Bad Pharma

It feels as if some people, perhaps, view research as a game, where the idea is to get away with as much as you can, rather than to conduct fair tests of the treatments we use.

eighteen of the twenty-nine industry-funded trials presented a conclusion in the abstract that misrepresented the main outcome measure. All of the nonindustry-funded studies were fine

the CCSG trial found that aspirin was effective at preventing stroke and death in men, but not in women;30 as a result, women were under-treated for a decade, until further trials and overviews showed a benefit.

The human brain is a fairly bad random-number generator, for example, and simple frauds have often been uncovered by forensic statisticians looking at last-digit frequency: if you’re pencilling numbers into a column at random, you might have a slight unconscious preference for the number seven. To avoid this you might use a random-number generator, but here you would run into the odd problem of telltale uniformity in your randomness.

It’s also fair to say that sciences like medicine or psychology lend themselves to fabrication, because so many factors can vary between studies, meaning that picture-perfect replication is rare, and as a result nobody will be very suspicious if your results conflict with someone else’s. In an area of science where the results of experiments are more straightforwardly ‘yes/no’, failed replication would expose a fraudster much more quickly.

These spontaneous reports are then categorised by hand, and collated into what is effectively a giant spreadsheet, with one row for every drug on the market, and one column for every imaginable type of side effect. Then you look at how often each type of side effect is reported for each drug, and try to decide whether the figure is higher than you’d expect to see simply from chance. (If you’re statistically minded, the names of the tools used, such as ‘proportional reporting ratios’ and ‘Bayesian confidence propagation neural networks’, will give you a clue as to how this is done. If you’re not statistically minded, then you’re not missing out; at least, no more here than elsewhere in your life.)

Putting this in context: your drug might make one in every 5,000 people literally explode – their head blows off, their intestines fly out – through some idiosyncratic mechanism that nobody could have foreseen. But at the point when the drug is approved, after only 1,000 people have taken it, it’s very likely that you’ll never have witnessed one of these spectacular and unfortunate deaths. After 50,000 people have taken your drug, though, out there in the real world, you’d expect to have seen about ten people explode overall (since, on average, it makes one in every 5,000 people explode).

in 2008, shortly after being elected President, Barack Obama demonstrated to many academics and doctors that he had a clear understanding of the deep problems in health care, by committing to spend $1 billion on head-to-head trials of commonly used treatments, in order to find out which is best. In return he was derided by right-wing critics as ‘anti-industry’

we have no way of knowing what amazing new drugs might have been created if we incentivised companies by insisting that they demonstrate superiority

‘expanded access programme’. This is common when patients have shown no response to any other medication, and are regarded as too unfit for clinical trials (although I would argue that trials should ideally include everyone eligible for treatment, since we only do them to try to answer the question of whether a drug works in real-world patients)