The Swine Flu Vaccine and Guillain-Barré Syndrome: A Case Study in Relative Risk and Specific Causation

DAVID A. FREEDMAN [*] PHILIP B. STARK [**] I INTRODUCTION This article discusses the role of epidemiologic evidence in toxic tort cases, focusing on relative risk. If a relative risk is above 2.0, can we infer specific causation? Relative risk compares groups in an epidemiologic study. One group is exposed to some hazard, like a toxic substance; another "control" group is not exposed. For present purposes, relative risk is a ratio: RR = Observed/Expected. The numerator in this fraction is the number of injuries observed in the exposed group. The "expected" number in the denominator is computed on the theory that exposure has no effect, so that injury rates in the exposed group should be the same as injury rates in the control group. Adjustments are often made to account for known differences between the two groups, for example, in the distribution of ages. The basic intuition connecting relative risk and probability of causation can be explained as follows. Suppose that the exposed and unexposed groups in an epidemiologic study are similar except for the exposure of interest, so that confounding is not an issue. For simplicity, suppose also that the two groups are the same size. To have specific numbers, suppose there are 400 injuries in the exposed group and 100 in the control group. In other words, the observed number of injuries is 400, compared to an expected number of 100. The relative risk is 400/100, or 4. Without exposure, there would be only 100 injuries among the exposed, so 300 of the 400 injuries may be attributable to the exposure and 100 to other factors. Apparently, then, each injury in the exposed group has a chance of 3/4 of being caused by exposure. Likewise, a relative risk of 3 corresponds to a chance of 2/3, while a relative risk of 2 corresponds to a chance of 1/2, which may be the minimum level needed to carry the burden of proof in civi l litigation. [1] The object here is to explore the scientific logic behind these intuitions. Of course, any epidemiologic study is likely to have problems of bias: Uncontrolled confounding appears to be the rule, rather than the exception. [2] When effects are large, such problems may not be material. When relative risk is near the critical value of 2.0, potential biases must be assessed more carefully. Individual differences also play an important role: The plaintiff may not resemble typical members of the study population; effects of such differences need to be considered. This is a salient difficulty in connecting relative risk to specific causation. With a randomized controlled experiment, for example, treatment and control groups are balanced in the aggregate but not at the level of individuals. Thus, even with the best research designs--where general causation is easily demonstrated--specific causation remains troublesome. We wanted to consider such issues in the context of a real example, in part to see how well the courtroom evidence stands up when examined retrospectively. We started from a list of legal opinions where relative risk and specific causation come together. [3] Generally, the evidence of harm was shaky. In one case--Manko v. United States [4]--there turned out to be a substantial body of epidemiologic evidence suggesting that the swine flu vaccine caused Guillain-Barre syndrome ("GBS"). Moreover, the vaccine campaign of 1976 is itself a fascinating case study of specific causation. GBS is a rare neurological disorder, sometimes triggered by vaccination or by infection. Paralysis can follow, although most patients make a complete recovery in a few weeks or months. The epidemiology of swine flu vaccine and GBS is summarized in Part II. Part III discusses Manko and the use of relative risk to demonstrate specific causation. Although the plaintiff prevailed, his proof of specific causation seems questionable, due in part to differences between him and typical members of the study population. …