At this point, his doctor did something that would today be forbidden; he lied to him. Suspecting that the cure had all been down to Mr Wright’s belief in the drug, the doctor told him that the newspapers were wrong, and that krebiozen was turning out to be a powerful remedy for cancer. The only reason for Mr Wright’s relapse, the doctor assured him, was that the dose he had been given came from a batch that had deteriorated somewhat while in the pharmacy. Fortunately for Mr Wright, the doctor went on, a new batch of double-strength krebiozen was due to arrive at the hospital in two days’ time. Two days later, the doctor started giving Mr Wright injections – of pure water.
Again the tumours melted away, and Mr Wright lived for a further two months without symptoms. Then another newspaper report appeared, this time announcing the final verdict of the American Medical Association: nationwide tests really had shown krebiozen to be useless. Again, Mr Wright’s tumours reappeared, and within a few days he was back at the hospital. Two days after his readmission, he was dead.
This story has been repeated many times in the literature on mind-body medicine, but it remains the only one of its kind. This in itself should make us suspicious, since, as we shall see, single cases can be notoriously misleading. True, the timing of the events is very suggestive. Both recoveries happened very shortly after Mr Wright’s beliefs about his prognosis had gone from pessimistic to optimistic, and both relapses occurred within a few days of the reverse change. But coincidences do happen.
To rule out coincidence, we would need to know what would have happened to Mr Wright if he hadn’t been treated and consequently become so optimistic. Would he still have got better anyway? Of course, we will never really know for sure. We can’t go back in time and observe what would have happened if his doctor had never given him the krebiozen or the water injections. We can, however, make an educated guess, based on what tends to happen to people with similar forms of cancer if they are untreated.
There are many forms of cancer, each with its own typical sequence of events. A few, such as lymphoma, are known to fluctuate spontaneously. In a high proportion of cases, the tumours wax and wane without any treatment at all. The fact that Mr Wright was suffering from lymphoma rather than any other form of cancer means that it is quite possible that his two brief remissions from the disease were simply spontaneous fluctuations, unrelated to the krebiozen or the water injections. The fact that the recoveries occurred just after each treatment could easily have been a coincidence. In fact, since no other similar stories have been recorded, this seems the most likely explanation. Despite what some people may say, there is no evidence that the placebo response can cure cancer.
NO EVIDENCE?
‘In my experience’ is a phrase that usually introduces a statement of rank prejudice or bias. The information that follows it cannot be checked, nor has it been subjected to any analysis other than some vague tally in the speaker’s memory.
MICHAEL CRICHTON, New England Journal of Medicine (1971)
To say that there is ‘no evidence’ that the placebo response can cure cancer might seem too strong. After all, there is the story of Mr Wright. Surely, it might be objected, that has some evidential value. Andrew Weil, one of the most famous proponents of alternative approaches to medicine, claims that individual case-histories and personal testimonials should be taken more seriously by medical scientists. He values ‘anecdotal evidence’ and wonders, with a hint of Freudian suspicion, ‘why so many doctors have a hard time with it’.21
In fact, the scepticism shown by many doctors today towards claims based on individual case-histories has nothing to do with any emotional unease. If anything, it is statistics that doctors have a hard time with, rather than individual case-histories. Doctors have to learn to override their natural tendencies to be swayed by personal narrative and anecdote, and it is not an easy lesson. It is a vitally important one, though, as the history of medicine has shown, over and over again, that anecdotes are worthless without a proper statistical analysis. Many hundreds of ideas about the origins of disease and claims for surefire remedies have been accepted by doctors on the basis of ‘anecdotal evidence’, only to be shown, by eventual statistical analysis, to be completely false. Take bloodletting, for example. The technique was first introduced in Egypt around 1000 BC, and then spread to Europe via Greece. For almost three thousand years it was the mainstay of medical practice in the West. Every doctor could testify to its efficacy from his own experience, and tell dozens of anecdotes about how a certain patient got better after being bled. No attempt was made to evaluate bloodletting by statistical methods until the nineteenth century, when the French physician Pierre Louis and others found that it was useless at best, and at worst positively harmful. Only then did doctors finally abandon the ancient technique that had been handed down to them by generations of physicians, all of whom had been convinced it was therapeutic.
As has already been noted, the statistical methods of modern medical research have attracted more than their fair share of critical remarks. These criticisms reveal much about human preferences, but nothing about the value of statistics. Certainly, stories of individual patients and their triumphs over disease grip us in a way that statistics do not. This is what makes the self-help books and the New Age treatises so convincing. These volumes are littered with amazing anecdotes about this person’s miraculous recovery from cancer, or that person’s amazing triumph over arthritis. Such books are notoriously lacking in statistics. The serious scientific books that do contain statistics, on the other hand, leave most of us cold and unconvinced. The personal immediacy of a single human narrative tends to have more impact than the dry numerical objectivity of a mass of statistics.
It takes a real effort of will to pay more attention to the statistical information, but this is what we must do if we are to make our decisions on a rational basis rather than by hearsay and rumour. Statistics may be unromantic, but they are a vital remedy for the instinctive human tendency to be persuaded by isolated cases and individual stories. Of course, the statistics need to be interpreted with care, and this requires skill, intelligence and patient attention to mathematical detail. And not even the most sophisticated clinical trial can guarantee truth. It follows from the very nature of statistical research that some clinical trials are bound to generate false conclusions. The doctor and writer James Le Fanu has observed that statistical research ‘has been shown to result in the adoption of ineffective treatments in 32 per cent of cases’.22 The irony of this remark should be clear; we only know that statistical research is flawed because of statistics. There is a more serious point, however, and that is that ‘anecdotal evidence’ is even less reliable than statistical evidence. Statistics are not infallible, but when it comes to medical research, they are the best tool we have.
THE HIERARCHY OF EVIDENCE
The hard-won lessons about the relative value of anecdotal and statistical evidence have been condensed by medical researchers into a simple formula that is now referred to as the ‘hierarchy of evidence’.23 Individual case-histories and clinical vignettes are quite properly located at the bottom of the ladder. Strictly speaking, then, we should not dismiss such stories altogether, but rather emphasise their limited evidential value. Various statistical methods of research are assigned different grades on the hierarchy of evidence, with randomised controlled trials coming very near the top. The pinnacle of the hierarchy, however, is reserved not for individual clinical trials, but for systematic reviews and meta-analyses. In these research papers, all the clinical trials on a particular topic are hunted down and their results analysed by means of yet more statistical devices.
The prestige attached to meta-analysis, a set of statistical techniques developed in the 1970s, by medical researchers has not met with universal agreement. One epidemiologist, for example, has written that ‘meta-analysis
