TORTINI

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

Daubert’s Error Rate

June 16th, 2015

In Daubert, the Supreme Court came to the realization that expert witness opinion testimony was allowed under the governing statute, Federal Rule of Evidence 702, only when that witness’s “scientific, technical, or other specialized knowledge” would help the fact finder. Knowledge clearly connotes epistemic warrant, and some of the Court’s “factors” speak directly to this warrant, such as whether the claim has been tested, and whether the opinion has an acceptable rate of error. The Court, however, continued to allow some proxies for that warrant, in the form of “general acceptance,” or “peer review.”

The “rate of error” factor has befuddled some courts in their attempt to apply the statutory requirements of Rule 702, especially when statistical evidence is involved. Some litigants have tried to suggest that a statistically significant result suffices alone to meet the demands of Rule 702, but this argument is clearly wrong. See, e.g., United States v. Vitek Supply Corp., 144 F.3d 476, 480, 485–86 (7th Cir. 1998) (stating that the purpose of the inquiry into rate of error is to determine whether tests are “accurate and reliable”) (emphasis added). See also Judicial Control of the Rate of Error in Expert Witness Testimony” (May 28, 2015). The magnitude of tolerable actual or potential error rate remains, however, a judicial mystery[1].

Sir Austin Bradford Hill described ruling out bias, confounding, and chance (or random error) as essential prerequisites to considering his nine factors used to assess whether an association is causal:

“Disregarding then any such problem in semantics we have this situation. Our observations reveal an association between two variables, perfectly clear-cut and beyond what we would care to attribute to the play of chance. What aspects of that association should we especially consider before deciding that the most likely interpretation of it is causation.”

Austin Bradford Hill, “The Environment and Disease: Association or Causation?” 58 Proc. Royal Soc’y Med. 295, 295 (1965). The better reasoned cases agree. See, e.g., Frischhertz v. SmithKline Beecham Corp., 2012 U.S. Dist. LEXIS 181507, *6 (E.D.La. 2012) (“The Bradford-Hill criteria can only be applied after a statistically significant association has been identified.”) (citing and quoting among other sources, Federal Judicial Center, Reference Manual on Scientific Evidence, 599 & n.141 (3d. ed. 2011)).

Citing the dictum in Matrixx Initiatives[2] as though it were a holding is not only ethically dubious, but also ignores the legal and judicial context of the Court’s statements[3]. There are, after all, some circumstances such as cases of death by blunt-force trauma, or bullet wounds, when epidemiological and statistical evidence is not needed. The Court did not purport to speak to all causation assessments; nor did it claim that it was addressing only instances in which there were “expected cases,” and “base-line risks,” in diseases that have an accepted occurrence and incidence among unexposed persons. It is, of course, in exactly those cases that statistical consideration of bias, confounding, and chance are essential before Bradford Hill’s factors can be parsed.

Lord Rutherford[4] is often quoted as having said that “[i]f your experiment needs statistics, you ought to have done a better experiment.” Today, physics and chemistry have dropped their haughty disdain for statistics in the face of their recognition that some processes can be understood only as stochastic and rate driven. In biology, we are a long way from being able to describe the most common disease outcomes as mechanistic genetic or epigenetic events. Statistical analyses, with considerations of random and systematic error, will be with us for a long time, whether the federal judiciary acknowledges this fact or not.

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Cases Discussing Error Rates in Rule 702 Decisions

SCOTUS

Daubert v. Merrell Dow Pharmaceuticals, Inc., 509 U.S. 579, 593 (1993) (specifying the “the known or potential rate of error” as one of several factors in assessing the scientific reliability or validity of proffered expert witness’s opinion)

Kumho Tire Co. v. Carmichael, 526 U.S. 137, 151 (1999) (suggesting that reliability in the form of a known and an acceptable error rate is an important consideration for admissibility)

US Court of Appeals

FIRST CIRCUIT

United States v. Shea, 957 F. Supp. 331, 334–45 (D.N.H. 1997) (rejecting criminal defendant’s objection to government witness’s providing separate match and error probability rates)

SECOND CIRCUIT

Rabozzi v. Bombardier, Inc., No. 5:03-CV-1397 (NAM/DEP), 2007 U.S. Dist. LEXIS 21724, at *7, *8, *20 (N.D.N.Y. Mar. 27, 2007) (excluding testimony from civil engineer about boat design, in part because witness failed to provide rate of error)

Sorto-Romero v. Delta Int’l Mach. Corp., No. 05-CV-5172 (SJF) (AKT), 2007 U.S. Dist. LEXIS 71588, at *22–23 (E.D.N.Y. Sept. 24, 2007) (excluding engineering opinion that defective wood-carving tool caused injury because of lack of error rate)

In re Ephedra Products Liability Litigation, 393 F. Supp. 2d 181, 184 (S.D.N.Y. 2005) (confusing assessment of random error with probability that statistical estimate of true risk ratio was correct)

Roane v. Greenwich Swim Comm., 330 F. Supp. 2d 306, 309, 319 (S.D.N.Y. 2004) (excluding mechanical engineer, in part because witness failed to provide rate of error)

Nook v. Long Island R.R., 190 F. Supp. 2d 639, 641–42 (S.D.N.Y. 2002) (excluding industrial hygienist’s opinion in part because witness was unable to provide a known rate of error).

United States v. Towns, 19 F. Supp. 2d 67, 70–72 (W.D.N.Y. 1998) (permitting clinical psychologist to opine about defendant’s mens rea and claimed mental illness causing his attempted bank robbery, in part because the proffer of opinion maintained that the psychologist would provide an error rate)  

Meyers v. Arcudi, 947 F. Supp. 581 (D. Conn. 1996) (excluding polygraph in civil action in part because of error rate)

THIRD CIRCUIT

United States v. Ewell, 252 F. Supp. 2d 104, 113–14 (D.N.J. 2003) (rejecting criminal defendant’s objection to government’s failure to quantify laboratory error rate)

Soldo v. Sandoz Pharmaceuticals Corp., 244 F. Supp. 2d 434, 568 (W.D. Pa. 2003) (excluding plaintiffs’ expert witnesses in part because court, and court-appointed expert witnesses, were unable to determine error rate).

Pharmacia Corp. v. Alcon Labs., Inc., 201 F. Supp. 2d 335, 360 (D.N.J. 2002) (excluding ; error too high).

FOURTH CIRCUIT

United States v. Moreland, 437 F.3d 424, 427–28, 430–31 (4th Cir. 2006) (affirming district court’s allowance of forensic chemist’s testimony that could not provide error rate because reviews of witness’s work found it to be free of error)

Buckman v. Bombardier Corp., 893 F. Supp. 547, 556–57 (E.D.N.C. 1995) (ruling that an expert witness may opine about comparisons between boat engines in rough water but only as a lay witness, because the comparison tests were unreliable, with a high estimated rate of error)

FIFTH CIRCUIT

Albert v. Jordan, Nos. 05CV516, 05CV517, 05CV518, 05CV519, 2007 U.S. Dist. LEXIS 92025, at *2–3 (W.D. La. Dec. 14, 2007) (allowing testimony of vocational rehabilitation expert witness, over objection, because witness provided “reliable” information, with known rate of error)

SIXTH CIRCUIT

United States v. Leblanc, 45 F. App’x 393, 398, 400 (6th Cir. 2002) (affirming exclusion of child psychologist, whose testimony about children’s susceptibility to coercive interrogation was based upon “‘soft science’ . . . in which ‘error is . . . rampant’.” (quoting the district court))

United States v. Sullivan, 246 F. Supp. 2d 696, 698–99 (E.D. Ky. 2003) (admitting expert witness’s opinion on the unreliability of eyewitness identification; confusing error rate of witness’s opinion with accuracy of observations made based upon order of presentation of photographs of suspect)

SEVENTH CIRCUIT

United States v. Vitek Supply Corp., 144 F.3d 476, 480, 485–86 (7th Cir. 1998) (affirming denial of defendant’s Rule 702 challenge based in part upon error rates; the purpose of the inquiry into rate of error is to determine whether tests are “accurate and reliable”; here the government’s expert witnesses used adequate controls and replication to ensure an acceptably low rate of error)

Phillips v. Raymond Corp., 364 F. Supp. 2d 730, 732–33, 740-41 (N.D. Ill. 2005) (excluding biomechanics expert witness who had not reliably tested his claims in a way to produce an accurate rate of error)

EIGHTH CIRCUIT

Bone Shirt v. Hazeltine, 461 F.3d 1011, 1020 (8th Cir. 2006) (affirming district court’s ruling to admit testimony of expert witness’s regression analysis in vote redistricting case); see id. at 1026 (Gruender, J., concurring) (expressing concern with the questioned testimony’s potential rate of error because it is “difficult to weigh this factor in Daubert’s analysis if ‘the effect of that error is unknown’.” (quoting court below, Bone Shirt v. Hazeltine, 336 F. Supp. 2d 976, 1002 (D.S.D. 2004))

United States v. Beasley, 102 F.3d 1440, 1444, 1446–48 (8th Cir. 1996) (confusing random error with general error rate) (affirming admissibility of expert witness testimony based upon DNA testing, because such testing followed acceptable standards in testing for contamination and “double reading”)

NINTH CIRCUIT

United States v. Chischilly, 30 F.3d 1144, 1148, 1152, 1154–55 (9th Cir. 1994) (affirming admissibility of testimony based upon DNA match in sex crime, noting that although error rate of error was unquantified, the government had made a sufficient showing of rarity of false positives to support an inference of low error rate)

Cascade Yarns, Inc. v. Knitting Fever, Inc., No. C10–861RSM, 2012 WL 5194085, at *7 (W.D. Wash. Oct. 18. 2012) (excluding expert witness opinion because error rate was too high)

United States v. Microtek Int’l Dev. Sys. Div., Inc., No. 99-298-KI, 2000 U.S. Dist. LEXIS 2771, at *2, *10–13, *15 (D. Or. Mar. 10, 2000) (excluding polygraph data based upon showing that claimed error rate came from highly controlled situations, and that “real world” situations led to much higher error (10%) false positive error rates)

TENTH CIRCUIT

Miller v. Pfizer, Inc., 356 F.3d 1326, 1330, 1334 (10th Cir. 2004) (affirming exclusion of plaintiffs’ expert witness, Dr. David Healy, based upon district court’s findings, made with the assistance of court-appointed expert witnesses, that Healy’s opinion was based upon studies that lacked sufficient sample size, adequate controls, and freedom from study bias, and thus prone to unacceptable error rate)

ELEVENTH CIRCUIT

Quiet Tech. DC-8, Inc. v. Hurel-Duboi U.K., Ltd., 326 F.3d 1333, 1343–45 (11th Cir. 2003) (affirming trial court’s admission of defendant’s aerospace engineer’s testimony, when the lower court had found that the error rate involved was “relatively low”; rejecting plaintiff’s argument that the witness had entered data incorrectly on ground that the asserted error would not affect the validity of the witness’s opinions)

Wright v. Case Corp., No. 1:03-CV-1618-JEC, 2006 U.S. Dist. LEXIS 7683, at *14 (N.D. Ga. Feb. 1, 2006) (granting defendant’s motion to exclude plaintiff’s mechanical engineering expert, because the expert’s alternative designs for the seat safety bar were not reliable due to potential feasibility issues, and because the associated error rate was therefore unquantifiable but potentially very high)

Benkwith v. Matrixx Initiatives, Inc., 467 F. Supp. 2d 1316, 1326, 1330, 1332 (M.D. Ala. 2006) (granting defendant’s motion to exclude testimony of an expert in the field of epidemiology regarding Zicam nasal spray’s causing plaintiff’s anosmia, because the opinions had not been tested and a rate of error could not be provided).

D.C. CIRCUIT

Ambrosini v. Upjohn Co., No. 84-3483 (NHJ), 1995 U.S. Dist. LEXIS 21318, at *16, *22–24 (D.D.C. Oct. 18, 1995) (finding that plaintiff’s teratology expert was not permitted to testify, because the methodology used was found to be unreliable and could not yield an accurate error rate)


[1] Jed S. Rakoff, “Science and the Law: Uncomfortable Bedfellows,” 38 Seton Hall L. Rev. 1379, 1382–83 (2008) (observing that an error rate of 13 percent in polygraph interpretation would likely be insufficiently reliable to support admissibility of testimony based upon polygraph results).

[2] Matrixx Initiatives, Inc. v. Siracusano, 131 S. Ct. 1309, 1319 (2011) (suggesting that courts “frequently permit expert testimony on causation based on evidence other than statistical significance”).

[3] See, e.g., WLF Legal Backgrounder on Matrixx Initiatives (June 20, 2011); “The Matrixx – A Comedy of Errors”; Matrixx Unloaded (Mar. 29, 2011)”; “The Matrixx Oversold” (April 4, 2011); “De-Zincing the Matrixx.”

[4] Ernest Rutherford, a British chemist, investigated radioactivity. He won the Nobel Prize in chemistry, in 1908.

The Eleventh Circuit Confuses Adversarial and Methodological Bias, Manifestly Erroneously

June 6th, 2015

The Eleventh Circuit’s decision in Adams v. Laboratory Corporation of America, is disturbing on many levels. Adams v. Lab. Corp. of Am., 760 F.3d 1322 (11th Cir. 2014). Professor David Bernstein has already taken the Circuit judges to task for their failure to heed the statutory requirements of Federal Rule of Evidence 702. See David Bernstein, “A regrettable Eleventh Circuit expert testimony ruling, Adams v. Lab. Corp. of America,Wash. Post (May 26, 2015). Sadly, the courts’ strident refusal to acknowledge the statutory nature of Rule 702, and the Congressional ratification of the 2000 amendments to Rule 702, have become commonplace in the federal courts. Ironically, the holding of the Supreme Court’s decision in Daubert itself was that the lower courts were not free to follow common law that had not been incorporated into the first version of the Rule 702.

There is much more wrong with the Adams case than just a recalcitrant disregard for the law: the Circuit displayed an equally distressing disregard for science. The case started as a negligent failure to diagnose cervical cancer claim against defendant Laboratory Corporation of America. Plaintiffs claimed that the failure to diagnose cancer led to delays in treatment, which eroded Mrs. Adam’s chance for a cure.

Before the Adams case arose, two professional organizations, the College of American Pathologists (CAP) and the American Society of Cytopathology (ASC) issued guidelines about how an appropriate retrospective review should be conducted. Both organizations were motivated by two concerns: protecting their members from exaggerated, over-extended, and bogus litigation claims, as well as by a scientific understanding that a false-negative finding by a cytopathologist does not necessarily reflect a negligent interpretation of a Pap smear[1]. Both organizations called for a standard of blinded review in litigation to protect against hind-sight bias. The Adams retained a highly qualified pathologist, Dr. Dorothy Rosenthal, who with full knowledge of the later diagnosis and the professional guidelines, reviewed the earlier Pap smears that were allegedly misdiagnosed as non-malignant. 760 F.3d at 1326. Rosenthal’s approach violated the CAP and ASC guidelines, as well as common sense.

The district judge ruled that Rosenthal’s approach was little more than an ipse dixit, and a subjective method that could not be reviewed objectively. Adams v. Lab. Corp. of Am., No. 1:10-CV-3309-WSD, 2012 WL 370262, at *15 (N.D. Ga. Feb. 3, 2012). In a published per curiam opinion, the Eleventh Circuit reversed, holding that the district judge’s analysis of Rosenthal’s opinion was “manifestly erroneous.” 760 F.3d at 1328. Judge Garza, of the Fifth Circuit, sitting by designation, concurred to emphasize his opinion that Rosenthal did not need a methodology, as long as she showed up with her qualifications and experience to review the contested Pap smears.

The Circuit opinion is a model of conceptual confusion. The judges refer to the professional society guidelines, but never provide citations. (See note 1, infra.). The Circuit judges are obviously concerned that the professional societies are promulgating standards to be used in judging claims against their own members for negligent false-negative interpretations of cytology or pathology. What the appellate judges failed to recognize, however, is that the professional societies had a strong methodological basis for insisting upon “blinded” review of the slides in controversy. Knowledge of the outcome must of necessity bias any subsequent review, such as plaintiffs’ expert witness, Rosenthal. Even a cursory reading of the two guidelines would have made clear that they had been based on more than simply a desire to protect members; they were designed to protect members against bogus claims, and cited data in support of their position[2]. Subsequent to the guidelines, several publications have corroborated the evidence-based need for blinded review[3].

The concepts of sensitivity, specificity, and positive predictive value are inherent in any screening procedure; they are very much part of the methodology of screening. These measures, along with statistical analyses of concordance and discordance among experienced cytopathologists, can be measured and assessed for accuracy and reliability. The Circuit judges in Adams, however, were blinded (in a bad way) to the scientific scruples that govern screenings. The per curiam opinion suggests that:

“[t]he only arguably appreciable differences between Dr. Rosenthal’s method and the review method for LabCorp’s cytotechnologists is that Dr. Rosenthal (1) already knew that the patient whose slides she was reviewing had developed cancer and (2) reviewed slides from just one patient. Those differences relate to the lack of blinded review, which we address later.”

760 F.3d at 1329 n. 10. And when the judges addressed the lack of blinded review, they treated hindsight bias, a cognitive bias and methodological flaw in the same way as they would have trial courts and litigants treat Dr. Rosenthal’s “philosophical bent” in favor of cancer patients — as “a credibility issue for the jury.” Id. at 1326-27, 1332. This conflation of methodological bias with adversarial bias, however, is a prescription for eviscerating judicial gatekeeping of flawed opinion testimony. Judge Garza, in a concurring opinion, would have gone further and declared that plaintiffs’ expert witness Rosenthal had no methodology and thus she was free to opine ad libitum.

Although Rosenthal’s “philosophical bent” might perhaps be left to the crucible of cross-examination, hindsight review bias could and should have been eliminated by insisting that Rosenthal wear the same “veil of ignorance” of Mrs. Adam’s future clinical course, which the defendant wore when historically evaluating the plaintiff’s Pap smears. Here Rosenthal’s adversarial bias was very probably exacerbated by her hindsight bias, and the Circuit missed a valuable opportunity to rein in both kinds of bias.

Certainly in other areas of medicine, such as radiology, physicians are blinded to the correct interpretation and evaluated on their ability to line up with a gold standard. The NIOSH B-reader examination, for all its problems, at least tries to qualify physicians in the use of the International Labor Organization’s pneumoconiosis scales for interpreting plain-film radiographs for pulmonary dust diseases, by having them read and interpret films blinded to the NIOSH/ILO consensus interpretation.


[1] See Patrick L. Fitzgibbons & R. Marshall Austin, “Expert review of histologic slides and Papanicolaou tests in the context of litigation or potential litigation — Surgical Pathology Committee and Cytopathology Committee of the College of American Pathologists,” 124 Arch. Pathol. Lab. Med. 1717 (2000); American Society of Cytopathology, “Guidelines for Review of Gyn Cytology Samples in the Context of Litigation or Potential Litigation” (2000).

[2] The CAP guideline, for instance, cited R. Marshall Austin, “Results of blinded rescreening of Papanicolaou smears versus biased retrospective review,” 121 Arch. Pathol. Lab. Med. 311 (1997).

[3] Andrew A. Renshaw, K.M Lezon, and D.C. Wilbur, “The human false-negative rate of rescreening Pap tests: Measured in a two-arm prospective clinical trial,” 93 Cancer (Cancer Cytopathol.) 106 (2001); Andrew A. Renshaw, Mary L. Young, and E. Blair Holladay, “Blinded review of Papanicolaou smears in the context of litigation: Using statistical analysis to define appropriate thresholds,” 102 Cancer Cytopathology 136 (2004) (showing that data from blinded reviews can be interpreted in a statistically appropriate way, and defining standards to improve the accuracy and utility of blinded reviews); D. V. Coleman & J. J. R. Poznansky, “Review of cervical smears from 76 women with invasive cervical cancer: cytological findings and medicolegal implications,” 17 Cytopathology 127 (2006); Andrew A. Renshaw, “Comparing Methods to Measure Error in Gynecologic Cytology and Surgical Pathology,” 130 Arch. Path. & Lab. Med. 626 (2009).

Judicial Control of the Rate of Error in Expert Witness Testimony

May 28th, 2015

In Daubert, the Supreme Court set out several criteria or factors for evaluating the “reliability” of expert witness opinion testimony. The third factor in the Court’s enumeration was whether the trial court had considered “the known or potential rate of error” in assessing the scientific reliability of the proffered expert witness’s opinion. Daubert v. Merrell Dow Pharmaceuticals, Inc., 509 U.S. 579, 593 (1993). The Court, speaking through Justice Blackmun, failed to provide much guidance on the nature of the errors subject to gatekeeping, on how to quantify the errors, and on to know how much error was too much. Rather than provide a taxonomy of error, the Court lumped “accuracy, validity, and reliability” together with a grand pronouncement that these measures were distinguished by no more than a “hen’s kick.” Id. at 590 n.9 (1993) (citing and quoting James E. Starrs, “Frye v. United States Restructured and Revitalized: A Proposal to Amend Federal Evidence Rule 702,” 26 Jurimetrics J. 249, 256 (1986)).

The Supreme Court’s failure to elucidate its “rate of error” factor has caused a great deal of mischief in the lower courts. In practice, trial courts have rejected engineering opinions on stated grounds of their lacking an error rate as a way of noting that the opinions were bereft of experimental and empirical evidential support[1]. For polygraph evidence, courts have used the error rate factor to obscure their policy prejudices against polygraphs, and to exclude test data even when the error rate is known, and rather low compared to what passes for expert witness opinion testimony in many other fields[2]. In the context of forensic evidence, the courts have rebuffed objections to random-match probabilities that would require that such probabilities be modified by the probability of laboratory or other error[3].

When it comes to epidemiologic and other studies that require statistical analyses, lawyers on both sides of the “v” frequently misunderstand p-values or confidence intervals to provide complete measures of error, and ignore the larger errors that result from bias, confounding, study validity (internal and external), inappropriate data synthesis, and the like[4]. Not surprisingly, parties fallaciously argue that the Daubert criterion of “rate of error” is satisfied by expert witness’s reliance upon studies that in turn use conventional 95% confidence intervals and measures of statistical significance in p-values below 0.05[5].

The lawyers who embrace confidence intervals and p-values as their sole measure of error rate fail to recognize that confidence intervals and p-values are means of assessing only one kind of error: random sampling error. Given the carelessness of the Supreme Court’s use of technical terms in Daubert, and its failure to engage in the actual evidence at issue in the case, it is difficult to know whether the Court intended to suggest that random error was the error rate it had in mind[6]. The statistics chapter in the Reference Manual on Scientific Evidence helpfully points out that the inferences that can be drawn from data turn on p-values and confidence intervals, as well as on study design, data quality, and the presence or absence of systematic errors, such as bias or confounding.  Reference Manual on Scientific Evidence at 240 (3d 2011) [Manual]. Random errors are reflected in the size of p-values or the width of confidence intervals, but these measures of random sampling error ignore systematic errors such as confounding and study biases. Id. at 249 & n.96.

The Manual’s chapter on epidemiology takes an even stronger stance: the p-value for a given study does not provide a rate of error or even a probability of error for an epidemiologic study:

“Epidemiology, however, unlike some other methodologies—fingerprint identification, for example—does not permit an assessment of its accuracy by testing with a known reference standard. A p-value provides information only about the plausibility of random error given the study result, but the true relationship between agent and outcome remains unknown. Moreover, a p-value provides no information about whether other sources of error – bias and confounding – exist and, if so, their magnitude. In short, for epidemiology, there is no way to determine a rate of error.”

Manual at 575. This stance seems not entirely justified given that there are Bayesian approaches that would produce credibility intervals accounting for sampling and systematic biases. To be sure, such approaches have their own problems and they have received little to no attention in courtroom proceedings to date.

The authors of the Manual’s epidemiology chapter, who are usually forgiving of judicial error in interpreting epidemiologic studies, point to one United States Court of Appeals case that fallaciously interpreted confidence intervals magically to quantify bias and confounding in a Bendectin birth defects case. Id. at 575 n. 96[7]. The Manual could have gone further to point out that, in the context of multiple studies, of different designs and analyses, cognitive biases involved in evaluating, assessing, and synthesizing the studies are also ignored by statistical measures such as p-values and confidence intervals. Although the Manual notes that assessing the role of chance in producing a particular set of sample data is “often viewed as essential when making inferences from data,” the Manual never suggests that random sampling error is the only kind of error that must be assessed when interpreting data. The Daubert criterion would appear to encompass all varieties or error, not just random error.

The Manual’s suggestion that epidemiology does not permit an assessment of the accuracy of epidemiologic findings misrepresents the capabilities of modern epidemiologic methods. Courts can, and do, invoke gatekeeping approaches to weed out confounded study findings. SeeSorting Out Confounded Research – Required by Rule 702” (June 10, 2012). The “reverse Cornfield inequality” was an important analysis that helped establish the causal connection between tobacco smoke and lung cancer[8]. Olav Axelson studied and quantified the role of smoking as a confounder in epidemiologic analyses of other putative lung carcinogens.[9] Quantitative methods for identifying confounders have been widely deployed[10].

A recent study in birth defects epidemiology demonstrates the power of sibling cohorts in addressing the problem of residual confounding from observational population studies with limited information about confounding variables. Researchers looking at various birth defect outcomes among offspring of women who used certain antidepressants in early pregnancy generally found no associations in pooled data from Iceland, Norway, Sweden, Finland, and Denmark. A putative association between maternal antidepressant use and a specific kind of cardiac defect (right ventricular outflow tract obstruction or RVOTO) did appear in the overall analysis, but was reversed when the analysis was limited to the sibling subcohort. The study found an apparent association between RVOTO defects and first trimester maternal exposure to selective serotonin reuptake inhibitors, with an adjusted odds ratio of 1.48 (95% C.I., 1.15, 1.89). In the adjusted analysis for siblings, the study found an OR of 0.56 (95% C.I., 0.21, 1.49) in an adjusted sibling analysis[11]. This study and many others show how creative analyses can elucidate and quantify the direction and magnitude of confounding effects in observational epidemiology.

Systematic bias has also begun to succumb to more quantitative approaches. A recent guidance paper by well-known authors encourages the use of quantitative bias analysis to provide estimates of uncertainty due to systematic errors[12].

Although the courts have failed to articulate the nature and consequences of erroneous inference, some authors would reduce all of Rule 702 (and perhaps 704, 403 as well) to a requirement that proffered expert witnesses “account” for the known and potential errors in their opinions:

“If an expert can account for the measurement error, the random error, and the systematic error in his evidence, then he ought to be permitted to testify. On the other hand, if he should fail to account for any one or more of these three types of error, then his testimony ought not be admitted.”

Mark Haug & Emily Baird, “Finding the Error in Daubert,” 62 Hastings L.J. 737, 739 (2011).

Like most antic proposals to revise Rule 702, this reform vision shuts out the full range of Rule 702’s remedial scope. Scientists certainly try to identify potential sources of error, but they are not necessarily very good at it. See Richard Horton, “Offline: What is medicine’s 5 sigma?” 385 Lancet 1380 (2015) (“much of the scientific literature, perhaps half, may simply be untrue”). And as Holmes pointed out[13], certitude is not certainty, and expert witnesses are not likely to be good judges of their own inferential errors[14]. Courts continue to say and do wildly inconsistent things in the course of gatekeeping. Compare In re Zoloft (Setraline Hydrochloride) Products, 26 F. Supp. 3d 449, 452 (E.D. Pa. 2014) (excluding expert witness) (“The experts must use good grounds to reach their conclusions, but not necessarily the best grounds or unflawed methods.”), with Gutierrez v. Johnson & Johnson, 2006 WL 3246605, at *2 (D.N.J. November 6, 2006) (denying motions to exclude expert witnesses) (“The Daubert inquiry was designed to shield the fact finder from flawed evidence.”).


[1] See, e.g., Rabozzi v. Bombardier, Inc., No. 5:03-CV-1397 (NAM/DEP), 2007 U.S. Dist. LEXIS 21724, at *7, *8, *20 (N.D.N.Y. Mar. 27, 2007) (excluding testimony from civil engineer about boat design, in part because witness failed to provide rate of error); Sorto-Romero v. Delta Int’l Mach. Corp., No. 05-CV-5172 (SJF) (AKT), 2007 U.S. Dist. LEXIS 71588, at *22–23 (E.D.N.Y. Sept. 24, 2007) (excluding engineering opinion that defective wood-carving tool caused injury because of lack of error rate); Phillips v. Raymond Corp., 364 F. Supp. 2d 730, 732–33 (N.D. Ill. 2005) (excluding biomechanics expert witness who had not reliably tested his claims in a way to produce an accurate rate of error); Roane v. Greenwich Swim Comm., 330 F. Supp. 2d 306, 309, 319 (S.D.N.Y. 2004) (excluding mechanical engineer, in part because witness failed to provide rate of error); Nook v. Long Island R.R., 190 F. Supp. 2d 639, 641–42 (S.D.N.Y. 2002) (excluding industrial hygienist’s opinion in part because witness was unable to provide a known rate of error).

[2] See, e.g., United States v. Microtek Int’l Dev. Sys. Div., Inc., No. 99-298-KI, 2000 U.S. Dist. LEXIS 2771, at *2, *10–13, *15 (D. Or. Mar. 10, 2000) (excluding polygraph data based upon showing that claimed error rate came from highly controlled situations, and that “real world” situations led to much higher error (10%) false positive error rates); Meyers v. Arcudi, 947 F. Supp. 581 (D. Conn. 1996) (excluding polygraph in civil action).

[3] See, e.g., United States v. Ewell, 252 F. Supp. 2d 104, 113–14 (D.N.J. 2003) (rejecting defendant’s objection to government’s failure to quantify laboratory error rate); United States v. Shea, 957 F. Supp. 331, 334–45 (D.N.H. 1997) (rejecting objection to government witness’s providing separate match and error probability rates).

[4] For a typical judicial misstatement, see In re Zoloft Products, 26 F. Supp.3d 449, 454 (E.D. Pa. 2014) (“A 95% confidence interval means that there is a 95% chance that the ‘‘true’’ ratio value falls within the confidence interval range.”).

[5] From my experience, this fallacious argument is advanced by both plaintiffs’ and defendants’ counsel and expert witnesses. See also Mark Haug & Emily Baird, “Finding the Error in Daubert,” 62 Hastings L.J. 737, 751 & n.72 (2011).

[6] See David L. Faigman, et al. eds., Modern Scientific Evidence: The Law and Science of Expert Testimony § 6:36, at 359 (2007–08) (“it is easy to mistake the p-value for the probability that there is no difference”)

[7] Brock v. Merrell Dow Pharmaceuticals, Inc., 874 F.2d 307, 311-12 (5th Cir. 1989), modified, 884 F.2d 166 (5th Cir. 1989), cert. denied, 494 U.S. 1046 (1990). As with any error of this sort, there is always the question whether the judges were entrapped by the parties or their expert witnesses, or whether the judges came up with the fallacy on their own.

[8] See Joel B Greenhouse, “Commentary: Cornfield, Epidemiology and Causality,” 38 Internat’l J. Epidem. 1199 (2009).

[9] Olav Axelson & Kyle Steenland, “Indirect methods of assessing the effects of tobacco use in occupational studies,” 13 Am. J. Indus. Med. 105 (1988); Olav Axelson, “Confounding from smoking in occupational epidemiology,” 46 Brit. J. Indus. Med. 505 (1989); Olav Axelson, “Aspects on confounding in occupational health epidemiology,” 4 Scand. J. Work Envt’l Health 85 (1978).

[10] See, e.g., David Kriebel, Ariana Zeka1, Ellen A Eisen, and David H. Wegman, “Quantitative evaluation of the effects of uncontrolled confounding by alcohol and tobacco in occupational cancer studies,” 33 Internat’l J. Epidem. 1040 (2004).

[11] Kari Furu, Helle Kieler, Bengt Haglund, Anders Engeland, Randi Selmer, Olof Stephansson, Unnur Anna Valdimarsdottir, Helga Zoega, Miia Artama, Mika Gissler, Heli Malm, and Mette Nørgaard, “Selective serotonin reuptake inhibitors and ventafaxine in early pregnancy and risk of birth defects: population based cohort study and sibling design,” 350 Brit. Med. J. 1798 (2015).

[12] Timothy L.. Lash, Matthew P. Fox, Richard F. MacLehose, George Maldonado, Lawrence C. McCandless, and Sander Greenland, “Good practices for quantitative bias analysis,” 43 Internat’l J. Epidem. 1969 (2014).

[13] Oliver Wendell Holmes, Jr., Collected Legal Papers at 311 (1920) (“Certitude is not the test of certainty. We have been cock-sure of many things that were not so.”).

[14] See, e.g., Daniel Kahneman & Amos Tversky, “Judgment under Uncertainty:  Heuristics and Biases,” 185 Science 1124 (1974).

Professor Bernstein’s Critique of Regulatory Daubert

May 15th, 2015

In the law of expert witness gatekeeping, the distinction between scientific claims made in support of litigation positions and claims made in support of regulations is fundamental. In re Agent Orange Product Liab. Litig., 597 F. Supp. 740, 781 (E.D.N.Y. 1984) (“The distinction between avoidance of risk through regulation and compensation for injuries after the fact is a fundamental one”), aff’d 818 F.2d 145 (2d Cir. 1987), cert. denied sub nom. Pinkney v. Dow Chemical Co., 487 U.S. 1234 (1988). Although scientists proffer opinions in both litigation and regulatory proceedings, their opinions are usually evaluated by substantially different standards. In federal litigation, civil and criminal, expert witnesses must be qualified and have an epistemic basis for their opinions, to satisfy the statutory requirements of Federal Rule of Evidence 702, and they must have reasonably relied upon otherwise inadmissible evidence (such as the multiple layers of hearsay involved in an epidemiologic study) under Rule 703. In regulatory proceedings, scientists are not subject to admissibility requirements and the sufficiency requirements set by the Administrative Procedures Act are extremely low[1].

Some industry stakeholders are aggrieved by the low standards for scientific decision making in certain federal agencies, and they have urged that the more stringent litigation evidentiary rules be imported into regulatory proceedings. There are several potential problems with such reform proposals. First, the epistemic requirements of science generally, or of Rules 702 and 703 in particular, are not particularly stringent. Scientific method leads to plenty of false positive and false negative conclusions, which are subject to daily challenge and revision. Scientific inference is not necessarily so strict, as much as ordinary reasoning is so flawed, inexact, and careless. Second, the call for “regulatory Daubert” ignores mandates of some federal agency enabling statutes and guiding regulations, which call for precautionary judgments, and which allow agencies to decide issues on evidentiary display that fall short of epistemic warrants for claims of knowledge.

Many lawyers who represent industry stakeholders have pressed for extension of Daubert-type gatekeeping to federal agency decision making. The arguments for constraining agency action find support in the over-extended claims that agencies and so-called public interest science advocates make in support of agency measures. Advocates and agency personnel seem to believe that worst-case scenarios and overstated safety claims are required as “bargaining” positions to achieve the most restrictive and possibly the most protective regulation that can be gotten from the administrative procedure, while trumping industry’s concerns about costs and feasibility. Still, extending Daubert to regulatory proceedings could have the untoward result of lowering the epistemic bar for both regulators and litigation fact finders.

In a recent article, Professor David Bernstein questions the expansion of Daubert into some regulatory realms. David E. Bernstein, “What to Do About Federal Agency Science: Some Doubts About Regulatory Daubert,” 22 Geo. Mason L. Rev. 549 (2015)[cited as Bernstein]. His arguments are an important counterweight to those who insist on changing agency rulemaking and actions at every turn. As an acolyte and a defender of scientific scruples and reasoning in the courts, Bernstein’s arguments are worth taking seriously.

Bernstein reminds us that bad policy, as seen in regulatory agency rulemaking or decisions, is not always a scientific issue. In any event, regulatory actions, unlike jury decisions, are not, or at least should not be, “black boxes.” The agency’s rationale and reasoning are publicly stated, subject to criticism, and open to revision. Jury decisions are opaque, non-transparent, potentially unreasoned, not carefully articulated, and not subject to revision absent remarkable failures of proof.

One line of argument[2] pursued by Professor Bernstein follows from his observation that Daubert procedures are required to curtail litigation expert witness “adversarial bias.” Id. at 555. Bernstein traces adversarial bias to three sources:

(1) conscious bias;

(2) unconscious bias; and

(3) selection bias.

Id. Conscious bias stems from deliberate attempts by “hired guns” to deliver opinions that satisfy the lawyers who retained them. The problem of conscious bias is presented by “hired guns” who will adapt their opinions to the needs of the attorney who hires them. Unconscious biases are the more subtle, but no less potent determinants of expert witness behavior, which are created by financial dependence upon, and allegiance to, the witness’s paymaster. Selection bias results from lawyers’ ability to choose expert witnesses to support their claims, regardless whether those witnesses’ opinions are representative of the scientific community. Id.

Professor Bernstein’s taxonomy of bias is important, but incomplete. First, the biases he identifies operate fulsomely in regulatory settings. Although direct financial remuneration is usually not a significant motivation for a scientist to testify before an agency, or to submit a whitepaper, professional advancement and cause advocacy are often powerful incentives at work. These incentives for self-styled public interest zealots may well create more powerful distortions of scientific judgment than any monetary factors in private litigation settings. As for selection bias, lawyers are ethically responsible for screening their expert witnesses, and there can be little doubt that once expert witnesses are disclosed, their opinions will align with their sponsoring parties’ interests. This systematic bias, however, does not necessarily mean that both side’s expert witnesses will necessarily be unrepresentative or unscientific. In the silicone gel breast implant litigation (MDL 926), Judge Pointer, the presiding judge, insisted that both sides’ witnesses were “too extreme,” and he was stunned when his court-appointed expert witnesses filed reports that vindicated the defendants’ expert witnesses’ positions[3]. The defendants had selected expert witnesses who analyzed the data on sound scientific principles; the plaintiffs had selected expert witnesses who overreached in their interpretation of the evidence. Furthermore, many scientific disputes, which find their way into the courtroom, will not have the public profile of silicone gel breast implants, and for which there may be no body of scientific community opinion from which lawyers could select “outliers,” even if they wished to do so.

Professor Bernstein’s offered taxonomy of bias is incomplete because it does not include the most important biases that jurors (and many judges) struggle to evaluate:

random errors;

systematic biases;

confounding; and

cognitive biases.

These errors and biases, along with their consequential fallacies of reasoning, apply with equal force to agency and litigation science. Bernstein does point out, however, an important institutional difference between jury or judge trials and agency review and decisions based upon scientific evidence: agencies often have extensive in-house expertise. Although agency expertise may sometimes be blinded by its policy agenda, agency procedures usually afford the public and the scientific community to understand what the agency decided, and why, and to respond critically when necessary. In the case of the Food and Drug Administration, agency decisions, whether pro- or contra-industry positions are dissected and critiqued by the scientific and statistical community with great care and relish. Nothing of the same sort is possible in response to a jury verdict.

Professor Bernstein is not a science nihilist, and he would not have reviewing courts give a pass to whatever nonsense federal agencies espouse. He calls for enforcement of available statutory requirements that agency action be based upon the “best available science,” and for requiring agencies to explicitly separate and state their policy and scientific judgments. Bernstein also urges greater use of agency peer review, such as occasionally seen from the Institute of Medicine (soon to be the National Academy of Medicine), and the use of Daubert-like criteria for testimony at agency hearings. Bernstein at 554.

Proponents of regulatory Daubert should take Professor Bernstein’s essay to heart, with a daily dose of atorvastatin. Importing Rule 702 into agency proceedings may well undermine the rule’s import in litigation, civil and criminal, while achieving little in the regulatory arena. Consider the pending OSHA rulemaking for lowering the permissible exposure limit (PEL) of crystalline silica in the workplace. OSHA, and along with some public health organizations, has tried to justify this rulemaking on the basis of many overwrought claims of the hazards of crystalline silica exposure at current levels. Clearly, there are some workers who continue to work in unacceptably hazardous conditions, but the harms sustained by these workers can be tied to violations of the current PEL; they are hardly an argument for lowering that current PEL. Contrary to the OSHA’s parade of horribles, silicosis mortality in the United States has steadily declined over the last several decades. The following chart draws upon NIOSH and other federal governmental data:

 

Silicosis Deaths by Year

 

Silicosis deaths, crude and age-adjusted death rates, for U.S. residents age 15 and over, 1968–2007

from Susan E. Dudley & Andrew P. Morriss, “Will the Occupational Safety and Health Administration’s Proposed Standards for Occupational Exposure to Respirable Crystalline Silica Reduce Workplace Risk?” 35 Risk Analysis (2015), in press, doi: 10.1111/risa.12341 (NIOSH reference number: 2012F03–01, based upon multiple cause-of-death data from National Center for Health Statistics, National Vital Statistics System, with population estimates from U.S. Census Bureau).

The decline in silicosis mortality is all the more remarkable because it occurred in the presence of stimulated reporting from silicosis litigation, and misclassification of coal workers’ pneumoconiosis in coal-mining states.

The decline in silicosis mortality may be helpfully compared with the steady rise in mortality from accidental falls among men and women 65 years old, or older:

CDC MMWR Death Rates from Unintentional Falls 2015

Yahtyng Sheu, Li-Hui Chen, and Holly Hedegaard, “QuickStats: Death Rates* from Unintentional Falls† Among Adults Aged ≥ 65 Years, by Sex — United States, 2000–2013,” 64 CDC MMWR 450 (May 1, 2015). Over the observation period, these death rates roughly doubled in both men and women.

Is there a problem with OSHA rulemaking? Of course. The agency has gone off on a regulatory frolic and detour trying to justify an onerous new PEL, without any commitment to enforcing its current silica PEL. OSHA has invoked the prospect of medical risks, many of which are unproven, speculative, and remote, such as lung cancer, autoimmune disease, and kidney disease. The agency, however, is awash with PhDs, and I fear that Professor Bernstein is correct that the distortions of the science are not likely to be corrected by applying Rule 702 to agency factfinding. Courts, faced with the complex prediction models, with disputed medical claims made by agency and industry scientists, will do what they usually do, shrug and defer. And the blow back of the “judicially approved” agency science in litigation contexts will be a cure worse than the disease. At bottom, the agency twisting of science is driven by policy goals and considerations, which require public debate and scrutiny, sound executive judgment, with careful legislative oversight and guidance.


[1] Even under the very low evidentiary and procedural hurdles, federal agencies still manage to outrun their headlights on occasion. See, e.g., Industrial Union Department v. American Petroleum Institute, 448 U.S. 607 (1980) (The Benzene Case); Gulf South Insulation v. U.S. Consumer Product Safety Comm’n, 701 F.2d 1137 (5th Cir. 1983); Corrosion Proof Fittings v. EPA, 947 F2d 1201 (5th Cir 1991).

[2] See also David E. Bernstein, “The Misbegotten Judicial Resistance to the Daubert Revolution,” 89 Notre Dame L. Rev. 27, 31 (2013); David E. Bernstein, “Expert Witnesses, Adversarial Bias, and the (Partial) Failure of the Daubert Revolution,” 93 Iowa L. Rev. 451, 456–57 (2008).

[3] Judge Pointer was less than enthusiastic about performing any gatekeeping role. Unlike most of today’s MDL judges, he was content to allow trial judges in the transferor districts to decide Rule 702 and other pre-trial issues. See Note, “District Judge Takes Issue With Circuit Courts’ Application of Gatekeeping Role” 3 Federal Discovery News (Aug. 1997) (noting that Chief Judge Pointer had criticized appellate courts for requiring district judges to serve as gatekeepers of expert witness testimony).

ALI Reporters Are Snookered by Racette Fallacy

April 27th, 2015

In the Reference Manual on Scientific Evidence, the authors of the epidemiology chapter advance instances of acceleration of onset of disease as an example of a situation in which reliance upon doubling of risk will not provide a reliable probability of causation calculation[1]. In a previous post, I suggested that the authors’ assertion may be unfounded. SeeReference Manual on Scientific Evidence on Relative Risk Greater Than Two For Specific Causation Inference” (April 25, 2014). Several epidemiologic methods would permit the calculation of relative risk within specific time windows from first exposure.

The American Law Institute (ALI) Reporters, for the Restatement of Torts, make similar claims.[2] First, the Reporters, citing the Manual’s second edition, repeat the Manual’s claim that:

 “Epidemiologists, however, do not seek to understand causation at the individual level and do not use incidence rates in group to studies to determine the cause of an individual’s disease.”

American Law Institute, Restatement (Third) of Torts: Liability for Physical and Emotional Harm § 28(a) cmt. c(4) & rptrs. notes (2010) [Comment c(4)]. In making this claim, the Reporters ignore an extensive body of epidemiologic studies on genetic associations and on biomarkers, which do address causation implicitly or explicitly, on an individual level.

The Reporters also repeat the Manual’s doubtful claim that acceleration of onset of disease prevents an assessment of attributable risk, although they acknowledge that an average earlier age of onset would form the basis of damages calculations rather than calculations for damages for an injury that would not have occurred but for the tortious exposure. Comment c(4). The Reporters go a step further than the Manual, however, and provide an example of the acceleration-of-onset studies that they have in mind:

“For studies whose results suggest acceleration, see Brad A. Racette, Welding-Related Parkinsonism: Clinical Features, Treatments, and Pathophysiology,” 56 Neurology 8, 12 (2001) (stating that authors “believe that welding acts as an accelerant to cause [Parkinson’s Disease]… .”

The citation to Racette’s 2001 paper[3] is curious, interesting, disturbing, and perhaps revealing. In this 2001 paper, Racette misrepresented the type of study he claimed to have done, and the inferences he drew from his case series are invalid. Any one experienced in the field of epidemiology would have dismissed this study, its conclusions, and its suggested relation between welding and parkinsonism.

Dr. Brad A. Racette teaches and practices neurology at Washington University in St. Louis, across the river from a hotbed of mass tort litigation, Madison County, Illinois. In the 1990s, Racette received referrals from plaintiffs’ attorneys to evaluate their clients in litigation over exposure to welding fumes. Plaintiffs were claiming that their occupational exposures caused them to develop manganism, a distinctive parkinsonism that differs from Parkinson’s disease [PD], but has signs and symptoms that might be confused with PD by unsophisticated physicians unfamiliar with both manganism and PD.

After the publication of his 2001 paper, Racette became the darling of felon Dicky Scruggs and other plaintiffs’ lawyers. The litigation industrialists invited Racette and his team down to Alabama and Mississippi, to conduct screenings of welding tradesmen, recruited by Scruggs and his team, for potential lawsuits for PD and parkinsonism. The result was a paper that helped Scruggs propel a litigation assault against the welding industry.[4]

Racette’s 2001 paper was accompanied by a press release, as have many of his papers, in which he was quoted as stating that “[m]anganism is a very different disease” from PD. Gila Reckess, “Welding, Parkinson’s link suspected” (Feb. 9, 2001)[5].

Racette’s 2001 paper provoked a strongly worded letter that called Racette and his colleagues out for misrepresenting the nature of their work:

“The authors describe their work as a case–control study. Racette et al. ascertained welders with parkinsonism and compared their concurrent clinical features to those of subjects with PD. This is more consistent with a cross-sectional design, as the disease state and factors of interest were ascertained simultaneously. Cross-sectional studies are descriptive and therefore cannot be used to infer causation.”

*****

“The data reported by Racette et al. do not necessarily support any inference about welding as a risk factor in PD. A cohort study would be the best way to evaluate the role of welding in PD.”

Bernard Ravina, Andrew Siderowf, John Farrar, Howard Hurtig, “Welding-related parkinsonism: Clinical features, treatment, and pathophysiology,” 57 Neurology 936, 936 (2001).

As we will see, Dr. Ravina and his colleagues were charitable to suggest that the study was more compatible with a cross-sectional study. Racette had set out to determine “whether welding-related parkinsonism differs from idiopathic PD.” He claimed that he had “performed a case-control study,” with a case group of welders and two control groups. His inferences drawn from his “data” are, however, fallacious because he employed an invalid study design.

In reality, Racette’s paper was nothing more than a chart review, a case series of 15 “welders” in the context of a movement disorder clinic. After his clinical and radiographic evaluation, Racette found that these 15 cases were clinically indistinguishable from PD, and thus unlike manganism. Racette did not reveal whether any of these 15 welders had been referred by plaintiffs’ counsel; nor did he suggest that these welding tradesmen made up a disproportionate number of his patient base in St. Louis, Missouri.

Racette compared his selected 15 career welders with PD to his general movement disorders clinic patient population, for comparison. From the patient population, Racette deployed two “control” groups, one matched for age and sex with the 15 welders, and the other group not matched. The America Law Institute reporters are indeed correct that Racette suggested that the average age of onset for these 15 welders was lower than that for his non-welder patients, but their uncritical embrace overlooked the fact that Racette’s suggestion does not support his claimed inference that in welders, therefore, “welding exposure acts as an accelerant to cause PD.”

Racette’s claimed inference is remarkable because he did not perform an analytical epidemiologic study that was capable of generating causal inferences. His paper incongruously presents odds ratios, although the controls have PD, the disease of interest, which invalidates any analytical inference from his case series. Given the referral and selection biases inherent in tertiary-care specialty practices, this paper can provide no reliable inferences about associations or differences in ages of onset. Even within the confines of a case series misrepresented to be a case-control study, Racette acknowledged that “[s]ubsequent comparisons of the welders with age-matched controls showed no significant differences.”

NOT A CASE-CONTROL STUDY

That Racette wrongly identified his paper as a case-control study is beyond debate. How the journal Neurology accepted the paper for publication is a mystery. The acceptance of the inference by the ALI Reporter, lawyers and judges, is regrettable.

Structurally, Racette’s paper could never quality as a case-control study, or any other analytical epidemiologic study. Here is how a leading textbook on case-control studies defines a case-control study:

“In a case-control study, individuals with a particular condition or disease (the cases) are selected for comparison with a series of individuals in whom the condition or disease is absent (the controls).”

James J. Schlesselman, Case-control Studies. Design, Conduct, Analysis at 14 (N.Y. 1982)[6].

Every patient in Racette’s paper, welders and non-welders, have the outcome of interest, PD. There is no epidemiologic study design that corresponds to what Racette did, and there is no way to draw any useful inference from Racette’s comparisons. Racette’s paper violates the key principle for a proper case-control study; namely, all subjects must be selected independently of the study exposure that is under investigation. Schlesselman stressed that that identifying an eligible case or control must not depend upon that person’s exposure status for any factor under consideration. Id. Racette’s 2001 paper deliberately violated this basic principle.

Racette’s study design, with only cases with the outcome of interest appearing in the analysis, recklessly obscures the underlying association between the exposure (welding) and age in the population. We would, of course, expect self-identified welders to be younger than the average Parkinson’s disease patient because welding is physical work that requires good health. An equally fallacious study could be cobbled together to “show” that the age-of-onset of Parkinson’s disease for sitcom actors (such as Michael J. Fox) is lower than the age-of-onset of Parkinson’s disease for Popes (such as John Paul II). Sitcom actors are generally younger as a group than Popes. Comparing age of onset between disparate groups that have different age distributions generates a biased comparison and an erroneous inference.

The invalidity and fallaciousness of Racette’s approach to studying the age-of-onset issue of PD in welders, and his uncritical inferences, have been extensively commented upon in the general epidemiologic literature. For instance, in studies that compared the age at death for left-handed versus right-handed person, studies reported an observed nine-year earlier death for left handers, leading to (unfounded) speculation that earlier mortality resulted from birth and life stressors and accidents for left handers, living in a world designed to accommodate right-handed person[7]. The inference has been shown to be fallacious and the result of social pressure in the early twentieth century to push left handers to use their right hands, a prejudicial practice that abated over the decades of the last century. Left handers born later in the century were less likely to be “switched,” as opposed to those persons born earlier and now dying, who were less likely to be classified as left-handed, as a result of a birth-cohort effect[8]. When proper prospective cohort studies were conducted, valid data showed that left-handers and right-handers have equivalent mortality rates[9].

Epidemiologist Ken Rothman addressed the fallacy of Racette’s paper at some length in one of his books:

“Suppose we study two groups of people and look at the average age at death among those who die. In group A, the average age of death is 4 years; in group B, it is 28 years. Can we say that being a member of group A is riskier than being a member of group B? We cannot… . Suppose that group A comprises nursery school students and group B comprises military commandos. It would be no surprise that the average age at death of people who are currently military commandos is 28 years or that the average age of people who are currently nursery students is 4 years. …

In a study of factory workers, an investigator inferred that the factory work was dangerous because the average age of onset of a particular kind of cancer was lower in these workers than among the general population. But just as for the nursery school students and military commandos, if these workers were young, the cancers that occurred among them would have to be occurring in young people. Furthermore, the age of onset of a disease does not take into account what proportion of people get the disease.

These examples reflect the fallacy of comparing the average age at which death or disease strikes rather than comparing the risk of death between groups of the same age.”

Kenneth J. Rothman, “Introduction to Epidemiologic Thinking,” in Epidemiology: An Introduction at 5-6 (N.Y. 2002).

And here is how another author of Modern Epidemiology[10] addressed the Racette fallacy in a different context involving PD:

“Valid studies of age-at-onset require no underlying association between the risk factor and aging or birth cohort in the source population. They must also consider whether a sufficient induction time has passed for the risk factor to have an effect. When these criteria and others cannot be satisfied, age-specific or standardized risks or rates, or a population-based case-control design, must be used to study the association between the risk factor and outcome. These designs allow the investigator to disaggregate the relation between aging and the prevalence of the risk factor, using familiar methods to control confounding in the design or analysis. When prior knowledge strongly suggests that the prevalence of the risk factor changes with age in the source population, case-only studies may support a relation between the risk factor and age-at-onset, regardless of whether the inference is justified.”

Jemma B. Wilk & Timothy L. Lash, “Risk factor studies of age-at-onset in a sample ascertained for Parkinson disease affected sibling pairs: a cautionary tale,” 4 Emerging Themes in Epidemiology 1 (2007) (internal citations omitted) (emphasis added).

A properly designed epidemiologic study would have avoided Racette’s fallacy. A relevant cohort study would have enrolled welders in the study at the outset of their careers, and would have continued to follow them even if they changed occupations. A case-control study would have enrolled cases with PD and controls without PD (or more broadly, parkinsonism), with cases and controls selected independently of their exposure to welding fumes. Either method would have determined the rate of PD in both groups, absolutely or relatively. Racette’s paper, which completely lacked non-PD cases, could not have possibly accomplished his stated objectives, and it did not support his claims.

Racette’s questionable work provoked a mass tort litigation and ultimately federal Multi-District Litigation 1535.[11] Ultimately, analytical epidemiologic studies consistently showed no association between welding and PD. A meta-analysis published in 2012 ended the debate[12] as a practical matter, and MDL 1535 is no more. How strange that the ALI reporters chose the Racette work as an example of their claims about acceleration of onset!


[1] Michael D. Green, D. Michal Freedman, and Leon Gordis, “Reference Guide on Epidemiology,” in Federal Judicial Center, Reference Manual on Scientific Evidence 549, 614 (Wash., DC 3d ed. 2011).

[2] Michael D. Green was an ALI Reporter, and of course, an author of the chapter in the Reference Manual.

[3] Brad A. Racette, L. McGee-Minnich, S. M. Moerlein, J. W. Mink, T. O. Videen, and Joel S. Perlmutter, “Welding-related parkinsonism: clinical features, treatment, and pathophysiology,” 56 Neurology 8 (2001).

[4] See Brad A. Racette, S.D. Tabbal, D. Jennings, L. Good, Joel S. Perlmutter, and Brad Evanoff, “Prevalence of parkinsonism and relationship to exposure in a large sample of Alabama welders,” 64 Neurology 230 (2005); Brad A. Racette, et al., “A rapid method for mass screening for parkinsonism,” 27 Neurotoxicology 357 (2006) (duplicate publication of the earlier, 2005, paper).

[5] Previously available at <http://record.wustl.edu/archive/2001/02-09-01/articles/welding.html>, last visited on June 27, 2005.

[6] See also Brian MacMahon & Dimitrios Trichopoulos, Epidemiology. Principles and Methods at 229 (2ed 1996) (“A case-control study is an inquiry in which groups of individuals are selected based on whether they do (the cases) or do not (the controls) have the disease of which the etiology is to be studied.”); Jennifer L. Kelsey, W.D. Thompson, A.S. Evans, Methods in Observational Epidemiology at 148 (N.Y. 1986) (“In a case-control study, persons with a given disease (the cases) and persons without the disease (the controls) are selected … .”).

[7] See, e.g., Diane F. Halpern & Stanley Coren, “Do right-handers live longer?” 333 Nature 213 (1988); Diane F. Halpern & Stanley Coren, “Handedness and life span,” 324 New Engl. J. Med. 998 (1991).

[8] Kenneth J. Rothman, “Left-handedness and life expectancy,” 325 New Engl. J. Med. 1041 (1991) (pointing out that by comparing age of onset method, nursery education would be found more dangerous than paratrooper training, given that the age at death of pres-schoolers wo died would be much lower than that of paratroopers who died); see also Martin Bland & Doug Altman, “Do the left-handed die young?” Significance 166 (Dec. 2005).

[9] See Philip A. Wolf, Ralph B. D’Agostino, Janet L. Cobb, “Left-handedness and life expectancy,” 325 New Engl. J. Med. 1042 (1991); Marcel E. Salive, Jack M. Guralnik & Robert J. Glynn, “Left-handedness and mortality,” 83 Am. J. Public Health 265 (1993); Olga Basso, Jørn Olsen, Niels Holm, Axel Skytthe, James W. Vaupel, and Kaare Christensen, “Handedness and mortality: A follow-up study of Danish twins born between 1900 and 1910,” 11 Epidemiology 576 (2000). See also Martin Wolkewitz, Arthur Allignol, Martin Schumacher, and Jan Beyersmann, “Two Pitfalls in Survival Analyses of Time-Dependent Exposure: A Case Study in a Cohort of Oscar Nominees,” 64 Am. Statistician 205 (2010); Michael F. Picco, Steven Goodman, James Reed, and Theodore M. Bayless, “Methodologic pitfalls in the determination of genetic anticipation: the case of Crohn’s disease,” 134 Ann. Intern. Med. 1124 (2001).

[10] Kenneth J. Rothman, Sander Greenland, Timothy L. Lash, eds., Modern Epidemiology (3d ed. 2008).

[11] Dicky Scruggs served on the Plaintiffs’ Steering Committee until his conviction on criminal charges.

[12] James Mortimer, Amy Borenstein, and Lorene Nelson, “Associations of welding and manganese exposure with Parkinson disease: Review and meta-analysis,” 79 Neurology 1174 (2012).

Reference Manual on Scientific Evidence on Relative Risk Greater Than Two For Specific Causation Inference

April 25th, 2015

The first edition of the Reference Manual on Scientific Evidence [Manual] was published in 1994, a year after the Supreme Court delivered its opinion in Daubert. The Federal Judicial Center organized and produced the Manual, in response to the kernel panic created by the Supreme Court’s mandate that federal trial judges serve as gatekeepers of the methodological propriety of testifying expert witnesses’ opinions. Considering the intellectual vacuum the Center had to fill, and the speed with which it had to work, the first edition was a stunning accomplishment.

In litigating specific causation in so-called toxic tort cases, defense counsel quickly embraced the Manual’s apparent endorsement of the doubling-of-the-risk argument, which would require relative risks in excess of two in order to draw inferences of specific causation in a given case. See Linda A. Bailey, Leon Gordis, and Michael D. Green, “Reference Guide on Epidemiology,” in Federal Judicial Center, Reference Manual on Scientific Evidence 123, 150, 168 (Washington, DC:, 1st ed., 1994) (“The relative risk from an epidemiological study can be adapted to this 50% plus standard to yield a probability or likelihood that an agent caused an individual’s disease. The threshold for concluding that an agent was more likely than not the cause of a disease than not is a relative risk greater than 2.0.”) (internal citations omitted).

In the Second Edition of the Manual, the authorship of the epidemiology chapter shifted, and so did its treatment of doubling of the risk. By adopting a more nuanced analysis, the Second Edition deprived defense counsel of a readily citable source for the proposition that low relative risks do not support inferences of specific causation. The exact conditions for when and how the doubling argument should prevail were, however, left fuzzy and unspecified. See Michael D. Green, D. Michal Freedman , and Leon Gordis, “Reference Guide on Epidemiology,” in Federal Judicial Center, Reference Manual on Scientific Evidence 333, 348-49 (Wash., DC, 2d ed. 2000)

The latest edition of the Manual attempts to correct the failings of the Second Edition by introducing an explanation and a discussion of some of the conditions that might undermine an inference, or opposition thereto, of specific causation from magnitude of relative risk. Michael D. Green, D. Michal Freedman, and Leon Gordis, “Reference Guide on Epidemiology,” in Federal Judicial Center, Reference Manual on Scientific Evidence 549, 612 (Wash., DC 3d ed., 2011).

The authors of the Manual now acknowledge that doubling of risk inference has “a certain logic as far as it goes,” but point out that there are some “significant assumptions and important caveats that require explication.” Id.

What are the assumptions according the Manual?

First, and foremost, there must be “[a] valid study and risk estimate.” Id. (emphasis in original). The identification of this predicate assumption is, of course, correct, but the authors overlook that the assumption is often trivially satisfied by the legal context in which the doubling argument arises. For instance, in the Landrigan and Caterinichio cases, cited below, the doubling issue arose not as an admissibility question of expert witness opinion, but on motions for directed verdict. In both cases, plaintiffs’ expert witnesses committed to opinions about plaintiffs’ being at risk from asbestos exposure, based upon studies that they identified. Defense counsel in those cases did not concede the existence of risk, the size of the risk, or the validity of the study, but rather stipulated such facts solely for purposes of their motions to dismiss. In other words, even if the plaintiffs’ relied upon studies were valid and the risk estimates accurate (with relative risks of 1.5), plaintiffs could not prevail because no reasonable jury could infer that plaintiffs’ colorectal cancers were caused by their occupational asbestos exposure. The procedural context of the doubling risk thus often pretermits questions of validity, bias, and confounding.

Second, the Manual identifies that there must be “[s]imilarity among study subjects and plaintiff.” Id. at 613. Again, this assumption is often either pretermitted for purposes of lodging a dispositive motion, conceded, or included as part of the challenge to an expert witness’s opinion’s admissibility. For example, in some litigations, plaintiffs will rely upon high-dose or high-exposure studies that are not comparable to the plaintiff’s actual exposure, and the defense may have shown that the only reliable evidence is that there is a small (relative risk less than two) or no risk at all from the plaintiff’s exposure. External validity objections may well play a role in a contest under Rule 702, but the resolution of a doubling of risk issue will require an appropriate measure of risk for the plaintiff whose injury is at issue.

In the course of identifying this second assumption, the Manual now points out that the doubling argument turns on applying “an average risk for the group” to each individual in the group. Id. This point again is correct, but the Manual does not come to terms with the challenge often made to what I call the assumption of stochastic risk. The Manual authors quote a leading textbook on epidemiology:

“We cannot measure the individual risk, and assigning the average value to everyone in the category reflects nothing more than our ignorance about the determinants of lung cancer that interact with cigarette smoke. It is apparent from epidemiological data that some people can engage in chain smoking for many decades without developing lung cancer. Others are or will become primed by unknown circumstances and need only to add cigarette smoke to the nearly sufficient constellation of causes to initiate lung cancer. In our ignorance of these hidden causal components, the best we can do in assessing risk is to classify people according to measured causal risk indicators and then assign the average observed within a class to persons within the class.”

Id at n.198., quoting from Kenneth J. Rothman, Sander Greenland, and Tim L. Lash, Modern Epidemiology 9 (3d ed. 2008). Although the textbook on this point is unimpeachable, taken at face value, it would introduce an evidentiary nihilism for judicial determinations of specific causation in cases in which epidemiologic measures of risk size are the only basis for drawing probabilistic inferences of specific causation. See also Manual at 614 n. 198., citing Ofer Shpilberg, et al., The Next Stage: Molecular Epidemiology, 50 J. Clin. Epidem. 633, 637 (1997) (“A 1.5-fold relative risk may be composed of a 5-fold risk in 10% of the population, and a 1.1-fold risk in the remaining 90%, or a 2-fold risk in 25% and a 1.1-fold for 75%, or a 1.5-fold risk for the entire population.”). The assumption of stochastic risk is, as Judge Weinstein recognized in Agent Orange, often the only assumption on which plaintiffs will ever have a basis for claiming individual causation on typical datasets available to support health effects claims. Elsewhere, the authors of the Manual’s chapter suggest that statistical “frequentists” would resist the adaptation of relative risk to provide a probability of causation because for the frequentist, the individual case either is or is not caused by the exposure at issue. Manual at 611 n.188. This suggestion appears to confuse the frequentist enterprise for evaluating evidence on the basis of statistical measures of the probability of observing at least as great a departure from expected in a sample rather than attempting to affixing a probability to the population parameter. The doubling argument derives from the well-known “urn model” in probability theory, which is not really at issue in the frequentist-Bayesian wars.

Third, the Manual authors state that the doubling argument assumes the “[n]onacceleration of disease.” In some cases, this statement is correct, but there is no evidence of acceleration, and because an acceleration-of-onset theory would diminish damages, typically defendants would have the burden of going forward with identifying the acceleration phenomenon. The authors go further, however, in stating that “for most of the chronic diseases of adulthood, it is not possible for epidemiologic studies to distinguish between acceleration of disease and causation of new disease.” Manual at 614. The inability to distinguish acceleration from causation of new cases would typically redound to the disadvantage of defendants that are making the doubling argument. In other words, the defendants would, by this supposed inability, be unable to mitigate damages by showing that the alleged harm would have occurred any way, but only later in time. See Manual at 615 n. 199 (“If acceleration occurs, then the appropriate characterization of the harm for purposes of determining damages would have to be addressed. A defendant who only accelerates the occurrence of harm, say, chronic back pain, that would have occurred independently in the plaintiff at a later time is not liable for the same amount of damages as a defendant who causes a lifetime of chronic back pain.”). More important, however, the Manual appears to be wrong that epidemiologic studies cannot identify acceleration of onset of a particular disease in an epidemiologic study or clinical trial. Many modern longitudinal epidemiologic studies and clinical trials use survival analysis and time windows to identify latency or time lagged outcomes in association with identified exposures.

The fourth assumption identified in the Manual is that the exposure under study acts independently of other exposures. The authors give the time-worn example of multiplicative synergy between asbestos and smoking, what elsewhere has been referred to as “The Mt. Sinai Catechism” (June 7, 2013). The example was improvidently chosen given that the multiplicative nature was doubtful when first advanced, and now has effectively been retracted or modified by the researchers following the health outcomes of asbestos insulators in the United States. More important for our purposes here, interactions can be quantified and added to the analysis of attributable risk; interactions are not insuperable barriers to reasonable apportiontment of risk.

Fifth, the Manual identifies two additional assumptions in that (a) the exposure at issue is not responsible for another outcome that competes with morbidity or mortality, and (b) the exposure does not provide a protective “effect” in a subpopulation of those studied. Manual at 615. On the first of these assumptions, the authors suggest that this assumption is required “because in the epidemiologic studies relied on, those deaths caused by the alternative disease process will mask the true magnitude of increased incidence of the studied disease when the study subjects die before developing the disease of interest.” Id. at 615 n.202. Competing causes, however, are frequently studied and can be treated as confounders in an appropriate regression or propensity score analysis to yield a risk estimate for each individual putative effect at issue. The second of the two assumptions is a rehash of the speculative assertion that the epidemiologic study (and the population it samples) may not have a stochastic distribution of risk. Although the stochastic assumption may not be correct, it is often favorable to the party asserting the claim who otherwise would not be able to show that he was not in a sub-population of people not affected at all, or even benefitted from the exposure. Again, modern epidemiology does not stop at identifying populations at risk, but continues to refine the assessment by trying to identify subpopulations that have the risk exclusively. The existence of multi-modal distributions of risk within a population is, again, not a barrier to the doubling argument.

With sufficiently large samples, epidemiologic studies may be able to identify subgroups that have very large relative risks, even when the overall sample under study had a relative risk under two. The possibility of such subgroups, however, should not be an invitation to wholesale speculation that a given plaintiff is in a “vulnerable” subgroup without reliable, valid evidence of what the risks for the identified subgroup are. Too often, the vulnerable plaintiff or subgroup claim is merely hand waving in an evidentiary vacuum. The Manual authors seem to adopt this hand-waving attitude when they give a speculative hypothetical example:

“For example, genetics might be known to be responsible for 50% of the incidence of a disease independent of exposure to the agent. If genetics can be ruled out in an individual’s case, then a relative risk greater than 1.5 might be sufficient to support an inference that the agent was more likely than not responsible for the plaintiff’s disease.”

Manual at 615-16 (internal citations omitted). The hypothetical is unclear whether “the genetics” cases are part of the study that yielded a relative risk of 1.5, but of course if the “genetics” were uniformly distributed in the population, and also in the sample studied in the epidemiologic study, then the “genetics” would appear to drop out of playing any role in elevating risk. But as the authors pointed out in their caveats about interaction, there may well be a role of interaction between the “genetics” and the exposure in the study such that “the genetics” cases occurred earlier or did not add anything to the disease burden that would have been caused by the exposure under study that reported out a relative risk of 1.5. So bottom line, plaintiff would need a study that applied the “genetics” to the epidemiologic study to see what relative risks might be observed in people without the genes at issue.

The Third Edition of the Manual does add more nuance to the doubling of risk argument, but alas more nuance yet is needed. The chapter is an important source to include in any legal argument for or against inferences of specific causation, but it is hardly the final word.

Below, I have updated a reference list of cases that reference the doubling argument.


Radiation

Johnston v. United States, 597 F. Supp. 374, 412, 425-26 (D. Kan. 1984) (rejecting even a relative risk of greater than two as supporting an inference of specific causation)

Allen v. United States, 588 F. Supp. 247, 418 (1984) (rejecting mechanical application of doubling of risk), rev’d on other grounds, 816 F.2d 1417 (10th Cir. 1987), cert. denied, 484 U.S. 1004 (1988)

In re TMI Litig., 927 F. Supp. 834, 845, 864–66 (M.D. Pa. 1996), aff’d, 89 F.3d 1106 (3d Cir. 1996), aff’d in part, rev’d in part, 193 F.3d 613 (3d Cir. 1999) (rejecting “doubling dose” trial court’s analysis), modified 199 F.3d 158 (3d Cir. 2000) (stating that a dose below ten rems is insufficient to infer more likely than not the existence of a causal link)

In re Hanford Nuclear Reservation Litig., 1998 WL 775340, at *8 (E.D. Wash. Aug. 21, 1998) (“‘[d]oubling of the risk’ is the legal standard for evaluating the sufficiency of the plaintiffs’ evidence and for determining which claims should be heard by the jury,” citing Daubert II), rev’d, 292 F.3d 1124, 1136-37 (9th Cir. 2002) (general causation)

In re Berg Litig., 293 F.3d 1127 (9th Cir. 2002) (companion case to In re Hanford)

Cano v. Everest Minerals Corp., 362 F. Supp. 2d 814, 846 (W.D. Tex. 2005) (relative risk less than 3.0 represents only a weak association)

Cook v. Rockwell Internat’l Corp., 580 F. Supp. 2d 1071, 1083n.8, 1084, 1088-89 (D. Colo. 2006) (citing Daubert II and “concerns” by Sander Greenland and David Egilman, plaintiffs’ expert witnesses in other cases), rev’d and remanded on other grounds, 618 F.3d 1127 (10th Cir. 2010), cert. denied, ___ U.S. ___ (May 24, 2012)

Cotroneo v. Shaw Envt’l & Infrastructure, Inc., No. H-05- 1250, 2007 WL 3145791, at *3 (S.D. Tex. Oct. 25, 2007) (citing Havner, 953 S.W.2d at 717) (radioactive material)


Swine Flu- GBS Cases

Cook v. United States, 545 F. Supp. 306, 308 (N.D. Cal. 1982)(“Whenever the relative risk to vaccinated persons is greater than two times the risk to unvaccinated persons, there is a greater than 50% chance that a given GBS case among vaccinees of that latency period is attributable to vaccination, thus sustaining plaintiff’s burden of proof on causation.”)

Robinson v. United States, 533 F. Supp. 320, 325-28 (E.D. Mich. 1982) (finding for the government and against claimant who developed acute signs and symptoms of GBS 17 weeks after innoculation, in part because of relative and attributable risks)

Padgett v. United States, 553 F. Supp. 794, 800 – 01 (W.D. Tex. 1982) (“From the relative risk, we can calculate the probability that a given case of GBS was caused by vaccination. . . . [A] relative risk of 2 or greater would indicate that it was more likely than not that vaccination caused a case of GBS.”)

Manko v. United States, 636 F. Supp. 1419, 1434 (W.D. Mo. 1986) (relative risk of 2, or less, means exposure not the probable cause of disease claimed) (incorrectly suggesting that relative risk of two means that there was a 50% chance the disease was caused by “chance alone”), aff’d in relevant part, 830 F.2d 831 (8th Cir. 1987)


IUD Cases – Pelvic Inflammatory Disease

Marder v. G.D. Searle & Co., 630 F. Supp. 1087, 1092 (D.Md. 1986) (“In epidemiological terms, a two-fold increased risk is an important showing for plaintiffs to make because it is the equivalent of the required legal burden of proof—a showing of causation by the preponderance of the evidence or, in other words, a probability of greater than 50%.”), aff’d mem. on other grounds sub nom. Wheelahan v. G.D.Searle & Co., 814 F.2d 655 (4th Cir. 1987) (per curiam)


Bendectin cases

Lynch v. Merrill-National Laboratories, 646 F.Supp. 856 (D. Mass. 1986)(granting summary judgment), aff’d, 830 F.2d 1190, 1197 (1st Cir. 1987)(distinguishing between chances that “somewhat favor” plaintiff and plaintiff’s burden of showing specific causation by “preponderant evidence”)

DeLuca v. Merrell Dow Pharm., Inc., 911 F.2d 941, 958-59 (3d Cir. 1990) (commenting that ‘‘[i]f New Jersey law requires the DeLucas to show that it is more likely than not that Bendectin caused Amy DeLuca’s birth defects, and they are forced to rely solely on Dr. Done’s epidemiological analysis in order to avoid summary judgment, the relative risk of limb reduction defects arising from the epidemiological data Done relies upon will, at a minimum, have to exceed ‘2’’’)

Daubert v. Merrell Dow Pharms., Inc., 43 F.3d 1311, 1321 (9th Cir.) (“Daubert II”) (holding that for epidemiological testimony to be admissible to prove specific causation, there must have been a relative risk for the plaintiff of greater than 2; testimony that the drug “increased somewhat the likelihood of birth defects” is insufficient) (“For an epidemiological study to show causation under a preponderance standard . . . the study must how that children whose mothers took Bendectin are more than twice as likely to develop limb reduction birth defects as children whose mothers did not.”), cert. denied, 516 U.S. 869 (1995)

DePyper v. Navarro, 1995 WL 788828 (Mich. Cir. Ct. Nov. 27, 1995)

Oxendine v. Merrell Dow Pharm., Inc., 1996 WL 680992 (D.C. Super. Ct. Oct. 24, 1996) (noting testimony by Dr. Michael Bracken, that had Bendectin doubled risk of birth defects, overall rate of that birth defect should have fallen 23% after manufacturer withdrew drug from market, when in fact the rate remained relatively steady)

Merrell Dow Pharms., Inc. v. Havner, 953 S.W.2d 706, 716 (Tex. 1997) (holding, in accord with the weight of judicial authority, “that the requirement of a more than 50% probability means that epidemiological evidence must show that the risk of an injury or condition in the exposed population was more than double the risk in the unexposed or control population”); id. at at 719 (rejecting isolated statistically significant associations when not consistently found among studies)


Silicone Cases

Hall v. Baxter Healthcare, 947 F. Supp. 1387, 1392, 1397, 1403-04 (D. Ore. 1996) (discussing relative risk of 2.0)

Pick v. American Medical Systems, Inc., 958 F. Supp. 1151, 1160 (E.D. La. 1997) (noting, correctly but irrelevantly, in penile implant case, that “any” increased risk suggests that the exposure “may” have played some causal role)

In re Breast Implant Litigation, 11 F. Supp. 2d 1217, 1226 -27 (D. Colo. 1998) (relative risk of 2.0 or less shows that the background risk is at least as likely to have given rise to the alleged injury)

Barrow v. Bristol-Myers Squibb Co., 1998 WL 812318 (M.D. Fla. Oct. 29, 1998)

Minnesota Mining and Manufacturing v. Atterbury, 978 S.W.2d 183, 198 (Tex.App. – Texarkana 1998) (noting that Havner declined to set strict criteria and that “[t]here is no requirement in a toxic tort case that a party must have reliable evidence of a relative risk of 2.0 or greater”)

Allison v. McGhan Med. Corp., 184 F.3d 1300, 1315n.16, 1316 (11th Cir. 1999) (affirming exclusion of expert testimony based upon a study with a risk ratio of 1.24; noting that statistically significant epidemiological study reporting an increased risk of marker of disease of 1.24 times in patients with breast implants was so close to 1.0 that it “was not worth serious consideration for proving causation”; threshold for concluding that an agent more likely than not caused a disease is 2.0, citing Federal Judicial Center, Reference Manual on Scientific Evidence 168-69 (1994))

Grant v. Bristol-Myers Squibb, 97 F. Supp. 2d 986, 992 (D. Ariz. 2000)

Pozefsky v. Baxter Healthcare Corp., No. 92-CV-0314, 2001 WL 967608, at *3 (N.D.N.Y. August 16, 2001) (excluding causation opinion testimony given contrary epidemiologic studies; noting that sufficient epidemiologic evidence requires relative risk greater than two)

In re Silicone Gel Breast Implant Litig., 318 F. Supp. 2d 879, 893 (C.D. Cal. 2004) (“The relative risk is obtained by dividing the proportion of individuals in the exposed group who contract the disease by the proportion of individuals who contract the disease in the non-exposed group.”) (noting that relative risk must be more than doubled at a minimum to permit an inference that the risk was operating in plaintiff’s case)

Norris v. Baxter Healthcare Corp., 397 F.3d 878 (10th Cir. 2005) (discussing but not deciding specific causation and the need for relative risk greater than two; no reliable showing of general causation)

Barrow v. Bristol-Meyers Squibb Co., 1998 WL 812318, at *23 (M.D. Fla., Oct. 29, 1998)

Minnesota Mining and Manufacturing v. Atterbury, 978 S.W.2d 183, 198 (Tex. App. – Texarkana 1998) (noting that “[t]here is no requirement in a toxic tort case that a party must have reliable evidence of a relative risk of 2.0 or greater”)


Asbestos

Lee v. Johns Manville Corp., slip op. at 3, Phila. Cty. Ct. C.P., Sept. Term 1978, No. 88 (123) (Oct. 26, 1983) (Forer, J.)(entering verdict in favor of defendants on grounds that plaintiff had failed to show that his colo rectal cancer had been caused by asbestos exposure after adducing evidence of a relative risk less than two)

Washington v. Armstrong World Indus., Inc., 839 F.2d 1121 (5th Cir. 1988) (affirming grant of summary judgment on grounds that there was insufficient evidence that plaintiff’s colon cancer was caused by asbestos)

Primavera v. Celotex Corp., Phila. Cty. Ct. C.P., December Term, 1981, No. 1283 (Bench Op. of Hon. Berel Caesar, (Nov. 2, 1988) (granting compulsory nonsuit on the plaintiff’s claim that his colorectal cancer was caused by his occupational exposure to asbestos)

In re Fibreboard Corp.,893 F.2d 706, 712 (5th Cir.1990) (“It is evident that these statistical estimates deal only with general causation, for population-based probability estimates do not speak to a probability of causation in any one case; the estimate of relative risk is a property of the studied population, not of an individual’s case.” (internal quotation omitted) (emphasis in original))

Grassis v. Johns-Manville Corp., 248 N.J. Super. 446, 455-56, 591 A.2d 671, 676 (App. Div. 1991) (rejecting doubling of risk threshold in asbestos gastrointestinal cancer claim)

Landrigan v. Celotex Corp., 127 N.J. 404, 419, 605 A.2d 1079 (1992) (reversing judgment entered on directed verdict for defendant on specific causation of claim that asbestos caused decedent’s colon cancer)

Caterinicchio v. Pittsburgh Corning Corp., 127 N.J. 428, 605 A.2d 1092 (1992) (reversing judgment entered on directed verdict for defendant on specific causation of claim that asbestos caused plaintiff’s colon cancer)

In re Joint E. & S. Dist. Asbestos Litig., 758 F. Supp. 199 (S.D.N.Y. 1991), rev’d sub nom. Maiorano v. Owens Corning Corp., 964 F.2d 92, 97 (2d Cir. 1992);

Maiorana v. National Gypsum, 827 F. Supp. 1014, 1043 (S.D.N.Y. 1993), aff’d in part and rev’d in part, 52 F.3d 1124, 1134 (2d Cir. 1995) (stating a preference for the district court’s instructing the jury on the science and then letting the jury weigh the studies)

Keene Corp. v. Hall, 626 A.2d 997 (Md. Spec. Ct. App. 1993) (laryngeal cancer)

Jones v. Owens-Corning Fiberglas Corp., 288 N.J. Super. 258, 266, 672 A.2d 230, 235 (App. Div. 1996) (rejecting doubling of risk threshold in asbestos gastrointestinal cancer claim)

In re W.R. Grace & Co., 355 B.R. 462, 483 (Bankr. D. Del. 2006) (requiring showing of relative risk greater than two to support property damage claims based on unreasonable risks from asbestos insulation products)

Kwasnik v. A.C. & S., Inc. (El Paso Cty., Tex. 2002)

Sienkiewicz v. Greif (U.K.) Ltd., [2009] EWCA (Civ) 1159, at ¶23 (Lady Justice Smith) (“In my view, it must now be taken that, saving the expression of a different view by the Supreme Court, in a case of multiple potential causes, a claimant can demonstrate causation in a case by showing that the tortious exposure has at least doubled the risk arising from the non-tortious cause or causes.”)

Sienkiewicz v. Greif  Ltd., [2011] UKSC 10.

“Where there are competing alternative, rather than cumulative, potential causes of a disease or injury, such as in Hotson, I can see no reason in principle why epidemiological reason should not be used to show that one of the causes was more than twice as likely as all the others put together to have caused the disease or injury.” (Lord Philips, at ¶ 93)

(arguing that statistical evidence should be considered without clearly identifying the nature and extent of its role) (Baroness Hale, ¶ 172-73)

(insisting upon difference between fact and probability of causation, with statistical evidence not probative of the former) (Lord Roger, at ¶143-59)

(“the law is concerned with the rights and wrongs of an individual situation, and should not treat people and even companies as statistics,” although epidemiologic evidence can appropriately be used he identified “in conjunction with specific evidence”) (Lord Mance, at ¶205)

(concluding that epidemiologic evidence can establish the probability, but not the fact of causation, and vaguely suggesting that whether epidemiologic evidence should be allowed was a matter of policy) (Lord Dyson, ¶218-19)

Dixon v. Ford Motor Co., 47 A. 3d 1038, 1046-47 & n.11 (Md. Ct. Special Appeals 2012)(“we can explicitly derive the probability of causation from the statistical measure known as ‘relative risk’, as did the U.S. Court of Appeals for the Third Circuit in DeLuca v. Merrell Dow Pharmaceuticals, Inc., 911 F.2d 941, 958 (3d Cir.1990), in a holding later adopted by several courts. For reasons we need not explore in detail, it is not prudent to set a singular minimum ‘relative risk’value as a legal standard. But even if there were some legal threshold, Dr. Welch provided no information that could help the finder of fact to decide whether the elevated risk in this case was ‘substantial’.”)(internal citations omitted), rev’d, 433 Md. 137, 70 A.3d 328 (2013)


Pharmaceutical Cases

Ambrosini v. Upjohn, 1995 WL 637650, at *4 (D.D.C. Oct. 18, 1995) (excluding plaintiff’s expert witness, Dr. Brian Strom, who was unable to state that mother’s use of Depo-Provero to prevent miscarriage more than doubled her child’s risk of a birth defect)

Ambrosini v. Labarraque, 101 F.3d 129, 135 (D.C. Cir. 1996)(Depo-Provera, birth defects) (testimony “does not warrant exclusion simply because it fails to establish the causal link to a specified degree of probability”)

Siharath v. Sandoz Pharms. Corp., 131 F. Supp. 2d 1347, 1356 (N.D. Ga. 2001)

Cloud v. Pfizer Inc., 198 F. Supp. 2d 1118, 1134 (D. Ariz. 2001) (sertraline and suicide)

Miller v. Pfizer, 196 F. Supp. 2d 1062, 1079 (D. Kan. 2002) (acknowledging that most courts require a showing of RR > 2, but questioning their reasoning; “Court rejects Pfizer’s argument that unless Zoloft is shown to create a relative risk [of akathisia] greater than 2.0, [expert’s] testimony is inadmissible”), aff’d, 356 F. 3d 1326 (10th Cir.), cert. denied, 543 U.S. 917 (2004)

XYZ, et al. v. Schering Health Care Ltd., [2002] EWHC 1420, at ¶21, 70 BMLR 88 (QB 2002) (noting with approval that claimants had accepted the need to  prove relative risk greater than two; finding that most likely relative risk was 1.7, which required finding against claimants even if general causation were established)

Smith v. Wyeth-Ayerst Laboratories Co., 278 F. Supp. 2d 684, 691 (W.D.N.C. 2003) (recognizing that risk and cause are distinct concepts) (“Epidemiologic data that shows a risk cannot support an inference of cause unless (1) the data are statistically significant according to scientific standards used for evaluating such associations; (2) the relative risk is sufficiently strong to support an inference of ‘more likely than not’; and (3)  the epidemiologic data fits the plaintiff’s case in terms of exposure, latency, and other relevant variables.”) (citing FJC Reference Manual at 384 – 85 (2d ed. 2000))

Kelley v. Sec’y of Health & Human Servs., 68 Fed. Cl. 84, 92 (Fed. Cl. 2005) (quoting Kelley v. Sec’y of Health & Human Servs., No. 02-223V, 2005 WL 1125671, at *5 (Fed. Cl. Mar. 17, 2005) (opinion of Special Master explaining that epidemiology must show relative risk greater than two to provide evidence of causation), rev’d on other grounds, 68 Fed. Cl. 84 (2005))

Pafford v. Secretary of HHS, No. 01–0165V, 64 Fed. Cl. 19, 2005 WL 4575936 at *8 (2005) (expressing preference for “an epidemiologic study demonstrating a relative risk greater than two … or dispositive clinical or pathological markers evidencing a direct causal relationship”) (citing Stevens v. Secretary of HHS, No.2001 WL 387418 at *12), aff’d, 451 F.3d 1352 (Fed. Cir. 2006)

Burton v. Wyeth-Ayerst Labs., 513 F. Supp. 2d 719, 730 (N.D. Tex. 2007) (affirming exclusion of expert witness testimony that did not meet Havner’s requirement of relative risks greater than two, Merrell Dow Pharm., Inc. v. Havner, 953 S.W.2d 706, 717–18 (Tex. 1997))

In re Bextra and Celebrex Marketing Sales Practices and Prod. Liab. Litig., 524 F. Supp. 2d 1166, 1172 (N.D. Calif. 2007) (observing that epidemiologic studies “can also be probative of specific causation, but only if the relative risk is greater than 2.0, that is, the product more than doubles the risk of getting the disease”)

In re Bextra & Celebrex, 2008 N.Y. Misc. LEXIS 720, *23-24, 239 N.Y.L.J. 27 (2008) (“Proof that a relative risk is greater than 2.0 is arguably relevant to the issue of specific, as opposed to general causation and is not required for plaintiffs to meet their burden in opposing defendants’ motion.”)

In re Viagra Products Liab. Litigat., 572 F. Supp. 2d 1071, 1078 (D. Minn. 2008) (noting that some but not all courts have concluded relative risks under two support finding expert witness’s opinion to be inadmissible)

Vanderwerf v. SmithKlineBeecham Corp., 529 F.Supp. 2d 1294, 1302 n.10 (D. Kan. 2008), appeal dism’d, 603 F.3d 842 (10th Cir. 2010) (“relative risk of 2.00 means that a particular event of suicidal behavior has a 50 per cent chance that is associated with the exposure to Paxil … .”)

Wright v. American Home Products Corp., 557 F. Supp. 2d 1032, 1035-36 (W.D. Mo. 2008) (fenfluramine case)

Beylin v. Wyeth, 738 F.Supp. 2d 887, 893 n.3 (E.D.Ark. 2010) (MDL court) (Wilson, J. & Montgomery, J.) (addressing relative risk of two argument in dictum; holding that defendants’ argument that for an opinion to be relevant it must show that the medication causes the relative risk to exceed two “was without merit”)

Merck & Co. v. Garza, 347 S.W.3d 256 (Tex. 2011), rev’g 2008 WL 2037350, at *2 (Tex. App. — San Antonio May 14, 2008, no pet. h.)

Scharff v. Wyeth, No. 2:10–CV–220–WKW, 2012 WL 3149248, *6 & n.9, 11 (M.D. Ala. Aug. 1, 2012) (post-menopausal hormone therapy case; “A relative risk of 2.0 implies a 50% likelihood that an exposed individual’s disease was caused by the agent. The lower relative risk in this study reveals that some number less than half of the additional cases could be attributed to [estrogen and progestin].”)

Cheek v. Wyeth, LLC (In re Diet Drugs), 890 F.Supp. 2d 552 (E.D. Pa. 2012)


Medical Malpractice – Failure to Prescribe; Delay in Treatment

Merriam v. Wanger, 757 A.2d 778, 2000 Me. 159 (2000) (reversing judgment on jury verdict for plaintiff on grounds that plaintiff failed to show that defendant failure to act were, more likely than not, a cause of harm)

Bonesmo v. The Nemours Foundation, 253 F. Supp. 2d 801, 809 (D. Del. 2003)

Theofanis v. Sarrafi, 791 N.E.2d 38,48 (Ill. App. 2003) (reversing and granting new trial to plaintiff who received an award of no damages when experts testified that relative risk was between 2.0 and 3.0)(“where the risk with the negligent act is at least twice as great as the risk in the absence of negligence, the evidence supports a finding that, more likely than not, the negligence in fact caused the harm”)

Cottrelle v. Gerrard, 67 OR (3d) 737 (2003), 2003 CanLII 50091 (ONCA), at ¶ 25 (Sharpe, J.A.) (less than a probable chance that timely treatment would have made a difference for plaintiff is insufficient), leave to appeal den’d SCC (April 22, 2004)

Joshi v. Providence Health System of Oregon Corp., 342 Or. 152, 156, 149 P. 3d 1164, 1166 (2006) (affirming directed verdict for defendants when expert witness testified that he could not state, to a reasonable degree of medical probability, beyond 30%, that administering t-PA, or other anti-coagulant would have changed the outcome and prevented death)

Ensink v. Mecosta County Gen. Hosp., 262 Mich. App. 518, 687 N.W.2d 143 (Mich. App. 2004) (affirming summary judgment for hospital and physicians when patient could not greater than 50% probability of obtaining a better result had emergency physician administered t-PA within three hours of stroke symptoms)

Lake Cumberland, LLC v. Dishman, 2007 WL 1229432, *5 (Ky. Ct. App. 2007) (unpublished) confusing 30% with a “reasonable probability”; citing without critical discussion an apparently innumerate opinion of expert witness Dr. Lawson Bernstein)

Mich. Comp. Laws § 600.2912a(2) (2009) (“In an action alleging medical malpractice, the plaintiff has the burden of proving that he or she suffered an injury that more probably than not was proximately caused by the negligence of the defendant or defendants. In an action alleging medical malpractice, the plaintiff cannot recover for loss of an opportunity to survive or an opportunity to achieve a better result unless the opportunity was greater than 50%.”)

O’Neal v. St. John Hosp. & Med. Ctr., 487 Mich. 485, 791 N.W.2d 853 (Mich. 2010) (affirming denial of summary judgment when failure to administer therapy (not t-PA) in a timely fashion supposedly more than doubled the risk of stroke)

Kava v. Peters, 450 Fed. Appx. 470, 478-79 (6th Cir. 2011) (affirming summary judgment for defendants when plaintiffs expert witnesses failed to provide clear testimony that plaintiff specific condition would have been improved by timely administration of therapy)

Smith v. Bubak, 643 F.3d 1137, 1141–42 (8th Cir. 2011) (rejecting relative benefit testimony and suggesting in dictum that absolute benefit “is the measure of a drug’s overall effectiveness”)

Young v. Mem’l Hermann Hosp. Sys., 573 F.3d 233, 236 (5th Cir. 2009) (holding that Texas law requires a doubling of the relative risk of an adverse outcome to prove causation), cert. denied, ___ U.S. ___, 130 S.Ct. 1512 (2010)

Gyani v. Great Neck Medical Group, 2011 WL 1430037 (N.Y. S.Ct. for Nassau Cty., April 4, 2011) (denying summary judgment to medical malpractice defendant on stroke patient’s claims that failure to administer t-PA, on naked assertions of proximate cause by plaintiff’s expert witness, and without considering actual magnitude of risk increased by alleged failure to treat)

Samaan v. St. Joseph Hospital, 670 F.3d 21 (1st Cir. 2012)

Goodman v. Viljoen, 2011 ONSC 821 (CanLII)(treating a risk ratio of 1.7 for harm, or 0.6 for prevention, as satisfying the “balance of probabilities” when taken with additional unquantified, unvalidated speculation), aff’d, 2012 ONCA 896 (CanLII), leave appeal den’d, Supreme Court of Canada No. 35230 (July 11, 2013)

Briante v. Vancouver Island Health Authority, 2014 Brit. Columbia S.Ct 1511, at ¶ 317 (plaintiff must show “on a balance of probabilities that the defendant caused the injury”)


Toxic Tort Cases

In re Agent Orange Product Liab. Litig., 597 F. Supp. 740, 785, 836 (E.D.N.Y. 1984) (“A government administrative agency may regulate or prohibit the use of toxic substances through rulemaking, despite a very low probability of any causal relationship.  A court, in contrast, must observe the tort law requirement that a plaintiff establish a probability of more than 50% that the defendant’s action injured him. … This means that at least a two-fold increase in incidence of the disease attributable to Agent Orange exposure is required to permit recovery if epidemiological studies alone are relied upon.”), aff’d 818 F.2d 145, 150-51 (2d Cir. 1987)(approving district court’s analysis), cert. denied sub nom. Pinkney v. Dow Chemical Co., 487 U.S. 1234 (1988)

Wright v. Willamette Indus., Inc., 91 F.3d 1105 (8th Cir. 1996)(“Actions in tort for damages focus on the question of whether to transfer money from one individual to another, and under common-law principles (like the ones that Arkansas law recognizes) that transfer can take place only if one individual proves, among other things, that it is more likely than not that another individual has caused him or her harm.  It is therefore not enough for a plaintiff to show that a certain chemical agent sometimes causes the kind of harm that he or she is complaining of.  At a minimum, we think that there must be evidence from which the factfinder can conclude that the plaintiff was exposed to levels of that agent that are known to cause the kind of harm that the plaintiff claims to have suffered. See Abuan v. General Elec. Co., 3 F.3d at 333.  We do not require a mathematically precise table equating levels of exposure with levels of harm, but there must be evidence from which a reasonable person could conclude that a defendant’s emission has probably caused a particular plaintiff the kind of harm of which he or she complains before there can be a recovery.”)

Sanderson v. Internat’l Flavors & Fragrances, Inc., 950 F. Supp. 981, 998 n. 17,  999-1000, 1004 (C.D. Cal.1996) (more than a doubling of risk is required in case involving aldehyde exposure and claimed multiple chemical sensitivities)

McDaniel v. CSX Transp., Inc., 955 S.W.2d 257, 264 (1997) (doubling of risk is relevant but not required as a matter of law)

Schudel v. General Electric Co., 120 F.3d 991, 996 (9th Cir. 1997) (polychlorinated biphenyls)

Lofgren v. Motorola, 1998 WL 299925 *14 (Ariz. Super. June 1, 1998) (suggesting that relative risk requirement in tricholorethylene cancer medical monitoring case was arbitrary, but excluding plaintiffs’ expert witnesses on other grounds)

Berry v. CSX Transp., Inc., 709 So. 2d 552 (Fla. D. Ct.App. 1998) (reversing exclusion of plaintiff’s epidemiologist in case involving claims of toxic encephalopathy from solvent exposure, before Florida adopted Daubert standard)

Bartley v. Euclid, Inc., 158 F.3d 261 (5th Cir. 1998) (evidence at trial more than satisfied the relative risk greater than two requirement), rev’d on rehearing en banc, 180 F.3d 175 (5th Cir. 1999)

Magistrini v. One Hour Martinizing Dry Cleaning, 180 F. Supp. 2d 584, 591-92, 605 n.27, 606–07 (D.N.J. 2002) (“When the relative risk reaches 2.0, the risk has doubled, indicating that the risk is twice as high among the exposed group as compared to the non-exposed group. Thus, ‘the threshold for concluding that an agent was more likely than not the cause of an individual’s disease is a relative risk greater than 2.0’.”) (quoting FJC Reference Manual at 384), aff’d, 68 F. App’x 356 (3d Cir. 2003)

Allison v. Fire Ins. Exchange, 98 S.W.3d 227, 239 (Tex. App. — Austin 2002, no pet. h.)

Ferguson v. Riverside School Dist. No. 416, 2002 WL 34355958 (E.D. Wash. Feb. 6, 2002) (No. CS-00-0097-FVS)

Daniels v. Lyondell-Citgo Refining Co., 99 S.W.3d 722, 727 (Tex. App. – Houston [1st Dist.] 2003) (affirming exclusion of expert witness testimony that did not meet Havner’s requirement of relative risks greater than two)

Exxon Corp. v. Makofski, 116 S.W.3d 176, 184-85 (Tex. App. — Houston 2003)

Frias v. Atlantic Richfield Co., 104 S.W.3d 925 (Tex. App. — Houston 2003)

Graham v. Lautrec, Ltd., 2003 WL 23512133, at *1 (Mich. Cir. Ct. 2003) (mold)

Mobil Oil Corp. v. Bailey, 187 S.W.3d 263, 268 (Tex. App. – Beaumont 2006) (affirming exclusion of expert witness testimony that did not meet Havner’s requirement of relative risks greater than two)

In re Lockheed Litig. Cases, 115 Cal. App. 4th 558 (2004)(alleging brain, liver, and kidney damage), rev’d in part, 23 Cal. Rptr. 3d 762, 765 (Cal. App. 2d Dist. 2005) (“[A] court cannot exclude an epidemiological study from consideration solely because the study shows a relative risk of less than 2.0.”), rev. dismissed, 192 P.3d 403 (Cal. 2007)

Novartis Grimsby Ltd. v. Cookson, [2007] EWCA (Civ) 1261, at para. 74 (causation was successfully established by risk ratio greater than two; per Lady Justice Smith: “Put in terms of risk, the occupational exposure had more than doubled the risk [of the bladder cancer complained of] due to smoking. . . . if the correct test for causation in a case such as this is the “but for” test and nothing less will do, that test is plainly satisfied on the facts as found. . . . In terms of risk, if the occupational exposure more than doubles the risk due to smoking, it must, as a matter of logic, be probable that the disease was caused by the former.”)

Watts v. Radiator Specialty Co., 990 So. 2d 143 (Miss. 2008) (“The threshold for concluding that an agent was more likely than not the cause of an individual’s disease is a relative risk greater than 2.0.”)

King v. Burlington Northern Santa Fe Ry, 762 N.W.2d 24, 36-37 (Neb. 2009) (reversing exclusion of proffered testimony of Arthur Frank on claim that diesel exposure caused multiple myeloma, and addressing in dicta the ability of expert witnesses to speculate reasons why specific causation exists even with relative risk less than two) (“If a study shows a relative risk of 2.0, ‘the agent is responsible for an equal number of cases of disease as all other background causes.’ This finding ‘implies a 50% likelihood that an exposed individual’s disease was caused by the agent.’ If the relative risk is greater than 2.0, the study shows a greater than 50–percent likelihood that the agent caused the disease.”)(internal citations to Reference Manual on Scientific Evidence (2d ed. 2000) omitted)

Henricksen v. Conocophillips Co., 605 F. Supp. 2d 1142, 1158 (E.D. Wash. 2009) (noting that under Circuit precedent, epidemiologic studies showing low-level risk may suffiicent to show general causation but are sufficient to show specific causation only if relative risk exceeds two) (excluding plaintiff‘s expert witness’s testimony because epidemiologic evidence is “contradictory and inconsistent”)

City of San Antonio v. Pollock, 284 S.W.3d 809, 818 (Tex. 2009) (holding testimony admitted insufficient as matter of law)

George v. Vermont League of Cities and Towns, 2010 Vt. 1, 993 A.2d 367, 375 (2010)

Blanchard v. Goodyear Tire & Rubber Co., No. 837-12-07 Wrcv (Eaton, J., June 28, 2010) (excluding expert witness, David Goldsmith, and entering summary judgment), aff’d, 190 Vt. 577, 30 A.3d 1271 (2011)

Pritchard v. Dow Agro Sciences, 705 F. Supp. 2d 471, 486 (W.D. Pa. 2010) (excluding opinions of Dr. Omalu on Dursban, in part because of low relative risk) (“Therefore, a relative risk of 2.0 is not dispositive of the reliability of an expert’s opinion relying on an epidemiological study, but it is a factor, among others, which the Court is to consider in its evaluation.”), aff’d, 430 Fed. Appx. 102, 2011 WL 2160456 (3d Cir. 2011)

Faust v. BNSF Ry., 337 S.W.3d 325, 337 (Tex. Ct. App. 2d Dist. 2011) (“To be considered reliable scientific evidence of general causation, an epidemiological study must (1) have a relative risk of 2.0 and (2) be statistically significant at the 95% confidence level.”) (internal citations omitted)

Nonnon v. City of New York, 88 A.D.3d 384, 398-99, 932 N.Y.S.2d 428, 437-38 (1st Dep’t 2011) (holding that the strength of the epidemiologic evidence, with relative risks greater than 2.0, permitted an inference of causation)

Milward v. Acuity Specialty Products Group, Inc., 969 F. Supp. 2d 101, 112-13 & n.7 (D. Mass. 2013) (avoiding doubling of risk issue and holding that plaintiffs’ expert witnesses failed to rely upon a valid exposure estimate and lacked sufficient qualifications to evaluate and weigh the epidemiologic studies that provided estimates of relative risk) (generalities about the “core competencies” of physicians or specialty practices cannot overcome an expert witness’s explicit admission of lacking the epidemiologic expertise needed to evaluate and weigh the epidemiologic studies and methods at issue in the case. Without the requisite qualifications, an expert witness cannot show that the challenged opinion has a sufficiently reliable scientific foundation in epidemiologic studies and method.)

Berg v. Johnson & Johnson, 940 F.Supp.2d 983 (D.S.D. 2013) (talc and ovarian cancer)


Other

In re Hannaford Bros. Co. Customer Data Sec. Breach Litig., 293 F.R.D. 21, 2:08-MD-1954-DBH, 2013 WL 1182733, *1 (D. Me. Mar. 20, 2013) (Hornby, J.) (denying motion for class certification) (“population-based probability estimates do not speak to a probability of causation in any one case; the estimate of relative risk is a property of the studied population, not of an individual’s case.”)

Adverse Liver Events and Causal Claims Against Black Cohosh

April 6th, 2015

Liver toxicity in pharmaceutical products liability cases is one of the more difficult categories of cases for judicial gatekeeping because of the possibility of idiosyncratic liver toxicity. Sometimes a plaintiff will exploit this difficulty and try to recover for an acute liver reaction.

Susan Grant began to take a black cohosh herbal remedy in 2002, and within a year, developed autoimmune hepatitis, which required her to undergo a liver transplant. She and her husband sued the seller of black cohosh for substantial damages. Grant v. Pharmavite, LLC, 452 F. Supp 2d 903 (D. Neb. 2006). Granted enlisted two expert witnesses, Michael Corbett, Ph.D, a toxicologist, and her treating gastroenterologist, Michael Sorrell, M.D. The defense relying upon liver expert, Phillip Guzelian, M.D., challenged the admissibility of plaintiffs’ expert witnesses’ opinions under the federal rules.

Struggling with the law, Senior Judge Strom observed that Nebraska law requires expert witness opinion testimony on causation. Id. at 906. Of course, in this diversity action, federal law controlled on the scope and the requirements of expert witness opinion testimony.

And in a similarly offbeat way, Judge Strom suggested that plaintiffs’ expert witnesses need not have opinion supported by evidence:

While it is not necessary that an opinion be backed by scientific research, it is necessary that an expert’s testimony, which contradicts all of the research, at minimum address and distinguish the contradictory research in order to support the expressed opinion.”

Id. at 907 (emphasis added). Senior Judge Strom thus suggests had there been no published research at all, then Dr. Corbett could just make up an opinion, not backed by scientific research. This is, of course, seriously wrong, but fortunately it amounts only to obiter detritus, because Judge Strom believed that given the available studies, the testifying expert witnesses had to do more than simply criticize the studies that disagreed with their subjective opinion.

Michael Corbett, Ph.D, a consultant in “chemical toxicology,” from Omaha, Nebraska, criticized existent studies, which generally failed to identify liver toxicity, but he failed to conduct his own studies. Id. at 907. And Corbett also failed to explain why he rejected the great weight of medical publications that found that black cohosh was not hepatotoxic. Id. Michael Sorrell, M.D., started out as Ms. Grant’s treating gastroenterologist, but became a litigation expert witness. He was generally unaware of the randomized clinical trials of black cohosh, or any study that, or group of scientists who, supported his opinion. Id. at 909.

To Dr. Sorrell’s credit, he did attempt to write up a case report, which was published after the termination of the case. Unfortunately for Dr. Sorrell and his colleagues, Ms. Grant and her lawyers were less than forthcoming about her medical history, which included medications and lifestyle variables that were apparently not shared with Dr. Sorrell. Id. at 909.

You know that the quality of gatekeeping due process is strained when judges fail to cite key studies sufficiently to permit their readers to find the scientific evidence. Between Google Scholar and PubMed, however, you can find Dr. Sorrell’s case report, which was published in 2005, before Judge Strom issued his Rule 702 opinion. Josh Levitsky, Tyron A. Alli, James Wisecarver, and Michael F. Sorrell, “Fulminant liver failure associated with the use of black cohosh,” 50 Digestive Dis. Sci. 538 (2005). If nothing else, Judge Strom provoked an erratum from Dr. Sorrell and colleagues:

“After the article was published, it was brought to the authors’ attention through legal documentation and testimony that the patient admitted to consuming alcohol and had been taking other medications at the time of her initial presentation of liver failure. From these records, she reported drinking no more than six glasses of wine per week. In addition, up until presentation, she was taking valacyclovir 500 mg daily for herpes prophylaxis for 2 years, an occasional pseudoephedrine tablet, calcium carbonate 500 mg three times daily, iron sulfate 325 mg daily and ibuprofen up to three times weekly. She had been taking erythromycin tablets but discontinued those 3 months prior to presentation.

The authors regret the omission of this information from the original case report. While this new information is important to include as a correction to the history, it does not change the authors’ clinical opinion … .”

The erratum omits that Ms. Grant was taking Advil (ibuprofen) at the time of her transplantation, and that she had been taking erythromycin for 2.5 years, stopping just a few months before her acute liver illness. The Valtrex use shows that Ms. Grant had a chronic herpes infection. In the past, plaintiff took such excessive doses of ibuprofen that she developed anemia. Grant v. Pharmavite, LLC, 452 F. Supp 2d at 909 n.1. Hardly an uncomplicated case report to interpret for causality and an interesting case history of confirmation bias. Remarkably, the journal charges $39.95 to download the erratum, as much as the case report itself!

And how has the plaintiff’s claim fared in the face of the evolving scientific record since Judge Strom’s opinion?

Not well.

See, e.g., Peter W Whiting, Andrew Clouston and Paul Kerlin, “Black cohosh and other herbal remedies associated with acute hepatitis,” 177 Med. J. Australia 432 (2002); Cohen SM, O’Connor AM, Hart J, et al. Autoimmune hepatitis associated with the use of black cohosh: a case study. 11 Menopause 575 (2004); Christopher R. Lynch, Milan E. Folkers, and William R. Hutson, “Fulminant hepatic failure associated with the use of black cohosh: A case report,” 12 Liver Transplantation 989 (2006); Elizabeth C-Y Chow, Marcus Teo, John A Ring and John W Chen, “Liver failure associated with the use of black cohosh for menopausal symptoms,” 188 Med. J. Australia 420 (2008); Gail B. Mahady, Tieraona Low Dog, Marilyn L. Barrett, Mary L. Chavez, Paula Gardiner, Richard Ko, Robin J. Marles, Linda S. Pellicore, Gabriel I. Giancaspro, and Dandapantula N. Sarma, “United States Pharmacopeia review of the black cohosh case reports of hepatotoxicity,” 15 Menopause 628 (2008) (toxicity only possible on available evidence); D. Joy, J. Joy, and P. Duane, “Black cohosh: a cause of abnormal postmenopausal liver function tests,” 11 Climacteric 84 (2008); Lily Dara, Jennifer Hewett, and Joseph Kartaik Lim, “Hydroxycut hepatotoxicity: A case series and review of liver toxicity from herbal weight loss supplements,” 14 World J. Gastroenterol. 6999 (2008); F. Borrelli & E. Ernst, “Black cohosh (Cimicifuga racemosa): a systematic review of adverse events,” Am. J. Obstet. & Gyn. 455 (2008); Rolf Teschke & A. Schwarzenboeck, “Suspected hepatotoxicity by Cimicifugae racemosae rhizoma (black cohosh, root): critical analysis and structured causality assessment,” 16 Phytomedicine 72 (2009); Stacie E. Geller, Lee P. Shulman, Richard B. van Breemen, Suzanne Banuvar, Ying Zhou, Geena Epstein, Samad Hedayat, Dejan Nikolic, Elizabeth C. Krause, Colleen E. Piersen, Judy L. Bolton, Guido F. Pauli, and Norman R. Farnsworth, “Safety and Efficacy of Black Cohosh and Red Clover for the Management of Vasomotor Symptoms: A Randomized Controlled Trial,” 16 Menopause 1156 (2009) (89 women randomized to four groups; no hepatic events in trial not powered to detect them); Rolf Teschke, “Black cohosh and suspected hepatotoxicity: inconsistencies, confounding variables, and prospective use of a diagnostic causality algorithm. A critical review,” 17 Menopause 426 (2010) (“The presented data do not support the concept of hepatotoxicity in a primarily suspected causal relationship to the use of BC and failure to provide a signal of safety concern, but further efforts have to be undertaken to dismiss or to substantiate the existence of BC hepatotoxicity as a special disease entity. The future strategy should be focused on prospective causality evaluations in patients diagnosed with suspected BC hepatotoxicity, using a structured, quantitative, and hepatotoxicity-specific causality assessment method.”); Fabio Firenzuoli, Luigi Gori, and Paolo Roberti di Sarsina, “Black Cohosh Hepatic Safety: Follow-Up of 107 Patients Consuming a Special Cimicifuga racemosa rhizome Herbal Extract and Review of Literature,” 2011 Evidence-Based Complementary & Alternative Med. 1 (2011); Rolf Teschke, Wolfgang Schmidt-Taenzer and Albrecht Wolff, “Spontaneous reports of assumed herbal hepatotoxicity by black cohosh: is the liver-unspecific Naranjo scale precise enough to ascertain causality?” 20 Pharmacoepidemiol. & Drug Safety 567 (2011) (causation unlikely or excluded); Rolf Teschke, Alexander Schwarzenboeck, Wolfgang Schmidt-Taenzer, Albrecht Wolff, and Karl-Heinz Hennermann, “Herb induced liver injury presumably caused by black cohosh: A survey of initially purported cases and herbal quality specifications,” 11 Ann. Hepatology 249 (2011).

Johnson of Accutane – Keeping the Gate in the Garden State

March 28th, 2015

Flag of Aquitaine     Nelson Johnson is the author of Boardwalk Empire: The Birth, High Times, and Corruption of Atlantic City (2010), a rattling good yarn, which formed the basis for a thinly fictionalized story of Atlantic City under the control of mob boss (and Republican politician) Enoch “Nucky” Johnson. HBO transformed Johnson’s book into a multi-season series, with Steve Buscemi playing Nucky Johnson (Thompson in the series). Robert Strauss, “Judge Nelson Johnson: Atlantic City’s Godfather — A Q&A with Judge Nelson Johnson,” New Jersey Monthly (Aug. 16, 2010).

Nelson Johnson is also known as the Honorable Nelson Johnson, a trial court judge in Atlantic County, New Jersey, where he inherited some of the mass tort docket of Judge Carol Higbee. Judge Higbee has since ascended to the Appellate Division of the New Jersey Superior Court. One of the litigations Judge Johnson presides over is the mosh pit of isotretinoin (Accutane) cases, involving claims that the acne medication causes irritable bowel syndrome (IBS) and Crohn’s disease (CD). Judge Johnson is not only an accomplished writer of historical fiction, but he is also an astute evaluator of the facts and data, and the accompanying lawyers’ rhetoric, thrown about in pharmaceutical products liability litigation.

Perhaps more than his predecessor ever displayed, Judge Johnson recently demonstrated his aptitude for facts and data in serving as a gatekeeper of scientific evidence, as required by the New Jersey Supreme Court, in Kemp v. The State of New Jersey, 174 NJ 412 (2002). Faced with a complex evidentiary display on the validity and reliability of the scientific evidence, Judge Johnson entertained extensive briefings, testimony, and oral argument. When the dust settled, the court ruled that the proffered testimony of Dr, Arthur Kornbluth and Dr. David Madigan did not meet the liberal New Jersey test for admissibility. In re Accutane, No. 271(MCL), 2015 WL 753674, 2015 BL 59277 (N.J.Super. Law Div. Atlantic Cty. Feb. 20, 2015). And in settling the dust, Judge Johnson dispatched several bogus and misleading “lines of evidence,” which have become standard ploys to clog New Jersey and other courthouses.

Case Reports

As so often is the case when there is no serious scientific evidence of harm in pharmaceutical cases, plaintiffs in the Accutane litigation relied heavily upon case and adverse event reports. Id. at *11. Judge Johnson was duly unimpressed, and noted that:

“[u]nsystematic clinical observations or case reports and adverse event reports are at the bottom of the evidence hierarchy.”

Id. at *16.

Bootstrapped, Manufactured Evidence

With respect to case reports that are submitted to the FDA’s Adverse Event Reporting System (FAERS), Judge Johnson acknowledged the “serious limitations” of the hearsay anecdotes that make up such reports. Despite the value of AERs in generating signals for future investigation, Judge Johnson, citing FDA’s own description of the reporting system, concluded that the system’s anecdotal data are “not evidentiary in a court of law.” Id. at 14 (quoting FDA’s description of FAERS).

Judge Johnson took notice of another fact; namely, the industry litigation creates evidence that it then uses to claim causal connections in the courtroom. Plaintiffs’ lawyers in pharmaceutical cases routinely file Medwatch adverse event reports, which thus inflate the “signal,” they claim supports the signal of harm from medication use. This evidentiary bootstrapping machine was hard at work in the isotretinoin litigation. See Derrick J. Stobaugh, Parakkal Deepak, and Eli D. Ehrenpreis, “Alleged Isotretinoin-Associated Inflammatory Bowel Disease: Disproportionate reporting by attorneys to the Food and Drug Administration Adverse Event Reporting System,” 69 J. Am. Acad. Dermatol. 398 (2013) (“Attorney-initiated reports inflate the pharmacovigilance signal of isotretinoin-associated IBD in the FAERS.”). Judge Johnson gave a wry hat tip to plaintiffs’ counsel’s industry, by acknowledging that the litigation industry itself had inflated this signal-generating process:

“The legal profession is a bulwark of our society, yet the courts should never underestimate the resourcefulness of some attorneys.”

In re Accutane, 2015 WL 753674, at *15.

Bias and Confounding

The epidemiologic studies referenced by the parties had identified a fairly wide range of “risk factors” for irritable bowel syndrome, including many prevalent factors in Westernized countries such as prior appendectomy, breast-feeding as an infant, stress, Vitamin D deficiency, tobacco or alcohol use, refined sugars, dietary animal fat, fast food. In re Accutane, 2015 WL 753674, at *9. The court also noted that there were four medications known to be risk factors for IBD: aspirin, nonsteroidal anti-inflammatory medications (NSAIDs), oral contraceptives, and antibiotics.

In reviewing the plaintiffs’ expert witnesses’ methodology, Judge Johnson found that they had been inordinately, and inappropriately selective in the studies chosen for reliance. The challenged witnesses had discounted and discarded most of the available studies in favor of two studies that were small, biased, and not population based. Indeed, one of the studies evidenced substantial selection bias by using referrals to obtain study participants, a process deprecated by the trial court as “cherry picking the subjects.” Id. at *18. “The scientific literature does not support reliance upon such insignificant studies to arrive at conclusions.” Id.

Animal Studies

Both sides in the isotretinoin cases seemed to concede the relative unimportance of animal studies. The trial court discussed the limitations on animal studies, especially the absence of a compelling animal model of human irritable bowel syndrome. Id. at *18.

Cherry Picking and Other Crafty Stratagems

With respect to the complete scientific evidentiary display, plaintiffs asserted that their expert witnesses had considered everything, but then failed to account for most of the evidence. Judge Johnson found this approach deceptive and further evidence of a cherry-picking, pathological methodology:

‘‘Finally, coursing through Plaintiffs’ presentation is a refrain that is a ruse. Repeatedly, counsel for the Plaintiffs and their witnesses spoke of ‛lines of evidence”, emphasizing that their experts examined ‛the same lines of evidence’ as did the experts for the Defense. Counsels’ sophistry is belied by the fact that the examination of the ‘lines of evidence’ by Plaintiffs’ experts was highly selective, looking no further than they wanted to—cherry picking the evidence—in order to find support for their conclusion-driven testimony in support of a hypothesis made of disparate pieces, all at the bottom of the medical evidence hierarchy.’’

Id. at *21.

New Jersey Rule of Evidence 703

The New Jersey rules of evidence, like the Federal Rules, imposes a reasonableness limit on what sorts of otherwise inadmissible evidence an expert witness may rely upon. SeeRULE OF EVIDENCE 703 — Problem Child of Article VII” (Sept. 9, 2011). Although Judge Johnson did not invoke Rule 703 specifically, he was clearly troubled by plaintiffs’ expert witnesses’ reliance upon an unadjusted odds ratio from an abstract, which did not address substantial confounding from a known causal risk factor – antibiotics use. Judge Johnson concluded that the reliance upon the higher, unadjusted risk figure, contrary to the authors’ own methods and conclusions, and without a cogent explanation for so doing was “pure advocacy” on the part of the witnesses. In re Accutane, 2015 WL 753674, at *17; see also id. at *5 (citing Landrigan v. Celotex Corp., 127 N.J. 404, 417 (1992), for the proposition that “when an expert relies on such data as epidemiological studies, the trial court should review the studies, as well as other information proffered by the parties, to determine if they are of a kind on which such experts ordinarily rely.”).

Discordance Between Courtroom and Professional Opinions

One of plaintiffs’ expert witnesses, Dr. Arthur Kornbluth actually had studied putative association between isotretinoin and CD before he became intensively involved in litigation as an expert witness. In re Accutane, 2015 WL 753674, at *7. Having an expert witness who is a real world expert can be a plus, but not when that expert witness maintains a double standard for assessing causal connections. Back in 2009, Kornbluth published an article, “Ulcerative Colitis Practice Guidelines in Adults” in The American Journal of Gastroenterology. Id. at *10. This positive achievement became a large demerit when cross-examination at the Kemp hearing revealed that Kornbluth had considered but rejected the urgings of a colleague, Dr. David Sachar, to comment on isotretinoin as a cause of irritable bowel syndrome. In front of Judge Johnson, Dr. Kornbluth felt no such scruples. Id. at *11. Dr. Kornbluth’s stature in the field of gastroenterology, along with his silence on the issue in his own field, created a striking contrast with his stridency about causation in the courtroom. The contrast raised the trial court’s level of scrutiny and skepticism about his causal opinions in the New Jersey litigation. Id. (citing and quoting Soldo v. Sandoz Pharms. Corp, 244 F. Supp. 2d 434, 528 (W.D. Pa. 2003) (“Expert opinions generated as the result of litigation have less credibility than opinions generated as the result of academic research or other forms of ‘pure’ research.”) (“The expert’s motivation for his/her study and research is important. … We may not ignore the fact that a scientist’s normal work place is the lab or field, not the courtroom or the lawyer’s office.”).

Meta-Analysis

Meta-analysis has become an important facet of pharmaceutical and other products liability litigation[1]. Fortunately for Judge Johnson, he had before him an extremely capable expert witness, Dr. Stephen Goodman, to explain meta-analysis generally, and two meta-analyses performed on isotretinoin and irritable bowel outcomes. In re Accutane, 2015 WL 753674, at *8. Dr. Goodman explained that:

“the strength of the meta-analysis is that no one feature, no one study, is determinant. You don’t throw out evidence except when you absolutely have to.”

Id. Dr. Goodman further explained that plaintiffs’ expert witnesses’ failure to perform a meta-analysis was telling meta-analysis “can get us closer to the truth.” Id.

Some Nitpicking

Specific Causation

After such a commanding judicial performance by Judge Johnson, nitpicking on specific causation might strike some as ungrateful. For some reason, however, Judge Johnson cited several cases on the appropriateness of expert witnesses’ reliance upon epidemiologic studies for assessing specific causation or for causal apportionment between two or more causes. In re Accutane, 2015 WL 753674, at *5 (citing Landrigan v. Celotex Corp., 127 N.J. 404 (1992), Caterinicchio v. Pittsburgh Corning, 127 N.J. 428 (1992), and Dafler v. Raymark Inc., 259 N.J. Super. 17, 36 (App. Div. 1992), aff’d. o.b. 132 N.J. 96 (1993)). Fair enough, but specific causation was not at issue in the Accutane Kemp hearing, and the Landrigan and Caterinicchio cases are irrelevant to general causation.

In both Landrigan and Caterincchio, the defendants moved for directed verdicts by arguing that, assuming arguendo that asbestos causes colon cancer, the plaintiffs’ expert witnesses had not presented a sufficient opinion to support that Landrigan’s and Caterinnichio’s colon cancers were caused by asbestos. SeeLandrigan v. The Celotex Corporation, Revisited” (June 4, 2013). General causation was thus never at issue, and the holdings never addressed the admissibility of the expert witnesses’ causation opinions. Only sufficiency of the opinions that equated increased risks, less than 2.0, to specific causation was at issue in the directed verdicts, and the appeals taken from the judgments entered on those verdicts.

Judge Johnson, in discussing previous case law suggests that the New Jersey Supreme Court reversed and remanded the Landrigan case for trial, holding that “epidemiologists could help juries determine causation in toxic tort cases and rejected the proposition that epidemiological studies must show a relative risk factor of 2.0 before gaining acceptance by a court.” In re Accutane, 2015 WL 753674, at *5, citing Landrigan, 127 N.J. at 419. A close and fair reading of Landrigan, however, shows that it was about a directed verdict, 127 N.J. at 412, and not a challenge to the use of epidemiologic studies generally, or to their use to show general causation.

Necessity of Precise Biological Mechanism

In the Accutane hearings, the plaintiffs’ counsel and their expert witnesses failed to provide a precise biological mechanism of the cause of IBD. Judge Johnson implied that any study that asserted that Accutane caused IBD ‘‘would, of necessity, require an explication of a precise biological mechanism of the cause of IBD and no one has yet to venture more than alternate and speculative hypotheses on that question.’’ In re Accutane, 2015 WL 753674, at *8. Conclusions of causality, however, do not always come accompanied by understood biological mechanisms, and Judge Johnson demonstrated that the methods and evidence relied upon by plaintiffs’ expert witnesses could not, in any event, allow them to draw causal conclusions.

Interpreting Results Contrary to Publication Authors’ Interpretations

There is good authority, no less than the United States Supreme Court in Joiner, that there is something suspect in expert witnesses’ interpreting a published study’s results in contrary to the authors’ publication. Judge Johnson found that the plaintiffs’ expert witnesses in the Accutane litigation had inferred that two studies showed increased risk when the authors of those studies had concluded that their studies did not appear to show an increased risk. Id. at *17. There will be times, however, when a published study may have incorrectly interpreted its own data, when “real” expert witnesses can, and should, interpret the data appropriately. Accutane was not such a case. In In re Accutane, Judge Johnson carefully documented and explained how the plaintiffs’ expert witnesses’ supposed reinterpretation was little more than attempted obfuscation. His Honor concluded that the witnesses’ distortion of, and ‘‘reliance upon these two studies is fatal and reveals the lengths to which legal counsel and their experts are willing to contort the facts and torture the logic associated with Plaintiffs’ hypothesis.’’ Id. at *18.


[1] “The Treatment of Meta-Analysis in the Third Edition of the Reference Manual on Scientific Evidence” (Nov. 14, 2011) (The Reference Manual fails to come to grips with the prevalence and importance of meta-analysis in litigation, and fails to provide meaningful guidance to trial judges).

The Joiner Finale

March 23rd, 2015

“This is the end
Beautiful friend
This is the end
My only friend, the end”

Jim Morrison, “The End” (c. 1966)

 *          *          *          *           *          *          *          *          *          *  

The General Electric Co. v. Joiner, 522 U.S. 136 (1997), case was based upon polychlorinated biphenyl exposures (PCB), only in part. The PCB part did not hold up well legally in the Supreme Court; nor was the PCB lung cancer claim vindicated by later scientific evidence. See How Have Important Rule 702 Holdings Held Up With Time?” (Mar. 20, 2015).

The Supreme Court in Joiner reversed and remanded the case to the 11th Circuit, which then remanded the case back to the district court to address claims that Mr. Joiner had been exposed to furans and dioxins, and that these other chemicals had caused, or contributed to, his lung cancer, as well. Joiner v. General Electric Co., 134 F.3d 1457 (11th Cir. 1998) (per curiam). Thus the dioxins were left in the case even after the Supreme Court ruled.

After the Supreme Court’s decision, Anthony Roisman argued that the Court had addressed an artificial question when asked about PCBs alone because the case was really about an alleged mixture of exposures, and he held out hope that the Joiners would do better on remand. Anthony Z. Roisman, “The Implications of G.E. v. Joiner for Admissibility of Expert Testimony,” 1 Res Communes 65 (1999).

Many Daubert observers (including me) are unaware of the legal fate of the Joiners’ claims on remand. In the only reference I could find, the commentator simply noted that the case resolved before trial.[1] I am indebted to Michael Risinger, and Joseph Cecil, for pointing me to documents from PACER, which shed some light upon the Joiner “endgame.”

In February 1998, Judge Orinda Evans, who had been the original trial judge, and who had sustained defendants’ Rule 702 challenges and granted their motions for summary judgments, received and reopened the case upon remand from the 11th Circuit. In March, Judge Evans directed the parties to submit a new pre-trial order by April 17, 1998. At a status conference in April 1998, Judge Evans permitted the plaintiffs additional discovery, to be completed by June 17, 1998. Five days before the expiration of their additional discovery period, the plaintiffs moved for additional time; defendants opposed the request. In July, Judge Evans granted the requested extension, and gave defendants until November 1, 1998, to file for summary judgment.

Meanwhile, in June 1998, new counsel entered their appearances for plaintiffs – William Sims Stone, Kevin R. Dean, Thomas Craig Earnest, and Stanley L. Merritt. The docket does not reflect much of anything about the new discovery other than a request for a protective order for an unpublished study. But by October 6, 1998, the new counsel, Earnest, Dean, and Stone (but not Merritt) withdrew as attorneys for the Joiners, and by the end of October 1998, Judge Evans entered an order to dismiss the case, without prejudice.

A few months later, in February 1999, the parties filed a stipulation, approved by the Clerk, dismissing the action with prejudice, and with each party to bear its own coasts. Given the flight of plaintiffs’ counsel, the dismissals without and then with prejudice, a settlement seems never to have been involved in the resolution of the Joiner case. In the end, the Joiners’ case fizzled perhaps to avoid being Frye’d.

And what has happened since to the science of dioxins and lung cancer?

Not much.

In 2006, the National Research Council published a monograph on dioxin, which took the controversial approach of focusing on all cancer mortality rather than specific cancers that had been suggested as likely outcomes of interest. See David L. Eaton (Chairperson), Health Risks from Dioxin and Related Compounds – Evaluation of the EPA Reassessment (2006). The validity of this approach, and the committee’s conclusions, were challenged vigorously in subsequent publications. Paolo Boffetta, Kenneth A. Mundt, Hans-Olov Adami, Philip Cole, and Jack S. Mandel, “TCDD and cancer: A critical review of epidemiologic studies,” 41 Critical Rev. Toxicol. 622 (2011) (“In conclusion, recent epidemiologicalevidence falls far short of conclusively demonstrating a causal link between TCDD exposure and cancer risk in humans.”

In 2013, the Industrial Injuries Advisory Council (IIAC), an independent scientific advisory body in the United Kingdom, published a review of lung cancer and dioxin. The Council found the epidemiologic studies mixed, and declined to endorse the compensability of lung cancer for dioxin-exposed industrial workers. Industrial Injuries Advisory Council – Information Note on Lung cancer and Dioxin (December 2013). See also Mann v. CSX Transp., Inc., 2009 WL 3766056, 2009 U.S. Dist. LEXIS 106433 (N.D. Ohio 2009) (Polster, J.) (dioxin exposure case) (“Plaintiffs’ medical expert, Dr. James Kornberg, has opined that numerous organizations have classified dioxins as a known human carcinogen. However, it is not appropriate for one set of experts to bring the conclusions of another set of experts into the courtroom and then testify merely that they ‘agree’ with that conclusion.”), citing Thorndike v. DaimlerChrysler Corp., 266 F. Supp. 2d 172 (D. Me. 2003) (court excluded expert who was “parroting” other experts’ conclusions).


[1] Morris S. Zedeck, Expert Witness in the Legal System: A Scientist’s Search for Justice 49 (2010) (noting that, after remand from the Supreme Court, Joiner v. General Electric resolved before trial)

How Have Important Rule 702 Holdings Held Up With Time?

March 20th, 2015

The Daubert case arose from claims of teratogenicity of Bendectin. The history of the evolving scientific record has not been kind to those claims. SeeBendectin, Diclegis & The Philosophy of Science” (Oct. 26, 2013); Gideon Koren, “The Return to the USA of the Doxylamine-Pyridoxine Delayed Release Combination (Diclegis®) for Morning Sickness — A New Morning for American Women,” 20 J. Popul. Ther. Clin. Pharmacol. e161 (2013). Twenty years later, the decisions in the Daubert appeals look sound, even if the reasoning was at times shaky. How have other notable Rule 702 exclusions stood up to evolving scientific records?

A recent publication of an epidemiologic study on lung cancer among workers exposed to polychlorinated biphenyls (PCBs) raised an interested question about a gap in so-called Daubert scholarship. Clearly, there are some cases, like General Electric v. Joiner[1], in which plaintiffs lack sufficient, valid evidence to make out their causal claims. But are there cases of Type II injustices, for which, in the fullness of time, the insufficiency or invalidity of the available evidentiary display is “cured” by subsequently published studies?

In Joiner, Chief Justice Rehnquist noted that the district court had carefully analyzed the four epidemiologic studies claimed by plaintiff to support the association between PCB exposure and lung cancer. The first such study[2] involved workers at an Italian capacitor plant who had been exposed to PCBs.

The Chief Justice reported that the authors of the Italian capacitor study had noted that lung cancer deaths among former employees were more numerous than expected (without reporting whether there was any assessment of random error), but that they concluded that “there were apparently no grounds for associating lung cancer deaths (although increased above expectations) and exposure in the plant.”[3] The court frowned at the hired expert witnesses’ willingness to draw a causal inference when the authors of the Bertazzi study would not. As others have noted, this disapproval was beside the point of the Rule 702 inquiry. It might well be the case that Bertazzi and his co-authors could not or did not conduct a causal analysis, but that does not mean that the study’s evidence could not be part of a larger effort to synthesize the available evidence. In any event, the Bertazzi study was small and uninformative. Although all cancer mortality was increased (14 observed vs. 5.5 expected, based upon national rates; SMR = 253; 95% CI 144-415), the study was too small to be meaningful for lung cancer outcomes.

The second cited study[4], from an unpublished report, followed workers at a Monsanto PCB production facility. The authors of the Monsanto study reported that the lung cancer mortality rate among exposed workers “somewhat” higher than expected, but that the “increase, however, was not statistically significant and the authors of the study did not suggest a link between the increase in lung cancer deaths and the exposure to PCBs.” Again, the Court’s emphasis on what the authors stated is unfortunate. What is important is obscured because the Court never reproduced the data from this unpublished study.

The third study[5] cited by plaintiff’s hired expert witnesses was of “no help,” in that the study followed workers exposed to mineral oil, without any known exposure to PCBs. Although the workers exposed to this particular mineral oil had a statistically significantly elevated lung cancer mortality, the study made no reference to PCBs.

The fourth study[6] cited by plaintiffs’ expert witnesses followed a Japanese PCB-exposed group, which had a “statistically significant increase in lung cancer deaths.” The Court, however, was properly concerned that the cohort was exposed to numerous other potential carcinogens, including toxic rice oil by ingestion.

The paucity of this evidence led the Court to observe:

“Trained experts commonly extrapolate from existing data. But nothing in either Daubert or the Federal Rules of Evidence requires a district court to admit opinion evidence which is connected to existing data only by the ipse dixit of the expert. A court may conclude that there is simply too great an analytical gap between the data and the opinion proffered. … That is what the District Court did here, and we hold that it did not abuse its discretion in so doing.”

Joiner, 522 U.S. at 146 (1997).

Interestingly omitted from the Supreme Court’s discussion was why the plaintiffs’ expert witnesses failed to rely upon all the available epidemiology. The excluded witnesses relied upon an unpublished Monsanto study, but apparently ignored an unpublished investigation by NIOSH researchers, who found that there were “no excess deaths from cancers of the … the lung,” among PCB-exposed workers at a Westinghouse Electric manufacturing facility[7]. Actually, NIOSH reported a statistically non-significant decrease in lung cancer rate, with fairly a narrow confidence interval.

Two Swedish studies[8] were perhaps too small to add much to the mix of evidence, but lung cancer rates were not apparently increased in a North American study[9].

Joiner thus represents not only an analytical gap case, but also a cherry picking case, as well. The Supreme Court was eminently correct to affirm the shoddy evidence proffered in the Joiner case.

But has the District Judge’s exclusion of Joiner’s expert witnesses (Dr. Arnold Schecter and Dr. (Rabbi) Daniel Teitelbaum) stood up to the evolving scientific record?

A couple of weeks ago, researchers published a large, updated cohort study, funded by General Electric, on the mortality experience of workers in a plant that manufactured capacitors with PCBs[10]. Although the Lobby and the Occupational Medicine Zealots will whine about the funding source, the study is a much stronger study than anything relied upon by Mr. Joiner’s expert witnesses, and its results are consistent with the NIOSH study available to, but ignored by, Joiner’s expert witnesses. And the results are not uniformly good for General Electric, but on the end point of lung cancer for men, the standardized mortality ratio was 81 (95% C.I., 68 – 96), nominally statistically significantly below the expected SMR of 100.


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

[2] Bertazzi, Riboldi, Pesatori, Radice, & Zocchetti, “Cancer Mortality of Capacitor Manufacturing Workers, 11 Am. J. Indus. Med. 165 (1987).

[3] Id. at 172.

[4] J. Zack & D. Munsch, Mortality of PCB Workers at the Monsanto Plant in Sauget, Illinois (Dec. 14, 1979) (unpublished report), 3 Rec., Doc. No. 11.

[5] Ronneberg, Andersen, Skyberg, “Mortality and Incidence of Cancer Among Oil-Exposed Workers in a Norwegian Cable Manufacturing Company,” 45 Br. J. Indus. Med. 595 (1988).

[6] Kuratsune, Nakamura, Ikeda, & Hirohata, “Analysis of Deaths Seen Among Patients with Yusho – A Preliminary Report,” 16 Chemosphere 2085 (1987).

[7] Thomas Sinks, Alexander B. Smith, Robert Rinsky, M. Kathy Watkins, and Ruth Shults, Health Hazard Evaluation Report, HETA 89-116-209 (Jan. 1991) (reporting lung cancer SMR = 0.7 (95%CI, 0.4 – 1.2). This unpublished study was published by the time the Joiner case was litigated. Thomas Sinks, G. Steele, Alexander B. Smith, and Ruth Shults, “Mortality among workers exposed to polychlorinated biphenyls,” 136 Am. J. Epidemiol. 389 (1992). A follow-up on this unpublished study confirmed the paucity of lung cancer in the cohort. See Avima M. Ruder, Misty J. Hein, Nancy Nilsen, Martha A. Waters, Patricia Laber, Karen Davis-King, Mary M. Prince, and Elizabeth Whelan, “Mortality among Workers Exposed to Polychlorinated Biphenyls (PCBs) in an Electrical Capacitor Manufacturing Plant in Indiana: An Update,” 114 Environmental Health Perspect. 18 (2006).

[8] P. Gustavsson, C. Hogstedt, and C. Rappe, “Short-term mortality and cancer incidence in capacitor manufacturing workers exposed to polychlorinated biphenyls (PCBs),” 10 Am. J. Indus. Med. 341 (1986); P. Gustavsson & C. Hogstedt, “A cohort study of Swedish capacitor manufacturing workers exposed to polychlorinated biphenyls (PCBs),” 32 Am. J. Indus. Med. 234 (1997) (cancer incidence for entire cohort, SIR = 86, 95%; CI 51-137).

[9] David P. Brown, “Mortality of workers exposed to polychlorinated biphenyls–an update,” 42 Arch. Envt’l Health 333 (1987)

[10] See Renate D. Kimbrough, Constantine A. Krouskas, Wenjing Xu, and Peter G. Shields, “Mortality among capacitor workers exposed to polychlorinated biphenyls (PCBs), a long-term update,” 88 Internat’l Arch. Occup. & Envt’l Health 85 (2015).