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PLPs & Five-Legged Dogs

September 1st, 2023

All lawyers have heard the puzzle of “how many legs does a dog have if you call his tail a leg?” The puzzle is often misattributed to Abraham Lincoln, who used the puzzle at various times, including in jury speeches. The answer of course is: “Four. Saying that a tail is a leg does not make it a leg.” Quote investigators have traced the puzzle as far back as 1825, when newspapers quoted legislator John W. Hulbert as saying that something “reminded him of the story.”[1]

What do we call a person who becomes pregnant and delivers a baby?

A woman.

The current, trending fashion is to call such a person a PLP, a person who becomes pregnant and lactates. This façon de parler is particularly misleading if it is meant as an accommodation to the transgender population. Transgender women will not show up as pregnant or lactating, and transgender men will show up only if there transition is incomplete and has left them with functional female reproductive organs.

In 2010, Guinness World Records named Thomas Beatie the “World’s First Married Man to Give Birth.” Thomas Beatie is now legally a man, which is just another way of saying that he chose to identify as a man, and gained legal recognition for his choice. Beatie was born as a female, matured into a woman, and had ovaries and a uterus. Beatie was, in other words, biologically a female when she went through puberty and became biologically a woman.

Beatie underwent partial gender reassignment surgery, consisting at least of double mastectomy, and taking testosterone replacement therapy (off label), but retained ovaries and a uterus.

Guinness makes a fine stout, and we may look upon it kindly for having nurtured the statistical thinking of William Sealy Gosset. Guinness, however, cannot make a dog have five legs simply by agreeing to call its tail a leg. Beatie was not the first pregnant man; rather he was the first person, born with functional female reproductive organs, to have his male gender identity recognized by a state, who then conceived and delivered a newborn. If Guinness wants to call this the first “legal man” to give birth, by semantic legerdemain, that is fine. Certainly we can and should publicly be respectful of transgendered persons, and work to prevent them from being harassed or embarrassed. There may well be many situations in which we would change our linguistic usage to acknowledge a transsexual male as the mother of a child.[2] We do not, however, have to change biology to suit their choices, or to make useless gestures to have them feel included when their inclusion is not relevant to important scientific and medical issues.

Sadly, the NASEM would impose this politico-semanticism upon us while addressing the serious issue whether women of child-bearing age should be included in clinical trials.  At a recent workshop on “Developing a Framework to Address Legal, Ethical, Regulatory, and Policy Issues for Research Specific to Pregnant and Lactating Persons,”[3] the Academies introduced a particularly ugly neologism, “pregnant and lactating persons,” or PLP for short. The workshop reports:

“Approximately 4 million pregnant people in the United States give birth annually, and 70 percent of these individuals take at least one prescription medication during their pregnancy. Yet, pregnant and lactating persons are often excluded from clinical trials, and often have to make treatment decisions without an adequate understanding of the benefits and risks to themselves and their developing fetus or newborn baby. An ad hoc committee of the National Academies of Sciences, Engineering, and Medicine will develop a framework for addressing medicolegal and liability issues when planning or conducting research specific to pregnant and lactating persons.”[4]

The full report from NASEM, with fulsome use of the PLP phrase, is now available.[5]

J.K. Rowling is not the only one who is concerned about the erasure of the female from our discourse. Certainly we can acknowledge that transgenderism is real, without allowing the exception to erase biological facts about reproduction. After all, Guinness’s first pregnant “legal man” could not lactate, as a result of bilateral mastectomies, and thus the “legal man” was not a pregnant person who could lactate. And the pregnant “legal man” had functioning ovaries and uterus, which is not a matter of gender identity, but physiological functioning of biological female sex organs. Furthermore, including transgendered women, or “legal women,” without functional ovaries and uterus, in clinical trials will not answer difficult question about whether experimental therapies may harm women’s reproductive function or their offspring in utero or after birth.

The inclusion of women in clinical trials is a serious issue precisely because experimental therapies may hold risks for participating women’s offspring in utero. The law may not permit a proper informed consent by women for their conceptus. And because of the new latitude legislatures enjoy to impose religion-based bans on abortion, a women who conceives while taking an experimental drug may not be able to terminate her pregnancy that has been irreparably harmed by the drug.

The creation of the PLP category really confuses rather than elucidates how we answer the ethical and medical questions involved in testing new drugs or treatments for women. NASEM’s linguistic gerrymandering may allow some persons who have suffered from gender dysphoria to feel “included,” and perhaps to have their choices “validated,” but the inclusion of transgender women, or partially transgendered men, will not help answer the important questions facing clinical researchers. Taxpayers who fund NASEM and NIH deserve better clarity and judgment in the use of governmental funds in supporting clinical trials.

When and whence comes this PLP neologism?  An N-Gram search shows that “pregnant person” was found in the database before 1975, and that the phrase has waxed and waned since.

N-Gram for pregnant person, conducted September 1, 2023

A search of the National Library of Medicine PubMed database found several dozen hits, virtually all within the last two years. The earliest use was in 1970,[6] with a recrudenscence 11 years later.[7]

                                             

From PubMed search for “pregnant person,” conducted Sept. 1, 2023 

In 2021, the New England Journal of Medicine published a paper on the safety of Covid-19 vaccines in “pregnant persons.”[8] As of last year, the Association of American Medical Colleges sponsored a report about physicians advocating for inclusion of “pregnant people” in clinical trials, in a story that noted that “[p]regnant patients are often excluded from clinical trials for fear of causing harm to them or their babies, but leaders in maternal-fetal medicine say the lack of data can be even more harmful.”[9] And currently, the New York State Department of Health advises that “[d]ue to changes that occur during pregnancy, pregnant people may be more susceptible to viral respiratory infections.”[10]

The neologism of PLP was not always so. Back in the dark ages, 2008, the National Cancer Institute issued guidelines on the inclusion of pregnant and breast-feeding women in clinical trials.[11] As recently as June 2021, The World Health Organization was still old school in discussing “pregnant and lactating women.”[12] The same year, over a dozen female scientists, published a call to action about the inclusion of “pregnant women” in COVID-19 trials.[13]

Two years ago, I gingerly criticized the American Medical Association’s issuance of a linguistic manifesto on how physicians and scientists should use language to advance the Association’s notions of social justice.[14] I criticized the Association’s efforts at the time, but its guide to “correct” usage was devoid of the phrase “pregnant persons” or “lactating persons.”[15] Pregnancy is a function of sex, not of gender.

[1] “Suppose You Call a Sheep’s Tail a Leg, How Many Legs Will the Sheep Have?” QuoteResearch (Nov. 15, 2015).

[2] Sam Dylan More, “The pregnant man – an oxymoron?” 7 J. Gender Studies 319 (1998).

[3] National Academies of Sciences, Engineering, and Medicine, “Research with Pregnant and Lactating Persons: Mitigating Risk and Liability: Proceedings of a Workshop in Brief,” (2023).

[4] NASEM, “Research with Pregnant and Lactating Persons: Mitigating Risk and Liability: Proceedings of a Workshop–in Brief” (2023).

[5] National Academies of Sciences, Engineering, and Medicine, Inclusion of pregnant and lactating persons in clinical trials: Proceedings of a workshop (2023).

[6] W.K. Keller, “The pregnant person,” 68 J. Ky. Med. Ass’n 454 (1970).

[7] Vibiana M. Andrade, “The toxic workplace: Title VII protection for the potentially pregnant person,” 4 Harvard Women’s Law J. 71 (1981).

[8] Tom T. Shimabukuro, Shin Y. Kim, Tanya R. Myers, Pedro L. Moro, Titilope Oduyebo, Lakshmi Panagiotakopoulos, Paige L. Marquez, Christine K. Olson, Ruiling Liu, Karen T. Chang, Sascha R. Ellington, Veronica K. Burkel, et al., for the CDC v-safe COVID-19 Pregnancy Registry Team, “Preliminary Findings of mRNA Covid-19 Vaccine Safety in Pregnant Persons,” 384 New Engl. J. Med. 2273 (2021).

[9] Bridget Balch, “Prescribing without data: Doctors advocate for the inclusion of pregnant people in clinical research,” AAMC (Mar. 22, 2022).

[10] New York State Department of Health, “Pregnancy & COVID-19,” last visited August 31, 2023.

[11] NCI, “Guidelines Regarding the Inclusion of Pregnant and Breast-Feeding Women on Cancer Clinical Treatment Trials,” (May 29, 2008).

[12] WHO, “Update on WHO Interim recommendations on COVID-19 vaccination of pregnant and lactating women,” (June 10, 2021).

[13] Melanie M. Taylor, Loulou Kobeissi, Caron Kim, Avni Amin, Anna E Thorson, Nita B. Bellare, Vanessa Brizuela, Mercedes Bonet, Edna Kara, Soe Soe Thwin, Hamsadvani Kuganantham, Moazzam Ali, Olufemi T. Oladapo, Nathalie Broutet, “Inclusion of pregnant women in COVID-19 treatment trials: a review and global call to action,”9 Health Policy E366 (2021).

[14] American Medical Association, “Advancing Health Equity: A Guide to Language, Narrative and Concepts,” (2021); see Harriet Hall, “The AMA’s Guide to Politically Correct Language: Advancing Health Equity,” Science Based Medicine (Nov. 2, 2021).

[15] “When the American Medical Association Woke Up” (Nov.17, 2021).

Posted in Scientific Evidence, Scientific Publishing | 1 Comment »

Links, Ties, and Other Hook Ups in Risk Factor Epidemiology

July 5th, 2023

Many journalists struggle with reporting the results from risk factor epidemiology. Recently, JAMA Network Open published an epidemiologic study (“Williams study”) that explored whether exposure to Agent Orange among United States military veterans was associated with bladder cancer.[1] The reported study found little to no association, but lay and scientific journalists described the study as finding a “link,”[2] or a “tie,”[3] thus suggesting causality. One web-based media report stated, without qualification, that Agent Orange “increases bladder cancer risk.”[4]

Even the authors of the Williams study described the results inconsistently and hyperbolically. Within the four corners of the published article, the authors described their having found a “modestly increased risk of bladder cancer,” and then, on the same page, they reported that “the association was very slight (hazard ratio, 1.04; 95% C.I.,1.02-1.06).”

In one place, the Williams study states it looked at a cohort of 868,912 veterans with exposure to Agent Orange, and evaluated bladder cancer outcomes against outcomes in 2,427,677 matched controls. Elsewhere, they report different numbers, which are hard to reconcile. In any event, the authors had a very large sample size, which had the power to detect theoretically small differences as “statistically significant” (p < 0.05). Indeed, the study was so large that even a very slight disparity in rates between the exposed and unexposed cohort members could be “statistically significantly” different, notwithstanding that systematic error certainly played a much larger role in the results than random error. In terms of absolute numbers, the researchers found 50,781 bladder cancer diagnoses, on follow-up of 28,672,655 person-years. There were overall 2.1% bladder cancers among the exposed servicemen, and 2.0% among the unexposed. Calling this putative disparity a “modest association” is a gross overstatement, and it is difficult to square the authors’ pronouncement of a “modest association” with a “very slight increased risk.”

The authors also reported that there was no association between Agent Orange exposure and aggressiveness of bladder cancer, with bladder wall muscle invasion taken to be the marker of aggressiveness. Given that the authors were willing to proclaim a hazard ratio of 1.04 as an association, this report of no association with aggressiveness is manifestly false. The Williams study found a decreased odds of a diagnosis of muscle-invasive bladder cancer among the exposed cases, with an odds ratio of 0.91, 95% CI 0.85-0.98 (p = 0.009). The study thus did not find an absence of an association, but rather an inverse association.

Causality

Under the heading of “Meaning,” the authors wrote that “[t]hese findings suggest an association between exposure to Agent Orange and bladder cancer, although the clinical relevance of this was unclear.” Despite disclaiming a causal interpretation of their results, Williams and colleagues wrote that their results “support prior investigations and further support bladder cancer to be designated as an Agent Orange-associated disease.”

Williams and colleagues note that the Institute of Medicine had suggested that the association between Agent Orange exposure and bladder cancer outcomes required further research.[5] Requiring additional research was apparently sufficient for the Department of Veterans Affairs, in 2021, to assume facts not in evidence, and to designate “bladder cancer as a cancer caused by Agent Orange exposure.”[6]

Williams and colleagues themselves appear to disavow a causal interpretation of their results: “we cannot determine causality given the retrospective nature of our study design.” They also acknowledged their inability to “exclude potential selection bias and misclassification bias.” Although the authors did not explore the issue, exposed servicemen may well have been under greater scrutiny, creating surveillance and diagnostic biases.

The authors failed to grapple with other, perhaps more serious biases and inadequacy of methodology in their study. Although the authors claimed to have controlled for the most important confounders, they failed to include diabetes as a co-variate in their analysis, even though diabetic patients have a more than doubled increased risk for bladder cancer, even after adjustment for smoking.[7] Diabetic patients would also have been likely to have had more visits to VA centers for healthcare and more opportunity to have been diagnosed with bladder cancer.

Futhermore, with respect to the known confounding variable of smoking, the authors trichotomized smoking history as “never,” “former,” or “current” smoker. The authors were missing smoking information in about 13% of the cohort. In a univariate analysis based upon smoking status (Table 4), the authors reported the following hazard ratios for bladder cancer, by smoking status:

Smoking status at bladder cancer diagnosis

Never smoked      1   [Reference]

Current smoker   1.10 (1.00-1.21)

Former smoker    1.08 (1.00-1.18)

Unknown              1.17 (1.05-1.31)

This analysis for smoking risk points to the fragility of the Agent Orange analyses. First, the “unknown” smoking status is associated with roughly twice the risk for current or former smokers. Second, the risk ratios for muscle-invasive bladder cancer were understandably higher for current smokers (OR 1.10, 95% CI 1.00-1.21) and former smokers (OR 1.08, 95% CI 1.00-1.18) than for non-smoking veterans.

Third, the Williams’ study’s univariate analysis of smoking and bladder cancer generates risk ratios that are quite out of line with independent studies of smoking and bladder cancer risk. For instance, meta-analyses of studies of smoking and bladder cancer risk report risk ratios of 2.58 (95% C.I., 2.37–2.80) for any smoking, 3.47 (3.07–3.91) for current smoking, and 2.04 (1.85–2.25) for past smoking.[8] These smoking-related bladder cancer risks are thus order(s) of magnitude greater than the univariate analysis of smoking risk in the Williams study, as well as the multivariate analysis of Agent Orange risk reported.

Fourth, the authors engage in the common, but questionable practice of categorizing a known confounder, smoking, which should ideally be reported as a continuous variable with respect to quantity consumed, years smoked, and years since quitting.[9] The question here, given that the study is very large, is not the loss of power,[10] but bias away from the null. Peter Austin has shown, by Monte Carlo simulation, that categorizing a continuous variable in a logistic regression results in inflating the rate of finding false positive associations.[11] The type I (false-positive) error rates increases with sample size, with increasing correlation between the confounding variable and outcome of interest, and the number of categories used for the continuous variables. The large dataset used by Williams and colleagues, which they see as a plus, works against them by increasing the bias from the use of categorical variables for confounding variables.[12]

The Williams study raises serious questions not only about the quality of medical journalism, but also about how an executive agency such as the Veterans Administration evaluates scientific evidence. If the Williams study were to play a role in compensation determinations, it would seem that veterans with muscle-invasive bladder cancer would be turned away, while those veterans with less serious cancers would be compensated. But with 2.1% incidence versus 2.0%, how can compensation be rationally permitted in every case?

[1] Stephen B. Williams, Jessica L. Janes, Lauren E. Howard, Ruixin Yang, Amanda M. De Hoedt, Jacques G. Baillargeon, Yong-Fang Kuo, Douglas S. Tyler, Martha K. Terris, Stephen J. Freedland, “Exposure to Agent Orange and Risk of Bladder Cancer Among US Veterans,” 6 JAMA Network Open e2320593 (2023).

[2] Elana Gotkine, “Exposure to Agent Orange Linked to Risk of Bladder Cancer,” Buffalo News (June 28, 2023); Drew Amorosi, “Agent Orange exposure linked to increased risk for bladder cancer among Vietnam veterans,” HemOnc Today (June 27, 2023).

[3] Andrea S. Blevins Primeau, “Agent Orange Exposure Tied to Increased Risk of Bladder Cancer,” Cancer Therapy Advisor (June 30, 2023); Mike Bassett, “Agent Orange Exposure Tied to Bladder Cancer Risk in Veterans — Increased risk described as ‘modest’, and no association seen with aggressiveness of cancer,” Medpage Today (June 27, 2023).

[4] Darlene Dobkowski, “Agent Orange Exposure Modestly Increases Bladder Cancer Risk in Vietnam Veterans,” Cure Today (June 27, 2023).

[5] Institute of Medicine – Committee to Review the Health Effects in Vietnam Veterans of Exposure to Herbicides (Tenth Biennial Update), Veterans and Agent Orange: Update 2014 at 10 (2016) (upgrading previous finding of “inadequate” to “suggestive”).

[6] Williams study, citing U.S. Department of Veterans Affairs, “Agent Orange exposure and VA disability compensation.”

[7] Yeung Ng, I. Husain, N. Waterfall, “Diabetes Mellitus and Bladder Cancer – An Epidemiological Relationship?” 9 Path. Oncol. Research 30 (2003) (diabetic patients had an increased, significant odds ratio for bladder cancer compared with non diabetics even after adjustment for smoking and age [OR: 2.69 p=0.049 (95% CI 1.006-7.194)]).

[8] Marcus G. Cumberbatch, Matteo Rota, James W.F. Catto, and Carlo La Vecchia, “The Role of Tobacco Smoke in Bladder and Kidney Carcinogenesis: A Comparison of Exposures and Meta-analysis of Incidence and Mortality Risks?” 70 European Urology 458 (2016).

[9] See generally, “Confounded by Confounding in Unexpected Places” (Dec. 12, 2021).

[10] Jacob Cohen, “The cost of dichotomization,” 7 Applied Psychol. Measurement 249 (1983).

[11] Peter C. Austin & Lawrence J. Brunner, “Inflation of the type I error rate when a continuous confounding variable is categorized in logistic regression analyses,” 23 Statist. Med. 1159 (2004).

[12] See, e.g., Douglas G. Altman & Patrick Royston, “The cost of dichotomising continuous variables,” 332 Brit. Med. J. 1080 (2006); Patrick Royston, Douglas G. Altman, and Willi Sauerbrei, “Dichotomizing continuous predictors in multiple regression: a bad idea,” 25 Stat. Med. 127 (2006); Valerii Fedorov, Frank Mannino, and Rongmei Zhang, “Consequences of dichotomization,” 8 Pharmaceut. Statist. 50 (2009). See also Robert C. MacCallum, Shaobo Zhang, Kristopher J. Preacher, and Derek D. Rucker, “On the Practice of Dichotomization of Quantitative Variables,” 7 Psychological Methods 19 (2002); David L. Streiner, “Breaking Up is Hard to Do: The Heartbreak of Dichotomizing Continuous Data,” 47 Can. J. Psychiatry 262 (2002); Henian Chen, Patricia Cohen, and Sophie Chen, “Biased odds ratios from dichotomization of age,” 26 Statist. Med. 3487 (2007); Carl van Walraven & Robert G. Hart, “Leave ‘em Alone – Why Continuous Variables Should Be Analyzed as Such,” 30 Neuroepidemiology 138 (2008); O. Naggara, J. Raymond, F. Guilbert, D. Roy, A. Weill, and Douglas G. Altman, “Analysis by Categorizing or Dichotomizing Continuous Variables Is Inadvisable,” 32 Am. J. Neuroradiol. 437 (Mar 2011); Neal V. Dawson & Robert Weiss, “Dichotomizing Continuous Variables in Statistical Analysis: A Practice to Avoid,” Med. Decision Making 225 (2012); Phillippa M. Cumberland, Gabriela Czanner, Catey Bunce, Caroline J. Doré, Nick Freemantle, and Marta García-Fiñana, “Ophthalmic statistics note: the perils of dichotomising continuous variables,” 98 Brit. J. Ophthalmol. 841 (2014); Julie R. Irwin & Gary H. McClelland, “Negative Consequences of Dichotomizing Continuous Predictor Variables,” 40 J. Marketing Research 366 (2003); Stanley E. Lazic, “Four simple ways to increase power without increasing the sample size,” PeerJ Preprints (23 Oct 2017).

Posted in Confounding, Peer Review, Scientific Evidence, Scientific Publishing | No Comments »

Judicial Flotsam & Jetsam – Retractions

June 12th, 2023

In scientific publishing, when scientists make a mistake, they publish an erratum or a corrigendum. If the mistake vitiates the study, then the erring scientists retract their article. To be sure, sometimes the retraction comes after an obscene delay, with the authors kicking and screaming.[1] Sometimes the retraction comes at the request of the authors, better late than never.[2]

Retractions in the biomedical journals, whether voluntary or not, are on the rise.[3] The process and procedures for retraction of articles often lack transparency. Many articles are retracted without explanation or disclosure of specific problems about the data or the analysis.[4] Sadly, however, misconduct in the form of plagiarism and data falsification is a frequent reason for retractions.[5] The lack of transparency for retractions, and sloppy scholarship, combine to create Zombie papers, which are retracted but continue to be cited in subsequent publications.[6]

LEGAL RETRACTIONS

The law treats errors very differently. Being a judge usually means that you never have to say you are sorry. Judge Andrew Hurwitz has argued that that our legal system would be better served if judges could and did “freely acknowledged and transparently corrected the occasional ‘goof’.”[7] Alas, as Judge Hurwitz notes, very few published decisions acknowledge mistakes.[8]

In the world of scientific jurisprudence, the judicial reticence to acknowledge mistakes is particularly dangerous, and it leads directly to the proliferation of citations to cases that make egregious mistakes. In the niche area of judicial assessment of scientific and statistical evidence, the proliferation of erroneous statements is especially harmful because it interferes with thinking clearly about the issues before courts. Judges believe that they have argued persuasively for a result, not by correctly marshaling statistical and scientific concepts, but by relying upon precedents erroneously arrived at by other judges in earlier cases. Regardless of how many cases are cited (and there are many possible “precedents”), the true parameter does not have a 95% probability of lying within the interval given by a given 95% confidence interval.[9] Similarly, as much as judges would like p-values and confidence intervals to eliminate the need to worry about systematic error, their saying so cannot make it so.[10] Even a mighty federal judge cannot make the p-value probability, or its complement, substitute for the posterior probability of a causal claim.[11]

Some cases in the books are so egregiously decided that it is truly remarkable that they would be cited for any proposition. I call these scientific Dred Scott cases, which illustrate that sometimes science has no criteria of validity that the law is bound to respect. One such Dred Scott case was the result of a bench trial in a federal district court in Atlanta, in Wells v. Ortho Pharmaceutical Corporation.[12]

Wells was notorious for its poor assessment of all the determinants of scientific causation.[13] The decision was met with a storm of opprobrium from the legal and medical community.[14] No scientists or legal scholars offered a serious defense of Wells on the scientific merits. Even the notorious plaintiffs’ expert witness, Carl Cranor, could muster only a distanced agnosticism:

“In Wells v. Ortho Pharmaceutical Corp., which involved a claim that birth defects were caused by a spermicidal jelly, the U.S. Court of Appeals for the 11th Circuit followed the principles of Ferebee and affirmed a plaintiff’s verdict for about five million dollars. However, some members of the medical community chastised the legal system essentially for ignoring a well-established scientific consensus that spermicides are not teratogenic. We are not in a position to judge this particular issue, but the possibility of such results exists.”[15]

Cranor apparently could not bring himself to note that it was not just scientific consensus that was ignored; the Wells case ignored the basic scientific process of examining relevant studies for both internal and external validity.

Notwithstanding this scholarly consensus and condemnation, we have witnessed the repeated recrudescence of the Wells decision. In Matrixx Initiatives, Inc. v. Siracusano,[16] in 2011, the Supreme Court, speaking through Justice Sotomayor, wandered into a discussion, irrelevant to its holding, whether statistical significance was necessary for a determination of the causality of an association:

“We note that courts frequently permit expert testimony on causation based on evidence other than statistical significance. See, e.g., Best v. Lowe’s Home Centers, Inc., 563 F. 3d 171, 178 (6th Cir 2009); Westberry v. Gislaved Gummi AB, 178 F. 3d 257, 263–264 (4th Cir. 1999) (citing cases); Wells v. Ortho Pharmaceutical Corp., 788 F. 2d 741, 744–745 (11th Cir. 1986). We need not consider whether the expert testimony was properly admitted in those cases, and we do not attempt to define here what constitutes reliable evidence of causation.”[17]

The quoted language is remarkable for two reasons. First, the Best and Westberry cases did not involve statistics at all. They addressed specific causation inferences from what is generally known as differential etiology. Second, the citation to Wells was noteworthy because the case has nothing to do with adverse event reports or the lack of statistical significance.

Wells involved a claim of birth defects caused by the use of spermicidal jelly contraceptive, which had been the subject of several studies, one of which at least yielded a nominally statistically significant increase in detected birth defects over what was expected.

Wells could thus hardly be an example of a case in which there was a judgment of causation based upon a scientific study that lacked statistical significance in its findings. Of course, finding statistical significance is just the beginning of assessing the causality of an association. The most remarkable and disturbing aspect of the citation to Wells, however, was that the Court was unaware of, or ignored, the case’s notoriety, and the scholarly and scientific consensus that criticized the decision for its failure to evaluate the entire evidentiary display, as well as for its failure to rule out bias and confounding in the studies relied upon by the plaintiff.

Justice Sotomayor’s decision for a unanimous Court is not alone in its failure of scholarship and analysis in embracing the dubious precedent of Wells. Many other courts have done much the same, both in state[18] and in federal courts,[19] and both before and after the Supreme Court decided Daubert, and even after Rule 702 was amended in 2000.[20] Perhaps even more disturbing is that the current edition of the Reference Manual on Scientific Evidence glibly cites to the Wells case, for the dubious proposition that

“Generally, researchers are conservative when it comes to assessing causal relationships, often calling for stronger evidence and more research before a conclusion of causation is drawn.”[21]

We are coming up on the 40th anniversary of the Wells judgment. It is long past time to stop citing the case. Perhaps we have reached the stage of dealing with scientific evidence at which errant and aberrant cases should be retracted, and clearly marked as retracted in the official reporters, and in the electronic legal databases. Certainly the technology exists to link the scholarly criticism with a case citation, just as we link subsequent judicial treatment by overruling, limiting, and criticizing.

[1] Laura Eggertson, “Lancet retracts 12-year-old article linking autism to MMR vaccines,” 182 Canadian Med. Ass’n J. E199 (2010).

[2] Notice of retraction for Teng Zeng & William Mitch, “Oral intake of ranitidine increases urinary excretion of N-nitrosodimethylamine,” 37 Carcinogenesis 625 (2016), published online (May 4, 2021) (retraction requested by authors with an acknowledgement that they had used incorrect analytical methods for their study).

[3] Tianwei He, “Retraction of global scientific publications from 2001 to 2010,” 96 Scientometrics 555 (2013); Bhumika Bhatt, “A multi-perspective analysis of retractions in life sciences,” 126 Scientometrics 4039 (2021); Raoul R.Wadhwa, Chandruganesh Rasendran, Zoran B. Popovic, Steven E. Nissen, and Milind Y. Desai, “Temporal Trends, Characteristics, and Citations of Retracted Articles in Cardiovascular Medicine,” 4 JAMA Network Open e2118263 (2021); Mario Gaudino, N. Bryce Robinson, Katia Audisio, Mohamed Rahouma, Umberto Benedetto, Paul Kurlansky, Stephen E. Fremes, “Trends and Characteristics of Retracted Articles in the Biomedical Literature, 1971 to 2020,” 181 J. Am. Med. Ass’n Internal Med. 1118 (2021); Nicole Shu Ling Yeo-Teh & Bor Luen Tang, “Sustained Rise in Retractions in the Life Sciences Literature during the Pandemic Years 2020 and 2021,” 10 Publications 29 (2022).

[4] Elizabeth Wager & Peter Williams, “Why and how do journals retract articles? An analysis of Medline retractions 1988-2008,” 37 J. Med. Ethics 567 (2011).

[5] Ferric C. Fanga, R. Grant Steen, and Arturo Casadevall, “Misconduct accounts for the majority of retracted scientific publications,” 109 Proc. Nat’l Acad. Sci. 17028 (2012); L.M. Chambers, C.M. Michener, and T. Falcone, “Plagiarism and data falsification are the most common reasons for retracted publications in obstetrics and gynaecology,” 126 Br. J. Obstetrics & Gyn. 1134 (2019); M.S. Marsh, “Separating the good guys and gals from the bad,” 126 Br. J. Obstetrics & Gyn. 1140 (2019).

[6] Tzu-Kun Hsiao and Jodi Schneider, “Continued use of retracted papers: Temporal trends in citations and (lack of) awareness of retractions shown in citation contexts in biomedicine,” 2 Quantitative Science Studies 1144 (2021).

[7] Andrew D. Hurwitz, “When Judges Err: Is Confession Good for the Soul?” 56 Ariz. L. Rev. 343, 343 (2014).

[8] See id. at 343-44 (quoting Justice Story who dealt with the need to contradict a previously published opinion, and who wrote “[m]y own error, however, can furnish no ground for its being adopted by this Court.” U.S. v. Gooding, 25 U.S. 460, 478 (1827)).

[9] See, e.g., DeLuca v. Merrell Dow Pharms., Inc., 791 F. Supp. 1042, 1046 (D.N.J. 1992) (”A 95% confidence interval means that there is a 95% probability that the ‘true’ relative risk falls within the interval”) , aff’d, 6 F.3d 778 (3d Cir. 1993); In re Silicone Gel Breast Implants Prods. Liab. Litig, 318 F.Supp.2d 879, 897 (C.D. Cal. 2004); 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”). See also “Confidence in Intervals and Diffidence in the Courts” (Mar. 4, 2012).

[10] See, e.g., Brock v. Merrill Dow Pharmaceuticals, Inc., 874 F.2d 307, 311-12 (5th Cir. 1989) (“Fortunately, we do not have to resolve any of the above questions [as to bias and confounding], since the studies presented to us incorporate the possibility of these factors by the use of a confidence interval.”). This howler has been widely acknowledged in the scholarly literature. See David Kaye, David Bernstein, and Jennifer Mnookin, The New Wigmore – A Treatise on Evidence: Expert Evidence § 12.6.4, at 546 (2d ed. 2011); Michael O. Finkelstein, Basic Concepts of Probability and Statistics in the Law 86-87 (2009) (criticizing the blatantly incorrect interpretation of confidence intervals by the Brock court).

[11] In re Ephedra Prods. Liab. Litig., 393 F.Supp. 2d 181, 191 (S.D.N.Y. 2005) (Rakoff, J.) (“Generally accepted scientific convention treats a result as statistically significant if the P-value is not greater than .05. The expression ‘P=.05’ means that there is one chance in twenty that a result showing increased risk was caused by a sampling error — i.e., that the randomly selected sample accidentally turned out to be so unrepresentative that it falsely indicates an elevated risk.”); see also In re Phenylpropanolamine (PPA) Prods. Liab. Litig., 289 F.Supp. 2d 1230, 1236 n.1 (W.D. Wash. 2003) (“P-values measure the probability that the reported association was due to chance… .”). Although the erroneous Ephedra opinion continues to be cited, it has been debunked in the scholarly literature. See Michael O. Finkelstein, Basic Concepts of Probability and Statistics in the Law 65 (2009); Nathan A. Schachtman, “Statistical Evidence in Products Liability Litigation,” at 28-13, chap. 28, in Stephanie A. Scharf, George D. Sax, & Sarah R. Marmor, eds., Product Liability Litigation: Current Law, Strategies and Best Practices (2d ed. 2021).

[12] Wells v. Ortho Pharm. Corp., 615 F. Supp. 262 (N.D. Ga.1985), aff’d & modified in part, remanded, 788 F.2d 741 (11th Cir.), cert. denied, 479 U.S. 950 (1986).

[13] I have discussed the Wells case in a series of posts, “Wells v. Ortho Pharm. Corp., Reconsidered,” (2012), part one, two, three, four, five, and six.

[14] See, e.g., James L. Mills and Duane Alexander, “Teratogens and ‘Litogens’,” 15 New Engl. J. Med. 1234 (1986); Samuel R. Gross, “Expert Evidence,” 1991 Wis. L. Rev. 1113, 1121-24 (1991) (“Unfortunately, Judge Shoob’s decision is absolutely wrong. There is no scientifically credible evidence that Ortho-Gynol Contraceptive Jelly ever causes birth defects.”). See also Editorial, “Federal Judges v. Science,” N.Y. Times, December 27, 1986, at A22 (unsigned editorial) (“That Judge Shoob and the appellate judges ignored the best scientific evidence is an intellectual embarrassment.”);  David E. Bernstein, “Junk Science in the Courtroom,” Wall St. J. at A 15 (Mar. 24,1993) (pointing to Wells as a prominent example of how the federal judiciary had embarrassed American judicial system with its careless, non-evidence based approach to scientific evidence); Bert Black, Francisco J. Ayala & Carol Saffran-Brinks, “Science and the Law in the Wake of Daubert: A New Search for Scientific Knowledge,” 72 Texas L. Rev. 715, 733-34 (1994) (lawyers and leading scientist noting that the district judge “found that the scientific studies relied upon by the plaintiffs’ expert were inconclusive, but nonetheless held his testimony sufficient to support a plaintiffs’ verdict. *** [T]he court explicitly based its decision on the demeanor, tone, motives, biases, and interests that might have influenced each expert’s opinion. Scientific validity apparently did not matter at all.”) (internal citations omitted); Bert Black, “A Unified Theory of Scientific Evidence,” 56 Fordham L. Rev. 595, 672-74 (1988); Paul F. Strain & Bert Black, “Dare We Trust the Jury – No,” 18 Brief  7 (1988); Bert Black, “Evolving Legal Standards for the Admissibility of Scientific Evidence,” 239 Science 1508, 1511 (1988); Diana K. Sheiness, “Out of the Twilight Zone: The Implications of Daubert v. Merrill Dow Pharmaceuticals, Inc.,” 69 Wash. L. Rev. 481, 493 (1994); David E. Bernstein, “The Admissibility of Scientific Evidence after Daubert v. Merrell Dow Pharmacueticals, Inc.,” 15 Cardozo L. Rev. 2139, 2140 (1993) (embarrassing decision); Troyen A. Brennan, “Untangling Causation Issues in Law and Medicine: Hazardous Substance Litigation,” 107 Ann. Intern. Med. 741, 744-45 (1987) (describing the result in Wells as arising from the difficulties created by the Ferebee case; “[t]he Wells case can be characterized as the court embracing the hypothesis when the epidemiologic study fails to show any effect”); Troyen A. Brennan, “Causal Chains and Statistical Links: Some Thoughts on the Role of Scientific Uncertainty in Hazardous Substance Litigation,” 73 Cornell L. Rev. 469, 496-500 (1988); David B. Brushwood, “Drug induced birth defects: difficult decisions and shared responsibilities,” 91 W. Va. L. Rev. 51, 74 (1988); Kenneth R. Foster, David E. Bernstein, and Peter W. Huber, eds., Phantom Risk: Scientific Inference and the Law 28-29, 138-39 (1993) (criticizing Wells decision); Peter Huber, “Medical Experts and the Ghost of Galileo,” 54 Law & Contemp. Problems 119, 158 (1991); Edward W. Kirsch, “Daubert v. Merrell Dow Pharmaceuticals: Active Judicial Scrutiny of Scientific Evidence,” 50 Food & Drug L.J. 213 (1995) (“a case in which a court completely ignored the overwhelming consensus of the scientific community”); Hans Zeisel & David Kaye, Prove It With Figures: Empirical Methods in Law and Litigation § 6.5, at 93(1997) (noting the multiple comparisons in studies of birth defects among women who used spermicides, based upon the many reported categories of birth malformations, and the large potential for even more unreported categories); id. at § 6.5 n.3, at 271 (characterizing Wells as “notorious,” and noting that the case became a “lightning rod for the legal system’s ability to handle expert evidence.”); Edward K. Cheng , “Independent Judicial Research in the ‘Daubert’ Age,” 56 Duke L. J. 1263 (2007) (“notoriously concluded”); Edward K. Cheng, “Same Old, Same Old: Scientific Evidence Past and Present,” 104 Michigan L. Rev. 1387, 1391 (2006) (“judge was fooled”); Harold P. Green, “The Law-Science Interface in Public Policy Decisionmaking,” 51 Ohio St. L.J. 375, 390 (1990); Stephen L. Isaacs & Renee Holt, “Drug regulation, product liability, and the contraceptive crunch: Choices are dwindling,” 8 J. Legal Med. 533 (1987); Neil Vidmar & Shari S. Diamond, “Juries and Expert Evidence,” 66 Brook. L. Rev. 1121, 1169-1170 (2001); Adil E. Shamoo, “Scientific evidence and the judicial system,” 4 Accountability in Research 21, 27 (1995); Michael S. Davidson, “The limitations of scientific testimony in chronic disease litigation,” 10 J. Am. Coll. Toxicol. 431, 435 (1991); Charles R. Nesson & Yochai Benkler, “Constitutional Hearsay: Requiring Foundational Testing and Corroboration under the Confrontation Clause,” 81 Virginia L. Rev. 149, 155 (1995); Stephen D. Sugarman, “The Need to Reform Personal Injury Law Leaving Scientific Disputes to Scientists,” 248 Science 823, 824 (1990); Jay P. Kesan, “A Critical Examination of the Post-Daubert Scientific Evidence Landscape,” 52 Food & Drug L. J. 225, 225 (1997); Ora Fred Harris, Jr., “Communicating the Hazards of Toxic Substance Exposure,” 39 J. Legal Ed. 97, 99 (1989) (“some seemingly horrendous decisions”); Ora Fred Harris, Jr., “Complex Product Design Litigation: A Need for More Capable Fact-Finders,” 79 Kentucky L. J. 510 & n.194 (1991) (“uninformed judicial decision”); Barry L. Shapiro & Marc S. Klein, “Epidemiology in the Courtroom: Anatomy of an Intellectual Embarrassment,” in Stanley A. Edlavitch, ed., Pharmacoepidemiology 87 (1989); Marc S. Klein, “Expert Testimony in Pharmaceutical Product Liability Actions,” 45 Food, Drug, Cosmetic L. J. 393, 410 (1990); Michael S. Lehv, “Medical Product Liability,” Ch. 39, in Sandy M. Sanbar & Marvin H. Firestone, eds., Legal Medicine 397, 397 (7th ed. 2007); R. Ryan Stoll, “A Question of Competence – Judicial Role in Regulation of Pharmaceuticals,” 45 Food, Drug, Cosmetic L. J. 279, 287 (1990); Note, “A Question of Competence: The Judicial Role in the Regulation of Pharmaceuticals,” Harvard L. Rev. 773, 781 (1990); Peter H. Schuck, “Multi-Culturalism Redux: Science, Law, and Politics,” 11 Yale L. & Policy Rev. 1, 13 (1993); Howard A. Denemark, “Improving Litigation Against Drug Manufacturers for Failure to Warn Against Possible Side  Effects: Keeping Dubious Lawsuits from Driving Good Drugs off the Market,” 40 Case Western Reserve L.  Rev. 413, 438-50 (1989-90); Howard A. Denemark, “The Search for Scientific Knowledge in Federal Courts in the Post-Frye Era: Refuting the Assertion that Law Seeks Justice While Science Seeks Truth,” 8 High Technology L. J. 235 (1993)

[15] Carl Cranor & Kurt Nutting, “Scientific and Legal Standards of Statistical Evidence in Toxic Tort and Discrimination Suits,” 9 Law & Philosophy 115, 123 (1990) (internal citations omitted).

[16] 131 S.Ct. 1309 (2011) [Matrixx]

[17] Id. at 1319.

[18] Baroldy v. Ortho Pharmaceutical Corp., 157 Ariz. 574, 583, 760 P.2d 574 (Ct. App. 1988); Earl v. Cryovac, A Div. of WR Grace, 115 Idaho 1087, 772 P. 2d 725, 733 (Ct. App. 1989); Rubanick v. Witco Chemical Corp., 242 N.J. Super. 36, 54, 576 A. 2d 4 (App. Div. 1990), aff’d in part, 125 N.J. 421, 442, 593 A. 2d 733 (1991); Minnesota Min. & Mfg. Co. v. Atterbury, 978 S.W. 2d 183, 193 n.7 (Tex. App. 1998); E.I. Dupont de Nemours v. Castillo ex rel. Castillo, 748 So. 2d 1108, 1120 (Fla. Dist. Ct. App. 2000); Bell v. Lollar, 791 N.E.2d 849, 854 (Ind. App. 2003; King v. Burlington Northern & Santa Fe Ry, 277 Neb. 203, 762 N.W.2d 24, 35 & n.16 (2009).

[19] City of Greenville v. WR Grace & Co., 827 F. 2d 975, 984 (4th Cir. 1987); American Home Products Corp. v. Johnson & Johnson, 672 F. Supp. 135, 142 (S.D.N.Y. 1987); Longmore v. Merrell Dow Pharms., Inc., 737 F. Supp. 1117, 1119 (D. Idaho 1990); Conde v. Velsicol Chemical Corp., 804 F. Supp. 972, 1019 (S.D. Ohio 1992); Joiner v. General Elec. Co., 864 F. Supp. 1310, 1322 (N.D. Ga. 1994) (which case ultimately ended up in the Supreme Court); Bowers v. Northern Telecom, Inc., 905 F. Supp. 1004, 1010 (N.D. Fla. 1995); Pick v. American Medical Systems, 958 F. Supp. 1151, 1158 (E.D. La. 1997); Baker v. Danek Medical, 35 F. Supp. 2d 875, 880 (N.D. Fla. 1998).

[20] Rider v. Sandoz Pharms. Corp., 295 F. 3d 1194, 1199 (11th Cir. 2002); Kilpatrick v. Breg, Inc., 613 F. 3d 1329, 1337 (11th Cir. 2010); Siharath v. Sandoz Pharms. Corp., 131 F. Supp. 2d 1347, 1359 (N.D. Ga. 2001); In re Meridia Prods. Liab. Litig., Case No. 5:02-CV-8000 (N.D. Ohio 2004); Henricksen v. ConocoPhillips Co., 605 F. Supp. 2d 1142, 1177 (E.D. Wash. 2009); Doe v. Northwestern Mutual Life Ins. Co., (D. S.C. 2012); In re Chantix (Varenicline) Prods. Liab. Litig., 889 F. Supp. 2d 1272, 1286, 1288, 1290 (N.D. Ala. 2012); Farmer v. Air & Liquid Systems Corp. at n.11 (M.D. Ga. 2018); In re Abilify Prods. Liab. Litig., 299 F. Supp. 3d 1291, 1306 (N.D. Fla. 2018).

[21] Michael D. Green, D. Michal Freedman & Leon Gordis, “Reference Guide on Epidemiology,” 549, 599 n.143, in Federal Judicial Center, National Research Council, Reference Manual on Scientific Evidence (3d ed. 2011).

Posted in Confounding, Reference Manual on Scientific Evidence, Rule 702, Scientific Evidence, Scientific Misconduct, Scientific Publishing | 2 Comments »

Mass Tortogenesis

January 22nd, 2023

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

INITIATION

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

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

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

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

“Abstract

Background

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

Methods

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

Results

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

Conclusion

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

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

PROMOTION OF INITIATED MASS TORTS

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

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

“From:  ZZZ

To:  YYYYYYYYY

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

Hi,

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

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

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

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

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

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

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

Are you looking to help victims in this case

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

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

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

Thank you,

ZZZ”

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

“Proof”!

As in quod erat demonstrandum.

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

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

chorizo sausage links (courtesy of Wikipedia)[8]

And so it goes.

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

SYSTEMIC FAILURES TO PREVENT MASS TORTOGENESIS

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

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

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

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

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

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

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

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

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

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

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

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

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

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

The Rise of Agnothology as Conspiracy Theory

July 19th, 2022

A few egregious articles in the biomedical literature have begun to endorse explicitly asymmetrical standards for inferring causation in the context of environmental or occupational exposures. Very little if anything is needed for inferring causation, and nothing counts against causation.  If authors refuse to infer causation, then they are agents of “industry,” epidemiologic malfeasors, and doubt mongers.

For an example of this genre, take the recent article, entitled “Toolkit for detecting misused epidemiological methods.”[1] [Toolkit] Please.

The asymmetry begins with Trump-like projection of the authors’ own foibles. The principal hammer in the authors’ toolkit for detecting misused epidemiologic methods is personal, financial bias. And yet, somehow, in an article that calls out other scientists for having received money from “industry,” the authors overlooked the business of disclosing their receipt of monies from one of the biggest industries around – the lawsuit industry.

Under the heading “competing interests,” the authors state that “they have no competing interests.”[2]  Lead author, Colin L. Soskolne, was, however, an active, partisan expert witness for plaintiffs’ counsel in diacetyl litigation.[3] In an asbestos case before the Pennsylvania Supreme Court, Rost v. Ford Motor Co., Soskolne signed on to an amicus brief, supporting the plaintiff, using his science credentials, without disclosing his expert witness work for plaintiffs, or his long-standing anti-asbestos advocacy.[4]

Author Shira Kramer signed on to Toolkit, without disclosing any conflicts, but with an even more impressive résumé of pro-plaintiff litigation experience.[5] Kramer is the owner of Epidemiology International, in Cockeysville, Maryland, where she services the lawsuit industry. She too was an “amicus” in Rost, without disclosing her extensive plaintiff-side litigation consulting and testifying.

Carl Cranor, another author of Toolkit, takes first place for hypocrisy on conflicts of interest. As a founder of Council for Education and Research on Toxics (CERT), he has sterling credentials for monetizing the bounty hunt against “carcinogens,” most recently against coffee.[6] He has testified in denture cream and benzene litigation, for plaintiffs. When he was excluded under Rule 702 from the Milward case, CERT filed an amicus brief on his behalf, without disclosing that Cranor was a founder of that organization.[7], [8]

The title seems reasonably fair-minded but the virulent bias of the authors is soon revealed. The Toolkit is presented as a Table in the middle of the article, but the actual “tools” are for the most part not seriously discussed, other than advice to “follow the money” to identify financial conflicts of interest.

The authors acknowledge that epidemiology provides critical knowledge of risk factors and causation of disease, but they quickly transition to an effort to silence any industry commentator on any specific epidemiologic issue. As we will see, the lawsuit industry is given a complete pass. Not surprisingly, several of the authors (Kramer, Cranor, Soskolne) have worked closely in tandem with the lawsuit industry, and have derived financial rewards for their efforts.

Repeatedly, the authors tell us that epidemiologic methods and language are misused by “powerful interests,” which have financial stakes in the outcome of research. Agents of these interests foment uncertainty and doubt about causal relationships through “disinformation,” “malfeasance,” and “doubt mongering.” There is no correlative concern about false claiming or claim mongering..

Who are these agents who plot to sabotage “social justice” and “truth”? Clearly, they are scientists with whom the Toolkit authors disagree. The Toolkit gang cites several papers as exemplifying “malfeasance,”[9] but they never explain what was wrong with them, or how the malfeasors went astray.  The Toolkit tactics seem worthy of Twitter smear and run.

The Toolkit

The authors’ chart of “tools” used by industry might have been an interesting taxonomy of error, but mostly they are ad hominem attack on scientists with whom they disagree. Channeling Putin on Ukraine, those scientists who would impose discipline and rigor on epidemiologic science are derided as not “real epidemiologists,” and, to boot, they are guilty of ethical lapses in failing to advance “social justice.”

Mostly the authors give us a toolkit for silencing those who would get in the way of the situational science deployed at the beck and call of the lawsuit industry.[10] Indeed, the Toolkit authors are not shy about identifying their litigation goals; they tell us that the toolkit can be deployed in depositions and in cross-examinations to pursue “social justice.” These authors also outline a social agenda that greatly resembles the goals of cancel culture: expose the perpetrators who stand in the way of the authors’preferred policy choices, diminish their adversaries’ their influence on journals, and galvanize peer reviewers to reject their adversaries’ scientific publications. The Toolkit authors tell us that “[t] he scientific community should engage by recognizing and professionally calling out common practices used to distort and misapply epidemiological and other health-related sciences.”[11] What this advice translates into are covert and open ad hominem campaigns as peer reviewers to block publications, to deny adversaries tenure and promotions, and to use social and other media outlets to attack adversaries’ motives, good faith, and competence.

None of this is really new. Twenty-five years ago, the late F. Douglas K. Liddell railed at the Mt. Sinai mob, and the phenomenon was hardly new then.[12] The Toolkit’s call to arms is, however, quite open, and raises the question whether its authors and adherents can be fair journal editors and peer reviewers of journal submissions.

Much of the Toolkit is the implementation of a strategy developed by lawsuit industry expert witnesses to demonize their adversaries by accusing them of manufacturing doubt or ignorance or uncertainty. This strategy has gained a label used to deride those who disagree with litigation overclaiming: agnotology or the creation of ignorance. According to Professor Robert Proctor, a regular testifying historian for tobacco plaintiffs, a linguist, Iain Boal, coined the term agnotology, in 1992, to describe the study of the production of ignorance.[13]

The Rise of “Agnotology” in Ngram

Agnotology has become a cottage sub-industry of the lawsuit industry, although lawsuits (or claim mongering if you like), of course, remain their main product. Naomi Oreskes[14] and David Michaels[15] gave the agnotology field greater visibility with their publications, using the less erudite but catchier phrase “manufacturing doubt.” Although the study of ignorance and uncertainty has a legitimate role in epistemology[16] and sociology,[17] much of the current literature is dominated by those who use agnotology as propaganda in support of their own litigation and regulatory agendas.[18] One lone author, however, appears to have taken agnotology study seriously enough to see that it is largely a conspiracy theory that reduces complex historical or scientific theory, evidence, opinion, and conclusions to a clash between truth and a demonic ideology.[19]

Is there any substance to the Toolkit?

The Toolkit is not entirely empty of substantive issues. The authors note that “statistical methods are a critical component of the epidemiologist’s toolkit,”[20] and they cite some articles about common statistical mistakes missed by peer reviewers. Curiously, the Toolkit omits any meaningful discussion of statistical mistakes that increase the risk of false positive results, such as multiple comparisons or dichotomizing continuous confounder variables. As for the Toolkit’s number one identified “inappropriate” technique used by its authors’ adversaries, we have:

“A1. Relying on statistical hypothesis testing; Using ‘statistical significance’ at the 0.05 level of probability as a strict decision criterion to determine the interpretation of statistical results and drawing conclusions.”

Peer into the hearings of any federal court so-called Daubert motion, and you will see the lawsuit industry, and its hired expert witnesses, rail at statistical significance, unless of course, there is some subgroup that has nominal significance, in which case, they are all in for endorsing the finding as “conclusive.” 

Welcome to asymmetric, situational science.

[1] Colin L. Soskolne, Shira Kramer, Juan Pablo Ramos-Bonilla, Daniele Mandrioli, Jennifer Sass, Michael Gochfeld, Carl F. Cranor, Shailesh Advani & Lisa A. Bero, “Toolkit for detecting misused epidemiological methods,” 20(90) Envt’l Health (2021) [Toolkit].

[2] Toolkit at 12.

[3] Watson v. Dillon Co., 797 F.Supp. 2d 1138 (D. Colo. 2011).

[4] Rost v. Ford Motor Co., 151 A.3d 1032 (Pa. 2016). See “The Amicus Curious Brief” (Jan. 4, 2018).

[5] See, e.g., Sean v. BMW of North Am., LLC, 26 N.Y.3d 801, 48 N.E.3d 937, 28 N.Y.S.3d 656 (2016) (affirming exclusion of Kramer); The Little Hocking Water Ass’n v. E.I. Du Pont De Nemours & Co., 90 F.Supp.3d 746 (S.D. Ohio 2015) (excluding Kramer); Luther v. John W. Stone Oil Distributor, LLC, No. 14-30891 (5th Cir. April 30, 2015) (mentioning Kramer as litigation consultant); Clair v. Monsanto Co., 412 S.W.3d 295 (Mo. Ct. App. 2013 (mentioning Kramer as plaintiffs’ expert witness); In re Chantix (Varenicline) Prods. Liab. Litig., No. 2:09-CV-2039-IPJ, MDL No. 2092, 2012 WL 3871562 (N.D.Ala. 2012) (excluding Kramer’s opinions in part); Frischhertz v. SmithKline Beecham Corp., 2012 U.S. Dist. LEXIS 181507, Civ. No. 10-2125 (E.D. La. Dec. 21, 2012) (excluding Kramer); Donaldson v. Central Illinois Public Service Co., 199 Ill. 2d 63, 767 N.E.2d 314 (2002) (affirming admissibility of Kramer’s opinions in absence of Rule 702 standards).

[6]  “The Council for Education & Research on Toxics” (July 9, 2013) (CERT amicus brief filed without any disclosure of conflict of interest). Among the fellow travelers who wittingly or unwittingly supported CERT’s scheme to pervert the course of justice were lawsuit industry stalwarts, Arthur L. Frank, Peter F. Infante, Philip J. Landrigan, Barry S. Levy, Ronald L. Melnick, David Ozonoff, and David Rosner. See also NAS, “Carl Cranor’s Conflicted Jeremiad Against Daubert” (Sept. 23, 2018); Carl Cranor, “Milward v. Acuity Specialty Products: How the First Circuit Opened Courthouse Doors for Wronged Parties to Present Wider Range of Scientific Evidence” (July 25, 2011).

[7] Milward v. Acuity Specialty Products Group, Inc., 664 F. Supp. 2d 137, 148 (D. Mass. 2009), rev’d, 639 F.3d 11 (1st Cir. 2011), cert. den. sub nom. U.S. Steel Corp. v. Milward, 565 U.S. 1111 (2012), on remand, Milward v. Acuity Specialty Products Group, Inc., 969 F.Supp. 2d 101 (D. Mass. 2013) (excluding specific causation opinions as invalid; granting summary judgment), aff’d, 820 F.3d 469 (1st Cir. 2016).

[8] To put this effort into a sociology of science perspective, the Toolkit article is published in a journal, Environmental Health, an Editor in Chief of which is David Ozonoff, a long-time pro-plaintiff partisan in the asbestos litigation. The journal has an “ombudsman,”Anthony Robbins, who was one of the movers-and-shakers in forming SKAPP, The Project on Scientific Knowledge and Public Policy, a group that plotted to undermine the application of federal evidence law of expert witness opinion testimony. SKAPP itself now defunct, but its spirit of subverting law lives on with efforts such as the Toolkit. “More Antic Proposals for Expert Witness Testimony – Including My Own Antic Proposals” (Dec. 30, 2014). Robbins is also affiliated with an effort, led by historian and plaintiffs’ expert witness David Rosner, to perpetuate misleading historical narratives of environmental and occupational health. “ToxicHistorians Sponsor ToxicDocs” (Feb. 1, 2018); “Creators of ToxicDocs Show Off Their Biases” (June 7, 2019); Anthony Robbins & Phyllis Freeman, “ToxicDocs (www.ToxicDocs.org) goes live: A giant step toward leveling the playing field for efforts to combat toxic exposures,” 39 J. Public Health Pol’y 1 (2018).

[9] The exemplars cited were Paolo Boffetta, MD, MPH; Hans Olov Adami, Philip Cole, Dimitrios Trichopoulos, Jack Mandel, “Epidemiologic studies of styrene and cancer: a review of the literature,” 51 J. Occup. & Envt’l Med. 1275 (2009); Carlo LaVecchia & Paolo Boffetta, “Role of stopping exposure and recent exposure to asbestos in the risk of mesothelioma,” 21 Eur. J. Cancer Prev. 227 (2012); John Acquavella, David Garabrant, Gary Marsh G, Thomas Sorahan and Douglas L. Weed, “Glyphosate epidemiology expert panel review: a weight of evidence systematic review of the relationship between glyphosate exposure and non-Hodgkin’s lymphoma or multiple myeloma,” 46 Crit. Rev. Toxicol. S28 (2016); Catalina Ciocan, Nicolò Franco, Enrico Pira, Ihab Mansour, Alessandro Godono, and Paolo Boffetta, “Methodological issues in descriptive environmental epidemiology. The example of study Sentieri,” 112 La Medicina del Lavoro 15 (2021).

[10] The Toolkit authors acknowledge that their identification of “tools” was drawn from previous publications of the same ilk, in the same journal. Rebecca F. Goldberg & Laura N. Vandenberg, “The science of spin: targeted strategies to manufacture doubt with detrimental effects on environmental and public health,” 20:33 Envt’l Health (2021).

[11] Toolkit at 11.

[12] F.D.K. Liddell, “Magic, Menace, Myth and Malice,” 41 Ann. Occup. Hyg. 3, 3 (1997). See “The Lobby – Cut on the Bias” (July 6, 2020).

[13] Robert N. Proctor & Londa Schiebinger, Agnotology: The Making and Unmaking of Ignorance (2008).

[14] Naomi Oreskes & Erik M. Conway, Merchants of Doubt: How a Handful of Scientists Obscured the Truth on Issues from Tobacco Smoke to Global Warming (2010); Naomi Oreskes & Erik M. Conway, “Defeating the merchants of doubt,” 465 Nature 686 (2010).

[15] David Michaels, The Triumph of Doubt: Dark Money and the Science of Deception (2020); David Michaels, Doubt is Their Product: How Industry’s Assault on Science Threatens Your Health (2008); David Michaels, “Science for Sale,” Boston Rev. 2020; David Michaels, “Corporate Campaigns Manufacture Scientific Doubt,” 174 Science News 32 (2008); David Michaels, “Manufactured Uncertainty: Protecting Public Health in the Age of Contested Science and Product Defense,” 1076 Ann. N.Y. Acad. Sci. 149 (2006); David Michaels, “Scientific Evidence and Public Policy,” 95 Am. J. Public Health s1 (2005); David Michaels & Celeste Monforton, “Manufacturing Uncertainty: Contested Science and the Protection of the Public’s Health and Environment,” 95 Am. J. Pub. Health S39 (2005); David Michaels & Celeste Monforton, “Scientific Evidence in the Regulatory System: Manufacturing Uncertainty and the Demise of the Formal Regulatory Ssytem,” 13 J. L. & Policy 17 (2005); David Michaels, “Doubt is Their Product,” Sci. Am. 96 (June 2005); David Michaels, “The Art of ‘Manufacturing Uncertainty’,” L.A. Times (June 24, 2005).

[16] See, e.g., Sibilla Cantarini, Werner Abraham, and Elisabeth Leiss, eds., Certainty-uncertainty – and the Attitudinal Space in Between (2014); Roger M. Cooke, Experts in Uncertainty: Opinion and Subjective Probability in Science (1991).

[17] See, e.g., Ralph Hertwig & Christoph Engel, eds., Deliberate Ignorance: Choosing Not to Know (2021); Linsey McGoey, The Unknowers: How Strategic Ignorance Rules the World (2019); Michael Smithson, “Toward a Social Theory of Ignorance,” 15 J. Theory Social Behavior 151 (1985).

[18] See Janet Kourany & Martin Carrier, eds., Science and the Production of Ignorance: When the Quest for Knowledge Is Thwarted (2020); John Launer, “The production of ignorance,” 96 Postgraduate Med. J. 179 (2020); David S. Egilman, “The Production of Corporate Research to Manufacture Doubt About the Health Hazards of Products: An Overview of the Exponent BakeliteVR Simulation Study,” 28 New Solutions 179 (2018); Larry Dossey, “Agnotology: on the varieties of ignorance, criminal negligence, and crimes against humanity,” 10 Explore 331 (2014); Gerald Markowitz & David Rosner, Deceit and Denial: The Deadly Politics of Industrial Revolution (2002).

[19] See Enea Bianchi, “Agnotology: a Conspiracy Theory of Ignorance?” Ágalma: Rivista di studi culturali e di estetica 41 (2021).

[20] Toolkit at 4.

Posted in Causation, Cognitive Biases, Conflicts of Interest, Public Nuisances, Scientific Evidence, Scientific Misconduct, Scientific Publishing, statistical evidence | 1 Comment »

Larding Up the Literature

February 20th, 2021

Another bio-medical journal?

In October 2019, The Journal of Scientific Practice and Integrity published its inaugural volume one, number one issue, online. This journal purports to cover scientific integrity issues, which may well not be adequately covered in the major biomedical journals. There are reasons to believe, however, that this journal may be more of a threat to scientific integrity than a defender.

Thenew journal describes itself as:

“an interdisciplinary, peer-reviewed journal that publishes scholarly debate and original research on scientific practices that impact human and environmental health.”

The editorial board reads like a Who’s Who’s list of “political scientists” who testify a LOT for claimants, and who, when not working for the lawsuit industry, practice occupational and environmental medicine for the redistribution of wealth.

David Egilman, contemnor and frequent plaintiffs’ expert witness in personal injury litigation is editor in chief. Tess Bird, an Egilman protégé, is managing editor. Another Egilman protégé, Susana Rankin Bohme, an associate Director of Research at Corporate Accountability International, also sits on the editorial board. You may be forgiven for believing that this journal will be an Egilman vanity press. The editorial board also includes some high-volume testifying plaintiffs expert witnesses:

Peter Infante, of Peter F. Infante Consulting, LLC, Virginia

Adriane Fugh-Berman, of PharmedOut

Barry Castleman,

William E. Longo, President, MAS, LLC

David Madigan,

Michael R. Harbut,

David Rosner, and

Gerald Markowitz

The journal identifies the Collegium Ramazzini as one of its “partners.” Cue the “Интернационал”!

The first issue of this new journal features a letter[1] from the chief and managing editors, Egilman and Bird, which states wonderfully aspirational goals. The trick will be whether the journal can apply its ethical microscope to all actors in the world of scientific publishing, or whether this new journal is just not another lawsuit industry propaganda outlet.

Egilman’s previous editorial perch was at the International Journal of Occupational and Environmental Health, which was published by Maney Publishing. In 2015, the British company, the Taylor & Francis Group, acquired the IJOEH, with Maney’s other journals, and installed a new editor-in-chief, Andrew Maier. Egilman was cast out; hence the new journal.

Egilman’s new journal will feature among other types of articles, “reviews of legal testimony,” as a scholarly subject. It will be interesting to see whether such reviews assess the testimony of lawsuit industry witnesses, as well as manufacturing industry witnesses.

The new journal requires the use of the International Committee of Medical Journal Editors (ICMJE) conflict-of-interest and funding disclosure rules, and the use of the ICMJE form. Accordingly, authors “should” report all conflicts, including:

“[a]ny financial contributions, payments, or funding for the present work;

relevant financial activities outside of the submitted work;

any patents or copyrights broadly relevant to the work; and

any relationships that readers could perceive to influence the submitted work.”

There have been only two issues of Egilman’s new journal so far, but I decided to spot check compliance. The first article[2] I saw was by Colin Soskolne, who has testified for the lawsuit industry in a diacetyl case.[3] Oops; no disclosure.

Does Soskolne’s bias show? In the spot-checked article, authors Sokolne and Baur reprise a publication previously part of a 2018 Collegium Ramazzini convocation entitled “Corporate Influence Threatens the Public Health.” The aim of the convocation speakers was to press their claims that [manufacturing] corporate influence undermines scientific integrity through discernible methods, all by “those in the pay of industry”:

  • infiltrating journal editorial boards by scientists, with the resulting publication of poorly designed, biased research that foments doubt;
  • interfering with “the independent activities of IARC” and similar agencies;
  • blocking “much needed” regulation of “hazardous agents,” such as pesticides and polyfluoroalkyl substances (PFAS); and
  • promulgating causal criteria, which are baseless and which “block workers’ access to legal remedies for occupational illness and premature death.”[4]

There can be little doubt that Soskolne is not interested in messing with “those in the pay of the lawsuit industry.” Soskolne’s biases are fairly clear, clear enough for us to complain that he has not disclosed that he has been compensated by the lawsuit industry, and that he has deep positional conflicts as well. Ironically, he is writing in a journal that itself appears to lack “balance.” The editorial board of the journal for which Soskolne was writing is composed of many of “those in the pay of the lawsuit industry.”

Soskolne is keen to preserve the independence of IARC, but that perceived independence has become a sad, sick joke, with the exclusion of most anyone who has had any working relationship with manufacturing industry, while engaging many with deep ties to the lawsuit industry. Soskolne’s assessment of “much needed” regulation ultimately must be evaluated on the facts and data of each putative toxic substance. If the claim of harmful effects is correct, then regulation may well be “much needed.” If the claim is not correct, then regulation will be much “unneeded.” As for promulgating causal criteria, there is no doubt that the Soskolne, along with the editorial board of this new journal, would like to see the abrogation of causal criteria, so that workers have legal remedies ad libitum.

Soskolne and Baur provide their hit list of the methods of obfuscation or of techniques used to undermine science and policy.[5] There is precious little in their list, however, that is not common place among all journals that publish occupational and environmental epidemiology, including the journals that have been captured by the lawsuit industry’s scientists. Soskolne and Baur also provide a catalogue of how lawsuit industry scientists would subvert science and lock in their biased and selective interpretation of data:

  • elevate biological plausibility into sufficient basis for causal inference
  • conflate species and ignore species differences in order to allow animal studies to suffice for causal inference for humans
  • ignore substantial, relevant biological differences in even slight structural differences among various molecules to enable assertions of harm based upon similar molecular structure of a putative toxic substance

Soskolne ends with a quote from the “pink panthers,” two radical, labor historians, both editorial board members of this new journal, and who both have testified many times for the lawsuit industry:

“[A]s a society, we cannot entrust those with self-interest to be the judge and jury of what is and what is not a danger[;] … that can only lead to compromised science, a questionable decisionmaking process, and a potentially polluted world.”[6]

The pink panthers are, of course, correct, but we must understand that self-interest and conflict of interest can be, and are, both ideological, positional, as well as economic.

[1]  Tess Bird & David Egilman, “Letter from the Editors: An Introduction to the Journal of Scientific Practice and Integrity,” 1 J. Sci. Practice & Integrity 1 (2019).

[2]  Colin Soskolne & Xaver Baur, “How Corporate Influence Continues to Undermine the Public’s Health,” 1 J. Sci. Practice & Integrity 1 (2019), available at DOI: 10.35122/jospi.2019.878137 [cited as Soskolne & Baur]

[3]  See Watson v. Dillon Companies, 797 F. Supp. 2d 1138 (D. Colo. 2011) (addressing Soskolne’s testimony).
[4]  Soskolne & Baur at 1-2.

[5]  Soskolne & Baur at 3.

[6]  Soskolne & Baur at 4, quoting from Gerald Markowitz & David Rosner, “Monsanto, PCBs, and the creation of a ‘world-wide ecological problem’,” 39 J. Pub. Health Policy 463 (2018).

Posted in Cognitive Biases, Conflicts of Interest, Expert Witnesses, Scientific Publishing | No Comments »

Center for Truth in Science

February 2nd, 2021

The Center for Truth in Science

Well, now I have had the complete 2020 experience, trailing into 2021. CoVid-19, a.k.a. Trump flu happened. The worst for me is now mostly over, and I can see a light at the end of the tunnel. Fortunately it is not the hypoxemic end-of-life light at the end of the tunnel.

Kurt Gödel famously noted that the “the meaning of world is the separation of wish and fact.” The work of science in fields that touch on religion, politics, and other dogmas requires nothing less than separating wish from fact. Sadly, most people are cut off from the world of science by ignorance, lack of education, and social media that blur the distinction between wish and fact, and ultimately replace the latter with the former.

It should go without saying that truth is science and science is truth, but our current crises show that truth and science are both victims of the same forces that blur wish with fact. We might think that a center established for “truth in science” is as otiose as a center for justice in the law, but all the social forces at work to blur wish and fact make such a center an imperative for our time.

The Center for Truth in Science was established last year, and has already weighed in on important issues and scientific controversies that occupy American courtrooms and legislatures. Championing “fact-based” science, the Center has begun to tackle some of the difficult contemporary scientific issues that loom large on the judicial scene – talc, glyphosate, per- and polyfluoroalkyl substances, and other – as well as methodological and conceptual problems that underlie these issues. (Of course, there is no other kind of science than fact-based, but there are many pseudo-, non-fact based knock offs out there.) The Center has already produced helpful papers on various topics, with many more important papers in progress. The Center’s website is a welcomed resource for news and insights on science that matters for current policy decisions.

The Center is an important and exciting development, and its work promises to provide the tools to help us separate wish from fact. Nothing less than the meaning of the world is at stake.

Posted in Evidence, Scientific Evidence, Scientific Publishing, Uncategorized | Comments Off on Center for Truth in Science

Regressive Methodology in Pharmaco-Epidemiology

October 24th, 2020

Medications are rigorously tested for safety and efficacy in clinical trials before approval by regulatory agencies such as the U.S. Food & Drug Administration (FDA) or the European Medicines Agency (EMA). The approval process, however, contemplates that more data about safety and efficacy will emerge from the use of approved medications in pharmacoepidemiologic studies conducted outside of clinical trials. Litigation of safety outcomes rarely arises from claims based upon the pivotal clinical trials that were conducted for regulatory approval and licensing. The typical courtroom scenario is that a safety outcome is called into question by pharmacoepidemiologic studies that purport to find associations or causality between the use of a specific medication and the claimed harm.

The International Society for Pharmacoepidemiology (ISPE), established in 1989, describes itself as an international professional organization intent on advancing health through pharmacoepidemiology, and related areas of pharmacovigilance. The ISPE website defines pharmacoepidemiology as

“the science that applies epidemiologic approaches to studying the use, effectiveness, value and safety of pharmaceuticals.”

The ISPE conceptualizes pharmacoepidemiology as “real-world” evidence, in contrast to randomized clinical trials:

“Randomized controlled trials (RCTs) have served and will continue to serve as the major evidentiary standard for regulatory approvals of new molecular entities and other health technology. Nonetheless, RWE derived from well-designed studies, with application of rigorous epidemiologic methods, combined with judicious interpretation, can offer robust evidence regarding safety and effectiveness. Such evidence contributes to the development, approval, and post-marketing evaluation of medicines and other health technology. It enables patient, clinician, payer, and regulatory decision-making when a traditional RCT is not feasible or not appropriate.”

ISPE Position on Real-World Evidence (Feb. 12, 2020) (emphasis in original).

The ISPE publishes an official journal, Pharmacoepidemiology and Drug Safety, and sponsors conferences and seminars, all of which are watched by lawyers pursuing and defending drug and device health safety claims. The endorsement by the ISPE of the American Statistical Association’s 2016 statement on p-values is thus of interest not only to statisticians, but to lawyers and claimants involved in drug safety litigation.

The ISPE, through its board of directors, formally endorsed the ASA 2016 p-value statement on April 1, 2017 (no fooling) in a statement that can be found at its website:

The International Society for Pharmacoepidemiology, ISPE, formally endorses the ASA statement on the misuse of p-values and accepts it as an important step forward in the pursuit of reasonable and appropriate interpretation of data.

On March 7, 2016, the American Statistical Association (ASA) issued a policy statement that warned the scientific community about the use P-values and statistical significance for interpretation of reported associations. The policy statement was accompanied by an introduction that characterized the reliance on significance testing as a vicious cycle of teaching significance testing because it was expected, and using it because that was what was taught. The statement and many accompanying commentaries illustrated that p-values were commonly misinterpreted to imply conclusions that they cannot imply. Most notably, “p-values do not measure the probability that the studied hypothesis is true, or the probability that the data were produced by random chance alone.” Also, “a p-value does not provide a good measure of evidence regarding a model or hypothesis.” Furthermore, reliance on p-values for data

interpretation has exacerbated the replication problem of scientific work, as replication of a finding is often confused with replicating the statistical significance of a finding, on the erroneous assumption that replication should lead to studies getting similar p-values.

This official statement from the ASA has ramifications for a broad range of disciplines, including pharmacoepidemiology, where use of significance testing and misinterpretation of data based on P-values is still common. ISPE has already adopted a similar stance and incorporated it into our GPP [ref] guidelines. The ASA statement, however, carries weight on this topic that other organizations cannot, and will inevitably lead to changes in journals and classrooms.

There are points of interpretation of the ASA Statement, which can be discussed and debated. What is clear, however, is that the ASA never urged the abandonment of p-values or even of statistical significance. The Statement contained six principles, some of which did nothing other than to attempt to correct prevalent misunderstandings of p-values. The third principle stated that “[s]cientific conclusions and business or policy decisions should not be based only on whether a p-value passes a specific threshold.” (emphasis added).

This principle, as stated, thus hardly advocated for the abandonment of a threshold in testing; rather it made the unexceptional point that the ultimate scientific conclusion (say about causality) required more assessment than only determining whether a p-value passed a specified threshold.

Presumably, the ISPE’s endorsement of the ASA’s 2016 Statement embraces all six of the articulated principles, including the ASA’s fourth principle:

“4. Proper inference requires full reporting and transparency

P-values and related analyses should not be reported selectively. Conducting multiple analyses of the data and reporting only those with certain p-values (typically those passing a significance threshold) renders the reported p-values essentially uninterpretable. Cherry-picking promising findings, also known by such terms as data dredging, significance chasing, significance questing, selective inference, and “p-hacking,” leads to a spurious excess of statistically significant results in the published literature and should be vigorously avoided. One need not formally carry out multiple statistical tests for this problem to arise: Whenever a researcher chooses what to present based on statistical results, valid interpretation of those results is severely compromised if the reader is not informed of the choice and its basis. Researchers should disclose the number of hypotheses explored during the study, all data collection decisions, all statistical analyses conducted, and all p-values computed. Valid scientific conclusions based on p-values and related statistics cannot be drawn without at least knowing how many and which analyses were conducted, and how those analyses (including p-values) were selected for reporting.”

The ISPE’s endorsement of the ASA 2016 Statement references the ISPE’s own

“Guidelines for Good Pharmacoepidemiology Practices (GPP),” which were promulgated initially in 1996, and revised as recently as June 2015. Good practices, as of 2015, provided that:

“Interpretation of statistical measures, including confidence intervals, should be tempered with appropriate judgment and acknowledgements of potential sources of error and limitations of the analysis, and should never be taken as the sole or rigid basis for concluding that there is or is not a relation between an exposure and outcome. Sensitivity analyses should be conducted to examine the effect of varying potentially critical assumptions of the analysis.”

All well and good, but this “good practices” statement might be taken as a bit anemic, given that it contains no mention of, or caution against, unqualified or unadjusted confidence intervals or p-values that come from multiple testing or comparisons. The ISPE endorsement of the ASA Statement now expands upon the ISPE’s good practices to include the avoidance of multiplicity and the disclosure of the full extent of analyses conducted in a study.

What happens in the “real world” of publishing, outside the board room?

Last month, the ISPE conducted its (virtual) 36th International Conference on Pharmacoepidemiology & Therapeutic Risk Management. The abstracts and poster presentations from this Conference were published last week as a Special Issue of the ISPE journal. I spot checked the journal contents to see how well the presentations lived up to the ISPE’s statistical aspirations.

One poster presentation addressed statin use and skin cancer risk in a French prospective cohort.[1]  The authors described their cohort of French women, who were 40 to 65 years old, in 1990, and were followed forward. Exposure to statin medications was assessed from 2004 through 2014. The analysis included outcomes of any skin cancer, melanoma, basal-cell carcinoma (BCC), and squamous-call carcinoma (SCC), among 66,916 women. Here is how the authors describe their findings:

There was no association between ever use of statins and skin cancer risk: the HRs were 0.96 (95% CI = 0.87-1.05) for overall skin cancer, 1.18 (95% CI = 0.96-1.47) for melanoma, 0.89 (95% CI = 0.79-1.01) for BCC, and 0.90 (95% CI = 0.67-1.21) for SCC. Associations did not differ by statin molecule nor by duration or dose of use. However, women who started to use statins before age 60 were at increased risk of BCC (HR = 1.45, 95% CI = 1.07-1.96 for ever vs never use).

To be fair, this was a poster presentation, but this short description of findings makes clear that the investigators looked at least at the following subgroups:

Exposure subgroups:

  • specific statin drug
  • duration of use
  • dosage
  • age strata

and

Outcome subgroups:

  • melanoma
  • basal-cell carcinoma
  • squamous-cell carcinoma

The reader is not told how many specific statins, how many duration groups, dosage groups, and age strata were involved in the exposure analysis. My estimate is that the exposure subgroups were likely in excess of 100. With three disease outcome subgroups, the total subgroup analyses thus likely exceeded 300. The authors did not provide any information about the full extent of their analyses.

Here is how the authors reported their conclusion:

“These findings of increased BCC risk in statin users before age 60 deserve further investigations.”

Now, the authors did not use the phrase “statistically significant,” but it is clear that they have characterized a finding of “increased BCC risk in statin users before age 60,” and in no other subgroup, and they have done so based upon a reported nominal “HR = 1.45, 95% CI = 1.07-1.96 for ever vs never use.” It is also clear that the authors have made no allowance, adjustment, modification, or qualification, for the wild multiplicity arising from their estimated 300 or so subgroups. Instead, they made an unqualified statement about “increased BCC risk,” and they offered an opinion about the warrant for further studies.

Endorsement of good statistical practices is a welcome professional organizational activity, but it is rather meaningless unless the professional societies begin to implement the good practices in their article selection, editing, and publishing activities.

[1]  Marie Al Rahmoun, Yahya Mahamat-Saleh, Iris Cervenka, Gianluca Severi, Marie-Christine Boutron-Ruault, Marina Kvaskoff, and Agnès Fournier, “Statin use and skin cancer risk: A French prospective cohort study,” 29 Pharmacoepidemiol. & Drug Safety s645 (2020).

Posted in Scientific Publishing, statistical evidence | Comments Off on Regressive Methodology in Pharmaco-Epidemiology

SKAPPOLOGY

May 26th, 2020

The Genetic Literacy Project (GLP) asks:

“Who is David and who is Goliath in the lobbying battle over agricultural biotechnology? Activists? Agro-business? In a commitment to transparency, the GLP has mined 5 years of data to help the public understand the funding network that shapes the biotechnology debate.”

The amount of money flowing into the campaign against genetically modified organisms (GMOs) is astonishing, but it does not stop the hypocritical complaints against industry’s sponsorship of studies to help show the safety of GMOs. In a recent on-line article, the GLP has published charts to map contributions from not-for-profit non-governmental organizations to anti-biotechnology advocacy groups. Close to a billion dollars ($850M) flowed into the coffers of these organizations from 2012 to 2016. The GLP’s work on tracking this funding is commendable for bringing balance to the debate about the effect of corporate money on health and environmental issues. Corporate includes the lawsuit industry and the advocacy industries.

Well actually, it would be a wonderful world if the GLP’s tracking were unnecessary. In one such alternative universe, people would ask to examine the evidence for and against claims, and they would have a healthy respect for uncertainty.

Studies funded by parties are routinely relied upon in litigation, and they are often pivotal in how courts decide significant claims of environmental or occupational harm.[1] Unfortunately, the sponsorship of studies by plaintiffs’ counsel, third-party litigation funding entities, and advocacy groups is often obscured or hidden.

* * * * * * * * * * * *

I recently happened upon an article of interest in an obscure journal, by a well-known author.[2]  The author, John C. Bailar, formerly an Editor-in-Chief of the Journal of the National Cancer Institute, was  professor emeritus in the University of Chicago’s Department of Public Health Sciences. He died in September 2016. Bailar was a graduate of the Yale University medical school, and also held a doctorate in statistics.

There is nothing ground breaking in Bailar’s article, but it is a nice summary of the ways that errors can creep into the scientific literature, short of actual fabrication or falsification of data.[3] It is also worth reading because it is an article that comes from one of the several Coronado Conferences, sponsored by an advocacy organization that has fraudulently concealed its funding, The Project on Scientific Knowledge and Public Policy, aka SKAPP.

To be sure, authors of SKAPP-funded articles have invariably cited their funding from SKAPP, and Bailar was no exception. Bailar made the following acknowledgements:

“Support for this paper was provided by The Project on Scientific Knowledge and Public Policy (SKAPP) at The George Washington University School of Public Health and Health Services. It is revised from a paper presented at SKAPP’s March 2006 Coronado Conference “Truth and Advocacy: The Quality and Nature of Litigation and Regulatory Science.” The papers from that conference will be published elsewhere.”[4]

The acknowledgement of support was rather anemic by SKAPP standards.  Most SKAPP-funded articles recited something closer to the following provided by David Michaels, who headed up SKAPP and worked as an expert witness for the litigation industry, until becoming the Administrator of the Occupational Health & Safety Administration, in President Obama’s administration:[5]

“DM [David Michaels] and CM [Celeste Monforton] are employed by the George Washington University School of Public Health and Health Services as part of the Project on Scientific Knowledge and Public Policy (SKAPP). Their salaries, in part, are funded by the Common Benefit Litigation Expense Trust, a fund established pursuant to a court order in the Silicone Gel Breast Implant Products Liability litigation. SKAPP’s funding is unrestricted; its funders are not given advance notice or the opportunity to review or approve any documents produced by the project. PL [Peter Lurie] is with Public Citizen’s Health Research Group.”

Michaels’ statement was perhaps a little more forthcoming, but few scientists or lay persons would know that his salary, and support, came from plaintiffs’ lawyers as part of an active litigation effort. Although Michaels claimed that the funding was unrestricted, like Big Tobacco funding, the sponsor, plaintiffs’ counsel, created a substantial selection effect in choosing beneficiaries who would deliver its pre-approved message. The Common Benefit Trust may sound like an eleemosynary, public-spirited, organization, with the imprimatur of the federal court system.  It was not.

Was Bailar influenced by his source of funding?  His topic would have permitted him many examples from the annals of science or litigation, but interestingly one of the few examples Bailar chose to give details about was a scientific dispute between the semiconductor industry and Richard Clapp, who was acting as an expert witness in litigation against that industry.  Although Clapp used a study design known to be inaccurate and biased, Bailar touted Clapp’s research over that sponsored by members of the industry.  Richard Clapp, in addition to have been an expert witness for the litigation industry on many occasions, also happened to have been a member of the SKAPP’s advisory committee. Hmmm.

Whence comes SKAPP funding?  SKAPP trades on most readers’ lack of familiarity with how “common benefit funds” are established.  They sound like some sort of disembodied charitable trust, such as the Pew. In fact, the silicone common benefit trust was nothing more than a funding device for mass federal litigation involving silicone breast implants. Ironically, the funding came from a litigation in which one leading judge described plaintiffs’ expert witnesses as “charlatans,” and the litigation claims as largely based upon fraud.[6] Cynics might believe that Bailar’s choice of Clapp versus the semiconductor industry, regardless of the merits, was driven by a desire to please SKAPP & Clapp.

The common benefit fund for the silicone-gel breast implant litigation was created by Order 13, “Establishing Plaintiffs’ Litigation Expense Fund to Compensate and Reimburse Attorneys for Services Performed and Expenses Incurred for Common Benefit.” The late Judge Sam Pointer, appointed to preside over MDL 926, In re Silicone Gel Breast Implants Products Liability Litigation, Master File No. CV 92-P-10000-S, entered the order on July 23, 1993.  Some of the pertinent terms of Order 13 illustrate how it was supposed to operate:

This order is entered in order to provide for the fair and equitable sharing among plaintiffs of the cost of special services performed and expenses incurred by attorneys acting for the common benefit of all plaintiffs.

  1. Plaintiffs’ Litigation Expense Fund to be Established. Plaintiffs’ National Liaison Counsel … are directed to establish an interest-bearing account to receive and disburse funds as provided in this order.

***

  1. Assessment.

(a)    All plaintiffs and their attorneys who, after this date, either agree — for a monetary consideration — to settle, compromise, dismiss, or reduce the amount of a claim or, with or without a trial, recover a judgment for monetary damages or other monetary relief, including both compensatory and punitive damages, with respect to a breast implant claim are hereby assessed:

(1)    5% of the “gross monetary recovery,” if the agreement is made or the judgment is entered after this date and before November 1, 1993, or

(2)    6% of the “gross monetary recovery,” if the agreement is made or the judgment is entered after October 31, 1993.

Defendants are directed to withhold this assessment from amounts paid to plaintiffs and their counsel, and to pay the assessment into the fund as a credit against the settlement or judgment.  ***

  1. Disbursements.

(a)    Payments may be made from the fund to attorneys who provide services or incur expenses for the joint and common benefit of plaintiffs in addition to their own client or clients.  Attorneys eligible are not limited to Plaintiffs’ National Liaison Counsel and members of Plaintiffs’ National Steering Committee, but include, for example, other attorneys called upon by them to assist in performing their responsibilities, State Liaison Counsel, and other attorneys performing similar responsibilities in state court actions in which the presiding state-court judge has imposed similar obligations upon plaintiffs to contribute to the fund.

(b)    Payments will be allowed only to compensate for special services performed, and to reimburse for special expenses incurred, for the joint and common benefit of all plaintiffs.

***

(c)    No amounts will be disbursed without review and approval by a committee of federal and state judicial officers to be designated by the court.  The committee may, however, utilize the services of a special master to assist in this review, and may authorize one or more of its members to act for the committee in approving particular types of applications for disbursement.

(d)    If the fund exceeds the amount needed to make payments as provided in this order, the court will order an refund to those who have contributed to the fund.  Any such refund will be made in proportion to the amount of the contributions.”

For a while, a defense lawyer, representing the defendants in the silicone MDL, participated in discussions concerning MDL 926 Order 13 funds, until the plaintiffs’ lawyers decided that his services were not needed, and excluded him from discussions of the use of the monies. The reality is that the plaintiffs’ lawyers in the silicone litigation were able to bamboozle the slim oversight committee into approving a propaganda campaign against Daubert gatekeeping, and that recipients of the plaintiffs’ lawyers’ largesse were able to misrepresent their funding as though it were from a federal court.

There are further ironies connected with the silicone common benefit trust.  First, the silicone litigation was effectively over when the court-appointed expert witnesses’ reports that announced that the plaintiffs’ expert witnesses lacked sound scientific evidence to support conclusions of causation.  SKAPP’s website reports that its activities started around 2002, by which time both the court-appointed witnesses, as well as the British Ministry of Health, and the Institute of Medicine’s select committee had reported that there was no basis for the plaintiffs’ causal claims in litigation.[7] The second irony is that SKAPP, through its sponsorship of various research and writing projects, had made the recipients of SKAPP money, by the terms of Order 13, agents of the silicone plaintiffs’ lawyers and their clients. Recipients of SKAPP funding who did not disclose that their support or salaries come from the coffers of plaintiffs’ counsel were engaged in misleading their readers and the scientific and legal communities.

I have written often in the past about SKAPP as an agent of plaintiffs’ counsel in mass tort litigation.[8] The concern is not new, but it has continuing significance because of the asymmetrical standard advanced by the lawsuit industry and its scientific advisors who seek to disqualify manufacturing industry and its scientific advisors from participating in scientific debate and argument about various health claims.[9]

[1]  See, e.g., Leaf River Forest Prods. v. Ferguson, 662 So. 2d 648, 657 (Miss. 1995) (litigation involving defense expert witness’s reliance upon dioxin studies funded by defendant paper mills); Maurer v. Heyer-Schulte Corp., No. Civ. A. 92-3485, 2002 WL 31819160 at *3 (E.D. La. Dec. 13, 2002) (granting defendant’s summary judgment against plaintiff’s claim that breast implants caused her harm; citing defendants’ sponsored epidemiologic studies showing no causal link, including epidemiologic study conducted in Sweden); Nat’l Res. Def. Council v. Evans, 232 F. Supp. 2d 1003, 1013 (N.D. Cal. 2002) (“commend[ing] defendants’ sponsorship of independent scientific research…”); FTC v. Pantron I, Corp., 1991 U.S. Dist. LEXIS 21858 (C.D. Cal. Sept 6, 1991) (finding study funded by defendants met “basic and fundamental requirements for scientific validity and reliability”).

[2]  John C. Bailar, “How to distort the scientific record without actually lying: truth, and the arts of science,” 11 European J. Oncol. 217 (2006).

[3]  Id. at 218.

[4]  Id. at 223.

[5]  David Michaels, Celeste Monforton & Peter Lurie, “Selected science: an industry campaign to undermine an OSHA hexavalent chromium standard,” 65 Envt’l Health 5 (2006).

[6]     Hon. Jack B. Weinstein, “Preliminary Reflections on Administration of Complex Litigation” 2009 Cardozo L. Rev. de novo 1, 14 (2009).

[7]   Independent Review Group, Silicone Breast Implants: The Report of the Independent Review Group 8, 22-23 (July 1998) (concluding that there was no demonstrable risk of connective tissue disease from silicone breast implants); Stuart Bondurant, Virginia Ernster, and Roger Herdman, eds., Safety of Silicone Breast Implants (1999) (rejecting plaintiffs’ theories and litigation claims of systemic disease).

[8]   “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). See also Walter Olson, Schools for Misrule: Legal Academia and an Overlawyered America 121-22 (2011); David E. Bernstein & Eric G. Lasker, “Defending Daubert: It’s Time to Amend Federal Rule of Evidence 702,” 57 William & Mary L. Rev. 1, 39 & n.211 (2015); Ted Frank, “Daubert Debate,” Overlawyered (July 5, 2003); Peter Nordberg, “Bernstein on SKAPP (part 1),” Daubert on the Web (Jul)y 02, 2003).

[9]   Consider the media hysteria over former President Obama’s nomination of Dr. Robert Califf, to serve as Chair of the Food and Drug Administration.[9] The criticism was based upon his having served as the founding director of the Duke Clinical Research Institute, which received funding directly from pharmaceutical companies. The Senate confirmed Califf (89 to 4), but the controversy highlights the hypocrisy in play. Brady Dennis, “Senate confirms Robert Califf as new FDA commissioner,” Wash. Post (Feb. 24, 2016).

Posted in Conflicts of Interest, Scientific Publishing | Comments Off on SKAPPOLOGY

Data Games – A Techno Thriller

April 22nd, 2020

Data Games – A Techno Thriller

Sherlock Holmes, Hercule Poirot, Miss Marple, Father Brown, Harry Bosch, Nancy Drew, Joe and Frank Hardy, Sam Spade, Columbo, Lennie Briscoe, Inspector Clouseau, and Dominic Da Vinci:

Move over; there is a new super sleuth in town.

Meet Professor Ken Wheeler.

Ken is a statistician, and so by profession, he is a data detective. In his day job, he teaches at a northeastern university, where his biggest challenges are managing the expectations of students and administrators, while trying to impart statistical learning. At home, Ken rarely manages to meet the expectations of his wife and son. But as some statisticians are wont to do, Ken sometimes takes on consulting gigs that require him to use his statistical skills to help litigants sort out the role of chance in cases that run from discrimination claims to rare health effects. In this contentious, sharp-elbowed environment, Ken excels. And truth be told, Ken actually finds great satisfaction in identifying the egregious errors and distortions of adversary statisticians

Wheeler’s sleuthing usually involves ascertaining random error or uncovering a lurking variable, but in Herberg I. Weisberg’s just-published novel, Data Games: A Techno Thriller, Wheeler is drawn into a high-stakes conspiracy of intrigue, violence, and fraud that goes way beyond the run-of-the-mine p-hacking and data dredging.

An urgent call from a scientific consulting firm puts Ken Wheeler in the midst of imminent disaster for a pharmaceutical manufacturer, whose immunotherapy anti-cancer wonder drug, Verbana, is under attack. A group of apparently legitimate scientists have obtained the dataset from Verbana’s pivotal clinical trial, and they appear on the verge of blowing Verbana out of the formulary with a devastating analysis that will show that the drug causes early dementia. Wheeler’s mission is to debunk the debunking analysis when it comes.

For those readers who are engaged in the litigation defense of products liability claims against medications, the scenario is familiar enough. The scientific group studying Verbana’s alleged side effect seems on the up-and-up, but they appear to engaged in a cherry-picking exercise, guided by a dubious theory of biological plausibility, known as the “Kreutzfeld hypothesis.”

It is not often that mystery novels turn on surrogate outcomes, biomarkers, genomic medicine, and predictive analytics, but Data Games is no ordinary mystery. And Wheeler is no ordinary detective. To be sure, the middle-aged Wheeler drives a middle-aged BMW, not a Bond car, and certainly not a Bonferroni. And Wheeler’s toolkit may not include a Glock, but he can handle the lasso, the jacknife, and the logit, and serve them up with SAS. Wheeler sees patterns where others see only chaos.

Unlike the typical Hollywood rubbish about stereotyped evil pharmaceutical companies, the hero of Data Games finds that there are sinister forces behind what looks like an honest attempt to uncover safety problems with Verbana. These sinister forces will use anything to achieve their illicit ends, including superficially honest academics with white hats. The attack on Verbana gets the FDA’s attention and an urgent hearing in White Oak, where Wheeler shines.

The author of Data Games, Herbert I. Weisberg, is himself a statistician, and a veteran of some of the dramatic data games he writes about in this novel. Weisberg is perhaps better known for his “homework” books, such asWillful Ignorance: The Mismeasure of Uncertainty (2014), and Bias and Causation: Models and Judgment for Valid Comparisons (2010). If, however, you ever find yourself in a pandemic lockdown, Weisberg’s Data Games: A Techno Thriller is a perfect way to escape. For under $3, you will be entertained, and you might even learn something about probability and statistics.

Posted in Data Sharing, Scientific Misconduct, Scientific Publishing, Underlying Data | Comments Off on Data Games – A Techno Thriller

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