The science columnist, author, and academic Dr. Ben Goldacre, has just written a new book about the pharmaceutical industry, Bad Pharma: How Drug Companies Mislead Doctors and Harm Patients. In connection with the publication of this book, The Guardian has published an excerpt. In this excerpt, Goldacre discusses a number of fallacies regularly committed by the pharmaceutical companies in their efforts to get their drugs approved for use by various government regulatory agencies. We can see these fallacies clearly exemplified in Dr. Goldacre's discussion of the anti-depressant reboxetine.
Though not approved for use in the US, reboxetine has been approved for use in many countries including the UK (where Dr. Goldacre is from, hence his experience prescribing the drug). As Dr. Goldacre notes, he has prescribed the drug in the past based on the best evidence available to him in the form of published studies of effectiveness and approval by the MHRA which regulates pharmaceutical in the UK.
The first fallacy that Goldacre discusses is the Suppression of Relevant Data. He notes that seven trials were conducted on the effectiveness of reboxetine, but only one, done on 254 patients was published. This study, unsurprisingly showed reboxetine to be effective. However, there were six other studies done on a total of over 2000 patients, and these studies showed that reboxetine was no better than placebo. These studies were suppressed by the drug manufacturer because they did not produce results favorable to the manufacturer. This is a clear example of the suppression of relevant data because the drug manufacturer was suppressing data relevant to determining the effectiveness of reboxetine.
We can see a similar example when looking at the data comparing reboxetine to other anti-depressants. Three published studies covering 507 patients showed reboxetine to be more effective than other anti-depressants, while other studies covering 1657 different patients, which showed reboxetine to be worse, remained unpublished. This is, again, a suppression of relevant data.
In addition, these are also example of Cherry Picking and Hasty Generalization. It is Cherry Picking in that the drug manufacturer is only selecting studies that are favorable while ignoring studies that are unfavorable. It is also a Hasty Generalization because through the cherry picking and suppression of relevant data the drug manufacturer is leading the various national regulatory agencies and doctors to draw substantive conclusions on the basis of limited data.
As Dr. Goldacre goes on to note, this is the result of a massive conflict of interest in that the drugs are tested by the people who make them, and these manufacturer stand to make a great deal of money so long as the drug receives approval. This gives the manufacturer an incentive to manipulate and fudge the data so that it produces results favorable to the manufacturer, even if these results aren't accurate. As Goldacre notes, a 2010 study jointly conducted by Harvard and Toronto found that 85% of studies funded by industry produced positive results while only 50% of government funded studies did. (I couldn't find a reference to this study, but here is a link to a 2012 study that seems to find a similar result). This clearly demonstrates that conflicts of interest can bias the results of pharmaceutical (and other) research.
So, given this serious problem with medical research and doubts about the accuracy of claims made about the effectiveness of pharmaceuticals, what can be done? I am sure Dr. Goldacre's book addresses this question in detail, but two obvious solutions present themselves (how feasible these would be is an entirely separate question).
One obvious solution would be to increase federal funding for medical and scientific research. That is, don't allow pharmaceutical manufacturers to test their own products, but have them tested by independent researchers. This funding could just be from the government (an unlikely proposition in today's political climate) or by a tax on pharmaceutical company profits (perhaps another unlikely proposition given the political climate).
A second solution, suggested by Dr. Steven Novella is perhaps more realistic. He advocates requiring all research data on human subjects be made publicly available. As Dr. Novella puts it, with the privilege of conducting human trials should come the obligation to make that data public. In this way, pharmaceutical companies couldn't cherry pick or suppress
relevant data because all the data would be out there for independent
researchers to evaluate.
Whatever the solution is, it is clear that this is a significant problem that must be addressed sooner rather than later if people are to continue to have confidence in the medical profession and if we are to empower doctors and patients to make fully informed decisions about medical care.