Substituting Risk for Specific Causation

Specious, Speculative, Spurious, and Sophistical

Some legal writers assert that all evidence is ultimately “probable,” but that assertion appears to be true only to the extent that the evidentiary support for any claim can be mapped on scale from 0 to 1, much as probability is.  Probability thus finds its way into discussions of burdens of persuasion as requiring the claim to be shown more probably than not, and expert witness certitude as requiring “reasonable degree of scientific probability.”

There is a contrary emphasis in the law on “actual truth,” which is different from “mere probability.”  The rejection of probabilism can be seen in some civil cases, in which courts have emphasized the need for individualistic data and conclusions, beyond generalizations that might be made about groups that clearly encompass the individual at issue. For example, the Supreme Court has held that charging more for funding a woman’s pension than a man’s is discriminatory because not all women will outlive all men, or the men’s average life expectancy. City of Los Angeles Dep’t of Water and Power v. Manhart, 435 U.S. 702, 708 (1978) (“Even a true generalization about a class is an  insufficient reason for disqualifying an individual to whom the generalization does not apply.”). See also El v. Southeastern Pennsylvania Transportation Authority, 479 F.3d 232, 237 n.6 (3d Cir. 2007) (“The burden of persuasion … is the obligation to convince the factfinder at trial that a litigant’s necessary propositions of fact are indeed true.”).

Specific causation is the soft underbelly of the toxic tort world, in large measure because courts know that risk is not specific causation. In the context of risk of disease, which is usually based upon a probabilistic group assessment, courts occasionally distinguish between risk and specific causation. SeeProbabilism Case Law” (Jan. 28, 2013) (collecting cases for and against probabilism).

In In re Fibreboard Corp., 893 F. 2d 706, 711-12 (5th Cir. 1990), the court rejected a class action approach to litigating asbestos personal injury claims because risk could not substitute for findings of individual causation:

“That procedure cannot focus upon such issues as individual causation, but ultimately must accept general causation as sufficient, contrary to Texas law. It is evident that these statistical estimates deal only with general causation, for ‘population-based probability estimates do not speak to a probability of causation in any one case; the estimate of relative risk is a property of the studied population, not of an individual’s case.’ This type of procedure does not allow proof that a particular defendant’s asbestos ‘really’ caused a particular plaintiff’s disease; the only ‘fact’ that can be proved is that in most cases the defendant’s asbestos would have been the cause.”

Id. at 711-12 (citing Steven Gold, “Causation in Toxic Torts: Burdens of Proof, Standards of Persuasion, and Statistical Evidence,” 96 Yale L.J. 376, 384, 390 (1986). See also Guinn v. AstraZeneca Pharms., 602 F.3d 1245, 1255 (11th Cir. 2010) (“An expert, however, cannot merely conclude that all risk factors for a disease are substantial contributing factors in its development. ‘The fact that exposure to [a substance] may be a risk factor for [a disease] does not make it an actual cause simply because [the disease] developed.’”) (internal citation omitted).

Specific causation is the soft underbelly of the toxic tort world, in large measure because courts know that risk is not specific causation. The analytical care of the Guinn case and others is often abandoned when it will stand in the way of compensation. The conflation of risk and (specific) causation is prevalent precisely because in many cases there is no scientific or medical way to discern what antecedent risks actually played a role in causing an individual’s disease.  Opinions about specific causation are thus frequently devoid of factual or logical support, and are propped up solely by hand waving about differential etiology and inference to the best explanation.

In the scientific world, most authors recognize that risk, even if real and above baseline, regardless of magnitude, does not support causal attribution in a specific case.[1]  Sir Richard Doll, who did so much to advance the world’s understanding of asbestosis as a cause of lung cancer, issued a caveat about the limits of specific causation inference. Richard Doll, “Proof of Causality: Deduction from Epidemiological Observation,” 45 Perspectives in Biology & Medicine 499, 500 (2002) (“That asbestos is a cause of lung cancer in this practical sense is incontrovertible, but we can never say that asbestos was responsible for the production of the disease in a particular patient, as there are many other etiologically significant agents to which the individual may have been exposed, and we can speak only of the extent to which the risk of the disease was increased by the extent of his or her exposure.”)

Similarly, Kenneth Rothman, a leading voice among epidemiologists, cautioned against conflating epidemiologic inferences about groups with inferences about causes in individuals. Kenneth Rothman, Epidemiology: An Introduction 44 (Oxford 2002) (“An elementary but essential principal that epidemiologists must keep in mind is that a person may be exposed to an agent and then develop disease without there being any causal connection between exposure and disease.”  … “In a courtroom, experts are asked to opine whether the disease of a given patient has been caused by a specific exposure.  This approach of assigning causation in a single person is radically different from the epidemiologic approach, which does not attempt to attribute causation in any individual instance.  Rather, the epidemiologic approach is to evaluate the proposition that the exposure is a cause of the disease in a theoretical sense, rather than in a specific person.”) (emphasis added).

The late David Freedman, who was the co-author of the chapters on statistics in all three editions of the Reference Manual on Scientific Evidence, was also a naysayer when it came to transmuting risk into cause:

“The scientific connection between specific causation and a relative risk of two is doubtful. *** Epidemiologic data cannot determine the probability of causation in any meaningful way because of individual differences.”

David Freedman & Philip Stark, “The Swine Flu Vaccine and Guillaine-Barré Syndrome:  A Case Study in Relative Risk and Specific Causation,” 64 Law & Contemporary Problems 49, 61 (2001) (arguing that proof of causation in a specific case, even starting with a relative risk of four, was “unconvincing”; citing Manko v. United States, 636 F. Supp. 1419, 1437 (W.D. Mo. 1986) (noting relative risk of 3.89–3.92 for GBS from swine-flu vaccine), aff’d in part, 830 F.2d 831 (8th Cir. 1987)).

Graham Colditz, who testified for plaintiffs in the hormone therapy litigation, similarly has taught that an increased risk of disease cannot be translated into the “but-for” standard of causation.  Graham A. Colditz, “From epidemiology to cancer prevention: implications for the 21st Century,” 18 Cancer Causes Control 117, 118 (2007) (“Knowledge that a factor is associated with increased risk of disease does not translate into the premise that a case of disease will be prevented if a specific individual eliminates exposure to that risk factor. Disease pathogenesis at the individual level is extremely complex.”)

Another epidemiologist, who wrote the chapter in the Federal Judicial Center’s Reference Manual on Scientific Evidence, on epidemiology, put the matter thus:

“However, the use of data from epidemiologic studies is not without its problems. Epidemiology answers questions about groups, whereas the court often requires information about individuals.

Leon Gordis, Epidemiology 362 (5th ed. 2014) (emphasis in original).

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In New Jersey, an expert witness’s opinion that lacks a factual foundation is termed a “net opinion.” Polzo v. County of Essex, 196 N.J. 569, 583 (2008) (explaining New Jersey law’s prohibition against “net opinions” and “speculative testimony”). Under federal law, Rule 702, such an opinion is simply called inadmissible.

Here is an interesting example of a “net opinion” from an expert witness, in the field of epidemiology, who has testified in many judicial proceedings:

 

                                                                                          November 12, 2008

George T. Brugess, Esq.
Hoey & Farina, Attorneys at Law
542 South Dearborn Street, Suite 200
Chicago, IL 60605

Ref: Oscar Brooks v. Ingram Barge and Jantran Inc.

* * * *

Because [the claimant] was employed 28 years, he falls into the greater than 20 years railroad employment category (see Table 3 of Garshick’s 2004 paper) which shows a significant risk for lung cancer that ranges from 1.24 to 1.50. This means that his diesel exposure was a significant factor in his contracting lung cancer. His extensive smoking was also a factor in his lung cancer, and diesel exposure combined with smoking is an explanation for the relatively early age, 61 years old, of his diagnosis.

Now assuming that diesel exposure truly causes lung cancer, what was the basis for this witness (David F. Goldsmith, PhD) to opine that diesel exposure was a “significant factor” in the claimant’s developing lung cancer?  None really.  There was no basis in the report, or in the scientific data, to transmute an exposure that yielded a risk ratio of 1.24 to 1.50 for lung cancer, in a similarly exposed population to diesel emissions, into a “significant factor.” The claimant’s cancer may have arisen from background, baseline risk.  The cancer may have arisen from the risk due to smoking, which would have been on the order of a 2,000% increase, or so.  The cancer may have arisen from the claimed carcinogenicity of diesel emissions, on the order of 25 to 50%, which was rather insubstantial compared with his smoking risk.  Potentially, the cancer arose from a combination of the risk from both diesel emissions and tobacco smoking. In the population of men who looked like Mr. Oscar Brooks, by far, the biggest reduction in incidence would be achieved by removing tobacco smoking.

There were no biomarkers that identified the claimant’s lung cancer as having been caused by diesel emissions.  The expert witness’s opinion was nothing more than an ipse dixit that equated a risk, and a rather small risk, with specific causation.  Notice how a 24% increased risk from diesel emissions was a “significant factor,” but the claimant’s smoking history was merely “a factor.”

Goldsmith’s report on specific causation was a net opinion that exemplifies what is wrong with a legal system that encourages and condones baseless expert witness testimony. In Agent Orange, Judge Weinstein pointed out that the traditional judicial antipathy to probabilism would mean no recovery in many chemical and medicinal exposure cases.  If the courts lowered their scruples to permit recovery on a naked statistical inference of greater than 50%, from relative risks greater than two, some cases might remain viable (but alas not the Agent Orange case itself). Judge Weinstein was, no doubt, put off by the ability of defendants, such as tobacco companies, to avoid liability because plaintiffs would never have more than evidence of risk.  In the face of relative risks often in excess of 30, with attributable risks in excess of 95%, this outcome was disturbing.

Judge Weinstein’s compromise was a pragmatic solution to the problem of adjudicating specific causation on the basis of risk evidence. Although as noted above, many scientists rejected any use of risk to support specific causation inferences, some scientists agreed with this practical solution.  Ironically, David Goldsmith, the author of the report in the Oscar Brooks case, supra, was one such writer who had embraced the relative risk cut off:

“A relative risk greater than 2.0 produces an attributable risk (sometimes called attributable risk percent10) or an attributable fraction that exceeds 50%.  An attributable risk greater than 50% also means that ‘it is more likely than not’, or, in other words, there is a greater than 50% probability that the exposure to the risk factor is associated with disease.”

David F. Goldsmith & Susan G. Rose, “Establishing Causation with Epidemiology,” in Tee L. Guidotti & Susan G. Rose, eds., Science on the Witness Stand:  Evaluating Scientific Evidence in Law, Adjudication, and Policy 57, 60 (OEM Press 2001).

In the Brooks case, Goldsmith did not have an increased risk even close to 2.0. The litigation industry ultimately would not accept anything other than full compensation for attributable risks greater than 0%.


[1] See, e.g., Sander Greenland, “Relation of the Probability of Causation to Relative Risk and Doubling Dose:  A Methodologic Error that Has Become a Social Problem,” 89 Am. J. Pub. Health 1166, 1168 (1999)(“[a]ll epidemiologic measures (such as rate ratios and rate fractions) reflect only the net impact of exposure on a population”); Joseph V. Rodricks & Susan H. Rieth, “Toxicological Risk Assessment in the Courtroom:  Are Available Methodologies Suitable for Evaluating Toxic Tort and Product Liability Claims?” 27 Regulatory Toxicol. & Pharmacol. 21, 24-25 (1998)(noting that a population risk applies to individuals only if all persons within the population are the same with respect to the influence of the risk on outcome); G. Friedman, Primer of Epidemiology 2 (2d ed. 1980)(epidemiologic studies address causes of disease in populations, not causation in individuals)

 

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