Lack of Statistically Significant Data May Not Prevent an Inference of Causation
Matrixx Initiatives is a typical securities fraud case. Matrixx Initiatives, Inc., sells over-the-counter pharmaceutical products, including Zicam Cold Remedy. The plaintiffs in the case were purchasers of Matrixx securities who alleged that certain statements made by Matrixx executives relating to the company's finances and Zicam's safety were misleading.
Specifically, the plaintiffs claimed that Matrixx made positive statements regarding the company's financial prospects while failing to disclose complaints that customers lost their sense of smell after using Zicam. For example, Matrixx executives publicly stated that Zicam was "poised for growth in the upcoming cough and cold season" and that the company had "very strong momentum." However, at the time Matrixx made these and other statements, it was aware of reported adverse side events as well as two lawsuits involving alleged loss of the sense of smell. Furthermore, it had been provided with a study potentially linking Zicam to loss of smell in certain users. The plaintiffs alleged that the executives' statements were misleading and caused Matrixx's stock value to increase temporarily then drop significantly when the reports linking Zicam use to the loss of smell as well as the product liability lawsuits were reported to the public.
Matrixx moved to dismiss the complaint, arguing among other things that the plaintiffs failed to plead that Matrixx made a material misrepresentation or omission. Regarding the adverse events related to loss of smell after using Zicam, Matrixx argued that because the plaintiffs had not alleged a statistically significant correlation between the use of Zicam and loss of smell, the plaintiffs failed to plead the element of material misrepresentation or omission. Matrixx argued that unless the plaintiffs alleged causation based on statistically significant evidence linking Zicam to loss of smell, the plaintiffs did not allege facts that investors would deem material.
The U.S. District Court agreed and dismissed the suit, explaining that the plaintiffs had not alleged a "statistically significant correlation between the use of Zicam and [loss of smell] so as to make failure to publicly disclose complaints and the University of Colorado study a material omission." Matrixx Initiatives, 131 S. Ct. at 1314. The Ninth Circuit Court of Appeals reversed the decision, holding that the district court erred "in requiring an allegation of statistical significance to establish materiality" and finding that the complaint adequately alleged that "information regarding the possible link between Zicam and [loss of smell] would have been significant to a reasonable investor." Id. at 1315.
The district court agreed and dismissed the suit, explaining that the plaintiffs had not alleged a "statistically significant correlation between the use of Zicam and [loss of smell] so as to make failure to publicly disclose complaints and the University of Colorado study a material omission." Matrixx Initiatives, 131 S. Ct. at 1314. The Ninth Circuit Court of Appeals reversed, holding that the district court erred "in requiring an allegation of statistical significance to establish materiality" and finding that the complaint adequately alleged that "information regarding the possible link between Zicam and [loss of smell] would have been significant to a reasonable investor." Id. at 1315.
On appeal from the Ninth Circuit, the U.S. Supreme Court granted certiorari to answer the question of whether a party can state a claim for securities fraud "based on a pharmaceutical company's failure to disclose reports of adverse events associated with a product if the reports do not disclose a statistically significant number of adverse events." The Supreme Court affirmed the Ninth Circuit's reversal and held that "materiality of adverse event reports cannot be reduced to a bright-line rule" that would require plaintiffs to allege a statistically significant number of adverse event reports to maintain an action for securities fraud against a pharmaceutical manufacturer.
In its analysis, the U.S. Supreme Court discussed the role of statistical significance in assessing causation in products liability lawsuits. The Court found that Matrixx's position incorrectly presumed "that statistical significance is the only reliable indication of causation," and the Court further explained that "[a] lack of statistically significant data does not mean that medical experts have no reliable basis for inferring a causal link between a drug and adverse events." Id. at 1319.
In support of this holding, the Court cited three circuit court opinions and explained that "courts frequently permit expert testimony on causation based on evidence other than statistical significance." Id. (citing Best v. Lowe's Home Ctrs., Inc., 563 F.3d 171, 178 (6th Cir. 2009); Westberry v. Gislaved Gummi AB, 178 F.3d 257, 263–64 (4th Cir. 1999); Wells v. Ortho Pharm. Corp., 788 F.2d 741, 744–45 (11th Cir. 1986)). Relying on these products liability cases where expert testimony was not excluded despite a lack of statistically significant evidence, the Supreme Court explained that "[i]t suffices to note that, as these courts have recognized 'medical professionals and researchers do not limit the data they consider to the results of randomized clinical trials or to statistically significant evidence.'" Id. at 1319–20 (citing Brief for Medical Researchers as Amici Curiae at 31, Matrixx Initiatives, 131 S. Ct. 1309 (No. 09-1156)).
Accordingly, the Supreme Court held that "[g]iven that medical professionals and regulators act on the basis of evidence of causation that is not statistically significant, it stands to reason that in certain cases reasonable investors would as well," id. at 1320, and, therefore, that plaintiffs had adequately pleaded the element of material misrepresentation or omission.
Matrixx Didn't Kill Daubert—Statistically Significant Data Still Matter
Litigants relying on non-statistically significant data in future pharmaceutical cases undoubtedly will rely on Matrixx to support arguments for greater admissibility of expert opinions that are based on non-statistically significant data. The better view, however, is that because the Court simply applied the rules that already govern the treatment of such evidence, Matrixx should not change the evaluation in future pharmaceutical cases. While the Supreme Court explained that courts permit expert testimony on causation based on evidence other than statistical significance, the cases cited by the Supreme Court for this proposition show that causation evidence and expert causation testimony are still controlled by the framework established in Daubert v. Merrill Dow Pharmaceuticals, Inc., 509 U.S. 579 (1993), and by Federal Rule of Evidence 702. Accordingly, when evaluating causation evidence, the proper question is not whether the expert opinion or scientific data relied on in proving causation is statistically significant, but whether the expert opinion is scientifically relevant and reliable.
Rule 702 of the Federal Rules of Evidence controls the admissibility of expert testimony and provides as follows:
If scientific, technical, or other specialized knowledge will assist the trier of fact to understand the evidence or to determine a fact in issue, a witness qualified as an expert by knowledge, skill, experience, training, or education, may testify thereto in the form of an opinion or otherwise, if (1) the testimony is based upon sufficient facts or data, (2) the testimony is the product of reliable principles and methods, and (3) the witness has applied the principles and methods reliably to the facts of the case.
Fed. R. Evid. 702 (emphasis added).
Daubert and Rule 702 "attempt to strike a balance between a liberal admissibility standard for relevant evidence on the one hand and the need to exclude 'junk science' on the other." Best, 563 F.3d at 176–77. As Matrixx confirmed, scientific evidence regarding causation does not necessarily fall into the "junk science" category simply because it is not premised on statistically significant data or epidemiological studies.
The cases cited by the Supreme Court illustrate situations in which expert testimony might be considered reliable even if it is not based on statistically significant data.
For example, in Westberry, the defendant argued that the district court improperly permitted expert opinion testimony relating to causation because the doctor's testimony was based on his differential diagnosis and not on epidemiological studies, peer-reviewed published studies, animal studies, or laboratory data. Because the plaintiff's expert relied only on a differential diagnosis, the defendant argued that the expert failed to provide a reliable scientific methodology to support his conclusion that the plaintiff's inhalation of the defendant's talcum powder lubricant caused the plaintiff's sinus disease. In affirming the judgment, the Fourth Circuit held that the expert's differential diagnosis and the temporal relationship between exposure to the lubricant and the plaintiff's onset and worsening symptoms provided a sufficient basis for the opinion. The Fourth Circuit explained that "the overwhelming majority of the courts of appeals … have held that a medical opinion on causation based upon a reliable differential diagnosis is sufficiently valid" to satisfy Rule 702's reliability requirement.
Similarly, in Best the plaintiff alleged that he lost his sense of smell after a pool cleaning liquid splashed on his face in the defendant's store. The district court granted summary judgment in favor of the defendant, finding that the plaintiff's expert, whose causation testimony was premised solely on his differential diagnosis, provided only "unscientific speculation." The Sixth Circuit reversed, holding that while "not every opinion that is reached via a differential-diagnosis method will meet the standard of reliability required by Daubert," under these circumstances, the opinion was sufficiently reliable. See also Wells v. Ortho Pharm. Corp., 788 F.2d 741, 744–45 (11th Cir. 1986) (holding that a district court's finding of causation was not erroneous when the district court permitted expert causation testimony based on the experts' experience and personal examinations, after it concluded that the epidemiological studies presented by both parties were inconclusive).
As these cases demonstrate, there are situations in which statistically significant data may not be available or even ethically obtainable to prove causation. "For example, when an adverse event is subtle or rare, an inability to obtain a data set of appropriate quality or quantity may preclude a finding of statistical significance" and "ethical considerations may prohibit researchers from conducting randomized clinical trials to confirm a suspected causal link for the purpose of obtaining statistically significant data." Matrixx, 131 S. Ct. at 1319.
The fact that there are situations in which courts may not require statistically significant data to prove causation, including the securities context as in the Matrixx case, does not mean that statistically significant data are not vitally important in many causation inquiries. In fact, in citing Best, Westberry, and Wells, the Court carefully limited the extent of its Matrixx holding. The Court was quick to point out that it was not considering whether the expert testimony had been properly admitted in those cases; nor was it attempting to define what constitutes reliable evidence of causation. Rather, the Court was simply recognizing that "medical professionals and researchers do not limit the data they consider to the results of randomized clinical trials or to statistically significant evidence."
The Matrixx Holding Is Much Narrower Than Plaintiffs May Argue
In Matrixx, the Supreme Court identified certain cases that permit expert causation testimony even where it is not premised on statistically significant data. However, the Court's holding does not, and was not intended to, broadly undermine the numerous cases in which the lack of statistically significant evidence is fatal to (or at least weighs heavily against) the admissibility of an expert's causation opinion.
Those cases include Wells v. SmithKline Beecham Corp., 601 F.3d 375, 380 (5th Cir. 2010), in which the Fifth Circuit affirmed the district court's exclusion of expert testimony and held that the circuit "has frowned on causative conclusions bereft of statistically significant epidemiological support." The Tenth Circuit also held in Norris v. Baxter Healthcare Corp., 397 F.3d 878, 887 (10th Cir. 2005), that "we cannot allow the jury to speculate based on an expert's opinion which relies only on clinical experience in the absence of showing a consistent, statistically significant association between breast implants and systemic disease." The U.S. District Court for the Western District of Pennsylvania has also held, in Soldo v. Sandoz Pharmaceuticals Corp., 244 F. Supp. 2d 434, 533–34 (W.D. Pa. 2003), that medical experts' causation opinions were unreliable because none of the epidemiologic studies relied on showed a statistically significant positive association between the drug and the disease at issue.
Conclusion
While the U.S. Supreme Court has acknowledged that in certain contexts reliable scientific methods for proving causation other than statistically significant epidemiological studies, the Supreme Court's holding in Matrixx does not fundamentally alter the framework for weeding out unreliable scientific causation evidence established under Daubert and Federal Rule of Evidence 702. The need for statistically significant evidence still depends upon a number of factors, and the Supreme Court's decision in Matrixx should not be viewed as altering the existing analysis of expert opinions in products liability cases. Matrixx is likely to have a greater impact in non-products liability cases.
Keywords: litigation, products liability, Matrixx, causation, adverse event, statistically significant