Bad Pharma: How Drug Companies Mislead Doctors and Harm Patients by Ben Goldacre

Author:Ben Goldacre [Goldacre, Ben]
Language: eng
Format: epub
ISBN: 9781452611693
Amazon: 1452661693
Publisher: Tantor Audio
Published: 2013-02-05T00:00:00+00:00

That is just one of many subgroup analyses that have misled us in medicine, often incorrectly identifying subgroups of people who wouldn’t benefit from a treatment that was usually effective. So, for example, we thought the hormone blocking drug tamoxifen was no good for treating breast cancer in women if they were younger than fifty (we were wrong). We thought clotbusting drugs were ineffective, or even harmful, when treating heart attacks in people who’d already had a heart attack (we were wrong). We thought drugs called ‘ACE inhibitors’ stopped reducing the death rate in heart failure patients if they were also on aspirin (we were wrong). Unusually, none of these findings was driven by financial avarice: they were driven by ambition, perhaps; excitement at new findings, certainly; ignorance of the risks of subgroup analysis; and, of course, chance.

Dodgy subgroups of trials, rather than patients

You can draw a net around a group of trials, by selectively quoting them, and make a drug seem more effective than it really is. When you do this on one use of one drug, it’s obvious what you’re doing. But you can also do it within a whole clinical research programme, and create a confusion that nobody yet feels able to contain.

We’ve already seen that positive trials are more likely to be published and disseminated than negative ones, and that this can be misleading. Essentially, the problem is this: when we systematically review only the published trials, we are only seeing a subset of the results, and a subset that contains more positive results. We’ve taken a basket out with us to shop for trials, and been given only the nicest trials to put in it. But we’d be foolish to imagine that only nice trials exist.

This same problem – of how you take a sample of trials – can present itself in another, much more interesting way, best illustrated with an example.

Bevacizumab is expensive cancer drug – its sales in 2010 were $2.7 billion – but it doesn’t work very well. If you look on ClinicalTrials.gov, the register of trials (which has its own problems, of course) you will find about 1,000 trials of this drug, in lots of different kinds of cancer: from kidney and lung to breast and bowel, it’s being thrown at everything.

Inevitably – sadly – lots of results from these trials are missing. In 2010 two researchers from Greece set about tracking down all the studies they could find.31 Looking only for the large ‘phase 3’ trials, where bevacizumab was compared against placebo, they found twenty-six that had finished. Of these, nine were published (representing 7,234 patients’ worth of data), and three had results presented at a conference (4,669 patients’ worth). But fourteen more trials, with 10,724 participating patients in total, remain unpublished.

That’s damnable, but it’s not the interesting bit.

They put all the results together, and overall it seems, regardless of which cancer you’re talking about, this drug gives a marginal, brief survival benefit, and to roughly the same extent in

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