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In the early 1940s, a similar notion had gripped the eccentric Oxford geneticist Edmund Ford. A firm believer in Darwinian evolution, Ford nonetheless knew that Darwin’s theory suffered from an important limitation: thus far, the evolutionary progression had been inferred indirectly from the fossil record, but never demonstrated directly on a population of organisms. The trouble with fossils, of course, is that they are fossilized—static and immobile in time. The existence of three fossils A, B, and C, representing three distinct and progressive stages of evolution, might suggest that fossil A generated B and fossil B generated C. But this proof is retrospective and indirect; that three evolutionary stages exist suggests, but cannot prove, that one fossil had caused the genesis of the next

The only formal method to prove the fact that populations undergo defined genetic changes over time involves capturing that change in the real world in real time—prospectively. Ford became particularly obsessed with devising such a prospective experiment to watch Darwin’s cogwheels in motion. To this end, he persuaded several students to tramp through the damp marshes near Oxford collecting moths. Each time a moth was captured, it was marked with a cellulose pen and released back into the wild. Year after year, Ford’s students had returned with galoshes and moth nets, recapturing and studying the moths that they had marked in the prior years and their unmarked descendants—in effect, creating a “census” of wild moths in the field. Minute changes in that cohort of moths, such as shifts in wing markings or variations in size, shape, and color, were recorded each year with great care. By charting those changes over nearly a decade, Ford had begun to watch evolution in action. He had documented gradual changes in the color of moth coats (and thus changes in genes), grand fluctuations in populations and signs of natural selection by moth predators—a macrocosm caught in a marsh.*

Both Doll and Hill had followed this work with deep interest. And the notion of using a similar cohort of humans occurred to Hill in the winter of 1951—purportedly, like most great scientific notions, while in his bath. Suppose a large group of men could be marked, à la Ford, with some fantastical cellulose pen, and followed, decade after decade after decade. The group would contain some natural mix of smokers and nonsmokers. If smoking truly predisposed subjects to lung cancer (much like bright-winged moths might be predisposed to being hunted by predators), then the smokers would begin to succumb to cancer at an increased rate. By following that cohort over time—by peering into that natural marsh of human pathology—an epidemiologist could calculate the precise relative risk of lung cancer among smokers versus nonsmokers.

But how might one find a large enough cohort? Again, coincidences surfaced. In Britain, efforts to nationalize health care had resulted in a centralized registry of all doctors, containing more than sixty thousand names. Every time a doctor in the registry died, the registrar was notified, often with a relatively detailed description of the cause of death. The result, as Doll’s collaborator and student Richard Peto described it, was the creation of a “fortuitous laboratory” for a cohort study. On October 31, 1951, Doll and Hill mailed out letters to about 59,600 doctors containing their survey. The questions were kept intentionally brief: respondents were asked about their smoking habits, an estimation of the amount smoked, and little else. Most doctors could respond in less than five minutes.

An astonishing number—41,024 of them—wrote back. Back in London, Doll and Hill created a master list of the doctors’ cohort, dividing it into smokers and nonsmokers. Each time a death in the cohort was reported, they contacted the registrar’s office to determine the precise cause of death. Deaths from lung cancer were tabulated for smokers versus nonsmokers. Doll and Hill could now sit back and watch cancer unfold in real time.

In the twenty-nine months between October 1951 and March 1954, 789 deaths were reported in Doll and Hill’s original cohort. Thirty-six of these were attributed to lung cancer. When these lung cancer deaths were counted in smokers versus nonsmokers, the correlation virtually sprang out: all thirty-six of the deaths had occurred in smokers. The difference between the two groups was so significant that Doll and Hill did not even need to apply complex statistical metrics to discern it. The trial designed to bring the most rigorous statistical analysis to the cause of lung cancer barely required elementary mathematics to prove its point.

Excerpted from pages 247-249 of ‘The Emperor of All Maladies: A biography of Cancer’ by Siddharth Mukherjee