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Consensus Rule – Shadows of Validity

April 26th, 2023

Back in 2011, at a Fourth Circuit Judicial Conference, Chief Justice John Roberts took a cheap shot at law professors and law reviews when he intoned:

“Pick up a copy of any law review that you see, and the first article is likely to be, you know, the influence of Immanuel Kant on evidentiary approaches in 18th Century Bulgaria, or something, which I’m sure was of great interest to the academic that wrote it, but isn’t of much help to the bar.”[1]

Anti-intellectualism is in vogue these days. No doubt, Roberts was jocularly indulging in an over-generalization, but for anyone who tries to keep up with the law reviews, he has a small point. Other judges have rendered similar judgments. Back in 1993, in a cranky opinion piece – in a law review – then Judge Richard A. Posner channeled the liar paradox by criticizing law review articles for “the many silly titles, the many opaque passages, the antic proposals, the rude polemics, [and] the myriad pretentious citations.”[2] In a speech back in 2008, Justice Stephen Breyer noted that “[t]here is evidence that law review articles have left terra firma to soar into outer space.”[3]

The temptation to rationalize, and to advocate for reflective equilibrium between the law as it exists, and the law as we think it should be, combine to lead to some silly and harmful efforts to rewrite the law as we know it.  Jeremy Bentham, Mr. Nonsense-on-Stilts, who sits stuffed in the hallway of the University of London, ushered in a now venerable tradition of rejecting tradition and common sense, in proposing all sorts of law reforms.[4]  In the early 1800s, Jeremy Bentham, without much in the way of actual courtroom experience, deviled the English bench and bar with sweeping proposals to place evidence law on what he thought was a rational foundation. As with his naïve utilitarianism, Bentham’s contributions to jurisprudence often ignored the realities of human experience and decision making. The Benthamite tradition of anti-tradition is certainly alive and well in the law reviews.

Still, I have a soft place in my heart for law reviews.  Although not peer reviewed, law reviews provide law students a tremendous opportunity to learn about writing and scholarship through publishing the work of legal scholars, judges, thoughtful lawyers, and other students. Not all law review articles are non-sense on stilts, but we certainly should have our wits about us when we read immodest proposals from the law professoriate.

*   *   *   *   *   *   *   *   *   *

Professor Edward Cheng has written broadly and insightfully about evidence law, and he certainly has the educational training to do so. Recently, Cheng has been bemused by the expert paradox, which wonders how lay persons, without expertise, can evaluate and judge issues of the admissibility, validity, and correctness of expert opinion. The paradox has long haunted evidence law, and it is at center stage in the adjudication of expert admissibility issues, as well as the trial of technical cases. Recently, Cheng has proposed a radical overhaul to the law of evidence, which would require that we stop asking courts to act as gatekeepers, and to stop asking juries to determine the validity and correctness of expert witness opinions before them. Cheng’s proposal would revert to the nose counting process of Frye and permit consideration of only whether there is an expert witness consensus to support the proffered opinion for any claim or defense.[5] Or in Plato’s allegory of the cave, we need to learn to be content with shadows on the wall rather than striving to know the real thing.

When Cheng’s proposal first surfaced, I wrote briefly about why it was a bad idea.[6] Since his initial publication, a law review symposium was assembled to address and perhaps to celebrate the proposal.[7] The papers from that symposium are now in print.[8] Unsurprisingly, the papers are both largely sympathetic (but not completely) to Cheng’s proposal, and virtually devoid of references to actual experiences of gatekeeping or trials of technical issues.

Cheng contends that the so-called Daubert framework for addressing the admissibility of expert witness opinion is wrong.  He does not argue that the existing law, in the form of Federal Rules of Evidence 702 and 703, does not call for an epistemic standard for both admitting opinion testimony, as well for the fact-finders’ assessments. There is no effort to claim that somehow four Supreme Court cases, and thousand of lower courts, have erroneously viewed the whole process. Rather, Cheng simply asserts non-expert judges cannot evaluate the reliability (validity) of expert witness opinions, and that non-expert jurors cannot “reach independent, substantive conclusions about specialized facts.”[9] The law must change to accommodate his judgment.

In his symposium contribution, Cheng expands upon his previous articulation of his proposed “consensus rule.”[10] What is conspicuously absent, however, is any example of failed gatekeeping that excluded valid expert witness opinion. One example, the appellate decision in Rosen v. Ciba-Geigy Corporation,[11] which Cheng does give, is illustrative of Cheng’s project. The expert witness, whose opinion was excluded, was on the faculty of the University of Chicago medical school; Richard Posner, the appellate judge who wrote the opinion that affirmed the expert witness’s exclusion, was on the faculty of that university’s law school. Without any discussion of the reports, depositions, hearings, or briefs, Cheng concludes that “the very idea that a law professor would tell medical school colleagues that their assessments were unreliable seems both breathtakingly arrogant and utterly ridiculous.”[12]

Except, of course, very well qualified scientists and physicians advance invalid and incorrect claims all the time. What strikes me as breathtakingly arrogant and utterly ridiculous is the judgment of a law professor who has little to no experience trying or defending Rule 702 and 703 issues labeling the “very idea” as arrogant and ridiculous. Aside from its being a petitio principia, we could probably add that the reaction is emotive, uninformed, and uninformative, and that it fails to support the author’s suggestion that “Daubert has it all wrong,” and that “[w]e need a different approach.”

Judges and jurors obviously will never fully understand the scientific issues before them.  If and when this lack of epistemic competence is problematic, we should honestly acknowledge how we are beyond the realm of the Constitution’s seventh amendment. Since Cheng is fantasizing about what the law should be, why not fantasize about not allowing lay people to decide complex scientific issues? Verdicts from jurors who do not have to give reasons for their decisions, and who are not in any sense peers of the scientists whose work they judge are normatively problematic.

Professor Cheng likens his consensus rule to how the standard of care is decided in medical malpractice litigation. The analogy is interesting, but hardly compelling in that it ignores “two schools of thought” doctrine.[13] In litigation of claims of professional malpractice, the “two schools of thought doctrine” is a complete defense.  As explained by the Pennsylvania Supreme Court,[14] physicians may defend against claims that they deviated from the standard of care, or of professional malpractice, by adverting to support for their treatment by a minority of professionals in their field:

“Where competent medical authority is divided, a physician will not be held responsible if in the exercise of his judgment he followed a course of treatment advocated by a considerable number of recognized and respected professionals in his given area of expertise.”[15]

The analogy to medical malpractice litigation seems inapt.

Professor Cheng advertises that he will be giving full-length book treatment to his proposal, and so perhaps my critique is uncharitable in looking at a preliminary, (antic?) law review article. Still, his proposal seems to ignore that “general acceptance” renders consensus, when it truly exists, as relevant to both the court’s gatekeeping decisions, and the fact finders’ determination of the facts and issues in dispute. Indeed, I have never seen a Rule 702 hearing that did not involve, to some extent, the assertion of a consensus, or the lack thereof.

To the extent that we remain committed to trials of scientific claims, we can see that judges and jurors often can detect inconsistencies, cherry picking, unproven assumptions, and other aspects of the patho-epistemology of exert witness opinions. It takes a community of scientists and engineers to build a space rocket, but any Twitter moron can determine when a rocket blows up on launch. Judges in particular have (and certainly should have) the competence to determine deviations from the scientific and statistical standards of care that pertain to litigants’ claims.

Cheng’s proposal also ignores how difficult and contentious it is to ascertain the existence, scope, and actual content of scientific consensus. In some areas of science, such as occupational and environmental epidemiology and medicine, faux consensuses are set up by would-be expert witnesses for both claimants and defendants. A search of the word “consensus” in the PubMed database yields over a quarter of a million hits. The race to the bottom is on. Replacing epistemic validity with sociological and survey navel gazing seems like a fool’s errand.

Perhaps the most disturbing aspect of Cheng’s proposal is what happens in the absence of consensus.  Pretty much anything goes, a situation that Cheng finds “interesting,” and I find horrifying:

“if there is no consensus, the legal system’s options become a bit more interesting. If there is actual dissensus, meaning that the community is fractured in substantial numbers, then the non-expert can arguably choose from among the available theories. If the expert community cannot agree, then one cannot possibly expect non-experts to do any better.”[16]

Cheng reports that textbooks and other documents “may be both more accurate and more efficient” evidence of consensus.[17] Maybe; maybe not.  Textbooks are typically often dated by the time they arrive on the shelves, and contentious scientists are not beyond manufacturing certainty or doubt in the form of falsely claimed consensus.

Of course, often, if not most of the time, there will be no identifiable, legitimate consensus for a litigant’s claim at trial. What would Professor Cheng do in this default situation? Here Cheng, fully indulging the frolic, tells us that we

“should hypothetically ask what the expert community is likely to conclude, rather than try to reach conclusions on their own.”[18]

So the default situation transforms jurors into tea-leaf readers of what an expert community, unknown to them, will do if and when there is evidence of a quantum and quality to support a consensus, or when that community gets around to articulating what the consensus is. Why not just toss claims that lack consensus support?

[1] Debra Cassens Weiss, “Law Prof Responds After Chief Justice Roberts Disses Legal Scholarship,” Am. Bar Ass’n J. (July 7, 2011).

[2] Richard A. Posner, “Legal Scholarship Today,” 45 Stanford L. Rev. 1647, 1655 (1993), quoted in Walter Olson, “Abolish the Law Reviews!” The Atlantic (July 5, 2012); see also Richard A. Posner, “Against the Law Reviews: Welcome to a world where inexperienced editors make articles about the wrong topics worse,”
Legal Affairs (Nov. 2004).

[3] Brent Newton, “Scholar’s highlight: Law review articles in the eyes of the Justices,” SCOTUS Blog (April 30, 2012); “Fixing Law Reviews,” Inside Higher Education (Nov. 19, 2012).

[4] “More Antic Proposals for Expert Witness Testimony – Including My Own Antic Proposals” (Dec. 30, 2014).

[5] Edward K. Cheng, “The Consensus Rule: A New Approach to Scientific Evidence,” 75 Vanderbilt L. Rev. 407 (2022).

[6] “Cheng’s Proposed Consensus Rule for Expert Witnesses” (Sept. 15, 2022);
“Further Thoughts on Cheng’s Consensus Rule” (Oct. 3, 2022).

[7] Norman J. Shachoy Symposium, The Consensus Rule: A New Approach to the Admissibility of Scientific Evidence (2022), 67 Villanova L. Rev. (2022).

[8] David S. Caudill, “The ‘Crisis of Expertise’ Reaches the Courtroom: An Introduction to the Symposium on, and a Response to, Edward Cheng’s Consensus Rule,” 67 Villanova L. Rev. 837 (2022); Harry Collins, “The Owls: Some Difficulties in Judging Scientific Consensus,” 67 Villanova L. Rev. 877 (2022); Robert Evans, “The Consensus Rule: Judges, Jurors, and Admissibility Hearings,” 67 Villanova L. Rev. 883 (2022); Martin Weinel, “The Adversity of Adversarialism: How the Consensus Rule Reproduces the Expert Paradox,” 67 Villanova L. Rev. 893 (2022); Wendy Wagner, “The Consensus Rule: Lessons from the Regulatory World,” 67 Villanova L. Rev. 907 (2022); Edward K. Cheng, Elodie O. Currier & Payton B. Hampton, “Embracing Deference,” 67 Villanova L. Rev. 855 (2022).

[9] Embracing Deference at 876.

[10] Edward K. Cheng, Elodie O. Currier & Payton B. Hampton, “Embracing Deference,” 67 Villanova L. Rev. 855 (2022) [Embracing Deference]

[11] Rosen v. Ciba-Geigy Corp., 78 F.3d 316 (7th Cir. 1996).

[12] Embracing Deference at 859.

[13] “Two Schools of Thought” (May 25, 2013).

[14] Jones v. Chidester, 531 Pa. 31, 40, 610 A.2d 964 (1992).

[15] Id. at 40.  See also Fallon v. Loree, 525 N.Y.S.2d 93, 93 (N.Y. App. Div. 1988) (“one of several acceptable techniques”); Dailey, “The Two Schools of Thought and Informed Consent Doctrine in Pennsylvania,” 98 Dickenson L. Rev. 713 (1994); Douglas Brown, “Panacea or Pandora’ Box:  The Two Schools of Medical Thought Doctrine after Jones v. Chidester,” 44 J. Urban & Contemp. Law 223 (1993).

[16] Embracing Deference at 861.

[17] Embracing Deference at 866.

[18] Embracing Deference at 876.

Posted in Evidence, Expert Witnesses, Frye, Rule 702, Rule 703, Scientific Evidence | 1 Comment »

Reference Manual – Desiderata for 4th Edition – Part VI – Rule 703

February 17th, 2023

One of the most remarkable, and objectionable, aspects of the third edition was its failure to engage with Federal Rule of Evidence of 703, and the need for courts to assess the validity of individual studies relied upon. The statistics chapter has a brief, but important discussion of Rule 703, as does the chapter on survey evidence. The epidemiology chapter mentions Rule 703 only in a footnote.[1]

Rule 703 appears to be the red-headed stepchild of the Federal Rules, and it is often ignored and omitted from so-called Daubert briefs.[2] Perhaps part of the problem is that Rule 703 (“Bases of an Expert”) is one of the mostly poorly drafted rules in the Federal Rules of Evidence:

“An expert may base an opinion on facts or data in the case that the expert has been made aware of or personally observed. If experts in the particular field would reasonably rely on those kinds of facts or data in forming an opinion on the subject, they need not be admissible for the opinion to be admitted. But if the facts or data would otherwise be inadmissible, the proponent of the opinion may disclose them to the jury only if their probative value in helping the jury evaluate the opinion substantially outweighs their prejudicial effect.”

Despite its tortuous wording, the rule is clear enough in authorizing expert witnesses to rely upon studies that are themselves inadmissible, and allowing such witnesses to disclose the studies that they have relied upon, when there has been the requisite showing of probative value that outweighs any prejudice.

The statistics chapter in the third edition, nonetheless, confusingly suggested that

“a particular study may use a method that is entirely appropriate but that is so poorly executed that it should be inadmissible under Federal Rules of Evidence 403 and 702. Or, the method may be inappropriate for the problem at hand and thus lack the ‘fit’ spoken of in Daubert. Or the study might rest on data of the type not reasonably relied on by statisticians or substantive experts and hence run afoul of Federal Rule of Evidence 703.”[3]

Particular studies, even when beautifully executed, are not admissible. And particular studies are not subject to evaluation under Rule 702, apart from the gatekeeping of expert witness opinion testimony that is based upon the particular studies. To be sure, the reference to Rule 703 is important and welcomed counter to the suggestion, elsewhere in the third edition, that courts should not look at individual studies. The independent review of individual studies is occasionally lost in the shuffle of litigation, and the statistics chapter is correct to note an evidentiary concern whether each individual study may or may not be reasonably relied upon by an expert witness. In any event, reasonably relied upon studies do not ipso facto become admissible.

The third edition’s chapter on Survey Research contains the most explicit direction on Rule 703, in terms of courts’ responsibilities.  In that chapter, the authors instruct that Rule 703:

“redirect[ed] attention to the ‘validity of the techniques employed’. The inquiry under Rule 703 focuses on whether facts or data are ‘of a type reasonably relied upon by experts in the particular field in forming opinions or inferences upon the subject’.”[4]

Although Rule 703 is clear enough on admissibility, the epidemiology chapter described epidemiologic studies broadly as admissible if sufficiently rigorous:

“An epidemiologic study that is sufficiently rigorous to justify a conclusion that it is scientifically valid should be admissible, as it tends to make an issue in dispute more or less likely.”[5]

The authors of the epidemiology chapter acknowledge, in a footnote, “that [h]earsay concerns may limit the independent admissibility of the study, but the study could be relied on by an expert in forming an opinion and may be admissible pursuant to Fed. R. Evid. 703 as part of the underlying facts or data relied on by the expert.”[6]

This footnote is curious, and incorrect. There is no question that hearsay “concerns” “may limit” admissibility of a study; hearsay is inadmissible unless there is a statutory exception.[7] Rule 703 is not one of the exceptions to the rule against hearsay in Article VIII of the Federal Rules of Evidence. An expert witness’s reliance upon a study does not make the study admissible. The authors cite two cases,[8] but neither case held that reasonable reliance by expert witnesses transmuted epidemiologic studies into admissible evidence. The text of Rule 703 itself, and the overwhelming weight of case law interpreting and applying the rule,[9]  makes clear that the rule does not render scientific studies admissible. The two cases cited by the epidemiology chapter, Kehm and Ellis, both involved “factual findings” in public investigative or evaluative reports, which were independently admissible under Federal Rule of Evidence 803(8)(C).[10] As such, the cases failed to support the chapter’s suggestion that Rule 703 is a rule of admissibility for epidemiologic studies. The third edition thus, in one sentence, confused Rule 703 with an exception to the rule against hearsay, which would prevent the statistically based epidemiologic studies from being received in evidence. The point was reasonably clear, however, that studies “may be offered” to explain an expert witness’s opinion. Under Rule 705, that offer may also be refused.

The Reference Manual was certainly not alone in advancing the notion that studies are themselves admissible. Other well-respected evidence scholars have misstated the law on this issue.[11] The fourth edition would do well to note that scientific studies, and especially epidemiologic studies, involve multiple levels of hearsay. A typical epidemiologic study may contain hearsay leaps from patient to clinician, to laboratory technicians, to specialists interpreting test results, back to the clinician for a diagnosis, to a nosologist for disease coding, to a national or hospital database, to a researcher querying the database, to a statistician analyzing the data, to a manuscript that details data, analyses, and results, to editors and peer reviewers, back to study authors, and on to publication. Those leaps do not mean that the final results are thus untrustworthy or not reasonably relied upon, but they do raise well-nigh insuperable barriers to admissibility. The inadmissibility of scientific studies is generally not problematic because Rule 703 permits testifying expert witnesses to formulate opinions based upon facts and data, which are not themselves admissible in evidence. The distinction between relied upon, and admissible, studies is codified in the Federal Rules of Evidence, and in virtually every state’s evidence law.

The fourth edition might well also note that under Rule 104(a), the Rules of Evidence themselves do not govern a trial court’s preliminary determination, under Rules 702 or 703, of the admissibility of an expert witness’s opinion, or the appropriateness of reliance upon a particular study. Although Rule 705 may allow disclosure of facts and data described in studies, it is not an invitation to permit testifying expert witnesses to become a conduit for off-hand comments and opinions in the introduction or discussion sections of relied upon articles.[12] The wholesale admission of such hearsay opinions undermines the court’s control over opinion evidence. Rule 703 authorizes reasonable reliance upon “facts and data,” not every opinion that creeps into the published literature.

Reference Manual’s Disregard of Study Validity in Favor of the “Whole Tsumish”

The third edition evidence considerable ambivalence in whether trial judges should engage in resolving disputes about the validity of individual studies relied upon by expert witnesses. Since 2000, Rule 702 clearly required such engagement, which made the Manual’s hesitancy, on the whole, unjustifiable.  The ambivalence with respect to study validity, however, was on full display in the late Professor Margaret Berger’s chapter, “The Admissibility of Expert Testimony.”[13] Berger’s chapter criticized “atomization,” or looking at individual studies in isolation, a process she described pejoratively as “slicing-and-dicing.”[14]

Drawing on the publications of Daubert-critic Susan Haack, Berger appeared to reject the notion that courts should examine the reliability of each study independently.[15] Berger described the “proper” scientific method, as evidenced by works of the International Agency for Research on Cancer (IARC), the Institute of Medicine, the National Institute of Health, the National Research Council, and the National Institute for Environmental Health Sciences, “is to consider all the relevant available scientific evidence, taken as a whole, to determine which conclusion or hypothesis regarding a causal claim is best supported by the body of evidence.”[16]

Berger’s description of the review process, however, was profoundly misleading in its incompleteness. Of course, scientists undertaking a systematic review identify all the relevant studies, but some of the “relevant” studies may well be insufficiently reliable (because of internal or external validity issues) to answer the research question at hand. All the cited agencies, and other research organizations and researchers, exclude studies that are fundamentally flawed, whether as a result of bias, confounding, erroneous data analyses, or related problems. Berger cited no support for her remarkable suggestion that scientists do not make “reliability” judgments about available studies when assessing the “totality of the evidence.”[17]

Professor Berger, who had a distinguished career as a law professor and evidence scholar, died in November 2010, before the third edition was published. She was no friend of Daubert,[18] but her antipathy remarkably outlived her. Berger’s critical discussion of “atomization” cited the notorious decision in Milward v. Acuity Specialty Products Group, Inc., 639 F.3d 11, 26 (1st Cir. 2011), which was decided four months after her passing.[19]

Professor Berger’s contention about the need to avoid assessments of individual studies in favor of the whole “tsumish” must also be rejected because Federal Rule of Evidence 703 requires that each study considered by an expert witness “qualify” for reasonable reliance by virtue of the study’s containing facts or data that are “of a type reasonably relied upon by experts in the particular field forming opinions or inferences upon the subject.” One of the deeply troubling aspects of the Milward decision is that it reversed the trial court’s sensible decision to exclude a toxicologist, Dr. Martyn Smith, who outran his headlights on issues having to do with a field in which he was clearly inexperienced – epidemiology.

Another curious omission in the third edition’s discussions of Milward is the dark ethical cloud of misconduct that hovers over the First Circuit’s reversal of the trial court’s exclusions of Martyn Smith and Carl Cranor. On appeal, the Council for Education and Research on Toxics (CERT) filed an amicus brief in support of reversing the exclusion of Smith and Cranor. The CERT amicus brief, however, never disclosed that CERT was founded by Smith and Cranor, and that CERT funded Smith’s research.[20]

Rule 702 requires courts to pay attention to, among other things, the sufficiency of the facts and data relied upon by expert witnesses. Rule 703’s requirement that individual studies must be reasonably relied upon is an important additional protreptic against the advice given by Professor Berger, in the third edition.

[1] The index notes the following page references for Rule 703: 214, 361, 363-364, and 610 n.184.

[2] See David E. Bernstein & Eric G. Lasker,“Defending Daubert: It’s Time to Amend Federal Rule of Evidence 702,” 57 William & Mary L. Rev. 1, 32 (2015) (“Rule 703 is frequently ignored in Daubert analyses”);  Schachtman, “Rule 703 – The Problem Child of Article VII,” 17 Proof 3 (Spring 2009); Schachtman “The Effective Presentation of Defense Expert Witnesses and Cross-examination of Plaintiffs’ Expert Witnesses”; at the ALI-ABA Course on Opinion and Expert Witness Testimony in State and Federal Courts (February 14-15, 2008). See also Julie E. Seaman, “Triangulating Testimonial Hearsay: The Constitutional Boundaries of Expert Opinion Testimony,” 96 Georgetown L.J. 827 (2008); “RULE OF EVIDENCE 703 — Problem Child of Article VII” (Sept. 19, 2011); “Giving Rule 703 the Cold Shoulder” (May 12, 2012); “New Reference Manual on Scientific Evidence Short Shrifts Rule 703,” (Oct. 16, 2011).

[3] RMSE3d at 214.

[4] RMSE3d at 364 (internal citations omitted).

[5] RMSE 3d at 610 (internal citations omitted).

[6] RSME3d at 601 n.184.

[7] Rule 802 (“Hearsay Rule”) “Hearsay is not admissible except as provided by these rules or by other rules prescribed by the Supreme Court pursuant to statutory authority or by Act of Congress.”

[8] Kehm v. Procter & Gamble Co., 580 F. Supp. 890, 902 (N.D. Iowa 1982) (“These [epidemiologic] studies were highly probative on the issue of causation—they all concluded that an association between tampon use and menstrually related TSS [toxic shock syndrome] cases exists.”), aff’d, 724 F.2d 613 (8th Cir. 1984); Ellis v. International Playtex, Inc., 745 F.2d 292, 303 (4th Cir. 1984). The chapter also cited another the en banc decision in Christophersen for the proposition that “[a]s a general rule, questions relating to the bases and sources of an expert’s opinion affect the weight to be assigned that opinion rather than its admissibility. . . . ” In the Christophersen case, the Fifth Circuit was clearly addressing the admissibility of the challenged expert witness’s opinions, not the admissibility of relied-upon studies. Christophersen v. Allied-Signal Corp., 939 F.2d 1106, 1111, 1113-14 (5th Cir. 1991) (en banc) (per curiam) (trial court may exclude opinion of expert witness whose opinion is based upon incomplete or inaccurate exposure data), cert. denied, 112 S. Ct. 1280 (1992).

[9] Interestingly, the authors of this chapter abandoned their suggestion, advanced in the second edition, that studies relied upon “might qualify for the learned treatise exception to the hearsay rule, Fed. R. Evid. 803(18), or possibly the catchall exceptions, Fed. R. Evid. 803(24) & 804(5).” which was part of their argument in the Second Edition. RMSE 2d at 335 (2000). See also RMSE 3d at 214 (discussing statistical studies as generally “admissible,” but acknowledging that admissibility may be no more than permission to explain the basis for an expert’s opinion, which is hardly admissibility at all).

[10] See Ellis, 745 F.2d at 299-303; Kehm, 724 F.2d at 617-18. These holdings predated the Supreme Court’s 1993 decision in Daubert, and the issue whether they are subject to Rule 702 has not been addressed.  Federal agency factual findings have been known to be invalid, on occasion.

[11] David L. Faigman, et al., Modern Scientific Evidence: The Law and Science of Expert Testimony v.1, § 23:1,at 206 (2009) (“Well conducted studies are uniformly admitted.”).

[12] Montori, et al., “Users’ guide to detecting misleading claims in clinical research reports,” 329 Br. Med. J. 1093, 1093 (2004) (advising readers on how to avoid being misled by published literature, and counseling readers to “Read only the Methods and Results sections; bypass the Discussion section.”)  (emphasis added).

[13] RSME 3d 11 (2011).

[14] Id. at 19.

[15] Id. at 20 & n. 51 (citing Susan Haack, “An Epistemologist in the Bramble-Bush: At the Supreme Court with Mr. Joiner,” 26 J. Health Pol. Pol’y & L. 217–37 (1999).

[16] Id. at 19-20 & n.52.

[17] See Berger, “The Admissibility of Expert Testimony,” RSME 3d 11 (2011).  Professor Berger never mentions Rule 703 at all!  Gone and forgotten.

[18] Professor Berger filed an amicus brief on behalf of plaintiffs, in Rider v. Sandoz Pharms. Corp., 295 F.3d 1194 (11th Cir. 2002).

[19] Id. at 20 n.51. (The editors note that the published chapter was Berger’s last revision, with “a few edits to respond to suggestions by reviewers.”) The addition of the controversial Milward decision cannot seriously be considered an “edit.”

[20] “From Here to CERT-ainty” (June 28, 2018); “ THE COUNCIL FOR EDUCATION AND RESEARCH ON TOXICS” (July 9, 2013).

Posted in Causation, Evidence, Reference Manual on Scientific Evidence, Rule 702, Rule 703 | 17 Comments »

Reference Manual – Desiderata for 4th Edition – Part III – Differential Etiology

February 1st, 2023

Admittedly, I am playing the role of the curmudgeon here by pointing out errors or confusions in the third edition of the Reference Manual.  To be sure, there are many helpful and insightful discussions throughout the Manual, but they do not need to be revised.  Presumably, the National Academies and the Federal Judicial Center are undertaking the project of producing a fourth edition because they understand that revisions, updates, and corrections are needed. Otherwise, why bother?

To be sure, there are aspects of the third edition’s epidemiology chapter that get some important points right. 

(1) The chapter at least acknowledges that small relative risks (1 < RR <3) may be insufficient to support causal inferences.[1]

(2) The chapter correctly notes that the method known as “differential etiology” addresses only specific causation, and that the method presupposes that general causation has been established.[2]

(3) The third edition correctly observes that clinicians generally are not concerned with etiology as much as with diagnosis of disease.[3] The authors of the epidemiology chapter correctly observe that “[f]or many health conditions, the cause of the disease or illness has no relevance to its treatment, and physicians, therefore, do not employ this term or pursue that question.”[4] This observation alone should help trial courts question whether many clinicians have even the pretense of expertise to offer expert causation opinions.[5]

(4) With respect to so-called differential etiology, the third edition correctly states that this mode of reasoning is a logically valid argument if premises are true; that is, general causation must be established for each “differential etiology.” The epidemiology chapter observes that “like any scientific methodology, [differential etiology] can be performed in an unreliable manner.”[6]

(5) The third edition reports that the differential etiology argument as applied in litigation is often invalid because not all the differentials other than the litigation claim have been ruled out.[7]

(6) The third edition properly notes that for diseases for which the causes are largely unknown, such as most birth defects, a differential etiology is of little benefit.[8] Unfortunately, the third edition offered no meaningful guidance for how courts should consider differential etiologies offered when idiopathic cases make up something less “than largely,” (0% < Idiopathic < 10%, 20%, 30%, 40, 50%, etc.).The chapter acknowledges that:

“Although differential etiologies are a sound methodology in principle, this approach is only valid if … a substantial proportion of competing causes are known. Thus, for diseases for which the causes are largely unknown, such as most birth defects, a differential etiology is of little benefit.”[9]

Accordingly, many cases reject proffered expert witness testimony on differential etiology, when the witnesses failed to rule out idiopathic causes in the case at issue. What is a substantial proportion?  Unfortunately, the third edition did not attempt to quantify or define “substantial.” The inability to rule out unknown etiologies remains the fatal flaw in much expert witness opinion testimony on specific causation.

Errant Opinions on Differential Etiology

The third edition’s treatment of differential etiology does leave room for improvement. One glaring error is the epidemiology chapter’s assertion that “differential etiology is a legal invention not used by physicians.”[10] Indeed, the third edition provides a definition for “differential etiology” that reinforces the error:

“differential etiology. Term used by the court or witnesses to establish or refute external causation for a plaintiff’s condition. For physicians, etiology refers to cause.”[11]

The third edition’s assertion about legal provenance and exclusivity can be quickly dispelled by a search on “differential etiology” in the National Library of Medicine’s PubMed database, which shows up dozens of results, going back to the early 1960s. Some citations are supplied in the notes.[12] A Google Ngram for “differential etiology” in American English shows prevalent usage well before any of the third edition’s cited cases:

The third edition’s erroneous assertion about the provenance of “differential etiology” has been echoed by other law professors. David Faigman, for instance, has claimed that in advancing differential etiologies, expert witnesses were inventing wholesale an approach that had no foundation or acceptance in their scientific disciplines:

“Differential etiology is ostensibly a scientific methodology, but one not developed by, or even recognized by, physicians or scientists. As described, it is entirely logical, but has no scientific methods or principles underlying it. It is a legal invention and, as such, has analytical heft, but it is entirely bereft of empirical grounding. Courts and commentators have so far merely described the logic of differential etiology; they have yet to define what that methodology is.”[13]

Faigman’s claim that courts and commentators have not defined the methodology underlying differential etiology is wrong. Just as hypothesis testing is predicated upon a probabilistic version of modus tollens, differential etiology is based upon “iterative disjunctive syllogism,” or modus tollendo ponens. Basic propositional logic recognizes that such syllogisms are valid arguments,[14] in which one of its premises is a disjunction (P v Q), and the other premise is the negation of one of the disjuncts:

P v Q

~P­­­_____

∴ Q

If we expand the disjunctive premise to more than one disjunction, we can repeat the inference (iteratively), eliminating one disjunct at a time, until we arrive at a conclusion that is a simple, affirmative proposition, without any disjunctions in it.

P v Q v R

~P­­­_____

∴ Q v R

     ~Q­­­_____

∴ R

Hence, the term “iterative disjunctive syllogism.” Sherlock Holmes’ fans, of course, will recognize that iterative disjunctive syllogism is nothing other than the process of elimination, as explained by the hero of Sir Arthur Conan Doyle’s short stories.[15]

The fourth edition should correct the error of the third edition, and it should dispel the strange notion that differential etiology is not used by scientists or clinicians themselves.

Supreme Nonsense on Differential Etiology

In 2011, the Supreme Court addressed differential etiology in a case, Matrixx Initiatives, in stunningly irrelevant and errant dicta. The third edition did not discuss this troublesome case, in which the defense improvidently moved to dismiss a class action complaint for securities violations allegedly arising from the failure to disclose multiple adverse event reports of anosmia from the use of the defendant’s product, Zicam. The basic reason for the motion on the pleadings was that the plaintiffs’ failed to allege a statistically significant and causally related increased risk of anosmia.  The Supreme Court made short work of the defense argument because material events, such as an FDA recall, did not require the existence of a causal relationship between Zicam use and anosmia. The defense complaints about statistical significance, causation, and their absence, were thus completely beside the point of the case.  Nonetheless, it became the Court’s turn for improvidence in addressing statistical and causation issues not properly before it. With respect to causation, the Court offered this by way of obiter dictum:

“We note that courts frequently permit expert testimony on causation based on evidence other than statistical significance. See, e.g., Best v. Lowe’s Home Centers, Inc., 563 F. 3d 171, 178 (6th Cir 2009); Westberry v. Gislaved Gummi AB, 178 F. 3d 257, 263–264 (4th Cir. 1999) (citing cases); Wells v. Ortho Pharmaceutical Corp., 788 F. 2d 741, 744–745 (11th Cir. 1986). We need not consider whether the expert testimony was properly admitted in those cases, and we do not attempt to define here what constitutes reliable evidence of causation.”[16]

This part of the Court’s opinion was stunningly wrong about the Court of Appeals’ decisions on statistical significance[17] and on causation. The Best and the Westberry decisions were both cases that turned on specific, not general, causation.  Statistical significance this was not part of the reasoning or rationale of the cited cases on specific caustion. Both cases assumed that general causation was established, and inquired into whether expert witnesses could reasonably and validly attribute the health outcome in the case to the exposures that were established causes of such outcomes.  The Court’s selection of these cases, quite irrelevant to its discussion, appears to have come from the Solicitor General’s amicus brief in Matrixx, but mindlessly adopted by the Court.

Although cited for an irrelevant proposition, the Supreme Court’s selection of the Best’s case was puzzling because the Sixth Circuit’s discussion of the issue is particularly muddled. Here is the relevant language from Best:

“[A] doctor’s differential diagnosis is reliable and admissible where the doctor

(1) objectively ascertains, to the extent possible, the nature of the patient’s injury…,

(2) ‘rules in’ one or more causes of the injury using a valid methodology,

and

(3) engages in ‘standard diagnostic techniques by which doctors normally rule out alternative causes” to reach a conclusion as to which cause is most likely’.”[18]

Of course, as the authors of the third edition’s epidemiology chapter correctly note, physicians rarely use this iterative process to arrive at causes of diseases in an individual; they use it to identify the disease or disease process that is responsible for the patient’s signs and symptoms.[19] The Best court’s description does not make sense in that it characterizes the process as ruling in “one or more” causes, and then ruling out alternative causes.  If an expert had ruled in only one cause, then there would be no need or opportunity to rule out an alternative cause.  If the one ruled-in cause was ruled out for other reasons, then the expert witness would be left with a case of idiopathic disease.

In any event, differential etiology was irrelevant to the general causation issue raised by the defense in Matrixx Initiatives. After the Supreme Court correctly recognized that causation was largely irrelevant to the securities fraud claim, it had no reason to opine on general causation.  Certainly, the Supreme Court had no reason to cite two cases on differential etiology in a case that did not even require allegations of general causation. The fourth edition of the Reference Manual should put Matrixx Initatives in its proper (and very limited) place.

[1] RMSE3d at 612 & n.193 (noting that “one commentator contends that, because epidemiology is sufficiently imprecise to accurately measure small increases in risk, in general, studies that find a relative risk less than 2.0 should not be sufficient for causation. The concern is not with specific causation but with general causation and the likelihood that an association less than 2.0 is noise rather than reflecting a true causal relationship. See Michael D. Green, “The Future of Proportional Liability,” in Exploring Tort Law (Stuart Madden ed., 2005); see also Samuel M. Lesko & Allen A. Mitchell, “The Use of Randomized Controlled Trials for Pharmacoepidemiology Studies,” in Pharmacoepidemiology 599, 601 (Brian Strom ed., 4th ed. 2005) (“it is advisable to use extreme caution in making causal inferences from small relative risks derived from observational studies”); Gary Taubes, “Epidemiology Faces Its Limits,” 269 Science 164 (1995) (explaining views of several epidemiologists about a threshold relative risk of 3.0 to seriously consider a causal relationship); N.E. Breslow & N.E. Day, “Statistical Methods in Cancer Research,” in The Analysis of Case-Control Studies 36 (IARC Pub. No. 32, 1980) (“[r]elative risks of less than 2.0 may readily reflect some unperceived bias or confounding factor”); David A. Freedman & Philip B. Stark, “The Swine Flu Vaccine and Guillain-Barré Syndrome: A Case Study in Relative Risk and Specific Causation,” 64 Law & Contemp. Probs. 49, 61 (2001) (“If the relative risk is near 2.0, problems of bias and confounding in the underlying epidemiologic studies may be serious, perhaps intractable.”). For many other supporting comments and observations, see “Small Relative Risks and Causation” (June 28, 2022).

[2] RMSE3d. at 618 (“Although differential etiologies are a sound methodology in principle, this approach is only valid if general causation exists … .”). In the case of a novel putative cause, the case may give rise to a hypothesis that the putative cause can cause the outcome, in general, and did so in the specific case.  That hypothesis must, of course, then be tested and supported by appropriate analytical methods before it can be accepted for general causation and as a putative specific cause in a particular individual.

[3] RMSE3d at 617.

[4] RMSE3d at 617 & n. 211 (citing Zandi v. Wyeth, Inc., No. 27-CV-06-6744, 2007 WL 3224242 (D. Minn. Oct. 15, 2007) (observing that physicians do assess the cause of patients’ breast cancers)).

[5] See, e.g., Tamraz v. BOC Group Inc., No. 1:04-CV-18948, 2008 WL 2796726 (N.D.Ohio July 18, 2008)(denying Rule 702 challenge to treating physician’s causation opinion), rev’d sub nom. Tamraz v. Lincoln Elec. Co., 620 F.3d 665 (6th Cir. 2010)(carefully reviewing record of trial testimony of plaintiffs’ treating physician; reversing judgment for plaintiff based in substantial part upon treating physician’s speculative causal assessment created by plaintiffs’ counsel), cert. denied, ___ U.S. ___ , 131 S. Ct. 2454 (2011).

[6] RMSE3d at 617-18 & n. 215.

[7] See, e.g, Milward v. Acuity Specialty Products Group, Inc., Civil Action No. 07–11944–DPW, 2013 WL 4812425 (D. Mass. Sept. 6, 2013) (excluding plaintiffs’ expert witnesses on specific causation), aff’d sub nom., Milward v. Rust-Oleum Corp., 820 F.3d 469 (1st Cir. 2016). Interestingly, the earlier appellate journey taken by the Milward litigants resulted in a reversal of a Rule 702 exclusion of plaintiff’s general causation expert witnesses. That reversal meant that there was no longer a final judgment.  The exclusion of specific causation witnesses was affirmed by the First Circuit, and the general causation opinion was no longer necessary to the final judgment. See “Differential Diagnosis in Milward v. Acuity Specialty Products Group” (Sept. 26, 2013); “Differential Etiology and Other Courtroom Magic” (June 23, 2014).

[8] RMSE3d at 617-18 & n. 214.

[9] See RMSE at 618 (internal citations omitted).

[10] RMSE3d at 691 (emphasis added).

[11] RMSE3d at 743.

[12] See, e.g., Kløve & D. Doehring, “MMPI in epileptic groups with differential etiology,” 18 J. Clin. Psychol. 149 (1962); Kløve & C. Matthews, “Psychometric and adaptive abilities in epilepsy with differential etiology,” 7 Epilepsia 330 (1966); Teuber & K. Usadel, “Immunosuppression in juvenile diabetes mellitus? Critical viewpoint on the treatment with cyclosporin A with consideration of the differential etiology,” 103  Fortschr. Med. 707 (1985); G.May & W. May, “Detection of serum IgA antibodies to varicella zoster virus (VZV)–differential etiology of peripheral facial paralysis. A case report,” 74 Laryngorhinootologie 553 (1995); Alan Roberts, “Psychiatric Comorbidity in White and African-American Illicity Substance Abusers” Evidence for Differential Etiology,” 20 Clinical Psych. Rev. 667 (2000); Mark E. Mullinsa, Michael H. Leva, Dawid Schellingerhout, Gilberto Gonzalez, and Pamela W. Schaefera, “Intracranial Hemorrhage Complicating Acute Stroke: How Common Is Hemorrhagic Stroke on Initial Head CT Scan and How Often Is Initial Clinical Diagnosis of Acute Stroke Eventually Confirmed?” 26 Am. J. Neuroradiology 2207 (2005); Qiang Fua, et al., “Differential Etiology of Posttraumatic Stress Disorder with Conduct Disorder and Major Depression in Male Veterans,” 62 Biological Psychiatry 1088 (2007); Jesse L. Hawke, et al., “Etiology of reading difficulties as a function of gender and severity,” 20 Reading and Writing 13 (2007); Mastrangelo, “A rare occupation causing mesothelioma: mechanisms and differential etiology,” 105 Med. Lav. 337 (2014).

[13] David L. Faigman & Claire Lesikar, “Organized Common Sense: Some Lessons from Judge Jack Weinstein’s Uncommonly Sensible Approach to Expert Evidence,” 64 DePaul L. Rev. 421, 439, 444 (2015). See also “David Faigman’s Critique of G2i Inferences at Weinstein Symposium” (Sept. 25, 2015).

[14] See Irving Copi & Carl Cohen Introduction to Logic at 362 (2005).

[15] See, e.g., Doyle, The Blanched Soldier (“…when you have eliminated all which is impossible, then whatever remains, however improbable, must be the truth.”); Doyle, The Beryl Coronet (“It is an old maxim of mine that when you have excluded the impossible, whatever remains, however improbable, must be the truth.”); Doyle, The Hound of the Baskervilles (1902) (“We balance probabilities and choose the most likely. It is the scientific use of the imagination.”); Doyle, The Sign of the Four, ch 6 (1890)(“‘You will not apply my precept’, he said, shaking his head. ‘How often have I said to you that when you have eliminated the impossible, whatever remains, however improbable, must be the truth? We know that he did not come through the door, the window, or the chimney. We also know that he could not have been concealed in the room, as there is no concealment possible. When, then, did he come?”)

[16] Matrixx Initiatives, Inc. v. Siracusano, 131 S. Ct. 1309, 1319 (2011). 

[17] The citation to Wells was clearly wrong in that the plaintiffs in that case had, in fact, relied upon studies that were nominally statistically significant, and so the Wells court could not have held that statistical significance was unnecessary.

[18] Best v. Lowe’s Home Centers, Inc., 563 F.3d 171, 179, 183-84 (6th Cir. 2009).

[19] See generally Harold C. Sox, Michael C. Higgins, and Douglas K. Owens, Medical Decision Making (2d ed. 2014). 

Posted in Causation, Reference Manual on Scientific Evidence, Rule 702 | 2 Comments »

Mass Tortogenesis

January 22nd, 2023

Mass torts are created much as cancer occurs in humans. The multistage model of tortogenesis consists of initiating and promoting events. The model describes, and in some cases, can even predict mass torts. The model also offers insights into prevention.

INITIATION

Initiating events can take a variety of forms. A change in a substance’s categorization in the International Agency for Research on Cancer’s treatment of cancer “hazards” will often initiate a mass tort by stirring interest in the lawsuit industry. A recent example of an IARC pronouncement’s initiating mass tort litigation is its reclassification of glyphosate as a “probable” human carcinogen.  Although the IARC monograph was probably flawed at its inception, and despite IARC’s specifying that its use of “probable” has no quantitative meaning, the IARC glyphosate monograph was a potent initiator of mass tort litigation against the manufacturer of glyphosate.

Regulatory rulemaking will often initiate a mass tort. Asbestos litigation existed as workman’s compensation cases from the 1930s, and as occasional, isolated cases against manufacturers, from the late 1950s.[1] By 1970, federal regulation of asbestos, in both occupational and environmental settings, however, helped create a legal perpetual motion machine that is still running, half a century later.

Publication of studies, especially with overstated results, will frequently initiate a mass tort. In 2007, the New England Journal of Medicine published a poorly done meta-analysis by Dr. Steven Nissen, on the supposed risk of heart attack from the use of rosiglitazone (Avandia).[2] Within days, lawsuits were filed against the manufacturer, GlaxoSmithKline, which ultimately paid over six billion dollars in settlements and costs.[3] Only after the harm of this mass tort was largely complete, the results of a mega-trial, RECORD,[4] became available, and the FDA changed its regulatory stance on rosiglitazone.[5]

More recently, on October 17, 2022, the Journal of the National Cancer Institute, published an observational epidemiologic study, “Use of Straighteners and Other Hair Products and Incident Uterine Cancer.”[6] Within a week or two, lawsuits began to proliferate. The authors were equivocal about their results, refraining from using explicit causal language, but suggesting that specific (phthalate) chemicals were “driving” the association:

“Abstract

Background

Hair products may contain hazardous chemicals with endocrine-disrupting and carcinogenic properties. Previous studies have found hair product use to be associated with a higher risk of hormone-sensitive cancers including breast and ovarian cancer; however, to our knowledge, no previous study has investigated the relationship with uterine cancer.

Methods

We examined associations between hair product use and incident uterine cancer among 33947 Sister Study participants aged 35-74 years who had a uterus at enrollment (2003-2009). In baseline questionnaires, participants in this large, racially and ethnically diverse prospective cohort self-reported their use of hair products in the prior 12 months, including hair dyes; straighteners, relaxers, or pressing products; and permanents or body waves. We estimated adjusted hazard ratios (HRs) and 95% confidence intervals (CIs) to quantify associations between hair product use and uterine cancer using Cox proportional hazard models. All statistical tests were 2-sided.

Results

Over an average of 10.9 years of follow-up, 378 uterine cancer cases were identified. Ever vs never use of straightening products in the previous 12 months was associated with higher incident uterine cancer rates (HR= 1.80, 95% CI = 1.12 to 2.88). The association was stronger when comparing frequent use (> 4 times in the past 12 months) vs never use (HR=2.55, 95% CI = 1.46 to 4.45; P trend=.002). Use of other hair products, including dyes and permanents or body waves, was not associated with incident uterine cancer.

Conclusion

These findings are the first epidemiologic evidence of association between use of straightening products and uterine cancer. More research is warranted to replicate our findings in other settings and to identify specific chemicals driving this observed association.”

The JNCI article might be considered hypothesis generating, but we can observe the article, in real time, initiating a mass tort. A petition for “multi-district litigation” status was filed not long after publication, and the lawsuit industry is jockeying for the inside post in controlling the litigation. Although the authors acknowledged that their findings were “novel,” and required more research, the lawsuit industry did not.

PROMOTION OF INITIATED MASS TORTS

As noted, within days of publication of the JNCI article on hair straighteners and uterine cancer, lawyers filed cases against manufacturers and sellers of hair straighteners. Mass tort litigation is a big business, truly industrial in scale, with its own eco-system of litigation finance, and claim finding and selling. Laws against champerty and maintenance have gone the way of the dodo. Part of the ethos of this eco-system is the constant deprecation of manufacturing industry’s “conflicts of industry,” while downplaying the conflicts of the lawsuit industry.

Here is an example of an email that a lawsuit industry lawyer might have received last month. The emphases below are mine:

“From:  ZZZ

To:  YYYYYYYYY

Date:  12/XX/2022
Subject:  Hair relaxer linked to cancer

Hi,

Here is the latest information on the Hair Relaxer/Straightener tort.

A recent National Institute of Health sister study showed proof that hair straightener products are linked to uterine cancer.

Several lawsuits have been filed against cosmetic hair relaxer companies since the release of the October 2022 NIH study.

The potential plaintiff pool for this case is large since over 50,000 women are diagnosed yearly.

A motion has been filed with the Judicial Panel on Multi District Litigation to have future cases moved to a class action MDL.

There are four cosmetic hair relaxers that are linked to this case so far.  Dark & Lovely, Olive Oil Relaxer, Motions, and Organic Root Stimulator.

Uterine fibroids and endometriosis have been associated with phthalate metabolites used in hair relaxers.

Are you looking to help victims in this case

ZZZ can help your firm sign up these thousands of these claimants monthly with your hair relaxer questionnaire, criteria, retainer agreement, and Hippa without the burden of doing this in house at an affordable cost per signed retainer for intake fees.

  • ZZZ intake fees are as low as $65 dollars per signed based upon a factors which are criteria, lead conversion %, and length of questionnaire.  Conversion rates are averaging 45%.
  • I can help point you in the right direction for reputable marketing agencies if you need lead sources or looking to purchase retainers.  

Please contact me to learn more about how we can help you get involved in this case.

Thank you,

ZZZ”

As you can see from ZZZ’s email, the JNCI article was the tipping point for the start of a new mass tort. ZZZ, however, was a promoter, not an initiator. Consider the language of ZZZ’s promotional efforts:

“Proof”!

As in quod erat demonstrandum.

Where is the Department of Justice when you have the makings of a potential wire fraud case?[7]

And “link.” Like sloppy journalists, the lawsuit industry likes to link a lot.

chorizo sausage links (courtesy of Wikipedia)[8]

And so it goes.

Absent from the promotional email are of course, mentions of the “novelty” of the JNCI paper’s finding, its use of dichotomized variables, its multiple comparisons, or its missing variables. Nor will you see any concern with how the JNCI authors inconsistently ascertained putative risk factors. Oral contraception was ascertained for over 10 years before base line, but hair straightener use was ascertained only for one year prior to baseline.

SYSTEMIC FAILURES TO PREVENT MASS TORTOGENESIS

Human carcinogenesis involves initiation and promotion, as well as failure of normal defense mechanisms against malignant transformation. Similarly, mass tortogenesis involves failure of defense mechanisms. Since 1993, the federal courts have committed to expert witness gatekeeping, by which they exclude expert witnesses who have outrun their epistemic headlights. Gatekeeping in federal court does not always go well, as for example in the Avandia mass tort, discussed above. In state courts, gatekeeping is a very uneven process.

Most states have rules or law that looks similar to federal law, but state judges, not uncommonly, look for ways to avoid their institutional responsibilities. In a recent decision involving claims that baby foods allegedly containing trace metals cause autism, a California trial judge shouted “not my job”[9]:

 “Under California law, the interpretation of epidemiological data — especially data reported in peer-reviewed, published articles — is generally a matter of professional judgment outside the trial court’s purview, including the interpretation of the strengths and weaknesses of a study’s design. If the validity of studies, their strengths and weaknesses, are subject to ‘considerable scientific interpretation and debate’, a court abuses its discretion by ‘stepping in and resolving the debate over the validity of the studies’. Nor can a court disregard ‘piecemeal … individual studies’ because it finds their methodology, ‘fully explained to the scientific community in peer-reviewed journals, to be misleading’ – ‘it is essential that… the body of studies be considered as a whole’. Flaws in study methodology should instead be ‘explored in detail through cross-examination and with the defense expert witnesses’ and affect ‘the weight[,] not the admissibility’ of an expert’s opinions.”

When courts disclaim responsibility for ensuring validity of evidence used to obtain judgments in civil actions, mass tortogenesis is complete, and the victim, the defendants, often must undergo radical treatment.

[1] The first civil action appears to have been filed by attorney William L. Brach on behalf of Frederick LeGrande, against Johns-Manville, for asbestos-related disease, on July 17, 1957, in LeGrande v. Johns-Manville Prods. Corp., No. 741-57 (D.N.J.).

[2] Steven E. Nissen, M.D., and Kathy Wolski, M.P.H., “Effect of Rosiglitazone on the Risk of Myocardial Infarction and Death from Cardiovascular Causes,” 356 New Engl. J. Med. 2457, 2457 (2007).

[3] In re Avandia Marketing, Sales Practices and Product Liability Litigation, 2011 WL 13576, *12 (E.D. Pa. 2011) (Rufe, J.).  See “Learning to Embrace Flawed Evidence – The Avandia MDL’s Daubert Opinion” (Jan. 10, 2011). Failed expert witness opinion gatekeeping promoted the mass tort into frank mass tort.

[4] Philip D. Home, Stuart J Pocock, et al., “Rosiglitazone Evaluated for Cardiovascular Outcomes in Oral Agent Combination Therapy for Type 2 Diabetes (RECORD),” 373 Lancet 2125 (2009) (reporting hazard ratios for cardiovascular deaths 0.84 (95% C.I., 0·59–1·18), and for myocardial infarction, 1·14 (95% C.I., 0·80–1·63). See “Revisiting the Avandia Scare: Results from the RECORD Trial” DiaTribe Learn (updated Aug. 14, 2021).

[5] FDA Press Release, “FDA requires removal of certain restrictions on the diabetes drug Avandia” (Nov. 25, 2013). And in December 2015, the FDA abandoned its requirement of a Risk Evaluation and Mitigation Strategy for Avandia. FDA, “Rosiglitazone-containing Diabetes Medicines: Drug Safety Communication – FDA Eliminates the Risk Evaluation and Mitigation Strategy (REMS)” (Dec. 16, 2015).

[6] Che-Jung Chang, Katie M O’Brien, Alexander P Keil, Symielle A Gaston, Chandra L Jackson, Dale P Sandler, and Alexandra J White, “Use of Straighteners and Other Hair Products and Incident Uterine Cancer,”114 J.Nat’l Cancer Instit. 1636 (2022).

[7] See, e.g., United States v. Harkonen, 2010 WL 2985257, at *5 (N.D. Calif. 2010) (denying defendant’s post–trial motions to dismiss the indictment, for acquittal, or for a new trial), aff’d, 510 Fed. Appx. 633, 2013 WL 782354, 2013 U.S. App. LEXIS 4472 (9th Cir. March 4, 2013), cert. denied 134 S.Ct. 824 (2013).

[8] See https://en.wikipedia.org/wiki/List_of_sausages.

[9] NC v Hain Celestial Group, Inc., 21STCV22822, Slip op. sur motion to exclude expert witnesses, Cal. Super. Ct. (Los Angeles May 24, 2022) (internal citations omitted).

Posted in Public Nuisances, Rule 702, Scientific Evidence, Scientific Publishing | 2 Comments »

Doctor Moline – Why Can’t You Be True?

December 18th, 2022

Doctor Moline, why can’t you be true?

Oh, Doc Moline, why can’t you be true?

You done started doing the things you used to do.

Mass torts are the product of the lawsuit industry, and since the 1960s, this industry has produced tort claims on a truly industrial scale. The industry now has an economic ally and adjunct in the litigation finance industry, and it has been boosted by the desuetude of laws against champerty and maintenance. The way that mass torts are adjudicated in some places could easily be interpreted as legalized theft.

One governor on the rapaciousness of the lawsuit industry has been the requirement that claims actually be proven in court. Since the Supreme Court’s ruling in Daubert, the defense bar has been able, on notable occasions, to squelch some instances of false claiming. Just as equity often varies with the length of the Chancellor’s foot, gatekeeping of scientific opinion about causation often varies with the scientific acumen of the trial judge. From the decision in Daubert itself, gatekeeping has been under assault form the lawsuit industry and its allies. I have, in these pages, detailed the efforts of the now defunct Project on Scientific Knowledge and Public Policy (SKAPP) to undermine any gatekeeping of scientific opinion testimony for scientific or statistical validity. SKAPP, as well as other organizations, and some academics, in aid of the lawsuit industry, have lobbied for the abandonment of the requirement of proving causation, or for the dilution of the scientific standards for expert opinions of causation.[1] The counter to this advocacy has been, and continues to be, an insistence that the traditional elements of a case, including general and specific causation, be sufficiently proven, with opinion testimony that satisfies the legal knowledge requirement for such testimony.

Alas, expert witness testimony can go awry in other ways besides merely failing to satisfy the validity and relevance requirements of the law of evidence.[2] One way I had not previously contemplated is suing for defamation or “product disparagement.”

We are now half a century since occupational exposures to various asbestos fibers came under general federal regulatory control, with regulatory requirements that employers warn their employees about the hazards involved with asbestos exposure. This federally enforced dissemination of information about asbestos hazards created a significant problem for the asbestos lawsuit industry.  Cases of mesothelioma have always occurred among persons non-occupationally exposed to asbestos, but as occupational exposure declined, the relative proportion of mesothelioma cases with no obvious occupational exposures increased. The lawsuit industry could not stand around and let these tragic cases go to waste.

Cosmetic talc variably has some mineral particulate that comes under the category of “elongate mineral particles,” (EMP), which the lawsuit industry could assert is “asbestos.” As a result, this industry has been able to reprise asbestos litigation into a new morality tale against cosmetic talc producers and sellers. LTL Management LLC was formerly known as Johnson & Johnson Consumer Inc. [J&J], a manufacturer and seller of cosmetic talc. J&J became a major target of the lawsuit industry in mesothelioma (and ovarian cancer) cases, based upon claims that EMP/asbestos in cosmetic talc caused their cancers. The lawsuit industry recruited its usual retinue of expert witnesses to support its litigation efforts.

Standing out in this retinue was Dr. Jacqueline Moline. On December 16, J&J did something that rarely happens in the world of mass torts; it sued Dr. Moline for fraud, injurious falsehood and product disparagement, and violations of the Lanham Act (§ 43(a), 15 U.S.C. § 1125(a)).[3] The gravamen of the complaint is that Dr. Moline, in 2020, published a case series of 33 persons who supposedly used cosmetic talc products and later developed malignant mesothelioma. According to her article, the 33 patients had no other exposures to asbestos, which she concluded, showed that cosmetic talc use can cause mesothelioma:

“Objective: To describe 33 cases of malignant mesothelioma among individuals with no known asbestos exposure other than cosmetic talcum powder.

Methods: Cases were referred for medico-legal evaluation, and tissue digestions were performed in some cases. Tissue digestion for the six ases described was done according to standard methodology.

Results: Asbestos of the type found in talcum powder was found in all six cases evaluated. Talcum powder usage was the only source of asbestos for all 33 cases.

Conclusions: Exposure to asbestos-contaminated talcum powders can cause mesothelioma. Clinicians should elicit a history of talcum powder usage in all patients presenting with mesothelioma.”[4]

Jacqueline Moline and Ronald Gordon both gave anemic conflicts disclosures: “Authors J.M. and R.G. have served as expert witnesses in asbestos litigation, including talc litigation for plaintiffs.”[5] Co-author Maya Alexandri was a lawyer at the time of publication; she is now a physician practicing emergency medicine, and also a fabulist. The article does not disclose the nature of Dr. Alexandri’s legal practice.

Dr. Moline is a professor and chair of occupational medicine at the Zucker School of Medicine at Hofstra/Northwell. She received her medical degree from the University of Chicago-Pritzker School of Medicine and a Master of Science degree in community medicine from the Mount Sinai School of Medicine. She completed a residency in internal medicine at Yale New Haven Hospital and an occupational and environmental medicine residency at Mount Sinai Medical Center. Dr. Moline is also a major-league testifier for the lawsuit industry.  Over the last quarter century, she has testified from sea to shining sea, for plaintiffs in asbestos, talc, and other litigations.[6]

According to J&J, Dr. Moline was listed as an expert witness for plaintiff, in over 200 talc mesothelioma cases against J&J.  There are, of course, other target defendants in this litigation, and the actual case count is likely higher. Moline has testified in 46 talc cases against J&J, and she has testified in 16 of those cases.[7] J&J estimates that she has made millions of dollars in service of the lawsuit industry.[8]

The authors’ own description of the manuscript makes clear the concern over the validity of personal and occupational histories of the 33 cases: “This manuscript is the first to describe mesothelioma among talcum powder consumers. Our case study suggest [sic] that cosmetic talcum powder use may help explain the high prevalence of idiopathic mesothelioma cases, particularly among women, and stresses the need for improved exposure history elicitation among physicians.”[9]

The Complaint alleges that Moline knew that her article, testimony, and public statements about the absence of occupational asbestos exposure in subjects of her case series, were false.  After having her testimony either excluded by trial courts, or held on appeal to be legally insufficient,[10] Moline set out to have a peer-reviewed publication that would support her claims. Because mesothelioma is sometimes considered, uncritically, as pathognomonic of amphibole asbestos exposure, Moline was obviously keen to establish the absence of occupational exposure in any of the 33 cases.

Alas, the truth appears to have caught up with Moline because some of the 33 cases were in litigation, in which the detailed histories of each case would be discovered. Defense counsel sought to connect the dots between the details of each of the 33 cases and the details of pending or past lawsuits. The federal district court decision in the case of Bell v. American International Industries blew open the doors of Moline’s alleged fraud.[11]  Betty Bell claimed that her use of cosmetic talc had caused her to develop mesothelioma. What Dr. Moline and Bell’s counsel were bound to have known was that Bell had had occupational exposure to asbestos. Before filing a civil action against talc product suppliers, Bell filed workers’ compensation against two textile industry employers.[12] Judge Osteen’s opinion in Bell documents the anxious zeal that plaintiffs’ counsel brought to bear in trying to suppress the true nature of Ms. Bell’s exposure. After Judge Osteen excoriated Moline and plaintiffs’ counsel for their efforts to conceal information about Bell’s occupational asbestos exposures, and about her inclusion in the 33 case series, plaintiffs’ counsel dismissed her case.

Another of the 33 cases was the New Jersey case brought by Stephen Lanzo, for whom Moline testified as an expert witness.[13] In the course of the Lanzo case, the defense developed facts of Mr. Lanzo’s prior asbestos exposure.  Crocidolite fibers were found in his body, even though the amphibole crocidolite is not a fiber type found in talc. Crocidolite is orders of magnitude more potent in causing human mesotheliomas than other asbestos fiber types.[14] Despite these facts, Dr. Moline appears to have included Lanzo as one of the 33 cases in her article.

And then there were others, too.

[1] See “Skappology” (May 26, 2020);  “SKAPP A LOT” (April 30, 2010); “Manufacturing Certainty” (Oct. 25, 2011); “David Michaels’ Public Relations Problem” (Dec. 2, 2011); “Conflicted Public Interest Groups” (Nov. 3, 2013).

[2] See, e.g., “Legal Remedies for Suspect Medical Science in Products Cases – Part One” (June 2, 2020); “Part Two” (June 3, 2020); “Part Three” (June 5, 2020); “Part 4” (June 7, 2020); “Part 5” (June 8, 2020).

[3] LTL Management LLC v. Dr. Jacqueline Miriam Moline,

Adv. Proc. No. 22- ____, in Chap. 11, Case No. 21-30589, Bankruptcy Ct., D.N.J. (Dec. 16, 2022) [Complaint]

[4] Jacqueline Moline, Kristin Bevilacqua, Maya Alexandri, and Ronald E. Gordon, “Mesothelioma Associated with the Use of Cosmetic Talc,” 62 J. Occup. & Envt’l Med. 11 (Jan. 2020) (emphasis added) [cited as Moline]

[5] Dr. Gordon has had other litigation activities of interest. See William C. Rempel, “Alleged Mob Case May Best Illustrate How Not to Play the Game : Crime: Scheme started in a Texas jail and ended with reputed mobsters charged in $30-million laundering scam,” L.A. Times (July 4, 1993).

[6] See., e.g., Fowler v. Akzo Nobel Chemicals, Inc., 251 N.J. 300, 276 A. 3d 1146 (2022); Lanzo v. Cyprus Amax Minerals Co., 467 N.J. Super. 476, 254 A.3d 691 (App. Div. 2021); Fishbain v. Colgate-Palmolive Co., No. A-1786-15T2 (N.J. App. Div. 2019); Buttitta v. Allied Signal, Inc., N.J. App. Div. (2017); Kaenzig v. Charles B. Chrystal Co., N.J. App. Div. (2015); Anderson v. A.J. Friedman Supply Co., 416 N.J. Super. 46, 3 A.3d 545 (App. Div. 2010); Cioni v. Avon Prods., Inc., 2022 NY Slip Op 33197(U) (2022); Zicklin v. Bergdorf Goodman Inc., 2022 NY Slip Op 32119(U) (N.Y.Sup. N.Y. Cty. 2022); Nemeth v. Brenntag North America, 183 A.D.3d 211, 123 N.Y.S.3d 12 (2020), rev’d, 38 N.Y.3d 336, 345 (2022) (Moline’s testimony insufficient); Olson v. Brenntag North America, Inc., 2020 NY Slip Op 33741(U) (N.Y.Sup. N.Y. Cty. 2020), rev’d, 207 A.D.3d 415, 416 (N.Y. 1st Dep’t 2022) (holding Moline’s testimony on causation insufficient).; Moldow v. A.I. Friedman, L.P., 2019 NY Slip Op 32060(U) (N.Y.Sup. N.Y. Cty. 2019); Zoas v BASF Catalysts, LLC., 2018 NY Slip Op 33009(U) (N.Y.Sup. N.Y. Cty. 2018); Prokocimer v. Avon Prods., Inc., 2018 NY Slip Op 33170(U) (Dec. 11, 2018); Shulman v. Brenntag North America, Inc., 2018 NY Slip Op 32943(U) (N.Y.Sup. N.Y. Cty. 2018); Pistone v. American Biltrite, Inc., 2018 NY Slip Op 30851(U) (2018); Evans v. 3M Co., 2017 NY Slip Op 30756(U) (N.Y.Sup. N.Y. Cty. 2017); Juni v. A.O. Smith Water Prods., 48 Misc.3d 460, 11 N.Y.S.3d 416 (2015), aff’d, 32 N.Y.3d 1116, 116 N.E.3d 75, 91 N.Y.S.3d 784 (2018); Konstantin v. 630 Third Ave. Associates, 121 A.D. 3d 230, 990 N.Y.S. 2d 174 (2014); Lopez v. Gem Gravure Co., 50 A.D.3d 1102, 858 N.Y.S.2d 226 (2008); Lopez v. Superflex, Ltd., 31 A.D. 3d 914, 819 N.Y.S. 2d 165 (2006); DeMeyer v. Advantage Auto, 9 Misc. 3d 306, 797 N.Y.S.2d 743 (2005); Amorgianos v. National RR Passenger Corp., 137 F. Supp. 2d 147 (E.D.N.Y. 2001), aff’d, 303 F. 3d 256 (2d Cir. 2002); Chapp v. Colgate-Palmolive Co., 2019 Wisc. App. 54, 935 N.W.2d 553 (2019); McNeal v. Whittaker, Clark & Daniels, Inc., 80 Cal. App. 853 (2022); Burnett v. American Internat’l Indus., Case No. 3:20-CV-3046 (W.D. Ark. Jan. 27, 2022); McAllister v. McDermott, Inc., Civ. Action No. 18-361-SDD-RLB (M.D.La. Aug. 14, 2020); Hanson v. Colgate-Palmolive Co., 353 F. Supp. 3d 1273 (S.D. Ga. 2018); Norman-Bloodsaw v. Lawrence Berkeley Laboratory, 135 F. 3d 1260 (9th Cir. 1998); Carroll v. Akebono Brake Corp., 514 P. 3d 720 (Wash. App. 2022).

[7] Complaint ¶15.

[8] Complaint ¶19.

[9] Moline at 11.

[10] See, e.g., In re New York City Asbestos Litig. (Juni), 148 A.D.3d 233, 236-37, 239 (N.Y. App. Div. 1st Dep’t 2017), aff’d, 2 N.Y.3d 1116, 1122 (2018); Nemeth v. Brenntag North America, 183 A.D.3d 211, 123 N.Y.S.3d 12 (N.Y. App. Div. 2020), rev’d, 38 N.Y.3d 336, 345 (2022); Olson v. Brenntag North America, Inc., 2020 NY Slip Op 33741(U) (N.Y.Sup. Ct. N.Y. Cty. 2020), rev’d, 207 A.D.3d 415, 416 (N.Y. App. Div. 1st Dep’t 2022).

[11] Bell v. American Internat’l Indus. et al., No. 1:17-CV-00111, 2022 U.S. Dist. LEXIS 199180 (M.D.N.C. Sept. 13, 2022) (William Lindsay Osteen, Jr., J.). See Daniel Fisher, “Key talc/cancer study cited by plaintiffs hid evidence of other exposure, lawyers say” (Dec. 1, 2022).

[12] According to the Complaint against Moline, Bell had filed workers’ compensation claims with the North Carolina Industrial Commission, back in 2015, declaring under oath that she had been exposed to asbestos while working with two textile manufacturing employers, Hoechst Celanese Corporation and Pillowtex Corporation. Complaint at ¶102. As frequently happens in civil actions, the claimant dismisses worker’s compensation without prejudice, to pursue the more lucrative payday in a civil action, without the burden of employers’ liens against the recovery. Complaint at 102.

[13] See “New Jersey Appellate Division Calls for Do-Over in Baby Powder Dust Up” (May 22, 2021).

[14] David H. Garabrant & Susan T. Pastula, “A comparison of asbestos fiber potency and elongate mineral particle (EMP) potency for mesothelioma in humans,” 361 Toxicology & Applied Pharmacol. 127 (2018) (“relative potency of chrysotile:amosite:crocidolite was 1:83:376”). See also D. Wayne Berman & Kenny S. Crump, “Update of Potency Factors for Asbestos-Related Lung Cancer and Mesothelioma,” 38(S1) Critical Reviews in Toxicology 1 (2008).

Posted in Expert Witness Discovery, Expert Witnesses, Rule 702, Scientific Evidence, Scientific Misconduct, Underlying Data | 29 Comments »

An Opinion to SAVOR

November 11th, 2022

The saxagliptin medications are valuable treatments for type 2 diabetes mellitus (T2DM). The SAVOR (Saxagliptin Assessment of Vascular Outcomes Recorded in Patients with Diabetes Mellitus) study was a randomized controlled trial, undertaken by manufacturers at the request of the FDA.[1] As a large (over sixteen thousand patients randomized) double-blinded cardiovascular outcomes trial, SAVOR collected data on many different end points in patients with T2DM, at high risk of cardiovascular disease, over a median of 2.1 years. The primary end point was a composite end point of cardiac death, non-fatal myocardial infarction, and non-fatal stroke. Secondary end points included each constituent of the composite, as well as hospitalizations for heart failure, coronary revascularization, or unstable angina, as well as other safety outcomes.

The SAVOR trial found no association between saxagliptin use and the primary end point, or any of the constituents of the primary end point.  The trial did, however, find a modest association between saxagliptin and one of the several secondary end points, hospitalization for heart failure (hazard ratio, 1.27; 95% C.I., 1.07 to 1.51; p = 0.007). The SAVOR authors urged caution in interpreting their unexpected finding for heart failure hospitalizations, given the multiple end points considered.[2] Notwithstanding the multiplicity, in 2016, the FDA, which does not require a showing of causation for adding warnings to a drug’s labeling, added warnings about the “risk” of hospitalization for heart failure from the use of saxagliptin medications.

And the litigation came.

The litigation evidentiary display grew to include, in addition to SAVOR, observational studies, meta-analyses, and randomized controlled trials of other DPP-4 inhibitor medications that are in the same class as saxagliptin. The SAVOR finding for heart failure was not supported by any of the other relevant human study evidence. The lawsuit industry, however, armed with an FDA warning, pressed its cases. A multi-district litigation (MDL 2809) was established. Rule 702 motions were filed by both plaintiffs’ and defendants’ counsel.

When the dust settled in this saxagliptin litigation, the court found that the defendants’ expert witnesses satisfied the relevance and reliability requirements of Rule 702, whereas the proferred opinions of plaintiff’s expert witness, Dr. Parag Goyal, a cardiologist at Cornell-Weill Hospital in New York, did not satisfy Rule 702.[3] The court’s task was certainly made easier by the lack of any other expert witness or published opinion that saxagliptin actually causes heart failure serious enough to result in hospitalization. 

The saxagliptin litigation presented an interesting array of facts for a Rule 702 show down. First, there was an RCT that reported a nominally statistically significant association between medication use and a harm, hospitalization for heart failure. The SAVOR finding, however, was in a secondary end point, and its statistical significance was unimpressive when considered in the light of the multiple testing that took place in the context of a cardiovascular outcomes trial.

Second, the heart failure increase was not seen in the original registration trials. Third, there was an effort to find corroboration in observational studies and meta-analyses, without success. Fourth, there was no apparent mechanism for the putative effect. Fifth, there was no support from trials or observational studies of other medications in the class of DPP-4 inhibitors.

Dr. Goyal testified that the heart failure finding in SAVOR “should be interpreted as cause and effect unless there is compelling evidence to prove otherwise.” On this record, the MDL court excluded Dr. Goyal’s causation opinions. Dr. Goyal purported to conduct a Bradford Hill analysis, but the MDL court appeared troubled by his glib dismissal of the threat to validity in SAVOR from multiple testing, and his ignoring the consistency prong of the Hill factors. SAVOR was the only heart failure finding in humans, with the remaining observational studies, meta-analyses, and other trials of DPP-4 inhibitors failing to provide supporting evidence.

The challenged defense expert witnesses defended the validity of their opinions, and ultimately the MDL court had little concern in permitting them through the judicial gate. The plaintiffs’ challenges to Suneil Koliwad, a physician with a doctorate in molecular physiology, Eric Adler, a cardiologist, and Todd Lee, a pharmaco-epidemiologist, were all denied. The plaintiffs challenged, among other things, whether Dr. Adler was qualified to apply a Bonferroni correction to the SAVOR results, and whether Dr. Lee was obligated to obtain and statistically analyze the data from the trials and studies ab initio. The MDL court quickly dispatched these frivolous challenges.

The saxagliptin MDL decision is an important reminder that litigants should remain vigilant about inaccurate assertions of “statistical significance,” even in premier, peer-reviewed journals. Not all journals are as careful as the New England Journal of Medicine in requiring qualification of claims of statistical significance in the face of multiple testing.

One legal hiccup in the court’s decision was its improvident citation to Daubert, for the proposition that the gatekeeping inquiry must focus “solely on principles and methodology, not on the conclusions they generate.”[4] That piece of obiter dictum did not survive past the Supreme Court’s 1997 decision in Joiner,[5] and it was clearly superseded by statute in 2000. Surely it is time to stop citing Daubert for this dictum.

[1] Benjamin M. Scirica, Deepak L. Bhatt, Eugene Braunwald, Gabriel Steg, Jaime Davidson, et al., for the SAVOR-TIMI 53 Steering Committee and Investigators, “Saxagliptin and Cardiovascular Outcomes in Patients with Type 2 Diabetes Mellitus,” 369 New Engl. J. Med. 1317 (2013).

[2] Id. at 1324.

[3] In re Onglyza & Kombiglyze XR Prods. Liab. Litig., MDL 2809, 2022 WL 43244 (E.D. Ken. Jan. 5, 2022).

[4] Daubert v. Merrell Dow Pharms., Inc., 509 U.S. 579, 595 (1993).

[5] General Electric Co. v. Joiner, 522 U.S. 136 (1997).

Posted in Causation, Meta-analysis, Rule 702, Scientific Evidence, statistical evidence | No Comments »

Further Thoughts on Cheng’s Consensus Rule

October 3rd, 2022

In “Cheng’s Proposed Consensus Rule for Expert Witnesses,”[1] I discussed a recent law review article by Professor Edward K. Cheng,[2] who has proposed dispensing with expert witness testimony as we know it in favor of having witnesses tell juries what the scientific consensus is on any subject. Cheng’s project is fraught with difficulties and contradictions; and it has clearly anticipatable bad outcomes. Four Supreme Court cases (Daubert, Joiner, Kumho Tire, and Weisgram), and a major revision in Rule 702, ratified by Congress, all embraced the importance of judicial gatekeeping of expert witness opinion testimony to the fact-finding function of trials. Professor Cheng now wants to ditch the entire notion of gatekeeping, as well as the epistemic basis – sufficient facts and data – for expert witnesses’ opinions in favor of reportage of which way the herd is going. Cheng’s proposal is perhaps the most radical attack, in recent times, on the nature of legal factfinding, whether by judges or juries, in the common law world.

Still, there are two claims within his proposal, which although overstated, are worth further discussion and debate. The first is that the gatekeeping role does not sit well with many judges. We see judges ill at ease in their many avoidance tactics, by which they treat serious methodological challenges to expert witness testimony as “merely going to the weight of the conclusion.” The second is that many judges, and especially juries, are completely at sea in the technical knowledge needed to evaluate the scientific issues in many modern day trials.

With respect to the claimed epistemic incompetence, the simpler remedy is to get rid of incompetent judges. We have commercial courts, vaccine courts, and patent courts. Why are litigants disputing a contract or a commercial practice entitled to epistemically competent judges, but litigants in health claim cases are not? Surely, the time has come to have courts with judges that have background and training in the health and statistical sciences. The time for “blue ribbon” juries of properly trained fact finders seems overdue. Somehow we must reconcile the seventh amendment right to a jury with the requirement of “due process” of law. The commitment to jury trials for causes of action known to the common law in 1787, or 1791, is stretched beyond belief for the sorts of technical and complex claims now seen in federal courts and state courts of general jurisdiction.[3]

Several courts have challenged the belief that the seventh amendment right to a jury applies in the face of complex litigation. The United States Court of Appeals explained its understanding of complexity that should remove a case from the province of the seventh amendment:

“A suit is too complex for a jury when circumstances render the jury unable to decide in a proper manner. The law presumes that a jury will find facts and reach a verdict by rational means. It does not contemplate scientific precision but does contemplate a resolution of each issue on the basis of a fair and reasonable assessment of the evidence and a fair and reasonable application of the relevant legal rules. See Schulz v. Pennsylvania RR, 350 U.S. 523, 526 (1956). A suit might be excessively complex as a result of any set of circumstances which singly or in combination render a jury unable to decide in the foregoing rational manner. Examples of such circumstances are an exceptionally long trial period and conceptually difficult factual issues.”[4]

The Circuit’s description of complexity certainly seems to apply to many contemporary claims of health effects.

We should recognize that Professor Cheng’s indictment, and conviction, of judicial gatekeeping and jury decision making as epistemically incompetent directly implies that the judicial process has no epistemic, truth finding function in technical cases of claimed health effects. Cheng’s proposed solution does not substantially ameliorate this implication, because consensus statements are frequently absent, and even when present, are plagued with their own epistemic weaknesses.

Consider for instance, the 1997 pronouncement of the International Agency for Research on Cancer that crystalline silica is a “known” human carcinogen.[5] One of the members of the working group responsible for the pronouncement explained:

“It is hardly surprising that the Working Group had considerable difficulty in reaching a decision, did not do so unanimously and would probably not have done so at all, had it not been explained that we should be concerned with hazard identification, not risk.”[6]

And yet, within months of the IARC pronouncement, state and federal regulatory agencies formed a chorus of assent to the lung cancer “risk” of crystalline silica. Nothing in the scientific record had changed except the permission of the IARC to stop thinking critically about the causation issue. Another consensus group came out, a few years after the IARC pronouncement, with a devastating critical assessment of the IARC review:

“The present authors believe that the results of these studies [cited by IARC] are inconsistent and, when positive, only weakly positive. Other, methodologically strong, negative studies have not been considered, and several studies viewed as providing evidence supporting the carcinogenicity of silica have significant methodological weaknesses. Silica is not directly genotoxic and is a pulmonary carcinogen only in the rat, a species that seems to be inappropriate for assessing particulate carcinogenesis in humans. Data on humans demonstrate a lack of association between lung cancer and exposure to crystalline silica. Exposure-response relationships have generally not been found. Studies in which silicotic patients were not identified from compensation registries and in which enumeration was complete did not support a causal association between silicosis and lung cancer, which further argues against the carcinogenicity of crystalline silica.”[7]

Cheng’s proposal would seem to suppress legitimate courtroom criticism of an apparent consensus statement, which was based upon a narrow majority of a working group, on a controversial dataset, with no examination of the facts and data upon which the putative consensus statement was itself based.

The Avandia litigation tells a cautionary tale of how fragile and ephemeral consensuses can be. A dubious meta-analysis by a well-known author received lead article billing in an issue of the New England Journal of Medicine, in 2007, and litigation claims started to roll in within hours.[8] In face of this meta-analysis, an FDA advisory committee recommended heightened warnings, and a trial court declined to take a careful look at the methodological flaws in the inciting meta-analytic study.[9] Ultimately, a large clinical trial exculpated the medication, but by then the harm had been done, and there was no revisiting of the gatekeeping decision to allow the claims to proceed.[10] The point should be obvious. In 2007, there appeared to be a consensus, with led to an FDA label change, despite the absence of sufficient facts and data to support the litigation claims. Even if plaintiffs’ claims passed through the gate in 2008, they were highly vulnerable to courtroom challenges to the original meta-analysis. Cheng’s proposal, however, would truncate the litigation process into an exploration whether or not there was a “consensus.”

Deviation from Experts’ Standards of Care

The crux of many Rule 702 challenges to an expert witness is that the witness has committed malpractice in his discipline. The challenger must identify a standard of care, and the challenged witness’s deviation(s) from that standard. The identification of the relevant standard of care will, indeed, sometimes involve a consensus, evidenced by texts, articles, professional society statements, or simply implicit in relevant works of scholarship or scientific studies. Consensuses about standards of care are, of course, about methodology. Consensuses about conclusions, however, may also be relevant because if a litigant’s expert witness proffers a conclusion at odds with consensus conclusions, the deviant conclusion implies deviant methodology.

Cheng’s treatment of statistical significance is instructive for how his proposal would create mischief in many different types of adjudications, but especially of claimed health effects. First, Cheng’s misrepresentation of consensus among statisticians is telling for the validity of his project.  After all, he holds an advanced degree in statistics, and yet, he is willing write that that:

“[w]hile historically used as a rule of thumb, statisticians have now concluded that using the 0.05 [p-value] threshold is more distortive than helpful.”[11]

Statisticians, without qualification! And as was shown, Cheng is demonstrably wrong in his use of the cited source to support his representation of what certainly seems like a consensus paper. His précis is not even remotely close to the language of the paper, but the consensus paper is hearsay and can only be used by an expert witness in support of an opinion.  Presumably, another expert witness might contradict the quoted opinion about what “statisticians” have concluded, but it is unclear whether a court could review the underlying A.S.A. paper, take judicial notice of the incorrectness of the proffered opinion, and then exclude the expert witness opinion.

After the 2016 publication of the A.S.A.’s consensus statement, some statisticians did indeed publish editorials claiming it was time to move beyond statistical significance testing. At least one editorial, by an A.S.A. officer was cited as representing an A.S.A. position, which led the A.S.A. President to appoint a task force to consider the call for an across-the-board rejection of significance testing. In 2021, that task force clearly endorsed significance testing as having a continued role in statistical practice.[12]

Where would this situation leave a gatekeeping court or a factfinding jury? Some obscure psychology journals have abandoned the use of significance testing, but the New England Journal of Medicine has retained the practice, while introducing stronger controls for claims of “significance” when the study at hands has engaged in multiple comparisons.

But Cheng, qua law professor and statistician (and would-be expert witness) claims “statisticians have now concluded that using the 0.05 [p-value] threshold is more distortive than helpful,” and the trial must chase not the validity of the inference of claimed causation but whether there is, or is not, a census about the use of a pre-specified threshold for p-values or confidence intervals. Cheng’s proposal about consensuses would turn trials into disputes about whether consensuses exist, and the scope of the purported agreement, not about truth.

In some instances, there might be a clear consensus, fully supported, on a general causation issue. Consider for instance, the known causal relationship between industrial benzene exposure and acute myelogenous leukemia (AML). This consensus turns out to be rather unhelpful when considering whether minute contamination of carbonated water can cause cancer,[13] or even whether occupational exposure to gasoline, with its low-level benzene (~1%) content, can cause AML.[14]

Frequently, there is also a deep asymmetry in consensus statements. When the evidence for a causal conclusion is very clear, professional societies may weigh in to express their confident conclusions about the existence of causation. Such societies typically do not issue statements that explicitly reject causal claims. The absence of a consensus statement, however, often can be taken to represent a consensus that professional societies do not endorse causal claims, and consider the evidence, at best, equivocal. Those dogs that have not barked can be, and have been, important considerations in gatekeeping.

Contrary to Cheng’s complete dismissal of judges’ epistemic competence, judges can, in many instances, render reasonable gatekeeping decisions by closely considering the absence of consensus statements, or systematic reviews, favoring the litigation claims.[15] At least in this respect, Professor Cheng is right to emphasize the importance of consensus, but he fails to note the importance of its absence, and the ability of litigants and their expert witnesses to inform gatekeeping judges of the relevance of consensus statements or their absence to the epistemic assessment of proferred expert witness opinion testimony.

[1] “Cheng’s Proposed Consensus Rule for Expert Witnesses,” (Sept. 15, 2022).

[2] Edward K. Cheng, “The Consensus Rule: A New Approach to Scientific Evidence,” 75 Vanderbilt L. Rev. 407 (2022) [Consensus Rule]

[3] There is an extensive discussion and debate of viability and the validity of asserting rights to trial by jury for many complex civil actions in the modern era. See, e.g., Stephan Landsman & James F. Holderman, “The Evolution of the Jury Trial in America,” 37 Litigation 32 (2010); Robert A. Clifford, “Deselecting the Jury in a Civil Case,” 30 Litigation 8 (Winter 2004); Hugh H. Bownes, “Should Trial by Jury Be Eliminated in Complex Cases,” 1 Risk 75 (1990); Douglas King, “Complex Civil Litigation and the Seventh Amendment Right to a Jury Trial,” 51 Univ. Chi. L. Rev. 581 (1984); Alvin B. Rubin, “Trial by Jury in Complex Civil Cases: Voice of Liberty or Verdict by Confusion?” 462 Ann. Am. Acad. Political & Social Sci. 87 (1982); William V. Luneburg & Mark A. Nordenberg, “Specially Qualified Juries and Expert Nonjury Tribunals: Alternatives for Coping with the Complexities of Modern Civil Litigation,” 67 Virginia L. Rev. 887 (1981); Richard O. Lempert, “Civil Juries and Complex Cases: Let’s Not Rush to Judgment,” 80 Mich. L. Rev. 68 (1981); Comment, “The Case for Special Juries in Complex Civil Litigation,” 89 Yale L. J. 1155 (1980); James S. Campbell & Nicholas Le Poidevin, “Complex Cases and Jury Trials: A Reply to Professor Arnold,” 128 Univ. Penn. L. Rev. 965 (1980); Barry E. Ungar & Theodore R. Mann, “The Jury and the Complex Civil Case,” 6 Litigation 3 (Spring 1980); Morris S. Arnold, “A Historical Inquiry into the Right to Trial by Jury in Complex Civil Litigation,”128 Univ. Penn. L. Rev. 829 (1980); Daniel H. Margolis & Evan M. Slavitt, “The Case Against Trial by Jury in Complex Civil Litigation,” 7 Litigation 19 (1980); Montgomery Kersten, “Preserving the Right to Jury Trial in Complex Civil Cases,” 32 Stanford L. Rev. 99 (1979); Maralynne Flehner, “Jury Trials in Complex Litigation,” 4 St. John’s Law Rev. 751 (1979); Comment, “The Right to a Jury Trial in Complex Civil Litigation,” 92 Harvard L. Rev. 898 (1979); Kathy E. Davidson, “The Right to Trial by Jury in Complex Litigation,” 20 Wm. & Mary L. Rev. 329 (1978); David L. Shapiro & Daniel R. Coquillette, “The Fetish of Jury Trial in Civil Cases: A Comment on Rachal v. Hill,” 85 Harvard L. Rev. 442 (1971); Comment, “English Judge May Not Order Jury Trial in Civil Case in Absence of Special Circumstances. Sims v. William Howard & Son Ltd. (C. A. 1964),” 78 Harv. L. Rev. 676 (1965); Fleming James, Jr., “Right to a Jury Trial in Civil Actions,” 72 Yale L. J. 655 (1963).

[4] In re Japanese Elec. Prods. Antitrust Litig., 63` F.2d 1069, 1079 (3d Cir 1980). See In re Boise Cascade Sec. Litig., 420 F. Supp. 99, 103 (W.D. Wash. 1976) (“In sum, it appears to this Court that the scope of the problems presented by this case is immense. The factual issues, the complexity of the evidence that will be required to explore those issues, and the time required to do so leads to the conclusion that a jury would not be a rational and capable fact finder.”). See also Ross v. Bernhard, 396 U.S. 532, 538 & n.10, 90 S. Ct. 733 (1970) (discussing the “legal” versus equitable nature of an action that might give rise to a right to trial by jury). Of course, the statistical and scientific complexity of claims was absent from cases tried in common law courts in 1791, at the time of the adoption of the seventh amendment.

[5] IARC Monograph on the Evaluation of Carcinogenic Risks to Humans of Silica, Some Silicates, Coal Dust and para-Aramid Fibrils, vol. 68 (1997).

[6] Corbett McDonald & Nicola Cherry, “Crystalline Silica and Lung Cancer: The Problem of Conflicting Evidence,” 8 Indoor Built Env’t 121, 121 (1999).

[7] Patrick A. Hessel, John F. Gamble, J. Bernard L. Gee, Graham Gibbs, Francis H.Y. Green, W. Keith C. Morgan, and Brooke T. Mossman, “Silica, Silicosis, and Lung Cancer: A Response to a Recent Working Group Report,” 42 J. Occup & Envt’l Med. 704, 704 (2000).

[8] Steven Nissen & K. Wolski, “Effect of Rosiglitazone on the Risk of Myocardial Infarction and Death from Cardiovascular Causes,” 356 New Engl. J. Med. 2457 (2007); Erratum, 357 New Engl. J. Med. 100 (2007).

[9] In re Avandia Mktg., Sales Practices & Prods. Liab. Litig., 2011 WL 13576 (E.D. Pa. Jan. 4, 2011).

[10] Philip D. Home, Stuart J Pocock, et al., “Rosiglitazone Evaluated for Cardiovascular Outcomes in Oral Agent Combination Therapy for Type 2 Diabetes (RECORD),” 373 Lancet 2125 (2009). The hazard ratios for cardiovascular death was 0.84 (95% C.I., 0·59–1·18), and for myocardial infarction, 1·14 (95% C.I., 0·80–1·63).

[11] Consenus Rule at 424 (emphasis added) (citing Ronald L. Wasserstein & Nicole A. Lazar, “The ASA Statement on p-Values: Context, Process, and Purpose,” 70 Am. Statistician 129, 131 (2016)).

[12] Yoav Benjamini, Richard D. DeVeaux, Bradly Efron, Scott Evans, Mark Glickman, Barry Braubard, Xuming He, Xiao Li Meng, Nancy Reid, Stephen M. Stigler, Stephen B. Vardeman, Christopher K. Wikle, Tommy Wright, Linda J. Young, and Karen Kafadar, “The ASA President’s Task Force Statement on Statistical Significance and Replicability,” 15 Annals of Applied Statistics 1084 (2021); see also “A Proclamation from the Task Force on Statistical Significance” (June 21, 2021).

[13] Sutera v. Perrier Group of America, Inc., 986 F. Supp. 655, 664-65 (D. Mass. 1997).

[14] Burst v. Shell Oil Co., 2015 WL 3755953, at *9 (E.D. La. June 16, 2015), aff’d, 650 F. App’x 170 (5th Cir. 2016). cert. denied. 137 S. Ct. 312 (2016); Henricksen v. ConocoPhillips Co., 605 F. Supp. 2d 1142, 1156 (E.D. Wa. 2009).

[15] In re Mirena Ius Levonorgestrel-Related Prod. Liab. Litig. (No. II), 341 F. Supp. 3d 213 (S.D.N.Y. 2018), aff’d, 982 F.3d 113 (2d Cir. 2020); In re Lipitor (Atorvastatin Calcium) Mktg., Sales Pracs. & Prods. Liab. Litig., 227 F. Supp. 3d 452 (D.S.C. 2017), aff’d, 892 F.3d 624 (4th Cir. 2018); In re: Zoloft (Sertraline Hydrocloride) Prod. Liab. Litig., No. 12-MD-2342, 2015 WL 7776911, at *1 (E.D. Pa. Dec. 2, 2015), aff’d, 858 F.3d 787 (3d Cir. 2017); In re Incretin-Based Therapies Prods. Liab. Litig., 524 F. Supp. 3d. 1007 (S.D. Cal. 2021); In re Viagra (Sildenafil Citrate) & Cialis (Tadalafil) Prod. Liab. Litig., 424 F. Supp. 3d 781, 798–99 (N.D. Cal. 2020).

Posted in Expert Witnesses, Rule 702, Scientific Evidence | 1 Comment »

Cheng’s Proposed Consensus Rule for Expert Witnesses

September 15th, 2022

Edward K. Cheng is the Hess Professor of Law in absentia from Vanderbilt Law School, while serving this fall as a visiting professor at Harvard. Professor Cheng is one of the authors of the multi-volume treatise, Modern Scientific Evidence, and the author of many articles on scientific and statistical evidence. Cheng’s most recent article, “The Consensus Rule: A New Approach to Scientific Evidence,”[1] while thought provoking, follows in the long-standing tradition of law school professors to advocate evidence law reforms, based upon theoretical considerations devoid of practical or real-world support.

Cheng’s argument for a radical restructuring of Rule 702 is based upon his judgment that jurors and judges are epistemically incompetent to evaluate expert witness opinion testimony. The current legal approach has trial judges acting as gatekeepers of expert witness testimony, and jurors acting as judges of factual scientific claims. Cheng would abolish these roles as beyond their ken.[2] Lay persons can, however, determine which party’s position is supported by the relevant expert community, which he presumes (without evidence) possesses the needed epistemic competence. Accordingly, Cheng would rewrite the legal system’s approach to important legal disputes, such as disputes over causal claims, from:

Whether a given substance causes a given disease

to

Whether the expert community believes that a given substance causes a given disease.

Cheng channels the philosophical understanding of the ancients who realized that one must have expertise to judge whether someone else has used that expertise correctly. And he channels the contemporary understanding that knowledge is a social endeavor, not the unique perspective of an individual in isolation. From these twin premisses, Cheng derives a radical and cynical proposal to reform the law of expert witness testimony. In his vision, experts would come to court not to give their own opinions, and certainly not to try to explain how they arrive at their opinions from the available evidence. For him, the current procedure is too much like playing chess with a monkey. The expert function would consist of telling the jury what the expert witness’s community believes.[3] Jurors would not decide the “actual substantive questions,” but simply decide what they believe the relevant expert witness community accepts as a consensus. This radical restructuring is what Cheng calls the “consensus rule.”

In this proposed “consensus rule,” there is no room for gatekeeping. Parties continue to call expert witnesses, but only as conduits for the “consensus” opinions of their fields. Indeed, Cheng’s proposal would radically limit expert witness to service as pollsters; their testimony would present only their views of what the consensus is in their fields. This polling information is the only evidence that the jury hear from expert witnesses, because this is the only evidence that Cheng believes the jury is epistemically competent to assess.[4]

Under Cheng’s Consensus Rule, when there is no consensus in the realm, the expert witness regime defaults to “anything goes,” without gatekeeping.[5] Judges would continue to exercise some control over who is qualified to testify, but only as far as the proposed experts must be in a position to know what the consensus is in their fields.

Cheng does not explain why, under his proposed “consensus rule,” subject matter experts are needed at all.  The parties might call librarians, or sociologists of science, to talk about the relevant evidence of consensus. If a party cannot afford a librarian expert witness, then perhaps lawyers could present directly the results of their PubMed, and other internet searches.

Cheng may be right that his “deferential approach” would eliminate having the inexpert passing judgment on the expert. The “consensus rule” would reduce science to polling, conducted informally, often without documentation or recording, by partisan expert witnesses. This proposal hardly better reflects, as he argues, the “true” nature of science. In Cheng’s vision, science in the courtroom is just a communal opinion, without evidence and without inference. To be sure, this alternative universe is tidier and less disputatious, but it is hardly science or knowledge. We are left with opinions about opinions, without data, without internal or external validity, and without good and sufficient facts and data.

Cheng claims that his proposed Consensus Rule is epistemically superior to Rule 702 gatekeeping. For the intellectual curious and able, his proposal is a counsel of despair. Deference to the herd, he tells us “is not merely optimal—it is the only practical strategy.”[6] In perhaps the most extreme overstatement of his thesis, Cheng tells us that

“deference is arguably not due to any individual at all! Individual experts can be incompetent, biased, error prone, or fickle—their personal judgments are not and have never been the source of reliability. Rather, proper deference is to the community of experts, all of the people who have spent their careers and considerable talents accumulating knowledge in their field.”[7]

Cheng’s hypothesized community of experts, however is worthy of deference only by virtue of the soundness of its judgments. If a community has not severely tested its opinions, then its existence as a community is irrelevant. Cheng’s deference is the sort of phenomenon that helped create Lysenkoism and other intellectual fads that were beyond challenge with actual data.

There is, I fear, some partial truth to Cheng’s judgment of juries and judges as epistemically incompetent, or challenged, to judge science, but his judgment seems greatly overstated. Finding aberrant jury verdicts would be easy, but Cheng provides no meaningful examples of gatekeeping gone wrong. Professor Cheng may have over-generalized in stating that judges are epistemically incompetent to make substantive expert determinations. He surely cannot be suggesting that judges never have sufficient scientific acumen to determine the relevance and reliability of expert witness opinion. If judges can, in some cases, make a reasonable go at gatekeeping, why then is Cheng advocating a general rule that strips all judges of all gatekeeping responsibility with respect to expert witnesses?

Clearly judges lack the technical resources, time, and background training to delve deeply into the methodological issues with which they may be confronted. This situation could be ameliorated by budgeting science advisors and independent expert witnesses, and by creating specialty courts staffed with judges that have scientific training. Cheng acknowledges this response, but he suggests that conflicts with “norms about generalist judges.”[8] This retreat to norms is curious in the face of Cheng’s radical proposals, and the prevalence of using specialist judges for adjudicating commercial and patent disputes.

Although Cheng is correct that assessing validity and reliability of scientific inferences and conclusions often cannot be reduced to a cookbook or checklist approach, not all expertise is as opaque as Cheng suggests. In his view, lawyers are deluded into thinking that they can understand the relevant science, with law professors being even worse offenders.[9] Cross-examining a technical expert witness can be difficult and challenging, but lawyers on both sides of the aisle occasionally demolish the most skilled and knowledgeable expert witnesses, on substantive grounds. And these demolitions happen to expert witnesses who typically, self-servingly claim that they have robust consensuses agreeing with their opinions.

While scolding us that we must get “comfortable with relying on the expertise and authority of others,” Cheng reassures us that deferring to authority is “not laziness or an abdication of our intellectual responsibility.”[10] According to Cheng, the only reason to defer to the opinion of expert is that they are telling us what their community would say.[11] Good reasons, sound evidence, and valid inference need not worry us in Cheng’s world.

Finding Consensus

Cheng tells us that his Consensus Rule would look something like:

“Rule 702A. If the relevant scientific community believes a fact involving specialized knowledge, then that fact is established accordingly.”

Imagine the endless litigation over what the “relevant” community is. For a health effect claim about a drug and heart attacks, is it the community of cardiologists or epidemiologists? Do we accept the pronouncements of the American Heart Association or those of the American College of Cardiology. If there is a clear consensus based upon a clinical trial, which appears to be based upon suspect data, is discovery of underlying data beyond the reach of litigants because the correctness of the allegedly dispositive study is simply not in issue? Would courts have to take judicial notice of the clear consensus and shut down any attempt to get to the truth of the matter?

Cheng acknowledges that cases will involve issues that are controversial or undeveloped, without expert community consensus. Many litigations start after publication of a single study or meta-analysis, which is hardly the basis for any consensus. Cheng appears content, in this expansive area, to revert to anything goes because if the expert community has not coalesced around a unified view, or if the community is divided, then the courts cannot do better than flipping a coin! Cheng’s proposal thus has a loophole the size of the Sun.

Cheng tells us, unhelpfully, that “[d]etermining consensus is difficult in some cases, and less so in others.”[12] Determining consensus may not be straightforward, but no matter. Consensus Rule questions are not epistemically challenging and thus “far more manageable,” because they requires no special expertise. (Again, why even call a subject matter expert witness, as opposed to a science journalist or librarian?) Cheng further advises that consensus is “a bit like the reasonable person standard in negligence,” but this simply conflates normative judgments with the scientific judgments.[13]

Cheng’s Consensus Rule would allow the use of a systematic review or a meta-analysis, not for evidence of the correctness of its conclusions, but only as evidence of a consensus.[14] The thought experiment of how this suggestion plays out in the real world may cause some agita. The litigation over Avandia began within days of the publication of a meta-analysis in the New England Journal of Medicine.[15] So some evidence of consensus; right? But then the letters to the editor within a few weeks of publication showed that the meta-analysis was fatally flawed. Inadmissible! Under the Consensus Rule the correctness or the methodological appropriateness of the meta-analysis is irrelevant. A few months later, another meta-analysis is published, which fails to find the risk that the original meta-analysis claimed. Is the trial now about which meta-analysis represents the community’s consensus, or are we thrown into the game of anything goes, where expert witnesses just say things, without judicial supervision?  A few years go by, and now there is a large clinical trial that supersedes all the meta-analyses of small trials.[16] Is a single large clinical trial now admissible as evidence of a new consensus, or are only systematic reviews and meta-analyses relevant evidence?

Cheng’s Consensus Rule will be useless in most determinations of specific causation.  It will be a very rare case indeed when a scientific organization issues a consensus statement about plaintiff John Doe. Very few tort cases involve putative causal agents that are thought to cause every instance of some disease in every person exposed to the agent. Even when a scientific community has addressed general causation, it will have rarely resolved all the uncertainty about the causal efficacy of all levels of exposure or the appropriate window of latency. So Cheng’s proposal guarantees to remove specific causation from the control of Rule 702 gatekeeping.

The potential for misrepresenting consensus is even greater than the misrepresentations of actual study results. At least the data are the data, but what will jurors do when they are regaled by testimony about the informal consensus reached in the hotel lobby of the latest scientific conference. Regulatory pronouncements that are based upon precautionary principles will be misrepresented as scientific consensus.  Findings by the International Agency for Research on Cancer that a substance is a IIA “probable human carcinogen” will be hawked as a consensus, even though the classification specifically disclaims any quantitative meaning for “probable,” and it directly equates to “insufficient” evidence of carcinogencity in humans.

In some cases, as Cheng notes, organizations such as the National Research Council, or the National Academy of Science, Engineering and Medicine (NASEM), will have weighed in on a controversy that has found its way into court.[17] Any help from such organizations will likely be illusory. Consider the 2006 publication of a comprehensive review of the available studies on non-pulmonary cancers and asbestos exposure by NASEM. The writing group presented its assessment of colorectal cancer as not causally associated with occupational asbestos exposure.[18] By 2007, the following year, expert witnesses for plaintiffs argued that the NASEM publication was no longer a consensus because one or two (truly inconsequential studies) had been published after the report and thus not considered. Under Cheng’s proposal, this dodge would appear to be enough to oust the consensus rule, and default to the “anything goes” rule. The scientific record can change rapidly, and many true consensus statements quickly find their way into the dustbin of scientific history.

Cheng greatly underestimates the difficulty in ascertaining “consensus.” Sometimes, to be sure, professional societies issue consensus statements, but they are often tentative and inconclusive. In many areas of science, there will be overlapping realms of expertise, with different disciplines issuing inconsistent “consensus” statements. Even within a single expert community, there may be two schools of thoughts about a particular issue.

There are instances, perhaps more than a few, when a consensus is epistemically flawed. If, as is the case in many health effect claims, plaintiffs rely upon the so-called linear no-threshold dose-response (LNT) theory of carcinogenesis, plaintiffs will point to regulatory pronouncements that embrace LNT as “the consensus.” When scientists are being honest, they generally recognize LNT as part of a precautionary principle approach, which may make sense as the foundation of “risk assessment.” The widespread assumption of LNT in regulatory agencies, and among scientists who work in such agencies, is understandable, but LNT remains an assumption. Nonetheless, we already see LNT hawked as a consensus, which under Cheng’s Consenus Rule would become the key dispositive issue, while quashing the mountain of evidence that there are, in fact, defense mechanisms to carcinogenesis that result in practical thresholds.

Beyond, regulatory pronouncements, some areas of scientific endeavor have themselves become politicized and extremist. Tobacco smoking surely causes lung cancer, but the studies of environmental tobacco smoking and lung cancer have been oversold. In areas of non-scientific disputes, such as history of alleged corporate malfeasance, juries will be treated to “the consensus” of Marxist labor historians, without having to consider the actual underlying historical documents. Cheng tells us that his Consensus Rule is a “realistic way of treating nonscientific expertise,”[19] which would seem to cover historian expert witness. Yet here, lawyers and lay fact finders are fully capable of exploring the glib historical conclusions of historian witnesses with cross-examination on the underlying documentary facts of the proffered opinions.

The Alleged Warrant for the Consensus Rule

If Professor Cheng is correct that the current judicial system, with decisions by juries and judges, is epistemically incompetent, does his Consensus Rule necessarily follow?  Not really. If we are going to engage in radical reforms, then the institutionalization of blue-ribbon juries would make much greater sense. As for Cheng’s claim that knowledge is “social,” the law of evidence already permits the use of true consensus statements as learned treatises, both to impeach expert witnesses who disagree, and (in federal court) to urge the truth of the learned treatise.

The gatekeeping process of Rule 702, which Professor Cheng would throw overboard, has important advantages in that judges ideally will articulate reasons for finding expert witness opinion testimony admissible or not. These reasons can be evaluated, discussed, and debated, with judges, lawyers, and the public involved. This gatekeeping process is rational and socially open.

Some Other Missteps in Cheng’s Argument

Experts on Both Sides are Too Extreme

Cheng’s proposal is based, in part, upon his assessment that the adversarial system causes the parties to choose expert witnesses “at the extremes.” Here again, Cheng provides no empirical evidence for his assessment. There is a mechanical assumption often made by people who do not bother to learn the details of a scientific dispute that the truth must somehow lie in the “middle.” For instance, in MDL 926, the silicone gel breast implant litigation, presiding Judge Sam Pointer complained about the parties’ expert witnesses being too extreme. Judge Pointer  believed that MDL judges should not entertain Rule 702 challenges, which were in his view properly heard by the transferor courts. As a result, Judge Robert Jones, and then Judge Jack Weinstein, conducted thorough Rule 702 hearings and found that the plaintiffs’ expert witnesses’ opinions were unreliable and insufficiently supported by the available evidence.[20] Judge Weinstein started the process of selecting court-appointed expert witnesses for the remaining New York cases, which goaded Judge Pointer into taking the process back to the MDL court level. After appointing four, highly qualified expert witnesses, Judge Pointer continued to believe that the parties’ expert witnesses were “extremists,” and that the courts’ own experts would come down somewhere between them.  When the court-appointed experts filed their reports, Judge Pointer was shocked that all four of his experts sided with the defense in rejecting the tendentious claims of plaintiffs’ expert witnesses.

Statistical Significance

Along the way, in advocating his radical proposal, Professor Cheng made some other curious announcements. For instance, he tells us that “[w]hile historically used as a rule of thumb, statisticians have now concluded that using the 0.05 [p-value] threshold is more distortive than helpful.”[21] Cheng’s purpose here is unclear, but the source he cited does not remotely support his statement, and certainly not his gross overgeneralization about “statisticians.” If this is the way he envisions experts will report “consensus,” then his program seems broken at its inception. The American Statistical Association’s (ASA) p-value “consensus” statement articulated six principles, the third of which noted that

“[s]cientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.”

This is a few light years away from statisticians’ concluding that statistical significance thresholds are more distortive than helpful. The ASA p-value statement further explains that

“[t]he widespread use of ‘statistical significance’ (generally interpreted as ‘p < 0.05’) as a license for making a claim of a scientific finding (or implied truth) leads to considerable distortion of the scientific process.”[22]

In the science of health effects, statistical significance remains extremely important, but it has never been a license for making causal claims. As Sir Austin Bradford Hill noted in his famous after-dinner speech, ruling out chance (and bias) as an explanation for an association was merely a predicate for evaluating the association for causality.[23]

Over-endorsing Animal Studies

Under Professor Cheng’s Consensus Rule, the appropriate consensus might well be one generated solely by animal studies. Cheng tells that “perhaps” scientists do not consider toxicology when the pertinent epidemiology is “clear.” When the epidemiology, however, is unclear, scientists consider toxicology.[24] Well, of course, but the key question is whether a consensus about causation in humans will be based upon non-human animal studies. Cheng seems to answer this question in the affirmative by criticizing courts that have required epidemiologic studies “even though the entire field of toxicology uses tissue and animal studies to make inferences, often in combination with and especially in the absence of epidemiology.”[25] The vitality of the field of toxicology is hardly undermined by its not generally providing sufficient grounds for judgments of human causation.

Relative Risk Greater Than Two

In the midst of his argument for the Consensus Rule, Cheng points critically to what he calls “questionable proxies” for scientific certainty. One such proxy is the judicial requirement of risk ratios in excess of two. His short discussion appears to be focused upon the inference of specific causation in a given case, but it leads to a non-sequitur:

“Some courts have required a relative risk of 2.0 in toxic tort cases, requiring a doubling of the population risk before considering causation.73 But the preponderance standard does not require that the substance more likely than not caused any case of the disease in the population, it requires that the substance more likely than not caused the plaintiff’s case.”[26]

Of course, it is exactly because we are interested in the probability of causation of the plaintiff’s case, that we advert to the risk ratio to give us some sense whether “more likely than not” the exposure caused plaintiff’s case. Unless plaintiff can show he is somehow unique, he is “any case.” In many instances, plaintiff cannot show how he is different from the participants of the study that gave rise to the risk ratio less than two.

[1] Edward K. Cheng, “The Consensus Rule: A New Approach to Scientific Evidence,” 75 Vanderbilt L. Rev. 407 (2022) [Consensus Rule].

[2] Consensus Rule at 410 (“The judge and the jury, lacking in expertise, are not competent to handle the questions that the Daubert framework assigns to them.”)

[3] Consensus Rule at 467 (“Under the Consensus Rule, experts no longer offer their personal opinions on causation or teach the jury how to assess the underlying studies. Instead, their testimony focuses on what the expert community as a whole believes about causation.”)

[4] Consensus Rule at 467.

[5] Consensus Rule at 437.

[6] Consensus Rule at 434.

[7] Consensus Rule at 434.

[8] Consensus Rule at 422.

[9] Consensus Rule at 429.

[10] Consensus Rule at 432-33.

[11] Consensus Rule at 434.

[12] Consensus Rule at 456.

[13] Consensus Rule at 457.

[14] Consensus Rule at 459.

[15] Steven E. Nissen, M.D., and Kathy Wolski, M.P.H., “Effect of Rosiglitazone on the Risk of Myocardial Infarction and Death from Cardiovascular Causes,” 356 New Engl. J. Med. 2457 (2007).

[16] P.D. Home, et al., “Rosiglitazone Evaluated for Cardiovascular Outcomes in Oral Agent Combination Therapy for Type 2 Diabetes (RECORD), 373 Lancet 2125 (2009).

[17] Consensus Rule at 458.

[18] Jonathan M. Samet, et al., Asbestos: Selected Health Effects (2006).

[19] Consensus Rule at 445.

[20] Hall v. Baxter Healthcare Corp., 947 F. Supp.1387 (D. Or. 1996) (excluding plaintiffs’ expert witnesses’ causation opinions); In re Breast Implant Cases, 942 F. Supp. 958 (E. & S.D.N.Y. 1996) (granting partial summary judgment on claims of systemic disease causation).

[21] Consenus Rule at 424 (citing Ronald L. Wasserstein & Nicole A. Lazar, “The ASA Statement on p-Values: Context, Process, and Purpose,” 70 Am. Statistician 129, 131 (2016)).

[22] Id.

[23] Austin Bradford Hill, “The Environment and Disease: Association or Causation?” 58 Proc. Royal Soc’y Med. 295, 295 (1965). See Schachtman, “Ruling Out Bias & Confounding is Necessary to Evaluate Expert Witness Causation Opinions” (Oct. 29, 2018); “Woodside & Davis on the Bradford Hill Considerations” (Aug. 23, 2013); Frank C. Woodside, III & Allison G. Davis, “The Bradford Hill Criteria: The Forgotten Predicate,” 35 Thomas Jefferson L. Rev. 103 (2013).

[24] Consensus Rule at 444.

[25] Consensus Rule at 424 & n. 74 (citing to one of multiple court advisory expert witnesses in Hall v. Baxter Healthcare Corp., 947 F. Supp.1387, 1449 (D. Or. 1996), who suggested that toxicology would be appropriate to consider when the epidemiology was not clear). Citing to one outlier advisor is a rather strange move for Cheng considering that the “consensus” was readily discernible to the trial judge in Hall, and to Judge Jack Weinstein, a few months later, in In re Breast Implant Cases, 942 F. Supp. 958 (E. & S.D.N.Y. 1996).

[26] Consensus Rule at 424 & n. 73 (citing Lucinda M. Finley, “Guarding the Gate to the Courthouse: How Trial Judges Are Using Their Evidentiary Screening Role to Remake Tort Causation Rules,” 49 Depaul L. Rev. 335, 348–49 (2000). See Schachtman, “Rhetorical Strategy in Characterizing Scientific Burdens of Proof” (Nov. 15, 2014).

Posted in Causation, Expert Witnesses, Rule 702, Scientific Evidence | 3 Comments »

Amicus Curious – Gelbach’s Foray into Lipitor Litigation

August 25th, 2022

Professor Schauer’s discussion of statistical significance, covered in my last post,[1] is curious for its disclaimer that “there is no claim here that measures of statistical significance map easily onto measures of the burden of proof.” Having made the disclaimer, Schauer proceeds to falls into the transposition fallacy, which contradicts his disclaimer, and, generally speaking, is not a good thing for a law professor eager to advance the understanding of “The Proof,” to do.

Perhaps more curious than Schauer’s error is his citation support for his disclaimer.[2] The cited paper by Jonah B. Gelbach is one of several of Gelbach’s papers that advances the claim that the p-value does indeed map onto posterior probability and the burden of proof. Gelbach’s claim has also been the center piece in his role as an advocate in support of plaintiffs in the Lipitor (atorvastatin) multi-district litigation (MDL) over claims that ingestion of atorvastatin causes diabetes mellitus.

Gelbach’s intervention as plaintiffs’ amicus is peculiar on many fronts. At the time of the Lipitor litigation, Sonal Singh was an epidemiologist and Assistant Professor of Medicine, at the Johns Hopkins University. The MDL trial court initially held that Singh’s proffered testimony was inadmissible because of his failure to consider daily dose.[3] In a second attempt, Singh offered an opinion for 10 mg daily dose of atorvastatin, based largely upon the results of a clinical trial known as ASCOT-LLA.[4]

The ASCOT-LLA trial randomized 19,342 participants with hypertension and at least three other cardiovascular risk factors to two different anti-hypertensive medications. A subgroup with total cholesterol levels less than or equal to 6.5 mmol./l. were randomized to either daily 10 mg. atorvastatin or placebo.  The investigators planned to follow up for five years, but they stopped after 3.3 years because of clear benefit on the primary composite end point of non-fatal myocardial infarction and fatal coronary heart disease. At the time of stopping, there were 100 events of the primary pre-specified outcome in the atorvastatin group, compared with 154 events in the placebo group (hazard ratio 0.64 [95% CI 0.50 – 0.83], p = 0.0005).

The atorvastatin component of ASCOT-LLA had, in addition to its primary pre-specified outcome, seven secondary end points, and seven tertiary end points.  The emergence of diabetes mellitus in this trial population, which clearly was at high risk of developing diabetes, was one of the tertiary end points. Primary, secondary, and tertiary end points were reported in ASCOT-LLA without adjustment for the obvious multiple comparisons. In the treatment group, 3.0% developed diabetes over the course of the trial, whereas 2.6% developed diabetes in the placebo group. The unadjusted hazard ratio was 1.15 (0.91 – 1.44), p = 0.2493.[5] Given the 15 trial end points, an adjusted p-value for this particular hazard ratio, for diabetes, might well exceed 0.5, and even approach 1.0.

On this record, Dr. Singh honestly acknowledged that statistical significance was important, and that the diabetes finding in ASCOT-LLA might have been the result of low statistical power or of no association at all. Based upon the trial data alone, he testified that “one can neither confirm nor deny that atorvastatin 10 mg is associated with significantly increased risk of type 2 diabetes.”[6] The trial court excluded Dr. Singh’s 10mg/day causal opinion, but admitted his 80mg/day opinion. On appeal, the Fourth Circuit affirmed the MDL district court’s rulings.[7]

Jonah Gelbach is a professor of law at the University of California at Berkeley. He attended Yale Law School, and received his doctorate in economics from MIT.

Professor Gelbach entered the Lipitor fray to present a single issue: whether statistical significance at conventionally demanding levels such as 5 percent is an appropriate basis for excluding expert testimony based on statistical evidence from a single study that did not achieve statistical significance.

Professor Gelbach is no stranger to antic proposals.[8] As amicus curious in the Lipitor litigation, Gelbach asserts that plaintiffs’ expert witness, Dr. Singh, was wrong in his testimony about not being able to confirm the ASCOT-LLA association because he, Gelbach, could confirm the association.[9] Ultimately, the Fourth Circuit did not discuss Gelbach’s contentions, which is not surprising considering that the asserted arguments and alleged factual considerations were not only dehors the record, but in contradiction of the record.

Gelbach’s curious claim is that any time a risk ratio, for an exposure and an outcome of interest, is greater than 1.0, with a p-value < 0.5,[10] the evidence should be not only admissible, but sufficient to support a conclusion of causation. Gelbach states his claim in the context of discussing a single randomized controlled trial (ASCOT-LLA), but his broad pronouncements are carelessly framed such that others may take them to apply to a single observational study, with its greater threats to internal validity.

Contra Kumho Tire

To get to his conclusion, Gelbach attempts to remove the constraints of traditional standards of significance probability. Kumho Tire teaches that expert witnesses must “employ[] in the courtroom the same level of intellectual rigor that characterizes the practice of an expert in the relevant field.”[11] For Gelbach, this “eminently reasonable admonition” does not impose any constraints on statistical inference in the courtroom. Statistical significance at traditional levels (p < 0.05) is for elitist scholarly work, not for the “practical” rent-seeking work of the tort bar. According to Gelbach, the inflation of the significance level ten-fold to p < 0.5 is merely a matter of “weight” and not admissibility of any challenged opinion testimony.

Likelihood Ratios and Posterior Probabilities

Gelbach maintains that any evidence that has a likelihood ratio (LR > 1) greater than one is relevant, and should be admissible under Federal Rule of Evidence 401.[12] This argument ignores the other operative Federal Rules of Evidence, namely 702 and 703, which impose additional criteria of admissibility for expert witness opinion testimony.

With respect to variance and random error, Gelbach tells us that any evidence that generates a LR > 1, should be admitted when “the statistical evidence is statistically significant below the 50 percent level, which will be true when the p-value is less than 0.5.”[13]

At times, Gelbach seems to be discussing the admissibility of the ASCOT-LLA study itself, and not the proffered opinion testimony of Dr. Singh. The study itself would not be admissible, although it is clearly the sort of hearsay an expert witness in the field may consider. If Dr. Singh were to have reframed and recalculated the statistical comparisons, then the Rule 703 requirement of “reasonable reliance” by scientists in the field of interest may not have been satisfied.

Gelbach also generates a posterior probability (0.77), which is based upon his calculations from data in the ASCOT-LLA trial, and not the posterior probability of Dr. Singh’s opinion. The posterior probability, as calculated, is problematic on many fronts.

Gelbach does not present his calculations – for the sake of brevity he says – but he tells us that the ASCOT-LLA data yield a likelihood ratio of roughly 1.9, and a p-value of 0.126.[14] What the clinical trialists reported was a hazard ratio of 1.15, which is a weak association on most researchers’ scales, with a two-sided p-value of 0.25, which is five times higher than the usual 5 percent. Gelbach does not explain how or why his calculated p-value for the likelihood ratio is roughly half the unadjusted, two-sided p-value for the tertiary outcome from ASCOT-LLA.

As noted, the reported diabetes hazard ratio of 1.15 was a tertiary outcome for the ASCOT trial, one of 15 calculated by the trialists, with p-values unadjusted for multiple comparisons.  The failure to adjust is perhaps excusable in that some (but certainly not all) of the outcome variables are overlapping or correlated. A sophisticated reader would not be misled; only when someone like Gelbach attempts to manufacture an inflated posterior probability without accounting for the gross underestimate in variance is there an insult to statistical science. Gelbach’s recalculated p-value for his LR, if adjusted for the multiplicity of comparisons in this trial, would likely exceed 0.5, rendering all his arguments nugatory.

Using the statistics as presented by the published ASCOT-LLA trial to generate a posterior probability also ignores the potential biases (systematic errors) in data collection, the unadjusted hazard ratios, the potential for departures from random sampling, errors in administering the participant recruiting and inclusion process, and other errors in measurements, data collection, data cleaning, and reporting.

Gelbach correctly notes that there is nothing methodologically inappropriate in advocating likelihood ratios, but he is less than forthcoming in explaining that such ratios translate into a posterior probability only if he posits a prior probability of 0.5.[15] His pretense to having simply stated “mathematical facts” unravels when we consider his extreme, unrealistic, and unscientific assumptions.

The Problematic Prior

Gelbach’s glibly assumes that the starting point, the prior probability, for his analysis of Dr. Singh’s opinion is 50%. This is an old and common mistake,[16] long since debunked.[17] Gelbach’s assumption is part of an old controversy, which surfaced in early cases concerning disputed paternity. The assumption, however, is wrong legally and philosophically.

The law simply does not hand out 0.5 prior probability to both parties at the beginning of a trial. As Professor Jaffee noted almost 35 years ago:

“In the world of Anglo-American jurisprudence, every defendant, civil and criminal, is presumed not liable. So, every claim (civil or criminal) starts at ground zero (with no legal probability) and depends entirely upon proofs actually adduced.”[18]

Gelbach assumes that assigning “equal prior probability” to two adverse parties is fair, because the fact-finder would not start hearing evidence with any notion of which party’s contentions are correct. The 0.5/0.5 starting point, however, is neither fair nor is it the law.[19] The even odds prior is also not good science.

The defense is entitled to a presumption that it is not liable, and the plaintiff must start at zero.  Bayesians understand that this is the death knell of their beautiful model.  If the prior probability is zero, then Bayes’ Theorem tells us mathematically that no evidence, no matter how large a likelihood ratio, can move the prior probability of zero towards one. Bayes’ theorem may be a correct statement about inverse probabilities, but still be an inadequate or inaccurate model for how factfinders do, or should, reason in determining the ultimate facts of a case.

We can see how unrealistic and unfair Gelbach’s implied prior probability is if we visualize the proof process as a football field.  To win, plaintiffs do not need to score a touchdown; they need only cross the mid-field 50-yard line. Rather than making plaintiffs start at the zero-yard line, however, Gelbach would put them right on the 50-yard line. Since one toe over the mid-field line is victory, the plaintiff is spotted 99.99+% of its burden of having to present evidence to build up 50% probability. Instead, plaintiffs are allowed to scoot from the zero yard line right up claiming success, where even the slightest breeze might give them winning cases. Somehow, in the model, plaintiffs no longer have to present evidence to traverse the first half of the field.

The even odds starting point is completely unrealistic in terms of the events upon which the parties are wagering. The ASCOT-LLA study might have shown a protective association between atorvastatin and diabetes, or it might have shown no association at all, or it might have show a larger hazard ratio than measured in this particular sample. Recall that the confidence interval for hazard ratios for diabetes ran from 0.91 to 1.44. In other words, parameters from 0.91 (protective association) to 1.0 (no association), to 1.44 (harmful association) were all reasonably compatible with the observed statistic, based upon this one study’s data. The potential outcomes are not binary, which makes the even odds starting point inappropriate.[20]

[1] “Schauer’s Long Footnote on Statistical Significance” (Aug. 21, 2022).

[2] Frederick Schauer, The Proof: Uses of Evidence in Law, Politics, and Everything Else 54-55 (2022) (citing Michelle M. Burtis, Jonah B. Gelbach, and Bruce H. Kobayashi, “Error Costs, Legal Standards of Proof, and Statistical Significance,” 25 Supreme Court Economic Rev. 1 (2017).

[3] In re Lipitor Mktg., Sales Practices & Prods. Liab. Litig., MDL No. 2:14–mn–02502–RMG, 2015 WL 6941132, at *1  (D.S.C. Oct. 22, 2015).

[4] Peter S. Sever, et al., “Prevention of coronary and stroke events with atorvastatin in hypertensive patients who have average or lower-than-average cholesterol concentrations, in the Anglo-Scandinavian Cardiac Outcomes Trial Lipid Lowering Arm (ASCOT-LLA): a multicentre randomised controlled trial,” 361 Lancet 1149 (2003). [cited here as ASCOT-LLA]

[5] ASCOT-LLA at 1153 & Table 3.

[6][6] In re Lipitor Mktg., Sales Practices & Prods. Liab. Litig., 174 F.Supp. 3d 911, 921 (D.S.C. 2016) (quoting Dr. Singh’s testimony).

[7] In re Lipitor Mktg., Sales Practices & Prods. Liab. Litig., 892 F.3d 624, 638-39 (2018) (affirming MDL trial court’s exclusion in part of Dr. Singh).

[8] See “Expert Witness Mining – Antic Proposals for Reform” (Nov. 4, 2014).

[9] Brief for Amicus Curiae Jonah B. Gelbach in Support of Plaintiffs-Appellants, In re Lipitor Mktg., Sales Practices & Prods. Liab. Litig., 2017 WL 1628475 (April 28, 2017). [Cited as Gelbach]

[10] Gelbach at *2.

[11] Kumho Tire Co. v. Carmichael, 526 U.S. 137, 152 (1999).

[12] Gelbach at *5.

[13] Gelbach at *2, *6.

[14] Gelbach at *15.

[15] Gelbach at *19-20.

[16] See Richard A. Posner, “An Economic Approach to the Law of Evidence,” 51 Stanford L. Rev. 1477, 1514 (1999) (asserting that the “unbiased fact-finder” should start hearing a case with even odds; “[I]deally we want the trier of fact to work from prior odds of 1 to 1 that the plaintiff or prosecutor has a meritorious case. A substantial departure from this position, in either direction, marks the trier of fact as biased.”).

[17] See, e.g., Richard D. Friedman, “A Presumption of Innocence, Not of Even Odds,” 52 Stan. L. Rev. 874 (2000). [Friedman]

[18] Leonard R. Jaffee, “Prior Probability – A Black Hole in the Mathematician’s View of the Sufficiency and Weight of Evidence,” 9 Cardozo L. Rev. 967, 986 (1988).

[19] Id. at p.994 & n.35.

[20] Friedman at 877.

Posted in Causation, Evidence, Expert Witnesses, Rule 702, Scientific Evidence, statistical evidence | No Comments »

Madigan’s Shenanigans & Wells Quelled in Incretin-Mimetic Cases

July 15th, 2022

The incretin-mimetic litigation involved claims that the use of Byetta, Januvia, Janumet, and Victoza medications causes pancreatic cancer. All four medications treat diabetes mellitus through incretin hormones, which stimulate or support insulin production, which in turn lowers blood sugar. On Planet Earth, the only scientists who contend that these medications cause pancreatic cancer are those hired by the lawsuit industry.

The cases against the manufacturers of the incretin-mimetic medications were consolidated for pre-trial proceedings in federal court, pursuant to the multi-district litigation (MDL) statute, 28 US Code § 1407. After years of MDL proceedings, the trial court dismissed the cases as barred by the doctrine of federal preemption, and for good measure, excluded plaintiffs’ medical causation expert witnesses from testifying.[1] If there were any doubt about the false claiming in this MDL, the district court’s dismissals were affirmed by the Ninth Circuit.[2]

The district court’s application of Federal Rule of Evidence 702 to the plaintiffs’ expert witnesses’ opinion is an important essay in patho-epistemology. The challenged expert witnesses provided many examples of invalid study design and interpretation. Of particular interest, two of the plaintiffs’ high-volume statistician testifiers, David Madigan and Martin Wells, proffered their own meta-analyses of clinical trial safety data. Although the current edition of the Reference Manual on Scientific Evidence[3] provides virtually no guidance to judges for assessing the validity of meta-analyses, judges and counsel do now have other readily available sources, such as the FDA’s Guidance on meta-analysis of safety outcomes of clinical trials.[4] Luckily for the Incretin-Mimetics pancreatic cancer MDL judge, the misuse of meta-analysis methodology by plaintiffs’ statistician expert witnesses, David Madigan and Martin Wells was intuitively obvious.

Madigan and Wells had a large set of clinical trials at their disposal, with adverse safety outcomes assiduously collected. As is the case with many clinical trial safety outcomes, the trialists will often have a procedure for blinded or unblinded adjudication of safety events, such as pancreatic cancer diagnosis.

At deposition, Madigan testified that he counted only adjudicated cases of pancreatic cancer in his meta-analyses, which seems reasonable enough. As discovery revealed, however, Madigan employed the restrictive inclusion criteria of adjudicated pancreatic cancer only to the placebo group, not to the experimental group. His use of restrictive inclusion criteria for only the placebo group had the effect of excluding several non-adjudicated events, with the obvious spurious inflation of risk ratios. The MDL court thus found with relative ease that Madigan’s “unequal application of criteria among the two groups inevitably skews the data and critically undermines the reliability of his analysis.” The unexplained, unjustified change in methodology revealed Madigan’s unreliable “cherry-picking” and lack of scientific rigor as producing a result-driven meta-analyses.[5]

The MDL court similarly found that Wells’ reports “were marred by a selective review of data and inconsistent application of inclusion criteria.”[6] Like Madigan, Wells cherry picked studies. For instance, he excluded one study, EXSCEL, on grounds that it reported “a high pancreatic cancer event rate in the comparison group as compared to background rate in the general population….”[7] Wells’ explanation blatantly failed, however, given that the entire patient population of the clinical trial had diabetes, a known risk factor for pancreatic cancer.[8]

As Professor Ioannidis and others have noted, we are awash in misleading meta-analyses:

“Currently, there is massive production of unnecessary, misleading, and conflicted systematic reviews and meta-analyses. Instead of promoting evidence-based medicine and health care, these instruments often serve mostly as easily produced publishable units or marketing tools.  Suboptimal systematic reviews and meta-analyses can be harmful given the major prestige and influence these types of studies have acquired.  The publication of systematic reviews and meta-analyses should be realigned to remove biases and vested interests and to integrate them better with the primary production of evidence.”[9]

Whether created for litigation, like the Madigan-Wells meta-analyses, or published in the “peer-reviewed” literature, courts will have to up their game in assessing the validity of such studies. Published meta-analyses have grown exponentially from the 1990s to the present. To date, 248,886 meta-analyses have been published, according the National Library of Medicine’s Pub-Med database. Last year saw over 35,000 meta-analyses published. So far, this year, 20,416 meta-analyses have been published, and we appear to be on track to have a bumper crop.

The data analytics from Pub-Med provide a helpful visual representation of the growth of meta-analyses in biomedical science.

 

Count of Publications with Keyword Meta-analysis in Pub-Med Database

In 1979, the year I started law school, one meta-analysis was published. Lawyers could still legitimately argue that meta-analyses involved novel methodology that had not been generally accepted. The novelty of meta-analysis wore off sometime between 1988, when Judge Robert Kelly excluded William Nicholson’s meta-analysis of health outcomes among PCB-exposed workers, on grounds that such analyses were “novel,” and 1990, when the Third Circuit reversed Judge Kelly, with instructions to assess study validity.[10] Fortunately, or not, depending upon your point of view, plaintiffs dropped Nicholson’s meta-analysis in subsequent proceedings. A close look at Nicholson’s non-peer reviewed calculations shows that he failed to standardize for age or sex, and that he merely added observed and expected cases, across studies, without weighting by individual study variance. The trial court never had the opportunity to assess the validity vel non of Nicholson’s ersatz meta-analysis.[11] Today, trial courts must pick up on the challenge of assessing study validity of meta-analyses relied upon by expert witnesses, regulatory agencies, and systematic reviews.

[1] In re Incretin-Based Therapies Prods. Liab. Litig., 524 F.Supp.3d 1007 (S.D. Cal. 2021).

[2] In re Incretin-Based Therapies Prods. Liab. Litig., No. 21-55342, 2022 WL 898595 (9th Cir. Mar. 28, 2022) (per curiam)

[3]  “The Treatment of Meta-Analysis in the Third Edition of the Reference Manual on Scientific Evidence” (Nov. 15, 2011).

[4] Food and Drug Administration, Center for Drug Evaluation and Research, “Meta-Analyses of Randomized Controlled Clinical Trials to Evaluate the Safety of Human Drugs or Biological Products – (Draft) Guidance for Industry” (Nov. 2018); Jonathan J. Deeks, Julian P.T. Higgins, Douglas G. Altman, “Analysing data and undertaking meta-analyses,” Chapter 10, in Julian P.T. Higgins, James Thomas, Jacqueline Chandler, Miranda Cumpston, Tianjing Li, Matthew J. Page, and Vivian Welch, eds., Cochrane Handbook for Systematic Reviews of Interventions (version 6.3 updated February 2022); Donna F. Stroup, Jesse A. Berlin, Sally C. Morton, Ingram Olkin, G. David Williamson, Drummond Rennie, David Moher, Betsy J. Becker, Theresa Ann Sipe, Stephen B. Thacker, “Meta-Analysis of Observational Studies: A Proposal for Reporting,” 283 J. Am. Med. Ass’n 2008 (2000); David Moher, Alessandro Liberati, Jennifer Tetzlaff, and Douglas G Altman, “Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement,” 6 PLoS Med e1000097 (2009).

[5] In re Incretin-Based Therapies Prods. Liab. Litig., 524 F.Supp.3d 1007, 1037 (S.D. Cal. 2021). See In re Lipitor (Atorvastatin Calcium) Mktg., Sales Practices & Prods. Liab. Litig. (No. II) MDL2502, 892 F.3d 624, 634 (4th Cir. 2018) (“Result-driven analysis, or cherry-picking, undermines principles of the scientific method and is a quintessential example of applying methodologies (valid or otherwise) in an unreliable fashion.”).

[6] In re Incretin-Based Therapies Prods. Liab. Litig., 524 F.Supp.3d 1007, 1043 (S.D. Cal. 2021).

[7] Id. at 1038.

[8] See, e.g., Albert B. Lowenfels & Patrick Maisonneuve, “Risk factors for pancreatic cancer,” 95 J. Cellular Biochem. 649 (2005).

[9] John P. Ioannidis, “The mass production of redundant, misleading, and conflicted systematic reviews and meta-analyses,” 94 Milbank Quarterly 485 (2016).

[10] In re Paoli R.R. Yard PCB Litig., 706 F. Supp. 358, 373 (E.D. Pa. 1988), rev’d and remanded, 916 F.2d 829, 856-57 (3d Cir. 1990), cert. denied, 499 U.S. 961 (1991). See also Hines v. Consol. Rail Corp., 926 F.2d 262, 273 (3d Cir. 1991).

[11] “The Shmeta-Analysis in Paoli” (July 11, 2019). See  James A. Hanley, Gilles Thériault, Ralf Reintjes and Annette de Boer, “Simpson’s Paradox in Meta-Analysis,” 11 Epidemiology 613 (2000); H. James Norton & George Divine, “Simpson’s paradox and how to avoid it,” Significance 40 (Aug. 2015); George Udny Yule, “Notes on the theory of association of attributes in statistics,” 2 Biometrika 121 (1903).

Posted in Causation, Expert Witness Hall of Shame, Meta-analysis, Rule 702, Scientific Evidence, Scientific Misconduct, statistical evidence | 1 Comment »

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