For your delectation and delight, desultory dicta on the law of delicts.

New Superhero?

December 31st, 2012

The Verdict. A Civil Action. Class ActionMy Cousin Vinnie.

Wonder Woman, Superman, Batman, Ironman.

America loves movies, and superheroes.

So 2013 should be an exciting year with a new superhero movie coming to a theater, or a courthouse, near you: Egilman.

Actor-producer-director Patrick Coppola has announced that he is developing a film, which has yet to be given a catchy name.  Coppola calls the film in development:  the DOCTOR DAVID EGILMAN PROJECT.  According to Coppola, he was hired by

“by world famous MD – Doctor David Egilman to create and write a Screenplay based on Doctor Egilman’s life and the many cases he has served on as an expert witness in various chemical poisoning trials. Doctor Egilman is a champion of the underdog and has several worldwide charities and medical clinics he funds and donates his time to.”

Patrick Coppola describes his screenplay for the “Doctor David Egilman Project” as a story of conspiracy among corporate suppliers of beryllium materials, the government, and the thought leaders in occupational medicine to suppress information about harm to workers. In this narrative, which is a familiar refrain for plaintiffs’ counsel in toxic tort litigation, profits always take precedence over safety, and unions mysteriously are silently complicit in the carnage.

Can’t wait!


Reanalysis of Epidemiologic Studies – Not Intrinsically WOEful

December 27th, 2012

A recent student law review article discusses reanalyses of epidemiologic studies, an important, and overlooked topic in the jurisprudence of scientific evidence.  Alexander J. Bandza, “Epidemiological-Study Reanalyses and Daubert: A Modest Proposal to Level the Playing Field in Toxic Tort Litigation,” 39 Ecology L. Q. 247 (2012).

In the Daubert case itself, the Ninth Circuit, speaking through Judge Kozinksi, avoided the methodological issues raised by Shanna Swan’s reanalysis of Bendectin epidemiologic studies, by assuming arguendo its validity, and holding that the small relative risk yielded by the reanalysis would not support a jury verdict of specific causation. Daubert v. Merrell Dow Pharm., Inc., 43 F.3d 1311, 1317–18 (9th Cir. 1995).

There is much that can, and should, be said about reanalyses in litigation and in the scientific process, but Bandza never really gets down to the business at hand. His 36 page article curiously does not begin to address reanalysis until the bottom of the 20th page. The first half of the article, and then some, reviews some time-worn insights and factoids about scientific evidence. Finally, at page 266, the author introduces and defines reanalysis:

“Reanalysis occurs ‘when a person other than the original investigator obtains an epidemiologic data set and conducts analyses to evaluate the quality, reliability or validity of the dataset, methods, results or conclusions reported by the original investigator’.”

Bandza at 266 (quoting Raymond Neutra et al., “Toward Guidelines for the Ethical Reanalysis and Reinterpretation of Another’s Research,” 17 Epidemiology 335, 335 (2006).

Bandza correctly identifies some of the bases for judicial hostility to re-analyses. For instance, some courts are troubled or confused when expert witnesses disagree with, or reevaluate, the conclusions of a published article. The witnesses’ conclusions may not be published or peer reviewed, and thus the proffered testimony fails one of the Daubert factors.  Bandza correctly notes that peer review is greatly overrated by judges. Bandza at 270. I would add that peer review is an inappropriate proxy for validity, a “test,” which reflects a distrust of the unpublished.  Unfortunately, this judicial factor ignores the poor quality of much of what is published, and the extreme variability in the peer review process. Judges overrate peer review because they are desperate for a proxy for validity of the studies relied upon, which will allow them to pass their gatekeeping responsibility on to the jury. Furthermore, the authors’ own conclusions are hearsay, and their qualifications are often not fully before the court.  What is important is the opinion of the expert witness who can be cross-examined and challenged.  SeeFOLLOW THE DATA, NOT THE DISCUSSION.” What counts is the validity of the expert witness’s reasoning and inferences.

Bandza’s article, which by title advertises itself to be about re-analyses, gives only a few examples of re-analyses without much detail.  He notes concerns that reanalyses may impugn the reputation of published scientists, and burden them with defending their data.  Who would have it any other way? After this short discussion, the article careens into a discussion of “weight of the evidence” (WOE) methodology. Bandza tells us that the rejection of re-analyses in judicial proceedings “implicitly rules out using the weight-of-the-evidence methodology often appropriate for, or even necessary to, scientific analysis of potentially toxic substances.” Bandza at 270.  This argument, however, is one sustained non-sequitur.  WOE is defined in several ways, but none of the definitions require or suggest the incorporation of re-analyses. Re-analyses raise reliability and validity issues regardless whether an expert witness incorporates them into a WOE assessment. Yet Bandza tells us that the rejection of re-analyses “Implicitly Ignores the Weight-of-the-Evidence Methodology Appropriate for the Scientific Analysis of Potentially Toxic Substances.” Bandza at 274. This conclusion simply does not follow from the nature of WOE methodology or reanalyses.

Bandza’s ipse dixit raises the independent issue whether WOE methodology is appropriate for scientific analysis. WOE is described as embraced or used by regulatory agencies, but that description hardly recommends the methodology as the basis for a scientific, as opposed to a regulatory, conclusion.  Furthermore, Bandza ignores the ambiguity and variability of WOE by referring to it as a methodology, when in reality, WOE is used to describe a wide variety of methods of reasoning to a conclusion. Bandza cites Douglas Weed’s article on WOE, but fails to come to grips with the serious objections raised by Weed in his article to the use of WOE methodologies.  Douglas Weed, “Weight of Evidence: A Review of Concept and Methods,” 25 Risk Analysis 1545, 1546–52 (2005) (describing the vagueness and imprecision of WOE methodologies). See also “WOE-fully Inadequate Methodology – An Ipse Dixit By Another Name.”

Bandza concludes his article with a hymn to the First Circuit’s decision in Milward v. Acuity Specialty Products Group, Inc., 639 F.3d 11 (1st Cir. 2011). Plaintiffs’ expert witness, Dr. Martyn Smith claimed to have performed a WOE analysis, which in turn was based upon a re-analysis of several epidemiologic studies. True, true, and immaterial.  The re-analyses were not inherently a part of a WOE approach. Presumably, Smith re-analyzed some of the epidemiologic studies because he felt that the data as presented did not support his desired conclusion.  Given the motivations at work, the district court in Milward was correct to look skeptically and critically at the re-analyses.

Bandza notes that there are procedural and evidentiary safeguards in federal court against unreliable or invalid re-analyses of epidemiologic studies.  Bandza at 277. Yes, there are safeguards but they help only when they are actually used. The First Circuit in Milward reversed the district court for looking too closely at the re-analyses, spouting the chestnut that the objections went to the weight not the admissibility of the evidence.  Bandza embraces the rhetoric of the Circuit, but he offers no description or analysis of the liberties that Martyn Smith took with the data, or the reasonableness of Smith’s reliance upon the re-analyzed data.

There is no necessary connection between WOE methodologies and re-analyses of epidemiologic studies.  Re-analyses can be done properly to support or deconstruct the conclusions of published papers.  As Bandza points out, some re-analyses may go on to be peer reviewed and published themselves.  Validity is the key, and WOE methodologies have little to do with the process of evaluating the original or the re-analyzed study.



Litmus Tests

December 27th, 2012

Rule 702 is, or is not, a litmus test for expert witness opinion admissibility.  Relative risk is, or is not, a litmus test for specific causation.  Statistical significance is, or is not, a litmus test for reasonable reliance upon the results of a study.  It is relatively easy to find judicial opinions on either side of the litmus divide.  Compare National Judicial College, Resource Guide for Managing Complex Litigation at 57 (2010) (Daubert is not a litmus test) with Cryer v. Werner Enterprises, Inc., Civ. Action No. 05-S-696-NE, Mem. Op. & Order at 16 n. 63 (N.D. Ala. Dec. 28, 2007) (describing the Eleventh Circuit’s restatement of Rule 702’s “litmus test” for the methodological reliability of proffered expert witness opinion testimony).

The “litmus test“ is one sorry, overworked metaphor.  Perhaps its appeal has to do with a vague collective memory that litmus paper is one of those “things of science,” which we used in high school chemistry, and never had occasion to use again. Perhaps, litmus tests have the appeal of “proofiness.”

The reality is different. The litmus test is a semi-quantitative test for acidity or alkalinity.  Neutral litmus is purple.  Under acidic conditions, litmus turns red; under basic conditions, it turns blue.  For some time, scientists have used pH meters when they want a precise quantification of acidity or alkalinity.  Litmus paper is a fairly crude test, which easily discriminates  moderate acidity from alkalinity (say pH 4 from pH 11), but is relatively useless for detecting an acidity at pH or 6.95, or alkalinity at 7.05.

So what exactly are legal authors trying to say when they say that some feature of a test is, or is not, a “litmus test”? The litmus test is accurate, but not precise at the important boundary at neutrality.  The litmus test color can be interpreted for degree of acidity or alkalinity, but it is not the preferred method to obtain a precise measurement. Saying that a judicial candidate’s views on abortion are a litmus test for the Senate’s evaluation of the candidate makes sense, given the relative binary nature of the outcome of a litmus test, and the polarization of political views on abortion. Apparently, neutral views or views close to neutrality on abortion are not a desideratum for judicial candidates.  A cruder, binary test is exactly what is desired by politicians.

The litmus test that is used for judicial candidates does not seem to work so well when used to describe scientific or statistical inference.  The litmus test is well understood, but fairly obsolete in modern laboratory practice.  When courts say things, such as statistical significance is not a litmus test for acceptability of a study’s results, clearly they are correct because measure of random error is only one aspect of judging a body of evidence for, or against, an association.  Yet courts seem to imply something else, at least at times:

statistical significance is not an important showing in making a case that an exposure is reliably associated with a particular outcome.

Here courts are trading in half truths.  Statistical significance is quantitative, and the choice of a level of significance is not based upon immutable law. So like the slight difference between a pH of 6.95 and 7.05, statistical significance tests have a boundary issue.  Nonetheless, a consideration of random error cannot be dismissed or overlooked on the theory that significance level is not a “litmus test.”  This metaphor obscures and attempts to excuse sloppy thinking.  It is time to move beyond this metaphor.


December 24th, 2012

Judge Helen Berrigan, who presides over the Paxil birth defects MDL in New Orleans, has issued a nicely reasoned Rule 702 opinion, upholding defense objections to plaintiffs expert witnesses, Paul Goldstein, Ph.D., and Shira Kramer, Ph.D. Frischhertz v SmithKline Beecham EDLa 2012 702 MSJ Op.

The plaintiff, Andrea Frischhertz, took GSK’s Paxil, a selective serotonin reuptake inhibitor (SSRI), for depression while pregnant with her daughter, E.F. The parties agreed that E.F. was born with a deformity of her right hand.  Plaintiffs originally claimed that E.F. had a heart defect, but their expert witnesses appeared to give up this claim at deposition, as lacking evidential support.

Adhering to Daubert’s Epistemiologic Lesson

Like many other lower federal courts, Judge Berrigan focused her analysis on the language of Daubert v. Merrell Dow Pharmaceuticals Inc., 509 U.S. 579 (1993), a case that has been superseded by subsequent cases and a revision to the operative statute, Rule 702.  Fortunately, the trial court did not lose sight of the key epistemological teaching of Daubert, which is based upon Rule 702:

“Regarding reliability, the [Daubert] Court said: ‘the subject of an expert’s testimony must be “scientific . . . knowledge.” The adjective “scientific” implies a grounding in the methods and procedures of science. Similarly, the word “knowledge” connotes more than subjective belief or unsupported speculation’.”

Slip Op. at 3 (quoting Daubert, 509 U.S. at 589-590).

There was not much to the plaintiffs’ expert witnesses’ opinion beyond speculation, but many other courts have been beguiled by speculation dressed up as “scientific … knowledge.”  Dr. Goldstein relied upon whole embryo culture testing of SSRIs, but in the face overwhelming evidence, Dr. Goldstein was forced to concede that this test may generate hypotheses about, but cannot predict, human risk of birth defects.  No doubt this concession made the trial court’s decision easier, but the result would have been required regardless of Dr. Goldstein’s exhibition of truthfulness at deposition.

Statistical Association – A Good Place to Begin

More interestingly, the trial court rejected the plaintiffs’ expert witnesses’ efforts to leapfrog finding a statistically significant association to parsing the so-called Bradford Hill factors:

“The Bradford-Hill criteria can only be applied after a statistically significant association has been identified. Federal Judicial Center, Reference Manual on Scientific Evidence, 599, n.141 (3d. ed. 2011) (“In a number of cases, experts attempted to use these guidelines to support the existence of causation in the absence of any epidemiologic studies finding an association . . . . There may be some logic to that effort, but it does not reflect accepted epidemiologic methodology.”). See, e.g., Dunn v. Sandoz Pharms., 275 F. Supp. 2d 672, 678 (M.D.N.C. 2003). Here, Dr. Goldstein attempted to use the Bradford-Hill criteria to prove causation without first identifying a valid statistically significant association. He first developed a hypothesis and then attempted to use the Bradford-Hill criteria to prove it. Rec. Doc. 187, Exh. 2, depo. Goldstein, p. 103. Because there is no data showing an association between Paxil and limb defects, no association existed for Dr. Goldstein to apply the Bradford-Hill criteria. Hence, Dr. Goldstein’s general causation opinion is not reliable.”

Slip op. at 6.

The trial court’s rejection of Dr. Goldstein’s attempted end run is particularly noteworthy given the Reference Manual’s weak-kneed attempt to suggest that this reasoning has “some logic” to it.  The Manual never articulates what “logic” commends Dr. Goldstein’s approach; nor does it identify any causal relationship ever established with such paltry evidence in the real world of science. The Manual does cite several legal cases that excused or overlooked the need to find a statistically significant association, and even elevated such reasoning into legally acceptable, admissibility method.  See Reference Manual on Scientific Evidence at 599 n. 141 (describing cases in which purported expert witnesses attempted to use Bradford Hill factors in the absence of a statistically significant association; citing Rains v. PPG Indus., Inc., 361 F. Supp. 2d 829, 836–37 (S.D. Ill. 2004); ); Soldo v. Sandoz Pharms. Corp., 244 F. Supp. 2d 434, 460–61 (W.D. Pa. 2003).  The Reference Manual also cited cases, without obvious disapproval, which completely dispatched with any necessity of considering any of the Bradford Hill factors, or the precondition of a statistically significant association.  See Reference Manual at 599 n. 144 (citing Cook v. Rockwell Int’l Corp., 580 F. Supp. 2d 1071, 1098 (D. Colo. 2006) (“Defendants cite no authority, scientific or legal, that compliance with all, or even one, of these factors is required. . . . The scientific consensus is, in fact, to the contrary. It identifies Defendants’ list of factors as some of the nine factors or lenses that guide epidemiologists in making judgments about causation. . . . These factors are not tests for determining the reliability of any study or the causal inferences drawn from it.“).

Shira Kramer Takes Her Lumpings

The plaintiffs’ other key expert witness, Dr. Shira Kramer, was a more sophisticated and experienced obfuscator.  Kramer attempted to provide plaintiffs with a necessary association by “lumping” all birth defects together in her analysis of epidemiologic data of birth defects among children of women who had ingested Paxil (or other SSRIs).  Given the clear evidence that different birth defects arise at different times, based upon interference with different embryological processes, the trial court discerned this “lumping” of end points to be methodologically inappropriate.  Slip op. at 8 (citing Chamber v. Exxon Corp., 81 F. Supp. 2d 661 (M.D. La. 2000), aff’d, 247 F.3d 240 (5th Cir. 2001) (unpublished).

Without her “lumping”, Dr. Kramer was left with only a weak, inconsistent claim of biological plausibility and temporality. Finding that Dr. Kramer’s opinion had outrun her headlights, Judge Berrigan, excluded Dr. Kramer as an expert witness, and granted GSK summary judgment.

Merry Christmas!