Bad Pharma: How Drug Companies Mislead Doctors and Harm Patients by Ben Goldacre Read Free Book Online Page A

failed in other conditions, but that have theoretical potential for the orphan disease. If the data from earlier work on these drugs in other diseases is missing, then the job of researching them for the orphan disease is both harder and more dangerous: perhaps they have already been shown to have benefits or effects that would help accelerate research; perhaps they have already been shown to be actively harmful when used on other diseases, and there are important safety signals that would help protect future research participants from harm. Nobody can tell you.
    Finally, and perhaps most shamefully, when we allow unflattering data to go unpublished, we betray the patients who participated in these studies: the people who have given their bodies, and sometimes their lives, in the implicit belief that they are doing something to create new knowledge, that will benefit others in the same position as them in the future. In fact, their belief is not implicit: often it’s exactly what we tell them, as researchers, and it is a lie, because the data might be withheld, and we know it.
    So whose fault is this?
    Why do negative trials disappear?
    In a moment we will see more clear cases of drug companies withholding data – in stories where we can identify individuals – sometimes with the assistance of regulators. When we get to these, I hope your rage might swell. But first, it’s worth taking a moment to recognise that publication bias occurs outside commercial drug development, and in completely unrelated fields of academia, where people are motivated only by reputation, and their own personal interests.
    In many respects, after all, publication bias is a very human process. If you’ve done a study and it didn’t have an exciting, positive result, then you might wrongly conclude that your experiment isn’t very interesting to other researchers. There’s also the issue of incentives: academics are often measured, rather unhelpfully, by crude metrics like the numbers of citations for their papers, and the number of ‘high-impact’ studies they get into glamorous well-read journals. If negative findings are harder to publish in bigger journals, and less likely to be cited by other academics, then the incentives to work at disseminating them are lower. With a positive finding, meanwhile, you get a sense of discovering something new. Everyone around you is excited, because your results are exceptional.
    One clear illustration of this problem came in 2010. A mainstream American psychology researcher called Daryl Bem published a competent academic paper, in a well-respected journal, showing evidence of precognition, the ability to see into the future. * These studies were well-designed, and the findings were statistically significant, but many people weren’t very convinced, for the same reasons you aren’t: if humans really could see into the future, we’d probably know about it already; and extraordinary claims require extraordinary evidence, rather than one-off findings.
    But in fact the study has been replicated, though Bem’s positive results have not been. At least two groups of academics have rerun several of Bem’s experiments, using the exact same methods, and both found no evidence of precognition. One group submitted their negative results to the Journal of Personality and Social Psychology – the very same journal that published Bem’s paper in 2010 – and that journal rejected their paper out of hand. The editor even came right out and said it: we never publish studies that replicate other work.
    Here we see the same problem as in medicine: positive findings are more likely to be published than negative ones. Every now and then, a freak positive result is published showing, for example, that people can see into the future. Who knows how many psychologists have tried, over the years, to find evidence of psychic powers, running elaborate, time-consuming experiments, on dozens of subjects – maybe hundreds –