Pharmageddon

by David Healy

  When it comes to treating people who are supposedly depressed, anti- depressant credentials in the form of comparable changes on depression rating scales have been generated for most of the benzodiazepines, for a number of antihistamines, for almost all the stimulants, as well as for the antipsychotics and anticonvulsants,26 and they could be generated for nicotine or indeed for snake oil, whose omega-3 oils appear to have some psychotropic properties. A key difference between these diverse drugs and the selective serotonin reuptake inhibitors (the SSRIs) such as Paxil, Prozac, and Zoloft, was that the SSRIs were newly patented for treating depression, while drugs like nicotine or the antihistamines were unpatentable for this purpose. There was no incentive for companies to bring these latter drugs to the market but no reason to believe these drugs would be any less helpful than Prozac for depression. In the case of Prozac and Paxil, there is evidence of a weak association between treatment and a change on a rating scale but the question is what lies behind that change. The fact that so many quite different drugs can also be linked to a comparable benefit shows we know next to nothing about what is going on.

  This is where the role of a mythic image of what a drug is supposed to do (a concept) can be of great importance to a marketing department. No one claims nicotine or benzodiazepines correct a lowering of serotonin in depression, whereas the SSRIs supposedly do. The idea that there is an imbalance of serotonin in depression is completely mythical. It arose in the marketing department of SmithKline Beecham, the maker of Paxil.27 The key thing about this myth is that it provides an image that functions like the imagery of bacterial colonies in a Petri dish shrinking back from an antibiotic, or images of cholesterol levels declining following treatment with statins, or bones becoming denser with biphosphonate treatment for osteoporosis. These images help create the impression that drugs “work,” when in fact the data from trials show these treatments have relatively minimal effects. These images create a spin that no data can overcome. Myths always have the last word.

  How minimal are the treatment effects? In 2006 the FDA asked companies making antidepressants to submit all placebo-controlled trials to the agency. Just as some people recover from infections without treatment, based on 100,000 patients who had been entered into these anti- depressant trials, the data showed that four out of ten people improve within a few weeks whether treated with a drug or not.28 This may in part be due to the natural history of depressions in which 40 percent recover within a few months whether treated or not. Advice from a clinician on diet, lifestyle, alcohol intake, and problem solving on work and relationship issues may make a difference. Perception by patients that they are being seen and cared for by a medical expert may also make a difference, and this effect may be enhanced by being given a substance they think will restore some chemical balance to normal—even if that imbalance is mythical and the substance a placebo. On the active drugs, five out of ten apparently responded. But what comparing an active drug to a placebo shows us is that of these five, four (80 percent) of apparent responders to an antidepressant would have improved had they received the placebo. In other words, only one in every ten patients responds specifically to the antidepressant, whereas four in every ten treated with a placebo show a response.

  If clinicians were really following the evidence, they should say that it's wonderful to have some evidence that antidepressants have benefits, but they would hold back on prescribing them indiscriminately and give a number of their patients a chance to recover without treatment. There is good reason to believe that many of those who recover without drug treatment are less likely to relapse in the longer run, which provides even more reason to wait judiciously in at least some cases.29 Given that the benefits obtained in the one out of ten are bought at a cost— overall more die on treatment than on placebo, more become dependent on treatment than on placebo, more on treatment have children born with birth defects than do those on placebo, and have many other side effects—the antidepressants arguably provide the perfect set of data to support Pinel's dictum that it is important to know when not to use a treatment.

  On grounds of self-interest, there are good reasons for doctors to wait in many nonacute cases. Until recently the magic was in the therapist, who might also give pills, which were an extension of his or her impact on us. Now the magic has passed into the capsule and the physician often seems little more than a conduit for medication. Therapists have forgotten how influential they might be in promoting healthier lifestyles for conditions from raised cholesterol to the inevitable but relatively inconsequential thinning of bones that happens after the menopause. With the focus that both doctor and patient now have on taking a pill, seldom do either heed the context in which a person has become distressed or unhealthy. Neither doctor nor patient appears to see how small a contribution this chemical manipulation is likely to make or to see the potential for a chemical manipulation to make things worse. In practice, doctors end up so often doing what suits drug companies- they persuade patients to go on treatments. Why? In no small part because they have become convinced that these treatments have been shown in randomized controlled trials to work.

  A consideration of these nondrug aspects of medical care doesn't just apply to drugs like the antidepressants. An antibiotic like penicillin might make a life-saving difference, but it's important to note that this may not be the only route to saving a life. Once the infection begins, an antibiotic may be by far the best way to help, and we would sue a doctor who let a patient die without treatment. But in the case of puerperal infections, long before the advent of penicillin, it had become clear that women were only likely to contract these disorders if they gave birth in hospitals where the infection could be transmitted readily from one woman to the next. Strict antiseptic procedures in hospitals could help, but giving birth outside the hospital made an infection much less likely.

  At the moment doctors appear to be under increasing pressure from insurance managers, hospital bureaucrats, and others to hand out drugs in response to medical problems. If patients aren't on a treatment, they aren't in treatment. No one, not even an insurance manager, would want to be linked to unnecessary deaths. In using drugs that have been shown to “work” in a statistically significant fashion, all concerned think they are avoiding this possibility. But while penicillin can clearly be shown to save lives, the same clarity can't be found with antidepressants, statins given to people with no prior cardiovascular events, asthma drugs, or treatments for osteoporosis and many other conditions. In all these cases, a shrewd selection of statistically significant changes on rating scales or blood tests as evidence that the treatment “works” has been used by pharmaceutical companies to mesmerize all the key players.

  “Working” in the case of all the best sellers in medicine, it bears repeating, means the drug produces changes on some measurement of interest to a drug company, rather than indicating the drug saves a life or returns someone to employment, or is better than an older drug in the field, or even makes a person simply feel better. When in the course of these trials patients are allowed to rate whether their quality of life has been improved, in results reminiscent of Sanjeebit Jachuk's study of propranolol, antidepressants, for instance, don't show any benefit over placebo. Such quality-of-life data from antidepressant trials are little known, however, because they remain almost universally unpublished.30 The bottom line is that while placebo-controlled trials have created appearances that the drugs work, with a few changes to the choice or rating scales or blood tests in these studies or taking into account the withdrawal effects many of these drugs have, it would be possible to show just the opposite for most of medicine's blockbusters.

  There is a fundamental psychological issue here on which companies play, an issue illuminated by a series of experiments Daniel Kahnemann and Amos Tversky conducted in the 1970s on what happens when we are asked to make judgments under conditions of uncertainty.31 Kahnemann and Tversky, who won a Nobel Prize for their work, gave descriptions of a shy, retiring, and
bookish personality to their test subjects and asked them to judge whether the person was a nurse or a librarian, having told them the personality profile had been drawn from a group that contains eight nurses and two librarians. Their subjects confidently said the person described was a librarian, when, given the probabilities, they should have said nurse. In the same way, statistics like those mentioned from the antidepressant trials (in which five out of ten seemed to improve from the drug, but closer inspection revealed that improvements in four out of those five could as well be due to placebo effects) should lead us, given the overwhelming odds, to attribute a positive response in a patient to a placebo effect. But like the subjects who chose librarian, we're more likely to jump to the conclusion that the antidepressant must have been the cause.

  As drug marketers know, we are all more confident with stereotypes than with rational analysis of the probabilities of a situation. When we see patients on a pill recover, probably because of powerful examples like those of penicillin and insulin, we assume the recovery has come about because of the pill. This bias may be reinforced by hearing “experts” claim that antidepressants or statins work or by seeing these claims in what are considered authoritative publications. A mythic image of increasing bone density or normalizing serotonin levels or lowering cholesterol levels helps increase our certainty.

  Neither clinicians nor patients are well equipped to make judgments based on data. Our psychology biases us against seeing what the data actually show, and this bias is aggravated by the selective publication of company trials that indicate a “positive” response to the drug and, ironically, by an apparatus put in place to ensure doctors adhere to the “evidence.” These factors have increasingly led to an almost automatic prescription of the latest drugs whether they are statins, hypoglycemics, biphosphonates, or psychotropic drugs.

  COMPANY TRIALS

  The job of medicine is to save lives, restore function, or improve on treatments already available. The aim of a drug company is to get their drugs on the market and generate profits by so doing. To see if a new treatment saves more lives or performs better than an older treatment, the obvious step is to compare the two. To get on the market, you could demonstrate superiority to an older treatment, but to satisfy the FDA or regulators in Europe or Japan you only have to beat the placebo. And if you recruit ever larger numbers of patients to trials, ever less clinically significant differences from placebo can become statistically significant. Perversely this will lead to the newer and weaker drug selling even better than the older one.

  Almost all the drugs trials now conducted are done by their manufacturers to get their compounds on the market or to establish a market niche. Once completed, these trials mark the point at which any science stops—a drug has been shown to “work,” companies say, and the job of doctors is now to prescribe it—whereas entry into the market should mark the point where science begins to establish who benefits from which drug. If only a small number of people respond specifically to a statin for cholesterol levels or a biphosphonate for osteoporosis, we should be identifying who these specific responders are. Until we answer this we remain in the position of congratulating ourselves on the use of plaster casts when in three out of four cases they have been put on the wrong limb—but of course this is the question no company wants answered.

  Even without fully understanding why a treatment helps, though, more can be done to improve how it is used. For instance, we have many different kinds of blood pressure medication, but almost no research to discover how they compare or who they suit. The first thiazide antihypertensives in the 1950s were succeeded by James Black's propranolol in the 1960s and 1970s, the ACE inhibitors in the 1980s, sartans in the 1990s, and a string of others, with each new drug marketed as the best. When the first proper head-to-head studies were done fifty years later, they showed that, in fact, the thiazides were the most effective and the safest.32 For fifty years we have used a succession of ever more expensive treatments, while the best and safest and least expensive treatments fell out of favor.

  Similarly, the SSRIs in clinical trials got far fewer severely depressed patients well than older antidepressants.33 But to get on the market they did not have to be compared to an older drug; they had only to beat the placebo. As a result of marketing, the more recent drugs have almost completely replaced older antidepressants, even for the most severe depressions, for which there is not a scrap of evidence the newer drugs work.

  The story is similar for the analgesics, drugs for osteoporosis, blood- sugar-lowering drugs, the antipsychotics, and almost every other best- selling drug. Best-sellers are not best sellers because they are in fact better than the drugs previously available. Yet in all these areas of treatment, doctors who are supposedly following the evidence make the latest drugs into best sellers.

  There is more going on here than simply squandering money in the pursuit of the trivial (though profitable) new drug or giving patients suboptimal medicine. Company trials have radically changed how doctors treat patients. Before 1962 when the FDA stepped in and required companies to provide evidence of trials to bring their drug on the market, doctors for centuries had to learn how to use a drug when it became available. Digitalis offers a good example. This drug works by removing excess fluid from the body in cases of heart failure, but as with all drugs, digitalis came with problems. So doctors, when giving it, would typically start at a low dose, and work upward depending on how the patient responded.

  But in company trials, no company is prepared to take a chance that their drug won't beat the placebo, so they err on the side of a higher or more poisonous dose. If these studies get the drug on the market, the trial results are then taken to mean that doctors should use the dose of the statin, analgesic, or antidepressant used in the trial, even though it is likely to be too high for many people. On the basis of early trials, the thiazides were given for hypertension in doses ten times higher than necessary, for example, while the lowest dose of Prozac for depression was four times higher than many people needed.34

  Once a drug is launched, companies could run studies to find the right starting dose or determine which drug suits which kinds of patients, but marketing departments have resisted studies of lower doses of a drug—on the grounds that they want to keep things simple for doctors. Their dream is one-size-fits-all treatment, and they refuse to make lower dose formulations of a medicine available. In this way companies are, in essence, removing the craft as well as the art from medicine and encouraging overmedication.

  But there are even bigger problems than this. Company trials trap both doctors and patients into treatment with the wrong medication. The antipsychotic group of drugs shows how badly wrong things can go. The first of these was chlorpromazine, a drug discovered in 1952 and widely cited as rivaling penicillin as a key breakthrough in modern medicine. It and succeeding tranquilizers had a magical effect on manic and delirious states and on some acute psychoses, sometimes restoring patients to normal functioning within days, or weeks, sometimes in hours. This was not a matter of small changes on a rating scale; there was no question but that chlorpromazine worked.35

  Its French discoverers were sure, however, that it was not a cure for schizophrenia. In some cases it provided a useful tranquilization, but in up to a third of schizophrenic patients it made their condition worse, and in a further third the benefits were minimal. Nevertheless, most company trials to bring the successors of chlorpromazine to the US market were undertaken in schizophrenia. When responders, minimal responders, and those who got worse were combined, the results for these drugs could be shown to be, on average, marginally better than for the placebo—which was all it took to get these drugs on the market. These results, reinforced by rebranding the tranquilizers as antipsychotics, made it seem these drugs “worked” for schizophrenia. For the FDA, and most doctors, the one in three patients who got worse on treatment vanish into a statistical ether—but these patients don't vanish from the hospital and the clinic.

 
The antipsychotics are drugs to use judiciously. They increase rates of heart attacks, strokes, diabetes, and suicides. Studies that have examined longer term outcomes for patients on these drugs universally show a reduction in life expectancy measured in decades, not just years.36 This is not an argument against their use, but it is definitely an argument for ensuring that they actually are producing benefits that warrant the risks undertaken. Unfortunately, even when faced with a patient who is not responding or responding negatively and for whom therefore the treatment should be stopped, the drug often keeps being given. Nursing staff, hospital administrators, relatives, and other doctors find it inconceivable that a doctor might not give a drug that “works” to a patient who is so clearly ill with the condition that the drug supposedly benefits—to the point that a refusal to prescribe is in many settings getting ever closer to being grounds for dismissal.

  In similar fashion, the company trials of statins for lowering cholesterol, biphosphonates for osteoporosis, and for other medicines that suggest these drugs “work” exert pressure on clinicians to prescribe and patients to acquiesce in treatment. This pressure cannot simply be put down to corruption by the pharmaceutical industry. No one, it seems, wants a doctor to wait judiciously to see if a treatment is really warranted. We might like the idea of an Alfred Worcester in books or movies but not in real life.

  In addition to these serious consequences for medical care, there is a huge ethical problem with company trials. Randomized controlled trials began in conditions of scarcity after World War II, when those who volunteered to be left untreated or to get a potentially dangerous new treatment did so for the sake of their families, their relatives, or the communities from which they came. They consented, in other words, because they thought they were helping to improve medical care, and in so doing they did in fact lay the basis for our current freedom from infectious diseases, malignant hypertension and other disorders, and our better life expectancies in the face of tumors. The same spirit is now invoked when patients are asked to consent to company-run trials. But they are not told that these studies are designed to secure a business advantage, that they will lead to marketing that often substitutes giving drugs for caring, that far from benefitting their communities the studies may result in treatments that shorten lives, or that data from these studies may be sequestered so that nobody ever finds out about the side effects of treatment. They never get a chance to decide freely whether to consent to this or not.