After the dubious decision in Milward, the First Circuit would seem an unlikely forum for perscrutations of expert witness opinion testimony. Milward v. Acuity Specialty Products Group, Inc., 639 F.3d 11 (1st Cir. 2011), cert. denied, ___ U.S.___ (2012). See “Milward — Unhinging the Courthouse Door to Dubious Scientific Evidence” (Sept. 2, 2011). Late last month, however, a First Circuit panel of the United States Court of Appeals held that Rule 702 required perscrutation of expert witness opinion, and then proceeded to perscrutate perspicaciously, in Samaan v. St. Joseph Hospital, 2012 WL 34262 (1st Cir. 2012).
The plaintiff, Mr. Samaan suffered an ischemic stroke, for which he was treated by the defendant hospital and physician. Plaintiff claimed that the defendants’ treatment deviated from the standard of care by failing to administer intravenous tissue plasminogen activator (t-PA). Id. at *1. The plaintiff’s only causation expert witness, Dr. Ravi Tikoo, opined that the defendants’ failure to administer t-PA caused plaintiffs’ neurological injury. Id. at *2. Dr. Tikoo’s opinions, as well as those of the defense expert witness, were based in large part upon data from a study done by one of the National Institutes of Health: The National Institute of Neurological Disorders and Stroke rt-PA Stroke Study Group, “Tissue Plasminogen Activator for Acute Ischemic Stroke,” 333 New Engl. J. Med. 1581 (1995).
Both the District Court and the Court of Appeals noted that the problem with Dr. Tikoo’s opinions lay not in the unreliability of the data, or in the generally accepted view that t-PA can, under certain circumstances, mitigate the sequelae of ischemic stroke; rather the problem lay in the analytical gap between those data and Dr. Tikoo’s conclusion that the failure to administer t-PA caused Mr. Samaan’s stroke-related injuries.
The district court held that Dr. Tikoo’s opinion failed to satisfy the requirements of Rule 702. Id. at *8 – *9. Dr. Tikoo examined odds ratios from the NINDS study, and others, and concluded that a patient’s chances of improved outcome after stroke increased 50% with t-PA, and thus Mr. Samaan’s healthcare providers’ failure to provide t-PA had caused his poor post-stroke outcome. Id. at *9. The appellate court similarly rejected the inference from an increased odds ratio to specific causation:
“Dr. Tikoo’s first analysis depended upon odds ratios drawn from the literature. These odds ratios are, as the term implies, ratios of the odds of an adverse outcome, which reflect the relative likelihood of a particular result.FN5 * * * Dr. Tikoo opined that the plaintiff more likely than not would have recovered had he received the drug.”
Id. at *10.
The Court correctly identified the expert witness’s mistake in inferring specific causation from an odds ratio of about 1.5, without any additional information. The Court characterized the testimonial flaw as one of “lack of fit,” but it was equally an unreliable inference from epidemiologic data to a conclusion about specific causation.
While the Court should be applauded for rejecting the incorrect inference about specific causation, we might wish that it had been more careful about important details. The Court misinterpreted the meaning of an odds ratio to be a relative risk. The NINDS study reported risk ratio results both as an odds ratio and as a relative risk. The Court’s sloppiness should be avoided; the two statistics are different, especially when the outcome of interest is not particularly rare.
Still, the odds ratio is interesting and important as an approximation for the relative risk, and neither measure of risk can substitute for causation, especially when the magnitude of the risk is small, and less than two-fold. The First Circuit recognized and focused in on this gap between risk and causal attribution in an individual’s case:
“[Dr. Tikoo’s] reasoning is structurally unsound and leaves a wide analytical gap between the results produced through the use of odds ratios and the conclusions drawn by the witness. When a person’s chances of a better outcome are 50% greater with treatment (relative to the chances of those who were not treated), that is not the same as a person having a greater than 50% chance of experiencing the better outcome with treatment. The latter meets the required standard for causation; the former does not. To illustrate, suppose that studies have shown that 10 out of a group of 100 people who do not eat bananas will die of cancer, as compared to 15 out of a group of 100 who do eat bananas. The banana-eating group would have an odds ratio of 1.5 or a 50% greater chance of getting cancer than those who eschew bananas. But this is a far cry from showing that a person who eats bananas is more likely than not to get cancer.
Even if we were to look only at the fifteen persons in the banana-eating group who did get cancer, it would not be likely that any particular person in that cohort got it from the consumption of bananas. Correlation is not causation, and a substantial number of persons with cancer within the banana-eating group would in all probability have contracted the disease whether or not they ate bananas.FN6
We think that this example exposes the analytical gap between Dr. Tikoo’s methods and his conclusions. Although he could present figures ranging higher than 50%, those figures were not responsive to the question of causation. Let us take the “stroke scale” figure from the NINDS study as an example. This scale measures the neurological deficits in different parts of the nervous system. Twenty percent of patients who experienced a stroke and were not treated with t-PA had a favorable outcome according to this scale, whereas that figure escalated to 31% when t-PA was administered.
Although this means that the patients treated with t-PA had over a 50% better chance of recovery than they otherwise would have had, 69% of those patients experienced the adverse outcome (stroke-related injury) anyway.FN7 The short of it is that while the odds ratio analysis shows that a t-PA patient may have a better chance of recovering than he otherwise would have had without t-PA, such an analysis does not show that a person has a better than even chance of avoiding injury if the drug is administered. The odds ratio, therefore, does not show that the failure to give t-PA was more likely than not a substantial factor in causing the plaintiff’s injuries. The unavoidable conclusion from the studies deemed authoritative by Dr. Tikoo is that only a small number of patients overall (and only a small fraction of those who would otherwise have experienced stroke-related injuries) experience improvement when t-PA is administered.”
*11 and n.6 (citing Milward).
The court in Samaan thus suggested, but did not state explicitly, that the study would have to have shown better than a 100% increase in the rate of recovery for attributability to have exceeded 50%. The Court’s timidity is regrettable. Yes, Dr. Tikoo’s confusing the percentage increased risk with the percentage of attributability was quite knuckleheaded. I doubt that many would want to subject themselves to Dr. Tikoo’s quality of care, at least not his statistical care. The First Circuit, however, stopped short of stating what magnitude increase in risk would permit an inference of specifc causation for Mr. Samaan’s post-stroke sequelae.
The Circuit noted that expert witnesses may present epidemiologic statistics in a variety of forms:
“to indicate causation. Either absolute or relative calculations may suffice in particular circumstances to achieve the causation standard. See, e.g., Smith v. Bubak, 643 F.3d 1137, 1141–42 (8th Cir.2011) (rejecting relative benefit testimony and suggesting in dictum that absolute benefit “is the measure of a drug’s overall effectiveness”); Young v. Mem’l Hermann Hosp. Sys., 573 F.3d 233, 236 (5th Cir.2009) (holding that Texas law requires a doubling of the relative risk of an adverse outcome to prove causation), cert. denied, ___ U.S. ___, 130 S.Ct. 1512, 176 L.Ed.2d 111 (2010).”
Id. at *11.
Although the citation to Texas law with its requirement of a doubling of a relative risk is welcome and encouraging, the Court seems to have gone out of its way to muddle its holding. First, the Young case involved t-PA and a claimed deviation from the standard of care in a stroke case, and was exactly on point. The Fifth Circuit’s reliance upon Texas substantive law left unclear to what extent the same holding would have been required by Federal Rule of Evidence 702.
Second, the First Circuit, with its banana hypothetical, appeared to confuse an odds ratio with a relative risk. The odds ratio is different from a relative risk, and typically an odds ratio will be higher than the corresponding relative risk, unless the outcome is rare. See Michael O. Finkelstein & Bruce Levin, Statistics for Lawyers at 37 (2d ed. 2001). In studies of medication efficacy, however, the benefit will not be particularly rare, and the rare disease assumption cannot be made.
Third, risk is not causation, regardless of magnitude. If the magnitude of risk is used to infer specific causation, then what is the basis for the inference, and how large must the risk be? In what way can epidemiologic statistics be used “to indicate” specific causation? The opinion tells us that Dr. Tivoo’s reliance upon an odds ratio of 1.5 was unhelpful, but why? The Court, which spoke so clearly and well in identifying the fallacious reasoning of Dr. Tivoo, faltered in identifying what use of risk statistics would permit an inference of specific causation in this case, where general causation was never in doubt.
The Fifth Circuit’s decision in Young, supra, invoked a greater than doubling of risk required by Texas law. This requirement is nothing more than a logical, common-sense recognition that risk is not causation, and that small risks alone cannot support an inference of specific causation. Requiring a relative risk greater than two makes practical sense despite the apoplectic objections of Professor Sander Greenland. See “Relative Risks and Individual Causal Attribution Using Risk Size” (Mar. 18, 2011).
Importantly, the First Circuit panel in Samaan did not engage in the hand-waving arguments that were advanced in Milward, and stuck to clear, transparent rational inferences. In footnote 6, the Samaan Court cited its earlier decision in Milward, but only with double negatives, and for the relevancy of odds ratios to the question of general causation:
“This is not to say that the odds ratio may not help to prove causation in some instances. See, e.g., Milward v. Acuity Specialty Prods. Group, Inc., 639 F.3d 11, 13–14, 23–25 (1st Cir.2011) (reversing exclusion of expert prepared to testify as to general rather than specific causation using in part the odds ratio).”
Id. at n.6.
The Samaan Court went on to suggest that inferring specific causation from the magnitude of risk was “theoretically possible”:
“Indeed, it is theoretically possible that a particular odds ratio calculation might show a better-than-even chance of a particular outcome. Here, however, the odds ratios relied on by Dr. Tikoo have no such probative force.“
Id. (emphasis added). But why and how? The implication of the Court’s dictum is that when the risk ratio is small, less than or equal to two, the ratio cannot be taken to have supported the showing of “better than even chance.” In Milward, one of the key studies relied upon by plaintiff’s expert witness reported an increased risk of only 40%. Although Milward presented primarily a challenge on general causation, the Samaan decision suggests that the low-dose benzene exposure plaintiffs are doomed, not by benzene, but by the perscrutation required by Rule 702.
