How have pharmaceutical companies corrupted medical literature?

Physicians, pharmacists, nurses, lawyers, administrators, policy makers and many others depend on medical journals for information.  As the best clinical outcomes are sought for each patient; evidence based practice is the standard.

Physicians look to medical journals for up to date, accurate information about current medications and treatment options.  Peer-reviewed journals containing double blinded randomized control trials are the gold standard, with a meta-analysis of those trials being the best evidence.

Prescribers make medication choices based on the published literature, their personal experience, and the experiences of their patients. 

What if our medical literature is being unduly influenced and altered by those with financial gains at stake?
What if throughout the process of testing and approving and marketing new medications, pharmaceutical companies are altering the information prescribers receive?

This article will discuss 7 stages at which biased and false information has already been and still may be introduced into medical literature.

1. Data Ownership
2. Drug Trial Design
3. Data Analysis
4. Ghostwriting Articles
5. Publication Bias/Omitted Information
6. Journal Reprints
7. Advertisements in Journals

STAGE 1: Data Ownership 


Problem: Drug trials are often designed to ensure that the resulting data are owned by the pharmaceutical company and are never made available to clinical research sites, prescribers, or the public. 

Example: In Denmark, 44 industry-initiated randomized trials were approved in 1994-1995 by the Scientific-Ethical Committee for Copenhagen and Frederiksberg.  
There were constraints on the publication rights in 40 (91%) of the protocols. 22 (50%) noted that the sponsor either owned the data, needed to approve the manuscript, or both. None of these constraints were stated in any of the trial publications.

Problem: In the competition for research funds, American academic institutions are likely to compromise ethical standards, granting data ownership and more to pharmaceutical companies.

Example: In a survey of 107 American medical schools it was found that 80% would allow a multicenter trial agreement that granted data ownership to the sponsor. 69% of the administrators said that the competition for research funds created pressures on them to compromise the conditions of the contract.
This leads to the following problem, found in a second survey of American medical schools: In a survey of 108 American medical schools it was found that “Academic institutions routinely engage in industry-sponsored research that fails to adhere to ICMJE (International Committee of Medical Journal Editors) guidelines regarding trial design, access to data, and publication rights.”

When drug trials are pre-designed to grant data ownership, analysis, and manuscript approval to the industry sponsor, the potential for biased publications escalates.

STAGE 2: Drug Trial Design

Problem: In head to head drug trials, the standard medication may be dosed or administered incorrectly, making the new drug look better by faulty comparison.

Many drug trials are designed to compare a new medication to the current standard medication.  If the standard medication is dosed incorrectly, or administered in the wrong way, efficacy may decrease.  In a head to head comparison, this can lead to the incorrect conclusion that the new medication is better because it had higher efficacy than the standard medication.

Example: Prior to FDA approval of Voriconazole, a study was designed to compared Voriconazole to Amphotericin B in the treatment of invasive aspergillosis:

277 patients were randomized into the two treatment groups and completed the trial.  The standard dosing and route of administration was followed:

• IV Voriconazole for 7 days, then oral medication.
• IV Amphotericin B

However the length of treatment was substantially different for the two groups.

• The median duration of voriconazole treatment was 77 days.
• The median duration of amphotericin B treatment was 10 days.

With the new medication (Voriconazole) being given for an additional 67 days it is not surprising that the conclusion stated: “Initial therapy with voriconazole led to better responses and improved survival and resulted in fewer severe side effects than the standard approach of initial therapy with amphotericin B.”

STAGE 3: Data Analysis

Problem: Data analysis is often controlled by the industry sponsor and data are often manipulated in favor of the new drug.
Example: When trial endpoints are changed or modified, it is impossible to know if new drugs met their goals.  A 2011 Study analyzed all Randomized Control Trials published in 6 medical journals over a 2 year period (2008-2010).  The journals selected were: New England Journal of Medicine, Lancet, JAMA, Annals of Internal Medicine, BMJ, Archives of Internal Medicine. Out of 2,592 original articles which were reviewed, only 316 reported a pre-specified primary endpoint. We don’t know what the other 2,276 trials were hoping to prove when they started the trial. Only the sponsoring drug company and the FDA likely have that information.  
Of the 316 studies that stated their pre-determined endpoint, 116 (37%) ended up reporting a surrogate primary endpoint and 106 (34%) used a composite primary endpoint.
Surrogate and composite endpoints do not always represent findings that are clinically or statistically significant.
Also, of the 118 trials in which the primary endpoint involved mortality: 32 (27%) used disease-specific mortality rather than all-cause mortality. Thus we do not the cause of death of many patients who died during the trials, whether they were disease related or not.
These data manipulations were found to be more common in drug industry sponsored trials. 
Trials which were exclusively industry sponsored were 16% more likely to use surrogate endpoints than trials which had mixed funding or non-industry funding.
Industry funded trials were also 23% more likely to only report disease specific mortality endpoints.

STAGE 4: Ghostwriting Articles

Problem: Ghostwriting.  When you don’t know who wrote an article you cannot judge the content by the author’s expertise or ethics.

Example: From 1999-2001, 96 journal articles were published about sertraline (Zoloft). Over half of the articles were prepared by one medical writing agency named Current Medical Directions. Their 55 articles were all positive in their portrayal of Zoloft, and only 2 of them acknowledged writing support from people not listed as authors.  Who analyzed the data?  Who wrote the bulk of the text?  Who made the conclusions? We don’t know.  These potentially ghost-written articles were published in well-respected journals such as JAMA (Journal of the American Medical Association), JAACAP (Journal of the American Academy of Child and Adolescent Psychiatry), and Archives of Family Medicine.  The articles written by CMD had, on average, a higher impact factor as well as higher citation rates than the other 41 articles. 

Problem: Articles are often prepared based on a researcher’s study, and then sent to the researcher for their approval, listing the researcher as the author. 

Example: Dr. David Healy had performed research on anti-depressants.  He received an email from a drug company representative stating “In order to reduce your workload to a minimum, we have had our ghostwriter produce a first draft based on your published work. I attach it here.”
The article listed Dr. Healy as the sole author, yet he hadn’t written a single word.  He did not agree with their “glowing review of the drug” and he suggested some changes.  The drug company replied stating that he had missed some 'commercially important' points. The ghostwritten paper was later published in a psychiatric journal in its original form - under another doctor's name.

STAGE 5: Publication Bias/Omitted Information

Problem:  Critical information is often not published.

Example: When research misconduct occurs, it is not mentioned in journal articles based on those flawed studies.
Every year, the FDA inspects several hundred clinical sites performing biomedical research on human subjects. When they find evidence of research misconduct, they publish it in a report on their website. From 1998-2013, the FDA identified 57 clinical trials with serious problems including falsification of data, protocol violations,  and failure to protect the safety of patients.
Those 57 Trials led to 78 Publications.  Only 3/78 publications (4%) mentioned the objectionable conditions or practices found during the inspection.  No corrections, retractions, expressions of concern, or other comments acknowledging the key issues identified by the inspection were subsequently published.

Problem: If a study’s results are unfavorable to a new drug, they are often not published, leading to a publication bias in favor of the new medication.

Example: A search for all studies performed on 12 antidepressants found 74 trials registered with the FDA.  37 trials showed positive results for the antidepressant and all but one of them were published.  One trial had neutral results.  The other 36 studies showed negative or questionable results from the antidepressants.  22 of them were not published, 11 were published in such a way as to make the outcome appear positive, and only 3 were published showing the negative results.

Only Published Trials

Thus, in the published literature, 94% of antidepressant trials showed positive results.  By contrast, FDA analysis of all antidepressant trials showed that only 51% were positive.  It should also be noted that 3,449 study participants never had their data published.

 Including Unpublished Trials

     

STAGE 6: Journal Reprints

Problem: Medical Journals can earn higher profits if they publish pharmaceutical industry sponsored papers.  This gives an incentive to give those papers preferential treatment.

Example: Medical Journals make money of journal publications and reprints.  Journals which publish a study funded by the pharmaceutical industry have higher numbers of reprints ordered.
In a study looking at reprint orders, Papers funded by the pharmaceutical industry were more likely to have reprints ordered than were control papers (odds ratio of 8.64.)  Even if a study was only partially funded by pharmaceutical companies it was still more likely to be re-ordered, (odds ratio of 3.72).
This matters because there is substantial money to be made off reprints.
In a study of income from reprints, it was found that The BMJ made £12 ,458 on average for a reprint order.  Lancet earned £287,353 per reprint order.11

STAGE 7: Advertisements in Journals

Problem: Drug advertisements in Medical Journals are often misleading or inaccurate.
Example: In 1992, Annals of Internal Medicine examined the accuracy of advertisements in 10 medical journals.  They found 109 full page pharmaceutical advertisements. The ad and the cited source were sent to three reviewers, (2 physicians in the field and a clinical pharmacist).  They concluded that 34% of advertisements required major revisions and 28% should not have been published.
Example: A 2003 study published in Lancet analyzed all advertisements for anti-hypertensives or lipid lowering agents in 6 medical journals for a period of one year.   Out of 287 advertisements, only 125 listed at least one reference.  18% of those references could not be found.  44% of the references did not support the statement in the advertisement.

DISCUSSION

"Medical journals are an extension of the marketing arm of the pharmaceutical companies" according to Richard Smith who worked for 13 years as editor of The BMJ (British Medical Journal).

The deeper we dig the more evident it becomes that our medical literature is not as pure or objective as we might wish to believe.  Often our journals are just another form of advertising.  This is not limited to journals with small circulation numbers or case reports only.  The most well respected journals with the highest circulation including NEJM, JAMA, BMJ, Lancet, and others have all suffered bias from pharmaceutical companies.

The potential for bias is evident from the very beginning of the process.  From the initial design of drug trials, contractual agreements ensure that the results will be owned and analyzed only by the sponsoring company.  While they must register the trial with the FDA, they are under no obligation to publish the results of their study.  Papers can be written by anyone.  Ghostwriters are commonly employed by pharmaceutical companies to prepare positive papers which will then be published under a researcher’s name.  While this may have some valid benefits, such as freeing up time for the researcher to continue his/her work, it is disingenuous.  The data are only as good as the person analyzing and explaining them.  If we don’t know the true credentials of the author, nor their financial interests, how can we judge the validity of their findings?

The same is true of journal editors.  How can we judge the contents of a journal when there is financial incentive to publish pharmaceutical sponsored papers.

Pharmaceutical companies can do excellent, valid research and bring good medications to the market. Authors can be trustworthy, journal editors can be ethical and discerning, advertisements can be accurate.

However, often these things don’t occur.  Physicians and hospitals spend thousands of dollars subscribing to medical journals.  A subscription to one database of medical literature can cost up to $500 per year. 

Patients are told by advertisements to “Ask your doctor.”  When they do, they are seeking their physicians informed, educated opinion.  Is that opinion based on evidence and fact?  Or is it based on a paper that was published for financial gain, after being ghostwritten by an unknown author, based on a study which was analyzed to skew results, from data which are proprietary and cannot be re-examined, with a protocol that was altered or not followed in the first place.

Physicians are required to give all patients “informed consent.”  If the data are that suspect, is there really any such thing?

 - written by Matt Larsen D.O. (References to all studies and quotes are available)

Label Things, Not People

I'm a doctor.  I should label a disease, Schizophrenia.  I should not label a person.  A schizophrenic.

We put people into groups, classes, designations.

I try to follow the advice of the Arbinger Institute when they said “Don’t lump the people you’re thinking about into an impersonal mass. Think of individuals…Think of the people.”

It’s a problem I have every day.  I’m a psychiatrist, and every day I am asked to label people.  I am asked to diagnose them and treat them.  Patient #1 has Schizophrenia, #2 has Borderline Personality Disorder, etc…  It’s very easy to change and say Patient #1 IS Schizophrenic, #2 IS Borderline. 

It’s easy to “stop seeing them as people and just see them as a diagnosis.  If I can do that then I can stop worrying about them, and their lives, and their feelings.  I can treat their stated symptoms and go home.  I don’t have to worry about their visitors, their comfort, their real needs or anything. This way is easier.  It’s simpler.  I could just slap a label on them and go home.

Some therapists would tell me to never use the word “patient” but rather “client.”

I still use the term patient because I think mental illness is an illness.  I don’t think my patients are illnesses, I think they have illnesses,

I once read a book called “Crucial Conversations”

The author said “Labeling is putting a label on people or ideas so we can dismiss them under a general stereotype or category… By employing a handy label, we are now dealing not with a complex human being, but with a bonehead.”

I still make this mistake with people every day.  I am a conservative independent, which means I usually agree with the republicans and disagree with the democrats – I’m just sick of political parties so I refuse to be a republican.

When one of my facebook friends wrote a post about “Plan B” for birth control, my autopilot conservative mind kicked – yep, that’s abortion, that’s murder, that’s wrong.  The friend posting must be a bleeding heart liberal.  She probably has never stopped to consider any opinion other than her own.  She must be blinded by her partisan and left wing ideation.  To quote the book – she must be “a bonehead.”

I labeled her.  I discounted her as a “liberal” and that meant I no longer had to consider anything she said as “valid.”  She was part of an “extreme” group, and everything about her must be wrong, tainted, misled, etc…  Forget the fact that she is one of the smartest people I knew in High school, she is now an OB/GYN, she is well read and stays current, and one of the most caring people I know. Luckily she did not instantly label me as a bonehead conservative.  She took time, assumed I was an intelligent human being, and she explained her views, and the reasoning behind it.  My viewpoint changed.  Not only did my view of the subject change, but my view of her changed.  She was once again a person, not a “bonehead liberal.”

It goes beyond politics.  This labeling and dismissing happens everywhere

In the book The Anatomy of Peace, the authors state:  "Lumping everyone of a particular race or culture or faith into a single stereotype is a way of failing to see them as people…we have a propensity to demonize others.  One way we do this is by lumping others into lifeless categories – bigoted whites, lazy blacks, crass Americans, arrogant Europeans, violent Arabs, manipulative Jews, and so on.  When we do this we make masses of unknown people into objects and many of them into our enemies."

Do those labels sound like presidential politics to anyone else?  I hear labels like: Socialist, Rich snob, Flip-Flopper, Baby-killer, Flaming Liberal, fascist, Tax-evader, Communist, Right Wing Hack, etc…

"Let's tell people he's not American."  "Let's tell people she's not Christian." -  It seems all the political parties want to do is find a label that scares people, then make it stick to the other side’s candidate.

Labels and stereotypes are killing us.   They allow us to ignore people, to write them off.  They allow us to dehumanize everyone who doesn’t agree with us.

We must see people as people, anything less is just plain wrong.

Start with language.  Stop defining people by some small aspect of their life.

I was born male, I was born white, and 75 years after I was born, I’ll be Old.

Suddenly, by being born, I just became the enemy of some of my democratic friends: and Old White Man.  The evil overlord of politics and business and religion, an old white male.

It is true that I will be an old white man.  But I will not JUST be an old white man.  I will be so much more, in every possible way.  You cannot know who I am by knowing my race, my religion, my birthplace, or even my diagnosis.

Ever heard people say “She’s so Bipolar, He’s ADD, She’s Borderline, He’s Schizophrenic, She’s Anorexic, He’s OCD, she’s an addict?

That doesn’t sound like labeling problems to be fixed.  That sounds like labeling people, because they ARE the problem, so we can dismiss them.

What did President Obama see when campaigning across the country 8 years ago?
He said: “Spend time actually talking to Americans, and you discover that most evangelicals are more tolerant than the media would have us believe, most secularists are more spiritual. Most rich people want the poor to succeed, and most of the poor are both more self-critical and hold higher aspirations than the popular culture allows.”

So that’s Step One: Label Things, Not People. That’s our job.  To notice how many times we label people, even if it’s only in our heads.  Then work to see them as a complex individuals, not a stereotype.