Bad Pharma: How Drug Companies Mislead Doctors and Harm Patients (19 page)

There are other quirks that lead regulators to feel – perhaps – disoriented as to where their allegiances lie. Up until 2010, for example, the EMA sat in the European Commission’s Enterprise and Industry Directorate, rather than under health, which might make you worry that political oversight was more focused on the economic benefits of a friendly relationship with the $600 billion pharmaceutical industry than on the interests of patients.
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In both the United States and the European Union, regulators are paid for almost entirely by drug companies, through the fees that are paid to pass regulatory hurdles. Until a few years ago, when approval was centralised to the EMA, this was a particular source of concern in Europe, because drug companies could choose which country they would seek approval in, and this created something of a competition. Overall this payment model has created an impression that the companies are the customer, but this is not simply because they write the cheques: this change in funding was brought in specifically to improve approval times for industry.

Approving a drug

So what do regulators mean by ‘effective’ when they measure the benefits of a new drug? The specific details for each drug are often a matter of ad hoc negotiation, and in the dark arts of getting a drug approved, inside knowledge and oral tradition are often as valuable as knowing the rules: for example, research has shown that applications from large companies, which have greater experience of the regulatory process, pass through to approval faster than those from smaller companies. 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.

‘Better than nothing’

This raises several serious problems, the first of which is ethical. It’s obviously wrong to put patients in a trial where half of them will be given a placebo, if there is a currently available option which is known to be effective, because you are actively depriving half of your patients of treatment for their disease. Remember, these are not healthy volunteers, giving their bodies over for financial reward: these are real patients, often with serious medical problems, hoping for treatment and exposing themselves to some inconvenience (but hopefully no more than that) in order to advance the state of medical knowledge for other sufferers in the future.

What’s more, if patients participate in a trial that uses a placebo instead of a currently available effective treatment, they are suffering a double sting. In all likelihood, the trial they’re taking part in is not attempting to answer a clinically meaningful question, relevant to medical practice. Because doctors and patients aren’t interested in whether a new drug is better than nothing, except as a matter of the most abstract and irrelevant science. We’re interested in the practical question of whether it’s better than the best currently available option, and when a drug is approved, at the very least we’d expect to see trials which answer this question.

That is not what we get. 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.
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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.

As we have seen, the Declaration of Helsinki is pretty hot on patients not being exposed to unnecessary harm in trials. It started to get hot on the misuse of placebos in a 2000 amendment which says that the use of dummy pills is only acceptable when

    for compelling and scientifically sound methodological reasons [placebo] is necessary to determine the efficacy or safety of an intervention and the patients who receive placebo…will not be subject to any risk of serious or irreversible harm. Extreme care must be taken to avoid abuse of this option.

You will be interested to note that this amendment marked the beginning of the process by which the FDA distanced itself from Helsinki as its main source of regulatory guidance, especially for trials conducted outside the USA (as we discussed earlier, in the section on CROs).
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This same perverse problem of inadequate comparators also exists in the EU.
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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 publicly accessible to doctors and patients).
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Many researchers have argued for this problem of ‘Better than what?’ to be flagged up as prominently as possible, ideally on the leaflet that patients receive in the packet, since this is the only part of the marketing and communications process on which the regulators can exert clear, unambiguous control. One recent paper suggested some plain, simple wording: ‘Although this drug has been shown to lower blood pressure more effectively than placebo, it has not been shown to be more effective than other members of the same drug class.’
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It has been ignored.

Surrogate outcomes

Placebo controls are not the only problem with the trials that are used to obtain marketing approval. Often, drugs are approved despite showing no benefit at all on real-world outcomes, such as heart attacks or death: instead, they are approved for showing a benefit on ‘surrogate outcomes’, such as a blood test, that is only weakly or theoretically associated with the real suffering and death that we are trying to avoid.

This is best understood with an example. Statins are drugs that lower cholesterol, but you don’t take them because you want to change your cholesterol figures on a blood test printout: you take them because you want to lower your risk of having a heart attack, or dying. Heart attack and death are the real outcomes of interest here, and cholesterol is just a surrogate for those, a process outcome, something that we hope is associated with the real outcome, but it might not be, either not at all, or perhaps not very well.

Often there is a fair reason for using a surrogate outcome, not as your only indicator, but at least for some of the data. People take a long time to die (it’s one of the great problems of research, if you can forgive the thought), so if you want an answer quickly, you can’t wait around for them to have a heart attack and die. In these circumstances, a surrogate outcome like a blood test is a reasonable thing to measure, as an interim arrangement. But you still have to do long-term follow-up studies at some stage, to find out if your hunch about the surrogate outcome was right after all. Unfortunately, the incentives for companies – which are by far the largest funders of trials – are all focused on short-term gains, either to get their drug on the market as soon as possible, or to get results before the drug comes off patent, while it still belongs to them.

This is a major problem for patients, because benefits on surrogate endpoints often don’t translate into real-life benefits. In fact, the history of medicine is full of examples where quite the opposite was true.

Probably the most dramatic and famous comes from the Cardiac Arrhythmia Suppression Trial (CAST), which tested three anti-arrhythmic drugs to see if they prevented sudden death in patients who were at higher risk because they had a certain kind of abnormal heart rhythm.
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The drugs prevented these abnormal rhythms, so everyone thought they must be great: they were approved onto the market to prevent sudden death in patients with abnormal rhythms, and doctors felt pretty good about prescribing them. When a proper trial measuring death was conducted, everyone felt a bit embarrassed: the drugs increased the risk of death to such a huge extent that the trial had to be stopped early. We had been cheerfully handing out tablets that killed people (it’s been estimated that well over a hundred thousand people died as a result).

Even when they don’t actively increase your risk of death, sometimes drugs which work well to change surrogate outcomes simply don’t make any difference to the real outcomes that we’re most interested in. Doxazosin is an expensive branded blood-pressure drug, and it works extremely well for lowering the blood-pressure reading in a doctor’s office – about as well as chlorthalidone, a simple old-fashioned blood-pressure drug that has been off patent for many years. Eventually, a trial was done comparing the two on real-world outcomes like heart failure (using government funding, since it was in nobody’s financial interest); and it had to stop early, because patients on doxazosin were doing so much worse.
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The manufacturer of doxazosin, Pfizer, mounted a magnificent marketing campaign, and there was barely any change in the use of the drug.
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I will discuss this kind of campaigning later.

There are endless examples of drugs for which the only evidence available uses surrogate outcomes. If you have diabetes, the thing you’re worried about is death, and horrible problems in your feet, your kidneys, your eyes and so on. You worry about your blood-sugar level and your weight because they are useful guides to whether your diabetes is under control, but they’re nothing compared to the basic important question: will this drug actually reduce my risk of dying? Right now, there are all sorts of new diabetes drugs on the market. The ‘glucagon-like peptide-1 receptor drugs’, for example, are pretty exciting to a lot of doctors. If you look at the latest systematic review of their benefits, published in December 2011 (this one just happens to be open in front of me – it could have been any number of drugs) you will see that they lower blood sugar, lower blood pressure, lower cholesterol, and all this great stuff;
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but nobody’s ever checked to see if they actually stop you dying, which is all that the people taking them really care about.

The same goes for side effects. Depo-provera is a reasonably good contraceptive, but there’s some concern about whether it makes you more vulnerable to fractures. The research into this looks at bone mineral density, rather than actual fractures.
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When you come to get your drug approved to go on the market, regulators will often permit you to show proof of effectiveness only on surrogate outcomes. For ‘accelerated approval’, for drugs that are the first in a new class, or are treating a condition that has no current treatment, they may let you get away with a surrogate outcome that has barely been validated, which means there is very little research into how well it really is associated with the real-world outcomes of the disease. For context here, it’s worth remembering that the examples above, where we were misled, came from surrogate outcomes that are regarded as ‘well validated’. This would be fine if getting onto the market was just the beginning of the story, a starting gun for cautious prescription, in the context of larger monitoring of real-world outcomes. Unfortunately, as we will now see, things aren’t like that.

Accelerated approval

Gathering and assessing trial evidence takes a long time, but regulators have to balance several opposing forces. Doctors with an eye on public health are often keen to make sure that the evidence for a new product is as good as possible, partly because many new drugs are only trivially useful in comparison with what already exists; but also because the pre-approval period is the time when demands on a drug company for compelling research are most likely to be met.

Drug companies, meanwhile, would like to get their drug on the market as swiftly and cheaply as possible. This isn’t just impatience for revenue; it’s also a fear of losing revenue outright, because the clock is already ticking for patent expiry even before the approval process starts. That strong commercial incentive is communicated in muscular fashion to governments, which push regulators to approve rapidly, and often measure speed of approval as a key outcome for the regulator.

This can have worrying effects, which might lead you to believe that quality of evidence is not the only factor affecting a drug’s approval. For many decades, for example, the FDA’s performance was measured by how many drugs it managed to approve in each calendar year.
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This led to a phenomenon known as the ‘December Effect’, whereby a very large proportion of the year’s approvals were rushed through in a panic during the last few weeks around Christmas. By graphing the proportion of approvals that were made in December over the course of thirty years (below, from Carpenter 2010), we can see the size of this effect, and also trace the arrival of a more aggressive pro-industry stance during Ronald Reagan’s presidency (1981–89). If approvals were evenly distributed throughout the year, we’d expect to only see 8 per cent in each month: during the late eighties, the proportion passing in December rose to more than half, and it’s hard to believe that this was simply when the assessments were complete.