Bad Pharma: How Drug Companies Mislead Doctors and Harm Patients
By Ben Goldacre
4/5
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About this ebook
We like to imagine that medicine is based on evidence and the results of fair testing and clinical trials. In reality, those tests and trials are often profoundly flawed. We like to imagine that doctors who write prescriptions for everything from antidepressants to cancer drugs to heart medication are familiar with the research literature about a drug, when in reality much of the research is hidden from them by drug companies. We like to imagine that doctors are impartially educated, when in reality much of their education is funded by the pharmaceutical industry. We like to imagine that regulators have some code of ethics and let only effective drugs onto the market, when in reality they approve useless drugs, with data on side effects casually withheld from doctors and patients.
All these problems have been shielded from public scrutiny because they're too complex to capture in a sound bite. But Ben Goldacre shows that the true scale of this murderous disaster fully reveals itself only when the details are untangled. He believes we should all be able to understand precisely how data manipulation works and how research misconduct in the medical industry affects us on a global scale.
With Goldacre's characteristic flair and a forensic attention to detail, Bad Pharma reveals a shockingly broken system and calls for regulation. This is the pharmaceutical industry as it has never been seen before.
Ben Goldacre
Ben Goldacre is a doctor and science writer who wrote the 'Bad Science' column in the Guardian from 2003 to 2011. He has made a number of documentaries for BBC Radio 4, and his first book Bad Science reached Number One in the nonfiction charts, has sold over 500,000 copies. . His second bestselling book, Bad Pharma, was published in 2013.
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Reviews for Bad Pharma
167 ratings13 reviews
- Rating: 4 out of 5 stars4/5You will look at your pills in a different way
- Rating: 4 out of 5 stars4/5In Bad Science, Ben Goldacre presented many of the flaws with science literacy in the general public. He introduced the major concepts of medical and scientific information with enlightening real world examples (homeopathy used to treat HIV, the MMR scare, etc.) and a healthy dose of humor. It was a wonderful introduction to the field and I use that book as a text book for my introduction to health information class. I had high hopes for Bad Pharma. This book is far more of a jeremiad. I think every point he made needed to be made and I share his ire. But the style I enjoyed so much in his first book was completely absent in his second. I felt like I was being scolded instead of informed, which made this a much more arduous book to complete. I would still suggest this title to anyone who wants to be involved in public health or health policy.
- Rating: 4 out of 5 stars4/5A very thorough but depressing look at the state of modern medicine and the pharmaceutical industry. More technical than his previous book Bad Science, Ben Goldacre makes a difficult subject accessible to a general audience. Looking at issues from drug licensing, to research into existing treatments, to publication bias and drugs marketing. This truly is a global business and as such we get examples from around the world, focussing specifically on the UK and USA. There are suggestions for improvements and issues to campaign on in all areas. Looses one star for being a little bit repetitive.
- Rating: 5 out of 5 stars5/5Bad Pharma is actually a fairly scary book to pick up when you’ve just collected a prescription from the chemist but I’d heard a lot about Bad Science (which I’ve since read) and thought Bad Pharma would be incredibly interesting. I certainly wasn’t wrong.This is pretty much a damaging expose of the pharmaceutical industry’s involvement in modern medicine. Not necessarily their manufacture and distribution of tablets that do improve people’s lives every day but more the unnecessary peddling of drugs that either do very little or are no more effective than drugs already on the market. We’ve all seen the washing powder ads for something ‘new and improved’, only to find out two months later that it’s got one slight miniscule change. How ludicrous would it be if the drug companies did something similar and then got it under patent for 10 years so they could charge incredibly high prices for it? Well, they do.Delving into issues such as pricing, drug trials, suppression of research and trial reports, Goldacre uncovers how strong the hold over our medication is and calls for changes across the board, citing things that patients, doctors, governments, researchers and the drug companies can do.I’m sure Goldacre didn’t make any drug rep friends via this book – and I’m quite sure he doesn’t care. It’s refreshing to read something that is so focussed on what’s right, regardless of the waves it makes. That said, having now gone back and read Bad Science, it’s not really a surprise. This is an absolutely fascinating read for anyone who has had any involvement with our health system or ever taken any medication whatsoever. So, that’s pretty much everyone!
- Rating: 4 out of 5 stars4/5It is possible to be so cynical that nothing that Goldacre describes is in the least surprising, but at the same time to be interested in the mechanism.Goldacre is currently making the problems described in this book is life's work. The book is meant to persuade people: patients, doctors and workers in the pharmaceutical industry, to make changes for the better. He suggests actions that people in all these groups could take. Some suggestions seem hopelessly naive, but perhaps they are included as satire.Goldacre addresses the book to a lay audience unfamiliar with statistics, using well-chosen analogies to get his point across. He uses identical phrasing throughout the book, to remind those less familiar with statistics, what effect the behavior he is discussing has on the best available knowledge about a particular drug.On a personal note, a near relative of mine nearly died from a adverse reaction to a medication he had been prescribed for bursitis in his elbow. We do not know if previous adverse reactions had been covered up by the industry, or if his reaction made it into the medical literature.
- Rating: 4 out of 5 stars4/5As with Goldacre's previous book, Bad Science, Bad Pharma is a critical review, but now where he scrutinizes Big Pharma and other parts of the medical industrial complex. His exposé is perhaps not that original, but his overview is fine and his suggestions for improvements worth considering for policy makers and others in the medical industrial complex. A bought this book and then ran into Peter Gøtzsche's book "Deadly Medicines and Organised Crime" in its Danish incarnation, and must say I switched to Gøtzsche's book and completed that before continuing with Goldacre's. I found more bite in Gøtzsche's book (he compares the drug industry with the mafia!) and he has the advantage of doing original research in the field, while Goldacre's contribution to the medical literature has been more discussive, - as far as I can determine. But Gøtzsche's and Goldacre's books support each other well in addressing problems with the drug regulation: We are not dealing with a single author which sees problems. We may also take they differences in suggested solutions as a indication that there may be no one simple solution, e.g., should we let the state make clinical trials or would that make a considerable burden on taxpayers? It may relieve the pharmaceutical industry of expensive trials and let the society - perhaps - get more unbiased results.
- Rating: 4 out of 5 stars4/5Ben Goldacre is a very angry man, with good reason. In this book he lays out how the pharmaceutical industry has distorted drug research in pursuit of profit, sometimes intentionally, sometimes entirely without malice but with equally devastating effects for patient welfare. This matters because patients are prescribed less effective drugs, or drugs which are outright harmful, at huge financial expense to those paying for the drugs. This isn’t a conspiracy theory book; Goldacre is quite clear that many valuable drugs have come out of the industry, and that most of the people who work in it want to make better drugs. He sets out in detail how and why bias is introduced into both research and prescribing practices, putting it in layman’s terms but linking to the research papers and court documents that back up what he’s saying. He also addresses the failings of the current regulatory system, and proposes ways to improve things — pointing out that unless real controls with serious financial penalties are put in place, even those companies which genuinely want to reform will be under commercial pressure to continue with bad practice in a race to the bottom.It’s a dense and at times exhausting read. But Goldacre has done a decent job of making the issue accessible to a wide audience with a direct interest, from patients to practising doctors and academics. You can skim a lot of the book to get the general gist, or you can read it in details without following the links, or you can dig into research material he drew on and has laid out in meticulous footnotes and citations. He concludes the original edition with practical suggestions about what individual people can do to improve things, often simply by asking questions.I read the second edition, which has a “what happened next” chapter about the reaction to the first edition. As he had predicted, there was a backlash in an attempt to discredit him — but there was also a lot of covert feedback from industry personnel acknowledging the problems and considering how to improve things. While there’s always a “the lurkers support me in email” issue with uncredited sources, he does also offer some examples of companies which have publicly moved to improve transparency.Bad Pharma is an angry but rational examination of a real problem that affects millions of people, including almost anyone reading this review. It’s a worthwhile read, even if it makes for uncomfortable reading for patients, doctors and companies alike.
- Rating: 4 out of 5 stars4/5We don't regulate our drugs and the drug companies enough and insist on ensuring that data about the edges of results, I begin to wonder if the drug companies had previous seen the side-effects I suffered with a blood pressure medication and if I could have avoided hundreds of euro in specialist fees in discovering this MYSELF!Interesting look at how drug companies present their goods and how the love of money is indeed the root of many evils. How bias can creep in with doctors and cause them to favour one drug company over another and prescribe their drugs and how this can, often inadvertently, cause harm. There is also a touch of a discussion of overmedicalisation of normal, where drug companies are encouraging doctors to have people on medication, even if they don't really need it. It's a conversation we need to have. Though there also needs to be more testing on the filler in drugs, particularly on generics.
- Rating: 4 out of 5 stars4/5I already knew that the pharmaceutical system was greatly flawed, but Goldacre puts a useful focus to the issues. Enjoyed his Britishisms.
- Rating: 5 out of 5 stars5/5Everyone should read this book. Boldacre shows how trials for drugs and their perceived usefulness can be manipulated - unpublished data and outright data suppression, trials stopped early, trials extended, ghost written journal articles, etc. How doctors are influenced by the drug industry, beginning in medical school and continuing throughout their practice.
Goldacre is himself a practicing physician and this book stems in part from his outrage at having prescribed medications when he thought were safe and effective after reviewing the available published data, only to find that in some cases the drugs were not only ineffective, but worse that nothing. - Rating: 4 out of 5 stars4/5Not quite as much fun as "Bad Science" being very much more serious and more concerned to build an irrefutable case against the pharma industry and its corruption of medicine. Also while one can laugh at quacks and phoneys this is much closer to home. He argues that there is built in distortion in the way medicine is pushed through the system, evidence is subtly distorted, selective results are given wide publicity so that scientific evidence-based medicine is deeply compromised. So costs are greater than they need be, side effects are suffered which could be avoided, continuous improvement is blocked.
- Rating: 4 out of 5 stars4/5Ben has alot of good points and appears well researched. It seems a bit alarmist but probably appropriately so. It is an unfortunate state of affairs. Ben also provides suggestions on how to help fix the situation. I recommend the book.
- Rating: 4 out of 5 stars4/5Goldacre has a way of making complex science subjects accessible to the wider public. His first book, Bad Science, highlighted the way that the media dealt with reporting science, and in this book he concentrates his ire onto the $600 billion global pharmacy industry, now dominated by a handful of behemoths.
And what he reveals is frankly terrifying. He details the way that the industry hides a large majority of the trial data, the way that the legislation requiring data to be published is ignored by companies, and in the EU it is still secret in some cases. There is loads of detail on the way that the data is cherry picked to demonstrate that a particular drug is so much better than the competition. There is lots of detail on the appalling way that the industry is regulated, even though it is very heavily regulated, most of it is ineffective and not enforced, and where the regulation could be improved to help patients and save lives these are not enforced or are not enacted on after lobbying from the industry.
The biggest chapter though is on the marketing that these companies employ. Their budgets for marketing are normally twice the R&D budgets, which gives you some idea of where their priorities lie. He explains how they sponsor various ‘conferences’ and provided sweeteners to medical professionals at all levels, from lunches to flights to what most people would consider bribes. The nefarious dealings of the drugs rep are dealt with too, from the pressure that they put onto doctors to use their medicines and the way that they collect data directly from surgeries and pharmacies. A lot of academic papers are ghost written, and a leading figure puts their name to it, shocking really.
There is some details on NICE, but not a huge amount. He looks at the way that they select the drugs for use in treatment, noting that even they do not have access to all the trail data for each medicine that they consider.
He also writes about how a lot of the drug companies fund patient groups either overtly with cash donations or covertly by funding particular conferences and so on. They have been proven to use them to exert pressure on national agencies (FDA and NICE) to supply the latest drugs regardless of the cost; i.e. £50K spent with a group means that they get their £21k per patient drug treatment approved, even though the trial evidence is not there or is at best not proven to be any more effective than the current items on the market. A real scandal.
Throughout the book he does give suggestions on how the situation can be improved but he does realise that they is an endemic problem and powerful vested interests do hold sway. Even just enforcing the current rules would make a difference, but it seems unlikely at the moment.
The phrase for illegal drugs used to be: Just Say No. Perhaps it should apply to legal drugs too...
Book preview
Bad Pharma - Ben Goldacre
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To whom it may concern
CONTENTS
Title Page
Copyright Notice
Dedication
Introduction
1 Missing Data
2 Where Do New Drugs Come From?
3 Bad Regulators
4 Bad Trials
5 Bigger, Simpler Trials
6 Marketing
Conclusion: Better Data
Afterword: What Happened Next?
Glossary
Acknowledgements, Further Reading and a Note on Errors
Notes
Index
Also by Ben Goldacre
About the Author
Copyright
INTRODUCTION
Medicine is broken: the plane flies, but it crashes much more often than it needs to. And I genuinely believe that if patients and the public ever fully understand what has been done to them – what doctors, academics and regulators have permitted – they will be angry. On this, only you can judge.
We like to imagine that medicine is based on evidence and the results of fair tests. In reality, those tests are often profoundly flawed. We like to imagine that doctors are familiar with the research literature, when in reality much of it is hidden from them by drug companies. We like to imagine that doctors are well-educated, when in reality much of their education is funded by industry. We like to imagine that regulators let only effective drugs onto the market, when in reality they approve hopeless drugs, with data on side effects casually withheld from doctors and patients.
I’m going to tell you how medicine works, just over the page, in one paragraph that will seem so absurd, so ludicrously appalling, that when you read it, you’ll probably assume I’m exaggerating. We’re going to see that the whole edifice of medicine is broken, because the evidence we use to make decisions is hopelessly and systematically distorted; and this is no small thing. Because in medicine, doctors and patients use abstract data to make decisions in the very real world of flesh and blood. If those decisions are misguided, they can result in death, and suffering, and pain.
This isn’t a simple story of cartoonish evil, and there will be no conspiracy theories. Drug companies are not withholding the secret to curing cancer, nor are they killing us all with vaccines. Those kinds of stories have, at best, a poetic truth: we all know, intuitively, from the fragments we’ve picked up, that something is wrong in medicine. But most of us, doctors included, don’t know exactly what.
These problems have been protected from public scrutiny because they’re too complex to capture in a soundbite, or even 3,000 words. This is why they’ve gone unfixed by politicians, at least to some extent; but it’s also why you’re holding a book of over four hundred pages. The people you should have been able to trust to fix these problems have failed you, and because you have to understand a problem properly in order to fix it yourself, this book contains all that you need to know.
So, to be clear, this whole book is about meticulously defending every assertion in the paragraph that follows.
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.
That’s a lot to stand up, and the details are much more horrific than that paragraph makes it sound. There are some individual stories that will make you seriously question the integrity of the individuals involved; some that will make you angry; and some, I suspect, that might make you very sad. But I hope you will come to see that this is not just a book about bad people. In fact, it’s possible for good people, in perversely designed systems, to casually perpetrate acts of great harm on strangers, sometimes without ever realising it. The current regulations – for companies, doctors and researchers – create perverse incentives; and we’ll have better luck fixing those broken systems than we will ever have trying to rid the world of avarice.
Some people will say that this book is an attack on the pharmaceutical industry, and of course it is. But it’s not only that. First, as you will see, the problems are diffuse, and doctors, regulators, academic journals, pharmacists, patient groups, and many more all play their part. Second, it’s not unbounded. I suspect that most of the people who work in this industry are fundamentally good-hearted, and there is no medicine without medicines. Drug companies around the world have produced some of the most amazing innovations of the past fifty years, saving lives on an epic scale. But that does not allow them to hide data, mislead doctors and harm patients.
Today, when an academic or doctor tells you that they are working for the pharmaceutical industry, they often do so with a look of quiet embarrassment. I want to work towards a world where doctors and academics can feel actively optimistic about collaborating with industry, to make better treatments and better patients. This will require big changes, and some of them have been a very long time coming.
To that end, because the stories I am telling you are so worrying, I’ve tried to go beyond simply documenting the problems. Where there are obvious fixes, I’ve set out what they are. But I’ve also included, at the end of each chapter, some suggestions on what you can do to improve things. These are tailored to whoever you might be: a doctor, a patient, a politician, a researcher, a regulator or a drug company.
More than anything, though, I don’t want you to lose sight of one thing: this is a pop science book. The tricks and distortions documented in these pages are beautiful, and intricate, and fascinating in their details. The true scale of this murderous disaster only fully reveals itself when the details are untangled. Good science has been perverted on an industrial scale, but this has happened slowly, and evolved naturally, over time. This has all been perpetrated by ordinary people, but many of them may not even know what they’ve done.
I want you to find them, and tell them.
What’s coming
The book follows a simple trajectory.
We start by defending our central claim: industry-sponsored studies are more likely to produce results that flatter the sponsor’s drug, which has now been demonstrated, beyond any doubt, by current research. In this section we also encounter the idea of a ‘systematic review’ for the first time. A systematic review is an unbiased survey of all the evidence on a given question. It is the best-quality evidence that can be used, and where they exist, systematic reviews are used for evidence throughout this book, with individual studies described only to give you a flavour of how the research has been done, or how mischief has been made.
Then we look at how the pharmaceutical industry manages to create all these positive trials for its drugs. Our first stop is to review the evidence showing that unflattering trial data can simply be withheld from doctors and patients. Companies are perfectly entitled to conduct seven studies, but only publish the two positive ones, and this behaviour is commonplace. What’s more, it happens in every field of science and medicine: from basic laboratory research, where selective publication fills the literature with false positive findings, wasting everyone’s time; through early research trials, where evidence that drugs might be dangerous is hidden from view; and on to major trials used to inform everyday clinical practice. Because so much trial data is withheld from doctors and patients, we can have no clear idea of the true effects of the treatments that we use every day in medicine. The stories in this section go from antidepressants, through statins, cancer drugs, diet pills, and right up to Tamiflu. Governments around the world have spent billions of dollars to stockpile this flu drug, in fear of a pandemic, and yet the evidence on whether it reduces the rate of pneumonia and death is being withheld right now, to this day.
Next, we take a step back, to look at where drugs come from. We cover the drug development process, from the moment someone dreams up a new molecule, through tests in labs, on animals, the first tests in humans, and then the early trials necessary to show that a drug works on patients. Here you will find, I suspect, some surprises. Risky ‘first-in-man’ drug tests are conducted on homeless people; but more than that, full clinical trials are being globalised, a new development that has arisen very suddenly, in only the last couple of years. This raises serious ethical problems, because trial participants in developing countries are often unlikely to benefit from expensive new drugs; but it also raises interesting new problems for trusting the data.
Then we look at regulation, and the hoops you must go through to get a drug onto the market. We will see that the bar is very low: that drugs must only prove that they are better than nothing, even when there are highly effective treatments on the market already. This means that real patients are given dummy placebo pills for no good reason, but also that drugs appear on the market which are worse than the treatments we already have. We will see that companies break their promises over follow-up studies, and that regulators let them do this. We will also see how data on side effects and effectiveness can be withheld from regulators, and that regulators, in turn, are obsessively secretive, withholding the data they do have from doctors and patients. Last, we will see the harm done by this secrecy: ‘many eyes’ are often very powerful, to spot problems with medicines, and some of the most frightening harms have been missed by regulators, and only identified by academics who were forced to fight hard for access to data.
Then we take a tour through ‘bad trials’. It is tempting to believe that a simple clinical trial is always a fair test of a treatment: and if done properly, it is. But several tricks have been introduced, over the course of many years, which allow researchers to overstate and exaggerate the benefits of the treatments they are testing. When you get here, you might think that some of these are innocent mistakes; in all seriousness, while I doubt that, I’m more interested in how clever they are. More important, we will see how obvious these tricks are, and how people who should know better at every step of the chain, from ethics committees through to academic journals, have allowed companies and researchers to engage in these shameful outright distortions.
After a brief detour to discuss how some of the problems around bad evidence, and missing evidence, could be addressed, we move on to marketing, which is where most previous books on drug companies have focused their attention.
Here we will see that pharmaceutical companies spend tens of billions of pounds every year trying to change the treatment decisions of doctors: in fact, they spend twice as much on marketing and advertising as they do on the research and development of new drugs. Since we all want doctors to prescribe medicine based on evidence, and evidence is universal, there is only one possible reason for such huge spends: to distort evidence-based practice. All of this money comes directly from patients and governments, so we ourselves are paying for this privilege. Doctors spend forty years practising medicine, with very little formal education after their initial training. Medicine changes completely in four decades, and as they try to keep up, doctors are bombarded with information: from ads that misrepresent the benefits and risks of new medicines; from sales reps who spy on patients’ confidential prescribing records; from colleagues who are quietly paid by drug companies; from ‘teaching’ that is sponsored by industry; from independent ‘academic’ journal articles that are quietly written by drug company employees; and worse.
Finally, we will see what can be done. While the deceit of a marketing drive can be ignored by an ethical doctor, the problems caused by distorted evidence affect everybody, without exception. The most expensive doctors in the world can only make decisions about your care on the basis of the evidence publicly available to them, and nobody has a special inside track. If this evidence is distorted, then we are all exposed to avoidable suffering, pain and death. The whole system needs to be fixed, and until it is, we are all, very truly, in this together.
How to read this book
I have set out to explain the flaws in our system for assessing the benefits of treatments, and for disseminating the evidence we collect. Often, one specific drug is used as an example to explain a wider systemic flaw, but this is not an almanac of good and bad drugs, and you certainly shouldn’t change your medication on the basis of what you read here. If you are concerned by what you read, then there is advice on what you can do to improve things for yourself, and for others, at the end of the book. Most of the harms discussed arise from our failure to do the best we can, not from handing out treatments that are worse than nothing. If that disappoints you, if you want more melodrama, then I suggest you go and read a book by a quack.
I deliberately haven’t gone overboard to explain every medical term, to save space and avoid distractions: this doesn’t mean that you miss out. If a symptom, for example, isn’t explained or defined, that means you genuinely don’t need this detail to understand the story; but I’ve left the long word in to help medics or academics find their feet, and to anchor the general principle in a specific corner of medicine for them. Acronyms and abbreviations are defined as we go, and used in a haphazard way after that, because this is how people talk in the real world. There’s a glossary at the back for some common ideas, really just in case you read sections out of order, but there’s nothing in there that doesn’t come up in the main text.
Similarly, I haven’t given the full names of most clinical trials, because they are conventionally known by their acronyms, and most medical textbooks wouldn’t bother either: the ‘ISIS trial’, the ‘CAST trial’, in the minds of most doctors and academics, are the real names. If you’re very interested, you can search for them online or in the endnotes, but they’re not relevant to your enjoyment or understanding of the arguments in this book. Drugs present a different problem, because they have two names: the generic name, which is the correct scientific name for the molecule; and then the brand name used by the company manufacturing it in their packaging and advertising, which is usually a bit catchier. In general, doctors and academics think you should always use the scientific name, because it tells you a little about the class of the molecule, and is less ambiguous; while journalists and patients will more often use brand names. But everybody is inconsistent about which name they use, and in this book, so am I. Again, this simply reflects how people talk about medicines in the real world.
All the specific studies discussed are referenced at the back of the book. Where there was a choice, I’ve tried to select papers in open-access journals, so that they can be read for free by all. I’ve also tried to reference papers that give a good overview of a field, or good books on a subject, so that you can read more on whole areas if you want to.
Last: to an extent, this is a field where you need to know everything, to understand how it impacts on everything else. I’ve bent over backwards to introduce the ideas in the best order, but if all this material is completely new to you, then yo u might spot some extra connections – or feel greater outrage in your belly – reading it a second time. I have not assumed any prior knowledge. I have, however, assumed that you might be willing to deploy a little intellectual horsepower here and there. Some of this stuff is hard. That’s precisely why these problems have been ignored, and that’s why I’ve had to explain it to you here, in this book. If you want to catch people with their trousers down, you have to go into their home.
Enjoy.
Ben Goldacre
August 2012
For the paperback edition of the book, I’ve made occasional small changes to the text, many of them in light of helpful comments from readers: this was to disambiguate, improve, toughen and occasionally correct small errors (such as n/3 instead of 3/n here, which broke my heart). Over the past year, even more evidence has been published about the ongoing problems described in the book. I’ve resisted the urge to expand every section, but some of this new evidence is covered in the new Afterword, ‘What Happened Next’. For the key problem of withheld trial data, there has been an international campaign over the course of 2013, with some small forward movement; this is also described at the end, and I hope it will rouse you to action.
Ben Goldacre
August 2013
1
Missing Data
Sponsors get the answer they want
Before we get going, we need to establish one thing beyond any doubt: industry-funded trials are more likely to produce a positive, flattering result than independently funded trials. This is our core premise, and you’re about to read a very short chapter, because this is one of the most well-documented phenomena in the growing field of ‘research about research’. It has also become much easier to study in recent years, because the rules on declaring industry funding have become a little clearer.
We can begin with some recent work: in 2010, three researchers from Harvard and Toronto found all the trials looking at five major classes of drug – antidepressants, ulcer drugs and so on – then measured two key features: were they positive, and were they funded by industry?¹ They found over five hundred trials in total: 85 per cent of the industry-funded studies were positive, but only 50 per cent of the government-funded trials were. That’s a very significant difference.
In 2007, researchers looked at every published trial that set out to explore the benefit of a statin.² These are cholesterol-lowering drugs which reduce your risk of having a heart attack, they are prescribed in very large quantities, and they will loom large in this book. This study found 192 trials in total, either comparing one statin against another, or comparing a statin against a different kind of treatment. Once the researchers controlled for other factors (we’ll delve into what this means later), they found that industry-funded trials were twenty times more likely to give results favouring the test drug. Again, that’s a very big difference.
We’ll do one more. In 2006, researchers looked into every trial of psychiatric drugs in four academic journals over a ten-year period, finding 542 trial outcomes in total. Industry sponsors got favourable outcomes for their own drug 78 per cent of the time, while independently funded trials only gave a positive result in 48 per cent of cases. If you were a competing drug put up against the sponsor’s drug in a trial, you were in for a pretty rough ride: you would only win a measly 28 per cent of the time.³
These are dismal, frightening results, but they come from individual studies. When there has been lots of research in a field, it’s always possible that someone – like me, for example – could cherry-pick the results, and give a partial view. I could, in essence, be doing exactly what I accuse the pharmaceutical industry of doing, and only telling you about the studies that support my case, while hiding the reassuring ones from you.
To guard against this risk, researchers invented the systematic review. We’ll explore this in more detail soon (here), since it’s at the core of modern medicine, but in essence a systematic review is simple: instead of just mooching through the research literature, consciously or unconsciously picking out papers here and there that support your pre-existing beliefs, you take a scientific, systematic approach to the very process of looking for scientific evidence, ensuring that your evidence is as complete and representative as possible of all the research that has ever been done.
Systematic reviews are very, very onerous. In 2003, by coincidence, two were published, both looking specifically at the question we’re interested in. They took all the studies ever published that looked at whether industry funding is associated with pro-industry results. Each took a slightly different approach to finding research papers, and both found that industry-funded trials were, overall, about four times more likely to report positive results.⁴ A further review in 2007 looked at the new studies that had been published in the four years after these two earlier reviews: it found twenty more pieces of work, and all but two showed that industry-sponsored trials were more likely to report flattering results.⁵
I am setting out this evidence at length because I want to be absolutely clear that there is no doubt on the issue. Industry-sponsored trials give favourable results, and that is not my opinion, or a hunch from the occasional passing study. This is a very well-documented problem, and it has been researched extensively, without anybody stepping out to take effective action, as we shall see.
There is one last study I’d like to tell you about. It turns out that this pattern of industry-funded trials being vastly more likely to give positive results persists even when you move away from published academic papers, and look instead at trial reports from academic conferences, where data often appears for the first time (in fact, as we shall see, sometimes trial results only appear at an academic conference, with very little information on how the study was conducted).
Fries and Krishnan studied all the research abstracts presented at the 2001 American College of Rheumatology meetings which reported any kind of trial, and acknowledged industry sponsorship, in order to find out what proportion had results that favoured the sponsor’s drug. There is a small punchline coming, and to understand it we need to cover a little of what an academic paper looks like. In general, the results section is extensive: the raw numbers are given for each outcome, and for each possible causal factor, but not just as raw figures. The ‘ranges’ are given, subgroups are perhaps explored, statistical tests are conducted, and each detail of the result is described in table form, and in shorter narrative form in the text, explaining the most important results. This lengthy process is usually spread over several pages.
In Fries and Krishnan [2004] this level of detail was unnecessary. The results section is a single, simple, and – I like to imagine – fairly passive-aggressive sentence:
The results from every RCT (45 out of 45) favored the drug of the sponsor.
This extreme finding has a very interesting side effect, for those interested in time-saving shortcuts. Since every industry-sponsored trial had a positive result, that’s all you’d need to know about a piece of work to predict its outcome: if it was funded by industry, you could know with absolute certainty that the trial found the drug was great.
How does this happen? How do industry-sponsored trials almost always manage to get a positive result? It is, as far as anyone can be certain, a combination of factors. It may be that companies are more likely to run trials when they’re most confident their treatment is going to ‘win’: this sounds reasonable, although even it conflicts with the ethical principle that you should only do a trial when there’s genuine uncertainty about which treatment is best (otherwise you’re exposing half of your participants to a treatment you already know to be inferior). Sometimes the chances of one treatment winning can be increased by outright design flaws. You can compare your new drug with something you know to be rubbish – an existing drug at an inadequate dose, perhaps, or a placebo sugar pill that does almost nothing. You can choose your patients very carefully, so they are more likely to get better on your treatment. You can peek at the results halfway through, and stop your trial early if they look good (which is – for interesting reasons we shall discuss – statistical poison). And so on.
But before we get to these fascinating methodological twists and quirks, these nudges and bumps that stop a trial from being a fair test of whether a treatment works or not, there is something very much simpler at hand.
Sometimes drug companies conduct lots of trials, and when they see that the results are unflattering, they simply fail to publish them. This is not a new problem, and it’s not limited to medicine. In fact, this issue of negative results that go missing in action cuts into almost every corner of science. It distorts findings in fields as diverse as brain imaging and economics, it makes a mockery of all our efforts to exclude bias from our studies, and despite everything that regulators, drug companies and even some academics will tell you, it is a problem that has been left unfixed for decades.
In fact, it is so deep-rooted that even if we fixed it today – right now, for good, forever, without any flaws or loopholes in our legislation – that still wouldn’t help, because we would still be practising medicine, cheerfully making decisions about which treatment is best, on the basis of decades of medical evidence which is – as you’ve now seen – fundamentally distorted.
But there is a way ahead.
Why missing data matters
Reboxetine is a drug I myself have prescribed. Other drugs had done nothing for this particular patient, so we wanted to try something new. I’d read the trial data before I wrote the prescription, and found only well-designed, fair tests, with overwhelmingly positive results. Reboxetine was better than placebo, and as good as any other antidepressant in head-to-head comparisons. It’s approved for use by the Medicines and Healthcare products Regulatory Agency (the MHRA) in the UK, but wisely, the US FDA chose not to approve it. (This is no proof of the FDA being any smarter; there are plenty of drugs available in the US that the UK never approved.) Reboxetine was clearly a safe and and effective treatment. The patient and I discussed the evidence briefly, and agreed it was the right treatment to try next. I signed a prescription saying I wanted my patient to have this drug.
But we had both been misled. In October 2010 a group of researchers were finally able to bring together all the trials that had ever been conducted on reboxetine.⁶ Through a long process of investigation – searching in academic journals, but also arduously requesting data from the manufacturers and gathering documents from regulators – they were able to assemble all the data, both from trials that were published, and from those that had never appeared in academic papers.
When all this trial data was put together it produced a shocking picture. Seven trials had been conducted comparing reboxetine against placebo. Only one, conducted in 254 patients, had a neat, positive result, and that one was published in an academic journal, for doctors and researchers to read. But six more trials were conducted, in almost ten times as many patients. All of them showed that reboxetine was no better than a dummy sugar pill. None of these trials was published. I had no idea they existed.
It got worse. The trials comparing reboxetine against other drugs showed exactly the same picture: three small studies, 507 patients in total, showed that reboxetine was just as good as any other drug. They were all published. But 1,657 patients’ worth of data was left unpublished, and this unpublished data showed that patients on reboxetine did worse than those on other drugs. If all this wasn’t bad enough, there was also the side-effects data. The drug looked fine in the trials which appeared in the academic literature: but when we saw the unpublished studies, it turned out that patients were more likely to have side effects, more likely to drop out of taking the drug, and more likely to withdraw from the trial because of side effects, if they were taking reboxetine rather than one of its competitors.
If you’re ever in any doubt about whether the stories in this book make me angry – and I promise you, whatever happens, I will keep to the data, and strive to give a fair picture of everything we know – you need only look at this story. I did everything a doctor is supposed to do. I read all the papers, I critically appraised them, I understood them, I discussed them with the patient, and we made a decision together, based on the evidence. In the published data, reboxetine was a safe and effective drug. In reality, it was no better than a sugar pill, and worse, it does more harm than good. As a doctor I did something which, on the balance of all the evidence, harmed my patient, simply because unflattering data was left unpublished.
If you find that amazing, or outrageous, your journey is just beginning. Because nobody broke any law in that situation, reboxetine is still on the market, and the system that allowed all this to happen is still in play, for all drugs, in all countries in the world. Negative data goes missing, for all treatments, in all areas of science. The regulators and professional bodies we would reasonably expect to stamp out such practices have failed us.
In a few pages, we will walk through the literature that demonstrates all of this beyond any doubt, showing that ‘publication bias’ – the process whereby negative results go unpublished – is endemic throughout the whole of medicine and academia; and that regulators have failed to do anything about it, despite decades of data showing the size of the problem. But before we get to that research, I need you to feel its implications, so we need to think about why missing data matters.
Evidence is the only way we can possibly know if something works – or doesn’t work – in medicine. We proceed by testing things, as cautiously as we can, in head-to-head trials, and gathering together all of the evidence. This last step is crucial: if I withhold half the data from you, it’s very easy for me to convince you of something that isn’t true. If I toss a coin a hundred times, for example, but only tell you about the results when it lands heads-up, I can convince you that this is a two-headed coin. But that doesn’t mean I really do have a two-headed coin: it means I’m misleading you, and you’re a fool for letting me get away with it. This is exactly the situation we tolerate in medicine, and always have. Researchers are free to do as many trials as they wish, and then choose which ones to publish.
The repercussions of this go way beyond simply misleading doctors about the benefits and harms of interventions for patients, and way beyond trials. Medical research isn’t an abstract academic pursuit: it’s about people, so every time we fail to publish a piece of research we expose real, living people to unnecessary, avoidable suffering.
TGN1412
In March 2006, six volunteers arrived at a London hospital to take part in a trial. It was the first time a new drug called TGN1412 had ever been given to humans, and they were paid £2,000 each.⁷ Within an hour these six men developed headaches, muscle aches, and a feeling of unease. Then things got worse: high temperatures, restlessness, periods of forgetting who and where they were. Soon they were shivering, flushed, their pulses racing, their blood pressure falling. Then, a cliff: one went into respiratory failure, the oxygen levels in his blood falling rapidly as his lungs filled with fluid. Nobody knew why. Another dropped his blood pressure to just 65/40, stopped breathing properly, and was rushed to an intensive care unit, knocked out, intubated, mechanically ventilated. Within a day all six were disastrously unwell: fluid on their lungs, struggling to breathe, their kidneys failing, their blood clotting uncontrollably throughout their bodies, and their white blood cells disappearing. Doctors threw everything they could at them: steroids, antihistamines, immune-system receptor blockers. All six were ventilated on intensive care. They stopped producing urine; they were all put on dialysis; their blood was replaced, first slowly, then rapidly; they needed plasma, red cells, platelets. The fevers continued. One developed pneumonia. And then the blood stopped getting to their peripheries. Their fingers and toes went flushed, then brown, then black, and then began to rot and die. With heroic effort, all escaped, at least, with their lives.
The Department of Health convened an Expert Scientific Group to try to understand what had happened, and from this two concerns were raised.⁸ First: can we stop things like this from happening again? It’s plainly foolish, for example, to give a new experimental treatment to all six participants in a ‘first-in-man’ trial at the same time, if that treatment is a completely unknown quantity. New drugs should be given to participants in a staggered process, slowly, over a day. This idea received considerable attention from regulators and the media.
Less noted was a second concern: could we have foreseen this disaster? TGN1412 is a molecule that attaches to a receptor called CD28 on the white blood cells of the immune system. It was a new and experimental treatment, and it interfered with the immune system in ways that are poorly understood, and hard to model in animals (unlike, say, blood pressure, because immune systems are very variable between different species). But as the final report found, there was experience with a similar intervention: it had simply not been published. One researcher presented the inquiry with unpublished data on a study he had conducted in a single human subject a full ten years earlier, using an antibody that attached to the CD3, CD2 and CD28 receptors. The effects of this antibody had parallels with those of TGN1412, and the subject on whom it was tested had become unwell. But nobody could possibly have known that, because these results were never shared with the scientific community. They sat unpublished, unknown, when they could have helped save six men from a terrifying, destructive, avoidable ordeal.
That original researcher could not foresee the specific harm he contributed to, and it’s hard to blame him as an individual, because he operated in an academic culture where leaving data unpublished was regarded as completely normal. The same culture exists today. The final report on TGN1412 concluded that sharing the results of all first-in-man studies was essential: they should be published, every last one, as a matter of routine. But phase 1 trial results weren’t published then, and they’re still not published now. In 2009, for the first time, a study was published looking specifically at how many of these first-in-man trials get published, and how many remain hidden.⁹ They took all such trials approved by one ethics committee over a year. After four years, nine out of ten remained unpublished; after eight years, four out of five were still unpublished.
In medicine, as we shall see time and again, research is not abstract: it relates directly to life, death, suffering and pain. With every one of these unpublished studies we are potentially exposed, quite unnecessarily, to another TGN1412. Even a huge international news story, with horrific images of young men brandishing blackened feet and hands from hospital beds, wasn’t enough to get movement, because the issue of missing data is too complicated to fit in one sentence.
When we don’t share the results of basic research, such as a small first-in-man study, we expose people to unnecessary risks in the future. Was this an extreme case? Is the problem limited to early, experimental, new drugs, in small groups of trial participants? No.
In the 1980s, US doctors began giving anti-arrhythmic drugs to all patients who’d had a heart attack. This practice made perfect sense on paper: we knew that anti-arrhythmic drugs helped prevent abnormal heart rhythms; we also knew that people who’ve had a heart attack are quite likely to have abnormal heart rhythms; we also knew that often these went unnoticed, undiagnosed and untreated. Giving anti-arrhythmic drugs to everyone who’d had a heart attack was a simple, sensible preventive measure.
Unfortunately, it turned out that we were wrong. This prescribing practice, with the best of intentions, on the best of principles, actually killed people. And because heart attacks are very common, it killed them in very large numbers: well over 100,000 people died unnecessarily before it was realised that the fine balance between benefit and risk was completely different for patients without a proven abnormal heart rhythm.
Could anyone have predicted this? Sadly, yes, they could have. A trial in 1980 tested a new anti-arrhythmic drug, lorcainide, in a small number of men who’d had a heart attack – less than a hundred – to see if it was any use. Nine out of forty-eight men on lorcainide died, compared with one out of forty-seven on placebo. The drug was early in its development cycle, and not long after this study it was dropped for commercial reasons. Because it wasn’t on the market, nobody even thought to publish the trial. The researchers assumed it was an idiosyncrasy of their molecule, and gave it no further thought. If they had published, we would have been much more cautious about trying other anti-arrhythmic drugs on people with heart attacks, and the phenomenal death toll – over 100,000 people in their graves prematurely – might have been stopped sooner. More than a decade later, the researchers finally did publish their results, with a mea culpa, recognising the harm they had done by not sharing them earlier:
When we carried out our study in 1980, we thought that the increased death rate that occurred in the lorcainide group was an effect of chance. The development of lorcainide was abandoned for commercial reasons, and this study was therefore never published; it is now a good example of ‘publication bias’. The results described here might have provided an early warning of trouble ahead.¹⁰
As we shall shortly see, this problem of unpublished data is widespread throughout medicine, and indeed the whole of academia, even though the scale of the problem, and the harm it causes, have been documented beyond any doubt. We will see stories on basic cancer research, Tamiflu, cholesterol blockbusters, obesity drugs, antidepressants and more, with evidence that goes from the dawn of medicine to the present day, and data that is still being withheld, right now, as I write, on widely used drugs which many of you reading this book will have taken this morning. We will also see how regulators and academic bodies have repeatedly failed to address the problem.
Because researchers are free to bury any result they please, patients are exposed to harm on a staggering scale throughout the whole of medicine, from research to practice. Doctors can have no idea about the true effects of the treatments they give. Does this drug really work best, or have I simply been deprived of half the data? Nobody can tell. Is this expensive drug worth the money, or have the data simply been massaged? No one can tell. Will this drug kill patients? Is there any evidence that it’s dangerous? No one can tell.
This is a bizarre situation to arise in medicine, a discipline where everything is supposed to be based on evidence, and where everyday practice is bound up in medico-legal anxiety. In one of the most regulated corners of human conduct we’ve taken our eyes off the ball, and allowed the evidence driving practice to be polluted and distorted. It seems unimaginable. We will now see how deep this problem goes.
Why we summarise data
Missing data has been studied extensively in medicine. But before I lay out that evidence, we need to understand exactly why it matters, from a scientific perspective.