Endpoint Problem
The endpoint problem refers to the use of surrogate biomarkers as stand-ins for true clinical outcomes, which can lead to false conclusions about causality if the correlation between surrogate and endpoint is not causal. This is illustrated by the historical debate over whether smoking causes lung cancer, where R.A. Fisher argued that observed correlations could be due to common causes or reverse causation.
THE IDEA
endpoint problem
. It’s time consuming and expensive to check whether a drug improves average life span, because in order to record someone’s life span you have to wait for them to die. HDL level is the surrogate endpoint, the easy-to-check biomarker that’s supposed to stand in for “long life with no heart attack.” But the correlation between HDL and absence of heart attack might not indicate any causal link.
Teasing apart correlations that come from causal relationships from those that don’t is a maddeningly hard problem, even in cases you might think of as obvious, like the relation between smoking and lung cancer. At the turn of the twentieth century, lung cancer was an extremely rare disease. But by 1947, the disease accounted for nearly a fifth of cancer deaths among British men, killing fifteen times as many people as it had a few decades earlier. At first, many researchers thought that lung cancer was simply being diagnosed more effectively than before, but it soon became clear that the increase in cases was too big and too fast to be accounted for by any such effect. Lung cancer really was on the rise. But no one was sure what to blame. Maybe it was smoke from factories, maybe increased levels of car exhaust, or maybe some substance not even thought of as a pollutant. Or maybe it was cigarette smoking, whose popularity had exploded during the same period.
By the early 1950s, large studies in England and America had shown a powerful association between cigarette smoking and lung cancer. Among nonsmokers, lung cancer was still a rare disease, but for smokers, the risk was spectacularly higher. A famous paper of Doll and Hill from 1950 found that among 649 male lung cancer patients in twenty London hospitals, only two were nonsmokers. That’s not as impressive as it sounds by modern standards; in midcentury London, smoking was an extremely popular habit, and nonsmokers were much rarer than they are now. Even so, in a population of 649 male patients admitted for complaints other than lung cancer, 27 were nonsmokers, a lot more than 2. What’s more, the association got stronger as smoking got heavier. Of the lung cancer patients, 168 went through more than twenty-five cigarettes a day, while only 84 men hospitalized for some other condition smoked that much.
Doll and Hill’s data showed that lung cancer and smoking were correlated; their relation was not one of strict determination (some heavy smokers don’t get lung cancer, while some nonsmokers do), but neither were the two phenomena independent. Their relation lay in that fuzzy, intermediate zone that Galton and Pearson had been the first to map.
The mere assertion of correlation is very different from an explanation. Doll and Hill’s study doesn’t show that smoking causes cancer; as they write, “The association would occur if carcinoma of the lung caused people to smoke or if both attributes were end-effects of a common cause.” That lung cancer causes smoking, as they point out, is not very reasonable; a tumor can’t go back in time and give someone a pack-a-day habit. But the problem of the common cause is more troubling.
Our old friend R. A. Fisher, the founding hero of modern statistics, was a vigorous skeptic of the tobacco-cancer link on exactly those grounds. Fisher was the natural intellectual heir to Galton and Pearson; in fact, he succeeded Pearson in 1933 as the Galton Chair of Eugenics at University College, London. (In deference to modern sensibilities, the position is now called the Galton Chair of Genetics.)
Fisher felt it was premature even to rule out the cancer-causes-smoking theory:
Is it possible then, that lung cancer—that is to say, the pre-cancerous condition which must exist and is known to exist for years in those who are going to show overt lung cancer—is one of the causes of smoking cigarettes? I don’t think it can be excluded. I don’t think we know enough to say that it is such a cause. But the pre-cancerous condition is one involving a certain amount of slight chronic inflammation. The causes of smoking cigarettes may be studied among your friends, to some extent, and I think you will agree that a slight cause of irritation—a slight disappointment, an unexpected delay, some sort of a mild rebuff, a frustration—are commonly accompanied by pulling out a cigarette and getting a little compensation for life’s minor ills in that way. And so, anyone suffering from a chronic inflammation in part of the body (something that does not give rise to conscious pain) is not unlikely to be associated with smoking more frequently, or smoking rather than not smoking. It is the kind of comfort that might be a real solace to anyone in the fifteen years of approaching lung cancer. And to take the poor chap’s cigarettes away from him would be rather like taking away his white stick from a blind man. It would make an already unhappy person a little more unhappy than he need be.
One sees here both a brilliant and rigorous statistician’s demand that all possibilities receive fair consideration, and a lifelong smoker’s affection for his habit. (Some have also seen the influence of Fisher’s work as a consultant to the Tobacco Manufacturer’s Standing Committee, a British industry group; in my view, Fisher’s reluctance to assert a causal relationship was consistent with his general statistical approach.) Fisher’s suggestion that the men in Doll and Hill’s sample might have been driven to smoke by precancerous inflammation never caught on, but his argument for a common cause gained more traction. Fisher, true to his academic title, was a devoted eugenicist, who believed that genetic differences determined a healthy portion of our fate and that the better sort of people were in grave danger, in these evolutionarily forgiving times, of being outbred by their natural inferiors. From Fisher’s point of view, it was perfectly natural to imagine that a common genetic factor, as yet unmeasured, was behind both lung cancer and the propensity to smoke cigarettes. That might seem rather speculative. But remember, at the time, the generation of lung cancer by smoking rested on equally mysterious grounds. No chemical component of tobacco had yet been shown to produce tumors in the lab.
There’s an elegant way to test for genetic influence on smoking, by studying twins. Say two twin siblings “match” if either both are smokers or both are not. You might expect matching to be fairly common, since twins typically grow up in the same home, with the same parents, and in the same cultural conditions, and that’s indeed what you see. But identical twins and fraternal twins are subject to these commonalities to exactly the same degree; so if identical twins are more likely to match than fraternal twins, it’s evidence that heritable factors exert some influence on smoking. Fisher presented some small-scale results to that effect, from unpublished studies, and more recent work has borne out his intuition; smoking appears to be subject to at least some heritable effects.
Which, of course, isn’t to say that those same genes are what give you lung cancer down the road. We know a lot more now about cancer and how tobacco brings it about. That smoking gives you cancer is no longer in serious dispute. And yet it’s hard not to be somewhat sympathetic to Fisher’s let’s-not-be-hasty approach. It’s good to be suspicious of correlations. The epidemiologist Jan Vandenbroucke wrote of Fischer’s articles on tobacco, “To my surprise, I found extremely well-written and cogent papers that might have become textbook classics for their impeccable logic and clear exposition of data and argument if only the authors had been on the right side.”
Over the course of the 1950s, scientific opinion on the question of lung cancer and smoking steadily converged toward consensus. True, there was still no clear biological mechanism for the generation of tumors by tobacco smoke, and there was still no case for the association between smoking and cancer that didn’t rest on observed correlations. But by 1959, so many such correlations had been seen, and so many possible confounding factors ruled out, that U.S. Surgeon General Leroy E. Burney was willing to assert, “The weight of evidence at present implicates smoking as the principal factor in the increased incidence of lung cancer.” Even then, this stance was not uncontroversial. John Talbott, the editor of the Journal of the American
When to use it
Evaluating the effectiveness of a new drug based on a biomarker (e.g., cholesterol level) rather than real clinical outcomes (e.g., heart attacks).
Assessing the link between a dietary component and disease in an observational study while controlling for potential confounders like socioeconomic status.
Interpreting epidemiological data on environmental exposures (e.g., air pollution) and health outcomes, considering possible reverse causation or confounding.
Understanding the role of genetic factors in a disease by studying twin data to disentangle heritability from environmental causes.
FROM THEORY TO EVERYDAY LIFE
In practice
HDL as a surrogate endpoint for heart disease
It’s time consuming and expensive to check whether a drug improves average life span, because recording someone’s life span means waiting for them to die. HDL level is the surrogate endpoint, the easy-to-check biomarker that’s supposed to stand in for 'long life with no heart attack.' But the correlation between HDL and absence of heart attack might not indicate any causal link.
Smoking and lung cancer: Correlation or causation?
The historical debate between Doll and Hill and R.A. Fisher. Doll and Hill's 1950 study showed a strong correlation between smoking and lung cancer among 649 male lung cancer patients, with only two nonsmokers. Fisher argued that a common genetic factor could be the cause, or even that precancerous inflammation might cause smoking. Establishing causation from correlation requires considering surrogate endpoints and confounding factors.
A MOMENT TO REFLECT
Put it to work.
Think of a current medical or scientific claim based on a surrogate endpoint. How would you evaluate whether the correlation is causal?
How did R.A. Fisher's alternative explanations for the smoking-lung cancer association challenge the idea of direct causation? What does this teach us about the limitations of observational studies?
In what situations might it be justified to rely on a surrogate endpoint despite the risk of misleading correlations?
Often confused with
References
- Study on smoking and lung cancer in London hospitals — Doll and Hill (1950)
- Fisher's arguments on smoking and cancer — R.A. Fisher
- Vandenbroucke's commentary on Fisher's papers — Jan Vandenbroucke
CONTINUE THE CONVERSATION
Source texts
- How Not to Be Wrong The Power of Mathematical Thinking (Ellenberg, Jordan)