Half The Lies You Tell Ain't True

You’ve probably seen all the fuss over Wyeth and the ghost-writing of medical articles, along with the associated smugness of certain commentators. According to my contacts in the medical comms industry, the practice as such is nothing new, and there are very, very strong guidelines. The creative outrage we’re seeing is really rather misplaced:

Well, this is 1998 information and back then, things were a LOT slacker and this kind of thing did go on. The last 5 years have seen a big change and the policy that Wyeth now has is pretty much in line with everyone else

and

Pharma has sorted this out and anyone behaving like that gets fired. In fact, not stating the source of funding for writing invokes the OIG Federal Anti-kickback Statute, and that is two years in chokey.

{REDACTED} have EXAMS on compliance and anyone breaching compliance in a way that results in negative press for us or our clients is fired.

Teapot, there’s a storm a-brewin’.

Anyway, I didn’t want to talk about that, except it’s a nice hook on which to hang examples of a different-but-similar kind of spin.

Via John Graham-Cumming (go sign his Turing petition) I found this wonderful, wonderful site that shows you just how medical comms, pharma companies, eco-terriers, homeopaths, publishers, bloggers, GPs, PR agencies, newspapers, organic interest groups and in fact just about anyone can lie to you without really lying. It’s precisely the sort of thing that Ben Goldacre tries to get the numpty public (and let’s face it, most scientists/medics) to understand, except with pretty graphs and funky webby clicknology.

2845 ways to spin the risk uses an interactive animation to show exactly how drugs, interventions, whatever can be made to look good, bad or indifferent, simply by displaying the same data in different ways.

chances

Play with the animation for a while, then go read the explanations. The whole ‘relative risk/absolute risk/number needed to treat’ thing is pretty well explained, along with bacon butties:

Yet another way to think of this is to consider how many people would need to eat large bacon sandwiches all their life in order to lead to one extra case of bowel cancer. This final quantity is known as the number needed to treat (NNT), although in this context it would perhaps better be called the number needed to eat. To find the NNT, simply express the two risks (with and without whatever you are interested in) as decimals, take the smaller from the larger and invert: in this case we get 1/(0.06 – 0.05) = 100. Now the risks do not seem at all remarkable.

Mmm. Bacon.

Interesting tidbits abound:

One of the most misleading, but rather common, tricks is to use relative risks when talking about the benefits of a treatment, for example to say that “Women taking tamoxifen had about 49% fewer diagnoses of breast cancer”, while harms are given in absolute risks – “the annual rate of uterine cancer in the tamoxifen arm was 30 per 10,000 compared to 8 per 10,000 in the placebo arm”. This will tend to exaggerate the benefits, minimise the harms, and in any case make it unable to compare them. This is known as ‘mismatched framing’

which is quite intriguing, but then we find that it

was found in a third of studies published in the British Medical Journal.

Ouch.

It’s a splendid breakdown of all the things we need to understand when, for example—oh I don’t know—understanding clinical trial results, perhaps; and I certainly haven’t got to grips with it all yet.

I should, but it’s lunchtime and I now fancy some bacon…

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Filed under Communication, Statistics.

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