On the Origin of Risk Relativism

The epidemiologic traditions that relative effect measures should be used to assess causality and that absolute measures should be used to assess impact are handed down from one generation to the next, without citation or critical reflection, as though their truth were self-evident.1–17 Unlike other received views, these can be traced to a single source, a 1959 paper by Cornfield et al18: Both the absolute and the relative measures serve a purpose. The relative measure is helpful in (1) appraising the possible noncausal nature of an agent having an apparent effect; (2) appraising the importance of an agent with respect to other possible agents inducing the same effect; and (3) properly reflecting the effects of disease misclassification or further refinement of classification. The absolute measure would be important in appraising the public health significance of an effect known to be causal. These general claims were embedded in a substantive controversy: the debate in the late 1950s and early 1960s over the health effects of cigarette smoking. This “landmark consensus paper”19 was “the culminating scientific paper of the decade”20 on the topic for some, but for others21 it was not worth mentioning. However the paper may have influenced the debate, there is no doubt the debate influenced the paper. CONTEXT Until the mid-1950s, most of the epidemiologic evidence on cigarette smoking and health pertained to lung cancer. Most of that evidence came from case-control studies. Validity threats ran the gamut, from selection bias to confounding to information bias.21 One hypothesis, “that cigarette-smoking and lung cancer, though not mutually causative, are both influenced by a common cause,”22 achieved prominence on the authority of its chief proponent, Fisher. He could not name the completely explanatory confounder, but believed it was a feature of the genotype. Meanwhile, considerations known today as “causal criteria” were under development. One list23 appeared in the same year as the paper by Cornfield et al.18 The criterion of specificity of effect was controversial from the start. Sartwell24 flatly rejected it, but one of Cornfield's coauthors, Lilienfeld,25 endorsed it with only mild qualification: “Generally speaking, it is difficult to quarrel with such a position, although there is a need to qualify the application of this criterion. Specificity of effect must be interpreted in terms of the degree of association of the characteristic with the disease.” Strength of association and specificity of effect thus became linked, as Susser26,27 later noted they must be. An exposure's association becomes specific by being stronger for one outcome than for others. What remains, if one accepts the criteria, is to determine the scale for measuring strength. In the mid-1950s, results from cohort studies began to appear.21 They allowed examination of the strength, and thereby the specificity, of smoking's association with many outcomes. Berkson28,29 took up the task enthusiastically, pointing to a lack of specificity in rate differences like those in Table 1. “For myself, I find it quite incredible that smoking should cause all these diseases. It appears to me that some other explanation must be formulated for the multiple statistical associations found with so wide a variety of categories of disease.”28 Berkson laced his skepticism with sarcasm: “The question raised by the findings is not, ‘Does cigarette smoking cause cancer of the lungs?’ so much as it is, ‘What disease does cigarette smoking not cause?’”29 It is easy to imagine such remarks eliciting laughter from clinicians and statisticians in the smoke-filled rooms of the day.TABLE 1: Death Rates, Ratios and Differences by Cigarette Smoking and Cause of Death in a Cohort Study of United States Men30Opinions differed much more widely on other hypothetical smoking effects than on lung cancer. Among Cornfield's coauthors, Hammond and Horn31 had concluded in 1954 that the association between smoking and coronary artery disease was causal, but in 1959 Lilienfeld32 was still harboring grave doubts: It has been shown that smokers and nonsmokers differ with respect to emotional characteristics. Since there are clinical impressions that emotional factors may have an influence on such diseases as peptic ulcer and coronary artery disease, self-selection should be considered a possible explanation for the association of smoking with these diseases. Further investigation is necessary before a final decision can be made. The 1964 Surgeon General's Advisory Committee33 shared Lilienfeld's reservations: “Male cigarette smokers have a higher death rate from coronary artery disease than nonsmoking males, but it is not clear that the association has causal significance.” This was the backdrop against which Cornfield et al18 argued for the superiority of ratio effect measures over difference measures in assessing causality. The overall evidence was stronger and more plausible for lung cancer than for coronary artery disease and other diseases. The association seemed specific to lung cancer, or nearly so, when the rate ratio was the strength metric, but not for the rate difference. As the time had come “for planning and activating public health measures” based on lung cancer alone, the skeptics' persistence was beginning to seem like obstructionism. ARGUMENT 1: THE CONFOUNDER-EXPOSURE ASSOCIATION In their first formal argument for the risk ratio over the risk difference in assessing causality, Cornfield et al18 showed how strong the association between a binary confounder and an exposure must be for the confounder to account for an association between the exposure and a disease. In the notation of Table 2, which differs slightly from the authors' notation, the confounder, present in both exposure groups, has a prevalence of p0 among the unexposed and a higher prevalence of p1 among the exposed: 0 < p0 < p1 < 1. The crude risks of the disease within exposure levels may thus be written as weighted averages: TABLE 2: Notation