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Reference Manual – Desiderata for 4th Edition – Part V – Specific Tortogens

February 14th, 2023

Examples are certainly helpful to explain and to show judges how real scientists reach causal conclusions. The Reference Manual should certainly give such examples of how scientists determine whether a claim has been adequately tested, and whether the claim has eliminated the myriad kinds of error that threaten such claims and require us to withhold our assent. The third edition of the Manual, however, advances some dodgy examples, without any data or citations. I have already pointed out that the third edition’s reference to clear cell adenocarcinoma of the vagina in young women as a “signal” disease caused only by DES is incorrect.[1] There are, alas, other troubling examples in the third edition, which are due for pruning.

Claimed Interaction Between Asbestos and Tobacco Risks for Lung Cancer

The third edition’s chapter on epidemiology discusses the complexities raised by potential interaction between multiple exposures. The discussion is appropriately suggesting that a relative risk cannot be used to determine the probability of individual causation “if the agent interacts with another cause in a way that results in an increase in disease beyond merely the sum of the increased incidence due to each agent separately.” The suggestion is warranted, although the chapter then is mum on whether there are other approaches that can be invoked to derive probabilities of causation when multiple exposures interact in a known way. Then the authors provided an example:

“For example, the relative risk of lung cancer due to smoking is around 10, while the relative risk for asbestos exposure is approximately 5. The relative risk for someone exposed to both is not the arithmetic sum of the two relative risks, that is, 15, but closer to the product (50- to 60-fold), reflecting an interaction between the two.²⁰⁰ Neither of the individual agent’s relative risks can be employed to estimate the probability of causation in someone exposed to both asbestos and cigarette smoke.”[2]

Putting aside for the moment the general issue of interaction, the chapter’s use of the Mt. Sinai catechism, of 5-10-50, for asbestos and tobacco smoking and lung cancer, is a poor choice. The evidence for multiplicative interaction was advanced by the late Irving Selikoff, and frankly the evidence was never very good. The supposed “non-smokers” were really “never smoked regularly,” and the smoking histories were taken by postcard surveys. The cohort of asbestos insulators was well aware of the study hypothesis, in that many of its members had compensations claims, and they had an interest in downplaying their smoking. Indeed, the asbestos workers’ union helped fund Selikoff’s work, and Selikoff had served as a testifying expert witness for claimants.

Given that “never smoked regularly” is not the same as never having smoked, and given that the ten-fold risk from smoking-alone was already an underestimate of lung cancer risk from smoking alone, the multiplicative model never was on a firm basis. The smoking-alone risk ratio was doubled in the American Cancer Society’s Cancer Prevention Survey Numbers One and Two, but the Mt. Sinai physicians, who frequently testified in lawsuits for claimants steadfastly held to their outdated statistical control group.[3] It is thus disturbing that the third edition’s authors trotted out a summary of asbestos / smoking lung cancer risks based upon Selikoff’s dodgy studies of asbestos insulation workers. The 5-10-50 dogma was already incorrect when the first edition went to press.

Not only were Selikoff’s study probably incorrect when originally published, updates to the insulation worker cohort published after his death, specifically undermine the multiplicative claim. In a 2013 publication by Selikoff’s successors, asbestos and smoking failed to show multiplicative interaction. Indeed, occupational asbestos exposure that had not manifested in clinically apparent asbestosis did not show any interaction with smoking. Only in a subgroup of insulators with clinically detectable asbestosis did the asbestosis and smoking show “supra-additive” (but not multiplicative) interaction.[4]

Manganese and Parkinson’s Disease

Table 1, of the toxicology chapter in the third edition, presented a “Sample of Selected Toxicological End Points and Examples of Agents of Concern in Humans.” The authors cautioned that the table was “not an exhaustive or inclusive list of organs, end points, or agents. Absence from this list does not indicate a relative lack of evidence for a causal relation as to any agent of concern.”[5] Among the examples presented in this Table 1 was neurotoxicity in the form of “Parkinson’s disease and manganese”[6]

The presence of this example of this example in Table 1 is curious on a number of fronts. First, one of the members of the Development Committee for the third edition was Judge Kathleen O’Malley, who presided over a multi-district litigation involving claims for parkinsonism and Parkinson’s disease against manufacturers of welding rods. It seemed unlikely that Judge O’Malley would have overlooked this section. See, e.g., In re Welding Fume Prods. Liab. Litig., 245 F.R.D. 279 (N.D. Ohio 2007) (exposure to manganese fumes allegedly increased the risk of later developing brain damage). More important, however, the authors’ inclusion of Parkinson’s disease as an outcome from manganese exposure is remarkable because that putative relationship has been extensively studied and rejected by leading researchers in the field of movement disorders.[7] In 2010, neuro-epidemiologists published a comprehensive meta-analysis that confirmed the absence of a relationship between manganese exposure and Parkinson’s disease.[8] The inclusion in Table 1 of a highly controversial relationship, manganese-Parkinson’s disease, suggests either undisclosed partisanship or ignorance of the relevant scientific evidence.

Mesothelioma

The toxicology chapter of the third edition also weighed in on mesothelioma as a supposed signature disease of asbestos exposure. The chapter’s authors described mesothelioma as “almost always caused by asbestos,”[9] which was no doubt true when mesothelioma was first identified as caused by fibrous amphibole minerals.[10] The last two decades, however, has seen a shift in the incidence of mesothelioma among industrially exposed workers, which reveals more cases without asbestos exposure and with other potential causes. Leading scientists in the field have acknowledged non-asbestos causes,[11] and recently researchers have identified genetic mutations that completely account for the causation of individual cases of mesothelioma.[12] It is time for the fourth edition to acknowledge other causes of mesothelioma, and to offer judges and lawyers guidance on genetic causes of sporadic diseases.

[1] See “Reference Manual – Desiderata for the Fourth Edition – Signature Disease” (Jan. 30, 2023).

[2] RMSE3d at 615 & n. 200. The chapter fails to cite support for the 5-10-50 dogma, but it is readily recognizable as the Mt. Sinai Catechism that was endlessly repeated by Irving Selikoff and his protégés.

[3] Michael J. Thun, Cathy A. Day-Lally, Eugenia E. Calle, W. Dana Flanders, and Clark W Heath, “Excess mortality among cigarette smokers: Changes in a 20-year interval,” 85 Am. J. Public Health 1223 (1995).

[4] Steve Markowitz, Stephen Levin, Albert Miller, and Alfredo Morabia, “Asbestos, Asbestosis, Smoking and Lung Cancer: New Findings from the North American Insulator Cohort,” 188 Am. J. Respir. & Critical Care Med. 90 (2013); see “The Mt. Sinai Catechism” (June 7, 2013).

[5] RMSE3d at 653-54.

[6] Reference Manual at 653.

[7] See e.g., Karin Wirdefeldt, Hans-Olaf Adami, Philip Cole, Dimitrios Trichopoulos, and Jack Mandel, “Epidemiology and etiology of Parkinson’s disease: a review of the evidence. 26 European J. Epidemiol. S1, S20-21 (2011); Tomas R. Guilarte, “Manganese and Parkinson’s Disease: A Critical Review and New Findings,” 118 Environ Health Perspect. 1071, 1078 (2010) (“The available evidence from human and nonhuman primate studies using behavioral, neuroimaging, neurochemical, and neuropathological end points provides strong support to the hypothesis that, although excess levels of [manganese] accumulation in the brain results in an atypical form of parkinsonism, this clinical outcome is not associated with the degeneration of nigrostriatal dopaminergic neurons as is the case in PD [Parkinson’s disease].”)

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

[9] Bernard D. Goldstein & Mary Sue Henifin, “Reference Guide on Toxicology,” RMSE3d 633, 635 (2011).

[10] See J. Christopher Wagner, C.A. Sleggs, and Paul Marchand, “Diffuse pleural mesothelioma and asbestos exposure in the North Western Cape Province,” 17 Br. J. Indus. Med. 260 (1960); J. Christopher Wagner, “The discovery of the association between blue asbestos and mesotheliomas and the aftermath,” 48 Br. J. Indus. Med. 399 (1991); see also Harriet Hardy, M.D., Challenging Man-Made Disease: The Memoirs of Harriet L. Hardy, M.D. 95 (1983); “Harriet Hardy’s Views on Asbestos Issues” (Mar. 13, 2013).

[11] Richard L. Attanoos, Andrew Churg, Allen R. Gibbs, and Victor L. Roggli, “Malignant Mesothelioma and Its Non-Asbestos Causes,” 142 Arch. Pathol. & Lab. Med. 753 (2018).

[12] Angela Bononia, Qian Wangb, Alicia A. Zolondick, Fang Baib, Mika Steele-Tanjia, Joelle S. Suareza , Sandra Pastorinoa, Abigail Sipesa, Valentina Signoratoa, Angelica Ferroa, Flavia Novellia , Jin-Hee Kima, Michael Minaaia,d, Yasutaka Takinishia, Laura Pellegrinia, Andrea Napolitanoa, Ronghui Xua , Christine Farrara , Chandra Goparajua, Cristian Bassig, Massimo Negrinig, Ian Paganoa , Greg Sakamotoa, Giovanni Gaudinoa, Harvey I. Pass, José N. Onuchic , Haining Yang, and Michele Carbone, “BAP1 is a novel regulator of HIF-1α,” 120 Proc. Nat’l Acad. Sci. e2217840120 (2023).

Posted in Causation, Reference Manual on Scientific Evidence | 1 Comment »

Reference Manual – Desiderata for 4th Edition – Part IV – Confidence Intervals

February 10th, 2023

Putting aside the idiosyncratic chapter by the late Professor Berger, most of the third edition of the Reference Manual presented guidance on many important issues. To be sure, there are gaps, inconsistencies, and mistakes, but the statistics chapter should be a must-read for federal (and state) judges. On several issues, especially statistical in nature, the fourth edition could benefit from an editor to ensure that the individual chapters, written by different authors, actually agree on key concepts. One such example is the third edition’s treatment of confidence intervals.[1]

The “DNA Identification” chapter noted that the meaning of a confidence interval is subtle,[2] but I doubt that the authors, David Kaye and George Sensabaugh, actually found it subtle or difficult. In the third edition’s chapter on statistics, David Kaye and co-author, the late David A. Freedman, gave a reasonable definition of confidence intervals in their glossary:

“confidence interval. An estimate, expressed as a range, for a parameter. For estimates such as averages or rates computed from large samples, a 95% confidence interval is the range from about two standard errors below to two standard errors above the estimate. Intervals obtained this way cover the true value about 95% of the time, and 95% is the confidence level or the confidence coefficient.”[3]

Intervals, not the interval, which is correct. This chapter made clear that it was the procedure of obtaining multiple samples with intervals that yielded the 95% coverage. In the substance of their chapter, Kaye and Freedman are explicit about how intervals are constructed, and that:

“the confidence level does not give the probability that the unknown parameter lies within the confidence interval.”[4]

Importantly, the authors of the statistics chapter named names; that is, they cited some cases that butchered the concept of the confidence interval.[5] The fourth edition will have a more difficult job because, despite the care taken in the statistics chapter, many more decisions have misstated or misrepresented the meaning of a confidence interval.[6] Citing more cases perhaps will disabuse federal judges of their reliance upon case law for the meaning of statistical concepts.

The third edition’s chapter on multiple regression defined confidence interval in its glossary:

“confidence interval. An interval that contains a true regression parameter with a given degree of confidence.”[7]

The chapter avoided saying anything obviously wrong only by giving a very circular definition. When the chapter substantively described a confidence interval, it ended up giving an erroneous one:

“In general, for any parameter estimate b, the expert can construct an interval around b such that there is a 95% probability that the interval covers the true parameter. This 95% confidence interval is given by: b ± 1.96 (SE of b).”[8]

The formula provided is correct, but the interpretation of a 95% probability that the interval covers the true parameter is unequivocably wrong.[9]

The third edition’s chapter by Shari Seidman Diamond on survey research, on the other hand, gave an anodyne example and a definition:

“A survey expert could properly compute a confidence interval around the 20% estimate obtained from this sample. If the survey were repeated a large number of times, and a 95% confidence interval was computed each time, 95% of the confidence intervals would include the actual percentage of dentists in the entire population who would believe that Goldgate was manufactured by the makers of Colgate.

* * * *

Traditionally, scientists adopt the 95% level of confidence, which means that if 100 samples of the same size were drawn, the confidence interval expected for at least 95 of the samples would be expected to include the true population value.”[10]

Similarly, the third edition’s chapter on epidemiology correctly defined the confidence interval operationally as a process of iterative intervals that collectively cover the true value in 95% of all the intervals:

“A confidence interval provides both the relative risk (or other risk measure) found in the study and a range (interval) within which the risk likely would fall if the study were repeated numerous times.”[11]

Not content to leave it well said, the chapter’s authors returned to the confidence interval and provided another, more problematic definition, a couple of pages later in the text:

“A confidence interval is a range of possible values calculated from the results of a study. If a 95% confidence interval is specified, the range encompasses the results we would expect 95% of the time if samples for new studies were repeatedly drawn from the same population.”[12]

The first sentence refers to “a study”; that is, one study, one range of values. The second sentence then tells us that “the range” (singular, presumably referring back to the single “a study”), will capture 95% of the results from many resamplings from the same population. Now the definition is not framed with respect to the true population parameter, but the results from many other samples. The authors seem to have given the first sample’s confidence interval the property of including 95% of all future studies, and that is incorrect. From reviewing the case law, courts remarkably have gravitated to the second, incorrect definition.

The glossary to the third edition’s epidemiology chapter clearly, however, runs into the ditch:

“confidence interval. A range of values calculated from the results of a study within which the true value is likely to fall; the width of the interval reflects random error. Thus, if a confidence level of .95 is selected for a study, 95% of similar studies would result in the true relative risk falling within the confidence interval.”[13]

Note that the sentence before the semicolon talked of “a study” with “a range of values,” and that there is a likelihood of that range including the “true value.” This definition thus used the singular to describe the study and to describe the range of values. The definition seemed to be saying, clearly but wrongly, that a single interval from a single study has a likelihood of containing the true value. The second full sentence ascribed a probability, 95%, to the true relative risk’s falling within “the interval.” To point out the obvious, “the interval,” is singular, and refers back to “a study,” also singular. At best, this definition was confusing; at worst, it was wrong.

The Reference Manual has a problem beyond its own inconsistencies, and the refractory resistance of the judiciary to statistical literacy. There are any number of law professors and even scientists who have held out incorrect definitions and interpretations of confidence intervals. It would be helpful for the fourth edition to caution its readers, both bench and bar, to the prevalent misunderstandings.

Here, for instance, is an example of a well-credentialed statistician, who gave a murky definition in a declaration filed in federal court:

“If a 95% confidence interval is specified, the range encompasses the results we would expect 95% of the time if samples for new studies were repeatedly drawn from the same population.”[14]

The expert witness correctly identifies the repeated sampling, but specifies a 95% probability to “the range,” which leaves unclear whether it is the range of all intervals or “a 95% confidence interval,” which is in the antecedent of the statement.

Much worse was a definition proffered in a recent law review article by well-known, respected authors:

“A 95% conﬁdence interval, in contrast, is a one-sided or two-sided interval from a data sample with 95% probability of bounding a ﬁxed, unknown parameter, for which no nondegenerate probability distribution is conceived, under speciﬁed assumptions about the data distribution.”[15]

The phrase “for which no nondegenerate probability distribution is conceived,” is unclear as to whether the quoted phrase refers to the conﬁdence interval or to the unknown parameter. It seems that the phrase modifies the noun closest to it in the sentence, the “ﬁxed, unknown parameter,” which suggests that these authors were simply trying to emphasize that they were giving a frequentist interpretation and not conceiving of the parameter as a random variable as Bayesians would. The phrase “no nondegenerate” appears to be a triple negative, since a degenerate distribution is one that does not have a variation. The phrase makes the deﬁnition obscure, and raises questions what is being excluded by the phrase.

The more concerning aspect of the quoted footnote is its obfuscation of the important distinction between the procedure of repeatedly calculating conﬁdence intervals (which procedure has a 95% success rate in the long run) and the probability that any given instance of the procedure, in a single confidence interval, contains the parameter. The latter probability is either zero or one.

The deﬁnition’s reference to “a” conﬁdence interval, based upon “a” data sample, actually leaves the reader with no way of understanding the deﬁnition to be referring to the repeated process of sampling, and the set of resulting intervals. The upper and lower interval bounds are themselves random variables that need to be taken into account, but by referencing a single interval from a single data sample, the authors misrepresent the confidence interval and invite a Bayesian interpretation.[16]

Sadly, there is a long tradition of scientists and academics in giving errant definitions and interpretations of the confidence interval.[17] Their error is not harmless because they invite the attribution of a high level of probability to the claim that the “true” population measure is within the reported confidence interval. The error encourages readers to believe that the confidence interval is not conditioned upon the single sample result, and it misleads readers into believing that not only random error, but systematic and data errors are accounted for in the posterior probability.[18]

[1] “Confidence in Intervals and Diffidence in the Courts” (Mar. 4, 2012).

[2] David H. Kaye & George Sensabaugh, “Reference Guide on DNA Identification Evidence” 129, 165 n.76.

[3] David H. Kaye & David A. Freedman, “Reference Guide on Statistics” 211, 284-5 (Glossary).

[4] Id. at 247.

[5] Id. at 247 n.91 & 92 (citing DeLuca v. Merrell Dow Pharms., Inc., 791 F. Supp. 1042, 1046 (D.N.J. 1992), aff’d, 6 F.3d 778 (3d Cir. 1993); SmithKline Beecham Corp. v. Apotex Corp., 247 F. Supp. 2d 1011, 1037 (N.D. Ill. 2003), aff’d on other grounds, 403 F.3d 1331 (Fed. Cir. 2005); In re Silicone Gel Breast Implants Prods. Liab. Litig, 318 F. Supp. 2d 879, 897 (C.D. Cal. 2004) (“a margin of error between 0.5 and 8.0 at the 95% confidence level . . . means that 95 times out of 100 a study of that type would yield a relative risk value somewhere between 0.5 and 8.0.”).

[6] See, e.g., Turpin v. Merrell Dow Pharm., Inc., 959 F.2d 1349, 1353–54 & n.1 (6th Cir. 1992) (erroneously describing a 95% CI of 0.8 to 3.10, to mean that “random repetition of the study should produce, 95 percent of the time, a relative risk somewhere between 0.8 and 3.10”); American Library Ass’n v. United States, 201 F.Supp. 2d 401, 439 & n.11 (E.D.Pa. 2002), rev’d on other grounds, 539 U.S. 194 (2003); Ortho–McNeil Pharm., Inc. v. Kali Labs., Inc., 482 F.Supp. 2d 478, 495 (D.N.J.2007) (“Therefore, a 95 percent confidence interval means that if the inventors’ mice experiment was repeated 100 times, roughly 95 percent of results would fall within the 95 percent confidence interval ranges.”) (apparently relying party’s expert witness’s report), aff’d in part, vacated in part, sub nom. Ortho McNeil Pharm., Inc. v. Teva Pharms Indus., Ltd., 344 Fed.Appx. 595 (Fed. Cir. 2009); Eli Lilly & Co. v. Teva Pharms, USA, 2008 WL 2410420, *24 (S.D. Ind. 2008) (stating incorrectly that “95% percent of the time, the true mean value will be contained within the lower and upper limits of the confidence interval range”); Benavidez v. City of Irving, 638 F.Supp. 2d 709, 720 (N.D. Tex. 2009) (interpreting a 90% CI to mean that “there is a 90% chance that the range surrounding the point estimate contains the truly accurate value.”); Pritchard v. Dow Agro Sci., 705 F. Supp. 2d 471, 481, 488 (W.D. Pa. 2010) (excluding Dr. Bennet Omalu who assigned a 90% probability that an 80% confidence interval excluded relative risk of 1.0), aff’d, 430 F. App’x 102 (3d Cir.), cert. denied, 132 S. Ct. 508 (2011); Estate of George v. Vermont League of Cities and Towns, 993 A.2d 367, 378 n.12 (Vt. 2010) (erroneously describing a confidence interval to be a “range of values within which the results of a study sample would be likely to fall if the study were repeated numerous times”); Garcia v. Tyson Foods, 890 F. Supp. 2d 1273, 1285 (D. Kan. 2012) (quoting expert witness Robert G. Radwin, who testified that a 95% confidence interval in a study means “if I did this study over and over again, 95 out of a hundred times I would expect to get an average between that interval.”); In re Chantix (Varenicline) Prods. Liab. Litig., 889 F. Supp. 2d 1272, 1290n.17 (N.D. Ala. 2012); 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.”), aff’d, 858 F.3d 787 (3d Cir. 2017); Duran v. U.S. Bank Nat’l Ass’n, 59 Cal. 4th 1, 36, 172 Cal. Rptr. 3d 371, 325 P.3d 916 (2014) (“Statisticians typically calculate margin of error using a 95 percent confidence interval, which is the interval of values above and below the estimate within which one can be 95 percent certain of capturing the ‘true’ result.”); In re Accutane Litig., 451 N.J. Super. 153, 165 A.3d 832, 842 (2017) (correctly quoting an incorrect definition from the third edition at p.580), rev’d on other grounds, 235 N.J. 229, 194 A.3d 503 (2018); In re Testosterone Replacement Therapy Prods. Liab., No. 14 C 1748, MDL No. 2545, 2017 WL 1833173, *4 (N.D. Ill. May 8, 2017) (“A confidence interval consists of a range of values. For a 95% confidence interval, one would expect future studies sampling the same population to produce values within the range 95% of the time.”); Maldonado v. Epsilon Plastics, Inc., 22 Cal. App. 5th 1308, 1330, 232 Cal. Rptr. 3d 461 (2018) (“The 95 percent ‘confidence interval’, as used by statisticians, is the ‘interval of values above and below the estimate within which one can be 95 percent certain of capturing the “true” result’.”); Escheverria v. Johnson & Johnson, 37 Cal. App. 5th 292, 304, 249 Cal. Rptr. 3d 642 (2019) (quoting uncritically and with approval one of plaintiff’s expert witnesses, Jack Siemiatycki, who gave the jury an example of a study with a relative risk of 1.2, with a “95 percent probability that the true estimate is between 1.1 and 1.3.” According to the court, Siemiatycki went on to explain that this was “a pretty tight interval, and we call that a confidence interval. We call it a 95 percent confidence interval when we calculate it in such a way that it covers 95 percent of the underlying relative risks that are compatible with this estimate from this study.”); In re Viagra (Sildenafil Citrate) & Cialis (Tadalafil) Prods. Liab. Litig., 424 F.Supp.3d 781, 787 (N.D. Cal. 2020) (“For example, a given study could calculate a relative risk of 1.4 (a 40 percent increased risk of adverse events), but show a 95 percent “confidence interval” of .8 to 1.9. That confidence interval means there is 95 percent chance that the true value—the actual relative risk—is between .8 and 1.9.”); Rhyne v. United States Steel Corp., 74 F. Supp. 3d 733, 744 (W.D.N.C. 2020) (relying upon, and quoting, one of the more problematic definitions given in the third edition at p.580: “If a 95% confidence interval is specified, the range encompasses the results we would expect 95% of the time if samples for new studies were repeatedly drawn from the population.”); Wilant v. BNSF Ry., C.A. No. N17C-10-365 CEB, (Del. Super. Ct. May 13, 2020) (citing third edition at p.573, “a confidence interval provides ‘a range (interval) within which the risk likely would fall if the study were repeated numerous times’.”; “[s]o a 95% confidence interval indicates that the range of results achieved in the study would be achieved 95% of the time when the study is replicated from the same population.”); Germaine v. Sec’y Health & Human Servs., No. 18-800V, (U.S. Fed. Ct. Claims July 29, 2021) (giving an incorrect definition directly from the third edition, at p.621; “[a] “confidence interval” is “[a] range of values … within which the true value is likely to fall[.]”).

[7] Daniel Rubinfeld, “Reference Guide on Multiple Regression” 303, 352.

[8] Id. at 342.

[9] See Sander Greenland, Stephen J. Senn, Kenneth J. Rothman, John B. Carlin, Charles Poole, Steven N. Goodman, and Douglas G. Altman, “Statistical tests, P values, conﬁdence intervals, and power: a guide to misinterpretations,” 31 Eur. J. Epidemiol. 337, 343 (2016).

[10] Shari Seidman Diamond, “Reference Guide on Survey Research” 359, 381.

[11] Michael D. Green, D. Michal Freedman, and Leon Gordis, “Reference Guide on Epidemiology,” 549, 573.

[12] Id. at 580.

[13] Id. at 621.

[14] In re Testosterone Replacement Therapy Prods. Liab. Litig., Declaration of Martin T. Wells, Ph.D., at 2-3 (N.D. Ill., Oct. 30, 2016).

[15] Joseph Sanders, David Faigman, Peter Imrey, and A. Philip Dawid, “Diﬀerential Etiology: Inferring Speciﬁc Causation in the Law from Group Data in Science,” 63 Arizona L. Rev. 851, 898 n.173 (2021).

[16] The authors are well-credentialed lawyers and scientists. Peter Imrey, was trained in, and has taught, mathematical statistics, biostatistics, and epidemiology. He is a professor of medicine in the Cleveland Clinic Lerner College of Medicine. A. Philip Dawid is a distinguished statistician, an Emeritus Professor of Statistics, Cambridge University, Darwin College, and a Fellow of the Royal Society. David Faigman is the Chancellor & Dean, and the John F. Digardi Distinguished Professor of Law at the University of California Hastings College of the Law. Joseph Sanders is the A.A. White Professor, at the University of Houston Law Center. I have previously pointed this problem in these authors’ article. “Differential Etiologies – Part One – Ruling In” (June 19, 2022).

[17] See, e.g., Richard W. Clapp & David Ozonoff, “Environment and Health: Vital Intersection or Contested Territory?” 30 Am. J. L. & Med. 189, 210 (2004) (“Thus, a RR [relative risk] of 1.8 with a confidence interval of 1.3 to 2.9 could very likely represent a true RR of greater than 2.0, and as high as 2.9 in 95 out of 100 repeated trials.”); Erica Beecher-Monas, Evaluating Scientific Evidence: An Interdisciplinary Framework for Intellectual Due Process 60-61 n. 17 (2007) (quoting Clapp and Ozonoff with obvious approval); Déirdre Dwyer, The Judicial Assessment of Expert Evidence 154-55 (Cambridge Univ. Press 2008) (“By convention, scientists require a 95 per cent probability that a finding is not due to chance alone. The risk ratio (e.g. ‘2.2’) represents a mean figure. The actual risk has a 95 per cent probability of lying somewhere between upper and lower limits (e.g. 2.2 ±0.3, which equals a risk somewhere between 1.9 and 2.5) (the ‘confidence interval’).”); Frank C. Woodside, III & Allison G. Davis, “The Bradford Hill Criteria: The Forgotten Predicate,” 35 Thomas Jefferson L. Rev. 103, 110 (2013) (“A confidence interval provides both the relative risk found in the study and a range (interval) within which the risk would likely fall if the study were repeated numerous times.”); Christopher B. Mueller, “Daubert Asks the Right Questions: Now Appellate Courts Should Help Find the Right Answers,” 33 Seton Hall L. Rev. 987, 997 (2003) (describing the 95% confidence interval as “the range of outcomes that would be expected to occur by chance no more than five percent of the time”); Arthur H. Bryant & Alexander A. Reinert, “The Legal System’s Use of Epidemiology,” 87 Judicature 12, 19 (2003) (“The confidence interval is intended to provide a range of values within which, at a specified level of certainty, the magnitude of association lies.”) (incorrectly citing the first edition of Rothman & Greenland, Modern Epidemiology 190 (Philadelphia 1998); John M. Conley & David W. Peterson, “The Science of Gatekeeping: The Federal Judicial Center’s New Reference Manual on Scientific Evidence,” 74 N.C.L.Rev. 1183, 1212 n.172 (1996) (“a 95% confidence interval … means that we can be 95% certain that the true population average lies within that range”).

[18] See Brock v. Merrill Dow Pharm., Inc., 874 F.2d 307, 311–12 (5th Cir. 1989) (incorrectly stating that the court need not resolve questions of bias and confounding because “the studies presented to us incorporate the possibility of these factors by the use of a confidence interval”). Bayesian credible intervals can similarly be misleading when the interval simply reflects sample results and sample variance, but not the myriad other ways the estimate may be wrong.

Posted in Evidence, Expert Witnesses, Reference Manual on Scientific Evidence, statistical evidence | No Comments »

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

February 1st, 2023

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

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

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

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

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

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

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

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

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

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

Errant Opinions on Differential Etiology

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

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

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

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

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

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

P v Q

~P_____

∴ Q

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

P v Q v R

~P_____

∴ Q v R

~Q_____

∴ R

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

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

Supreme Nonsense on Differential Etiology

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

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

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

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

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

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

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

and

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

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

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

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

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

[3] RMSE3d at 617.

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

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

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

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

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

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

[10] RMSE3d at 691 (emphasis added).

[11] RMSE3d at 743.

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

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

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

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

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

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

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

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

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

Reference Manual – Desiderata for 4th Edition – Part II – Epidemiology & Specific Causation

January 31st, 2023

There are many nits that a reader could pick with the third edition of the Reference Manual, but one non-trivial issue is raised by the epidemiology chapter’s pronouncement that:

“Epidemiology is concerned with the incidence of disease in populations, and epidemiologic studies do not address the question of the cause of an individual’s disease¹⁷⁸.”[1]

According to the Manual’s authors, the so-called specific-causation question is “beyond the domain of the science of epidemiology.” Epidemiologists do not investigate whether “an agent caused a specific plaintiff’s disease.”[2] The chapter insists that “[t]his question is not a question that is addressed by epidemiology. Rather, it is a legal question with which numerous courts have grappled.”[3]

Later on in the chapter, the authors repeat their opinion when they insist that the use of a threshold relative risk is “not epidemiology or an inquiry that an epidemiologist would undertake.”[4]

Strictly speaking the authors are correct that an epidemiologic study itself typically does not address the question individual causation. The authors of an epidemiologic study have no one person in mind, as does the factfinder in a civil action. The notion that epidemiology as a scientific discipline does not address the question of individual causation, however, seems just wrong. Tellingly, the authors’ footnote pointed to case law and a law review article, and not a single scientific source. The chapter does reference another legal source, the Third Restatement, which repeats the gist of the epidemiology chapter’s categorical statement:

“Scientists who conduct group studies do not examine specific causation in their research. No scientific methodology exists for assessing specific causation for an individual based on group studies. Nevertheless, courts have reasoned from the preponderance-of-the-evidence standard to determine the sufficiency of scientific evidence on specific causation when group-based studies are involved.”[5]

The chapter’s broad, sweeping characterization fails to consider:

genome-wide association studies that may identify genes or mutations that are highly penetrant and which identify a causal association in the carriers of the genes; and
epidemiologic studies that identify associations, shown to be causal, with risk ratios sufficiently great (say over 20) such that virtually all cases of the studied outcome would be avoided by removing the exposure that gave rise to such a large risk ratio; and
epidemiologic studies that allow causal associations to be inferred in limited sub-populations, with sufficiently high relative risks that the studies support specific causation opinions.

Perhaps even more important than the above counter-examples, the chapter authors ignore the myriad instances in which epidemiologic studies and clinical trials, and analyses of both, directly inform clinical judgments about individual patients or subjects. Clinicians use studies of groups, such as clinical trials, to identify therapeutic benefits from medications and other interventions. These data directly inform their prescription decisions for individual patients, or their decisions to recommend surgical or other medical interventions to individuals.[6] The classic text on medical decision making describes how group-level data provide the basis for individual clinical decisions on therapy:

“1.5 How do I choose among several risky treatment alternatives?

Choosing among risky treatment alternatives is difficult because the outcome of most treatments is uncertain: some people respond to treatment but others do not. If the outcome of a treatment is governed by chance, a clinician cannot know in advance which outcome of the treatment will result. Under these circumstances, the best way to achieve a good outcome is to choose the treatment alternative whose average outcome is best. This concept is called expected value decision making.”[7]

Medical practitioners and scientists frequently use epidemiologic data, based upon “group-based data” to make individual diagnostic judgments. The inferences from group data to individual range abound in the diagnostic process itself, where the specificity and sensitivity of disease signs and symptoms are measured by group data. Physicians must rely upon group data to make prognoses for individual patients, and they rely upon group data to predict future disease risks for individual patients. Future disease risks, as in the Framingham risk score for hard coronary heart disease, or the Gale model for breast cancer risk, are, of course, based upon “group-based data.”[8] A search on the phrase “prediction models” yielded 662,297 results in the National Library of Medicine PubMed database.

The epidemiology chapter has taken its position on the irrelevance of epidemiology to specific causation through all three editions of the Reference Manual. Perhaps its authors will rethink their dogma in the fourth.

[1] RMSE3d at 608. The internal footnote, 178, pointed to: “178. See DeLuca v. Merrell Dow Pharms., Inc., 911 F.2d 941, 945 & n.6 (3d Cir. 1990) (“Epidemiological studies do not provide direct evidence that a particular plaintiff was injured by exposure to a substance.”) (emphasis added in this post). The emphasis in the quote is mine because the DeLuca court suggested by implication that epidemiologic studies provided the basis for inferences about specific causation. The footnote also cited another case that simply cited an earlier edition of the Manual, which hardly advances the inquiry into whether the Manual was correct in the first place. See In re Viagra Prods. Liab. Litig., 572 F. Supp. 2d 1071, 1078 (D. Minn. 2008) (“Epidemiology focuses on the question of general causation (i.e., is the agent capable of causing disease?) rather than that of specific causation (i.e., did it cause a disease in a particular individual?)” (quoting the second edition of this reference guide)). Finally, the Manual cited a state court case, In re Asbestos Litig,, 900 A.2d 120, 133 (Del. Super. Ct. 2006), and a law review article, Michael Dore, “A Commentary on the Use of Epidemiological Evidence in Demonstrating Cause-in-Fact,” 7 Harv. Envtl. L. Rev. 429, 436 (1983).” Admittedly, the chapter’s position can be found in writings of other legal commentators, although repetition hardly makes it any less wrong. See, e.g., Andrew See, “Use of Human Epidemiology Studies in Proving Causation,” 67 Def. Couns. J. 478, 478 (2000) (“Epidemiology studies are relevant only to the issue of general causation and cannot establish whether an exposure or factor caused disease or injury in a specific individual.”); Melissa Moore Thomson, Causal Inference in Epidemiology: Implications for Toxic Tort Litigation, 71 N.C. L. Rev. 247, 255 (1992) (“statistic-based epidemiological study results should not be applied directly to establish the likelihood of causation in an individual plaintiff”);

[2] RMSE3d at 609 & n.179. Inconsistently, the epidemiology chapter reports, without criticism, that some courts have allowed expert witnesses to opine about specific causation, without detailing how epidemiologic science was helpful to the specific causation issues. See RMSE3d at 609 n. 181 (citing Ambrosini v. Labarraque, 101 F.3d 129, 137–41 (D.C. Cir. 1996); Zuchowicz v. United States, 870 F. Supp. 15 (D. Conn. 1994); Landrigan v. Celotex Corp., 605 A.2d 1079, 1088–89 (N.J. 1992)).

[3] RMSE3d at 609.

[4] RMSE3d at 611 n.186.

[5] See Restatement (Third) of Torts: Liability for Physical and Emotional Harm § 28 cmt.

c(3) (2010) (cited at RMSE3d at 610 n.182).

[6] See, e.g., Robert H. Fletcher, Suzanne W. Fletcher, and Grant S. Fletcher, Clinical Epidemiology: The Essentials (5th ed. 2015) (treating prognosis, diagnosis, treatment, and prevention as topics of consideration, all involving individual patient decisions, in clinical epidemiology); Grobbee & Arno W. Hoes, Clinical Epidemiology: Principles, Methods, and Applications for Clinical Research (2d ed. 2015).

[7] Harold C. Sox, Michael C. Higgins & Douglas K. Owens, Medical Decision Making 6 (2d ed. 2013).

[8] See, e.g., Ewout W. Steyerberg. Clinical Prediction Models: A Practical Approach to Development, Validation, and Updating (2d ed. 2019).

Posted in Uncategorized | 3 Comments »

Reference Manual – Desiderata for 4th Edition – Part I – Signature Diseases

January 30th, 2023

The fourth edition of the Reference Manual on Scientific Evidence is by all accounts under way. Each of the first three editions represented an improvement over previous editions, but the last edition continued to have substantive problems. The bar, the judiciary, and the scientific community hopefully await an improved fourth edition. Although I have posted previously about issues in the third edition, I am updating and adding to what I have written.[1] There were only a few reviews and acknowledgments of the third edition.[2] The editorial staff provided little to no opportunity for comments in advance of the third edition, and to date, there has been no call for public comment about the pending fourth edition. I hope there will be more opportunity for the legal and scientific community to comment in the production of the fourth edition.

There are several issues raised by the third edition’s treatment of specific causation, which I hope will be improved in the fourth edition. One such issue is the epidemiology chapter’s brief discussion of so-called signature diseases. The chapter takes the curious position that epidemiology has nothing to say about individual or specific causation, a position I will discuss in later posts. The chapter, however, carves out a limited exception to its (questionable) edict that epidemiology does not concern itself with specific causation. The chapter tells us, uncontroversially, that some diseases do not occur without exposure to a specific chemical or substance. In my view, the authors of this chapter then go astray in telling us that “[a]bestosis is a signature disease for asbestos, and vaginal adenocarcinoma (in young adult women) is a signature disease for in utero DES exposure.”

Now, by definition, only asbestos can cause asbestosis, but asbestosis presents clinically in a way that is indistinguishable in many cases from idiopathic pulmonary fibrosis and other interstitial fibrotic diseases of the lungs. Over the years, the diagnostic criteria for asbestosis have changed, but these criteria have always had a specificity and sensitivity less than 100%. Saying that a case of asbestosis must have been caused by asbestos begs the clinical question whether the case really is asbestosis.

The chapter’s characterization of vaginal adenocarcinoma as a signature disease of in utero DES exposure is also not correct. Although this cancer in young women is extremely rare, there is a baseline risk that allows the calculation of relative risks for young women exposed in utero. In older women, the relative risks are lower because the baseline risks are higher, and because the effect of DES is diminished for older onset cases.[3] The disease was known before the use of DES in pregnant women began after World War II.[4]

For support of their discussion of “signal diseases,” the authors of the epidemiology chapter chose, remarkably, to cite an article that was over 25 years old (now over 35 years old) at the time the third edition was published.[5] The referenced passage asks us to:

“Consider tort claims for what have come to be called signature disease. These are diseases characteristically caused by only a few substances – such as the vaginal adenocarcinoma usually associated with exposure to DES in utero – and mesothelioma, a cancer of the pleura caused almost exclusively by exposure to asbestos fibers in the air.”[6]

Well, “usually associated” does equal signature disease.[7] The relative risks for smoking and some kinds of lung cancer are higher than for DES in utero and clear cell vaginal adenocarcinoma, but no one calls lung cancer a signature disease of smoking. (Admittedly, smoking is the major cause and perhaps the most preventable cause of lung cancer in Western countries.)

The third edition’s reference to a source that describes mesothelioma as “caused almost exclusively by exposure to asbestos fibers” is also out of date.[8] Recognizing that casual comments and citations can influence credulous judges, the authors of the fourth edition should strive for greater accuracy in their discussions of such scientific issues. It may be time to find new examples of signature disease.

[1] “Reference Manual on Scientific Evidence v4.0” (Feb. 28, 2021); “Reference Manual on Scientific Evidence – 3rd Edition is Past Its Expiry” (Oct. 17, 2021).

[2] See, e.g., Adam Dutkiewicz, “Book Review: Reference Manual on Scientific Evidence, Third Edition,” 28 Thomas M. Cooley L. Rev. 343 (2011); John A. Budny, “Book Review: Reference Manual on Scientific Evidence, Third Edition,” 31 Internat’l J. Toxicol. 95 (2012); James F. Rogers, Jim Shelson, and Jessalyn H. Zeigler, “Changes in the Reference Manual on Scientific Evidence (Third Edition),” Internat’l Ass’n Def. Csl. Drug, Device & Biotech. Comm. Newsltr. (June 2012). See Schachtman “New Reference Manual’s Uneven Treatment of Conflicts of Interest” (Oct. 12, 2011).

[3] Janneke Verloop, Flora E. van Leeuwen, Theo J. M. Helmerhorst, Hester H. van Boven, and Matti A. Rookus, “Cancer risk in DES daughters,” 21 Cancer Causes & Control 999 (2010).

[4] See “Risk Factors for Vaginal Cancer,” American Cancer Soc’y website (last visited Jan. 29, 2023).

[5] Kenneth S. Abraham & Richard A. Merrill, Scientific Uncertainty in the Courts, 2 Issues Sci. & Tech. 93, 101 (Winter 1986).

[6] Id.

[7] See, e.g., Kadir Güzin, Semra Kayataş Eserm, Ayşe Yiğit, and Ebru Zemheri, “Primary clear cell carcinoma of the vagina that is not related to in utero diethylstilbestrol use,” 3 Gynecol. Surg. 281 (2006).

[8] Michele Carbone, Harvey I. Pass, Guntulu Ak, H. Richard Alexander Jr., Paul Baas, Francine Baumann, Andrew M. Blakely, Raphael Bueno, Aleksandra Bzura, Giuseppe Cardillo, Jane E. Churpek, Irma Dianzani, Assunta De Rienzo, Mitsuru Emi, Salih Emri, Emanuela Felley-Bosco, Dean A. Fennell, Raja M. Flores, Federica Grosso, Nicholas K. Hayward, Mary Hesdorffer, Chuong D. Hoang, Peter A. Johansson, Hedy L. Kindler, Muaiad Kittaneh, Thomas Krausz, Aaron Mansfield, Muzaffer Metintas, Michael Minaai, Luciano Mutti, Maartje Nielsen, Kenneth O’Byrne, Isabelle Opitz, Sandra Pastorino, Francesca Pentimalli, Marc de Perrot, Antonia Pritchard, Robert Taylor Ripley, Bruce Robinson, and Valerie Rusch, “Medical and Surgical Care of Patients With Mesothelioma and Their Relatives Carrying Germline BAP1 Mutations,” 17 J. Thoracic Oncol. 873 (2022). See also Mitchell Cheung, Yuwaraj Kadariya, Eleonora Sementino, Michael J. Hall, Ilaria Cozzi, Valeria Ascoli, Jill A. Ohar, and Joseph R. Testa, “Novel LRRK2 mutations and other rare, non-BAP1-related candidate tumor predisposition gene variants in high-risk cancer families with mesothelioma and other tumors,” 30 Human Molecular Genetics 1750 (2021); Thomas Wiesner, Isabella Fried, Peter Ulz, Elvira Stacher, Helmut Popper, Rajmohan Murali, Heinz Kutzner, Sigurd Lax, Freya Smolle-Jüttner, Jochen B. Geigl, and Michael R. Speicher, “Toward an Improved Definition of the Tumor Spectrum Associated With BAP1 Germline Mutations,” 30 J. Clin. Oncol. e337 (2012); Alexandra M. Haugh, BA1; Ching-Ni Njauw, MS2,3; Jeffrey A. Bubley, et al., “Genotypic and Phenotypic Features of BAP1 Cancer Syndrome: A Report of 8 New Families and Review of Cases in the Literature,” 153 J.Am. Med. Ass’n Dermatol. 999 (2017).

Posted in Asbestos, Causation, Reference Manual on Scientific Evidence | 6 Comments »

Mass Tortogenesis

January 22nd, 2023

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

INITIATION

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

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

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

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

“Abstract

Background

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

Methods

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

Results

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

Conclusion

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

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

PROMOTION OF INITIATED MASS TORTS

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

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

“From: ZZZ

To: YYYYYYYYY

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

Hi,

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

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

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

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

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

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

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

Are you looking to help victims in this case

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

ZZZ intake fees are as low as $65 dollars per signed based upon a factors which are criteria, lead conversion %, and length of questionnaire. Conversion rates are averaging 45%.

I can help point you in the right direction for reputable marketing agencies if you need lead sources or looking to purchase retainers.

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

Thank you,

ZZZ”

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

“Proof”!

As in quod erat demonstrandum.

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

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

chorizo sausage links (courtesy of Wikipedia)[8]

And so it goes.

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

SYSTEMIC FAILURES TO PREVENT MASS TORTOGENESIS

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Doctor Moline – Why Can’t You Be True?

December 18th, 2022

Doctor Moline, why can’t you be true?

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

You done started doing the things you used to do.

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

And then there were others, too.

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

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

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

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

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

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

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

[7] Complaint ¶15.

[8] Complaint ¶19.

[9] Moline at 11.

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

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

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

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

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

Posted in Expert Witness Discovery, Expert Witnesses, Rule 702, Scientific Evidence, Scientific Misconduct, Underlying Data | 22 Comments »

An Opinion to SAVOR

November 11th, 2022

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

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

And the litigation came.

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

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

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

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

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

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

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

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

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

[2] Id. at 1324.

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

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

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

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

Further Thoughts on Cheng’s Consensus Rule

October 3rd, 2022

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

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

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

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

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

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

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

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

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

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

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

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

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

Deviation from Experts’ Standards of Care

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Cheng’s Proposed Consensus Rule for Expert Witnesses

September 15th, 2022

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

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

Whether a given substance causes a given disease

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

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

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

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

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

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

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

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

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

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

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

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

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

Finding Consensus

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

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

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

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

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

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

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

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

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

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

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

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

The Alleged Warrant for the Consensus Rule

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

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

Some Other Missteps in Cheng’s Argument

Experts on Both Sides are Too Extreme

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

Statistical Significance

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

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

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

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

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

Over-endorsing Animal Studies

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

Relative Risk Greater Than Two

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

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

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

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

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

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

[4] Consensus Rule at 467.

[5] Consensus Rule at 437.

[6] Consensus Rule at 434.

[7] Consensus Rule at 434.

[8] Consensus Rule at 422.

[9] Consensus Rule at 429.

[10] Consensus Rule at 432-33.

[11] Consensus Rule at 434.

[12] Consensus Rule at 456.

[13] Consensus Rule at 457.

[14] Consensus Rule at 459.

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

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

[17] Consensus Rule at 458.

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

[19] Consensus Rule at 445.

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

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

[22] Id.

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

[24] Consensus Rule at 444.

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

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

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