we stop/delay it? I think it would be very difficult to delay except if one of our scientists could show them that their methodology was flawed...

Do we know the author? Can we exert any influence? this would be very dangerous as it would be seen as lilly behaving unethically and applies to the below points.
Who sits on the editorial board of the targeted journal? Can we influence them in any way, with respect to the limitations of this methodology? Should we conduct a communications initiative aimed at all influential referees, addressing the above point?

To review, one idea was to find out where the paper might get submitted for publication, then try to influence the editor, as well as sending out a "communications initiative" in an attempt to bias individuals who might review the article to determine its suitability for publication. Or, "influence" the author -- with what? Cash, a baseball bat, hookers and cocaine, what? How does a drug company that did not even sponsor study X call on study X's lead investigator and tell him, "Hey you really shouldn't publish that!" Unbelievable.

Happy Ending: The author in question has published multiple studies in the area, so either Lilly thought better of their idea to suppress the evidence or their efforts failed miserably. It would seem as if Lilly may wish to hire a Dr. Purple-type character for future efforts (1, 2, 3)??

Source (one of the infamous Zyprexa Documents).