I’ve finished Bad Pharma: How Drug Companies Mislead Doctors and Harm Patients
,a well-researched effort presented in overheated language by Ben Goldacre. With all of the trillions of dollars spent on drug development and drugs themselves, have you ever wondered why people don’t seem to feel better than they did back in the 1970s? There have been so many new painkillers, for example, but none seem to work much better than aspirin, a remedy known to Hippocrates (Wikipedia).
Here’s the main thesis of the book:
Drugs are tested by the people who manufacture them, in poorly designed trials, on hopelessly small numbers of weird, unrepresentative patients, and analysed using techniques which are flawed by design, in such a way that they exaggerate the benefits of treatments. Unsurprisingly, these trials tend to produce results that favour the manufacturer. When trials throw up results that companies don’t like, they are perfectly entitled to hide them from doctors and patients, so we only ever see a distorted picture of any drug’s true effects. Regulators see most of the trial data, but only from early on in a drug’s life, and even then they don’t give this data to doctors or patients, or even to other parts of government. This distorted evidence is then communicated and applied in a distorted fashion. In their forty years of practice after leaving medical school, doctors hear about what works through ad hoc oral traditions, from sales reps, colleagues or journals. But those colleagues can be in the pay of drug companies – often undisclosed – and the journals are too. And so are the patient groups. And finally, academic papers, which everyone thinks of as objective, are often covertly planned and written by people who work directly for the companies, without disclosure. Sometimes whole academic journals are even owned outright by one drug company. Aside from all this, for several of the most important and enduring problems in medicine, we have no idea what the best treatment is, because it’s not in anyone’s financial interest to conduct any trials at all. These are ongoing problems, and although people have claimed to fix many of them, for the most part they have failed; so all these problems persist, but worse than ever, because now people can pretend that everything is fine after all.
We’re nearly 30 years into Prozac Nation. The pills are cheap and published research shows that they work well. Is everyone cheerful?
In 2008 a group of researchers decided to check for publication of every trial that had ever been reported to the US Food and Drug Administration for all the antidepressants that came onto the market between 1987 and 2004. The researchers found seventy-four studies in total, representing 12,500 patients’ worth of data. Thirty-eight of these trials had positive results, and found that the new drug worked; thirty-six were negative. The results were therefore an even split between success and failure for the drugs, in reality. Then the researchers set about looking for these trials in the published academic literature, the material available to doctors and patients. This provided a very different picture. Thirty-seven of the positive trials – all but one – were published in full, often with much fanfare. But the trials with negative results had a very different fate: only three were published. Twenty-two were simply lost to history, never appearing anywhere other than in those dusty, disorganised, thin FDA files.
How about the efforts at reform? Goldacre shows that they’ve failed on both sides of the Atlantic.
The 1997 FDA Modernization Act created clinicaltrials.gov, a register run by the US government National Institutes of Health. This legislation required that trials should be registered, but only if they related to an application to put a new drug on the market, and even then, only if it was for a serious or life-threatening disease. The register opened in 1998, and the website clinicaltrials.gov went online in 2000. The entry criteria were widened in 2004. But soon it all began to fall apart. … But the first problem for the US register, which could have been used universally, was that people simply chose not to use it. The regulations required only a very narrow range of trials to be posted, and nobody else was in a hurry to post their trials if they didn’t have to.
In 2007 the FDA Amendment Act was passed. This is much tighter: it requires registration of all trials of any drug or device, at any stage of development other than ‘first-in-man’ tests, if they have any site in the US, or involve any kind of application to bring a new drug onto the market. It also imposes a startling new requirement: all results of all trials must be posted to clinicaltrials.gov, in abbreviated summary tables, within one year of completion, for any trial on any marketed drug that completes after 2007. Once again, to great fanfare, everyone believed that the problem had been fixed. But it hasn’t been, for two very important reasons. First, unfortunately, despite the undoubted goodwill, requiring the publication of all trials starting from ‘now’ does absolutely nothing for medicine today. … But there is a second, more disturbing reason why these regulations should be taken with a pinch of salt: they have been widely ignored. A study published in January 2012 looked at the first slice of trials subject to mandatory reporting, and found that only one in five had met its obligation to post results.62 Perhaps this is not surprising: the fine for non-compliance is $10,000 a day, which sounds spectacular, until you realise that it’s only $3.5 million a year, which is chickenfeed for a drug bringing in $4 billion a year. And what’s more, no such fine has ever been levied, throughout the entire history of the legislation.
The search functions on the FDA website are essentially broken, while the content is haphazard and badly organised, with lots missing, and too little information to enable you to work out if a trial was prone to bias by design. Once again – partly, here, through casual thoughtlessness and incompetence – it is impossible to get access to the basic information that we need.
So: let’s say we want to find the results from all the trials the FDA has, on a drug called pregabalin, in which the drug is used to treat pain for diabetics whose nerves have been affected by their disease (a condition called ‘diabetic peripheral neuropathy’). You want the FDA review on this specific use, which is the PDF document containing all the trials in one big bundle. But if you search for ‘pregabalin review’, say, on the FDA website, you get over a hundred documents: none of them is clearly named, and not one of them is the FDA review document on pregabalin. If you type in the FDA application number – the unique identifier for the FDA document you’re looking for – the FDA website comes up with nothing at all. If you’re lucky, or wise, you’ll get dropped at the Drugs@FDA page: typing ‘pregabalin’ there brings up three ‘FDA applications’. Why three? Because there are three different documents, each on a different condition that pregabalin can be used to treat. The FDA site doesn’t tell you which condition each of these three documents is for, so you have to use trial and error to try to find out. That’s not as easy as it sounds. I have the correct document for pregabalin and diabetic peripheral neuropathy right here in front of me: it’s almost four hundred pages long, but it doesn’t tell you that it’s about diabetic peripheral neuropathy until you get to page 19. There’s no executive summary at the beginning – in fact, there’s no title page, no contents page, no hint of what the document is even about, and it skips randomly from one sub-document to another, all scanned and bundled up in the same gigantic file. … unlike almost any other serious government document in the world, the PDFs from the FDA are a series of photographs of pages of text, rather than the text itself. This means you cannot search for a phrase. Instead, you have to go through it, searching for that phrase, laboriously, by eye.
Clinical research trials is increasingly outsourced to private companies and increasingly done on patients outside the U.S. and EU. How much money is involved when a trial is done in the U.S.? And what’s the cost savings for going offshore?
In the US, meanwhile, the use of private community doctors to conduct trials has expanded enormously, with incentives approaching $1 million a year for the most enterprising medics.
As the former chief executive of GSK explained in a recent interview, running a trial in the US costs $30,000 per patient, while a CRO can do it in Romania for $3,000.
In the past, only 15 per cent of clinical trials were conducted outside the USA. Now it’s more than half. The average rate of growth in the number of trials in India is 20 per cent a year, in China 47 per cent, in Argentina 27 per cent, and so on, simply because they are better at attracting CRO business, at lower cost. At the same time, trials in the US are falling by 6 per cent a year (and in the UK by 10 per cent a year).
One problem with these trial is that they generally use patients who have only one condition and who may not be getting any treatment for it. Goldacre asks “Are those findings really transferable, and relevant, to American patients, on all their tablets?”
What does it take to get a drug approved by the FDA?
In general, however, a company would expect to have to provide two or three trials, with a thousand or more participants, showing that its drug works. This is where the smoke and mirrors begin. Although the notion of a simple randomised trial should be straightforward, in reality there are all kinds of distortions and perversions that can come into play, in the comparisons that are made, and the outcomes that are measured for success. For me, ‘What works?’ is the most basic practical question that every patient faces, and the answer isn’t complicated. Patients want to know: what’s the best treatment for my disease? The only way to answer this question when a new drug comes along is by comparing it against the best currently available treatment. But that is not what drug regulators require of a treatment for it to get onto the market. Often, even when there are effective treatments around already, regulators are happy for a company simply to show that its treatment is better than nothing – or rather, better than a dummy placebo pill with no medicine in it – and the industry is happy to clear that low bar.
A paper from 2011 looked at the evidence supporting every single one of the 197 new drugs approved by the FDA between 2000 and 2010, at the time they were approved.15 Only 70 per cent had data to show they were better than other treatments (and that’s after you ignore drugs for conditions for which there was no current treatment). A full third had no evidence comparing them with the best currently available treatment, even though that’s the only question that matters to patients.
This same perverse problem of inadequate comparators also exists in the EU.17 To get a licence to market your drug, the EMA does not require you to show that it is better than the best currently available treatment, even if that treatment is universally used: you simply have to show that it is better than nothing. A study from 2007 found that only half the drugs approved between 1999 and 2005 had been studied in comparison with other treatments at the time they were allowed onto the market (and, shamefully, only one third of those trials were published and
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by J.K. Rowling under the pen name of “Robert Galbraith” (I was not a fan of the Harry Potter books and thought that I should give the world’s most successful writer a second try). The plot concerns a private detective who takes a break from his usual work of helping women turn their marriages into cash by searching for a missing writer: “Strike had recently helped several wealthy young women rid themselves of City husbands who had become much less attractive to them since the financial crash. There was something appealing about restoring a husband to a wife, for a change.” The prose style can be peculiar: “And by the same power of will that in the army had enabled him to fall instantly asleep on bare concrete, on rocky ground, on lumpy camp beds that squeaked rusty complaints about his bulk whenever he moved, he slid smoothly into sleep like a warship sliding out on dark water.”
, i.e., that he calculates investment returns for the uber-rich by looking at different people who happened to make the Forbes list at different times. It turns out that 
(see my review of the book in these postings: