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

Weight of the Evidence in Science and in Law

July 29th, 2017

woe to that man by whom the offense cometh”

         Matthew 18:7

Weight of the evidence (WOE) has cropped up again in recent trial and appellate court proceedings involving the admissibility of scientific expert witness opinion testimony. With some consistency, the WOE approach advocated is vacuous. The proponents of WOE do not specify what type of evidence is considered, whether all evidence was considered, or how competing and conflicting evidence was weighed.

Interpreted sympathetically, WOE might be taken to mean that “scientific judgment” was exercised with respect to causal inference, without describing exactly what was done. Although sympathetic, this interpretation renders the purported methodology meaningless. WOE-ful scientists might just as well say that they used scientific method. Not surprisingly, WOE is absent from virtually all major epidemiology textbooks

Despite the vacuity of WOE, or because of it, some lawyers, who constitute the lawsuit industry, are particularly fond of WOE.1 Expert witnesses who support the lawsuit industry have defended their “right” to inflict WOE on the litigation system, tooth and nail.2

Carl Cranor, a philosophy professor and a hired expert witness in litigation for plaintiffs’ counsel, has written about WOE and attempted to defend WOE as a scientific methodology. Cranor has caricaturized criticisms of WOE, including mine, by suggesting that the International Agency for Research on Cancer’s use of WOE rebuts my suggestion that WOE is no method at all.3 Cranor’s defense fails, however, because IARC’s method, for all its deficiencies, never invokes a method mired in WOE.

Perhaps the Lawsuit Industry likes WOE as much as it likes the equally vague term, “link.” WOE frees them from the requirement of any meaningful methodology, which means that any conclusion is possible. Under WOE, any conclusion can survive gatekeeping as an opinion. WOE frees the putative expert witness from the need to consider the quality of research. WOE-ful authors such as Carl Cranor invoke WOE or seek to inflict WOE without mentioning the crucial “nuts and bolts” of scientific inference, such as concepts of

  • Internal and external validity
  • Assessment of random error
  • Assessment of known and residual confounding
  • Known and potential threats to validity in
  • Appropriate methods of systematic review
  • Appropriate synthesis across studies, such as systematic review and meta-analysis

These important concepts are lost in the miasma of WOE.

In the published scientific literature, it is a commonplace that WOE is either poorly or not defined and specified. The phrase is vague and ambiguous; its use, inconsistent.4  Even authors sympathetic to the WOE mission have reluctantly concluded that the term is most often used in a way that “does not lend itself to transparency or repeatability except in simple cases.”5

Another reason that WOE resonates so strongly with the Lawsuit Industry is that having expert witnesses proclaim WOE as their methodology permits trial counsel to claim that the proffered opinions are immune to gatekeeping because, after all, weight-of-the-evidence questions are for the jury. Lawyers learn early on about WOE factual issues in appellate review of a wide variety of evidentiary and sufficiency issues in criminal and civil cases.6 Unless against the great WOE, WOE questions are for the jury.

Even venerable judges fall for this semantic confusion. In 1995, the Second Circuit, before the major revision of Rule 702, in 2000, noted that in discharging their gatekeeping role, trial judges do not assume:

“‘the role of St. Peter at the gates of heaven, performing a searching inquiry into the depth of an expert witness’s soul’ that would ‘inexorably lead to evaluating witness credibility and weight of the evidence, the ageless role of the jury’.”

McCullock v. H.B. Fuller Co., 61 F.3d 1038, 1045 (2d Cir.1995) (internal citations omitted).

Of course, the expert witness’s soul is not at issue, but his methodology is. More important, however, note how the appellate court adverted to “weight of the evidence” as something that the jury must evaluate, along with witness credibility. The expert witness WOE litigation strategy deliberately trades upon the confusion between WOE in the allocation between judge and jury, and valid scientific methodology in causal inference. McCullock is proof that judges can be, and are, bamboozled by the litigation strategy.

Twenty years after McCullock, federal appellate judges are still falling for the deliberate confusion between legal and scientific WOE. The Ninth Circuit recently held that the reliability test of Federal Rule of Evidence 702 is:

“‘is not the correctness of the expert’s conclusions but the soundness of his methodology’, and when an expert meets the threshold established by Rule 702, the expert may testify and the fact finder decides how much weight to give that testimony. Challenges that go to the weight of the evidence are within the province of a fact finder, not a trial court judge. A district court should not make credibility determinations that are reserved for the jury.”

City of Pomona v. SQM North America Corp., 750 F.3d 1036, 1044 (9th Cir. 2014) (internal citation omitted), cert. denied, 135 S. Ct. 870 (2014). Characterizing a methodological dispute as one that “merely” concerns the “weight of the evidence” is a strategy to remove the dispute from judicial gatekeeping altogether.

Recently, the Third Circuit displayed this confusion of WOE with methodological impropriety by mischaracterizing failure to correct for multiple testing as merely an improper calculation that ordinarily goes to the weight of the evidence, not its admissibility. Karlo v. Pittsburgh Glass Works, LLC, 849 F.3d 61, 83 (3d Cir. 2017).

The Third Circuit, in Karlo, cited to a Supreme Court case that predated Daubert v. Merrell Dow Pharmaceuticals, 509 U.S. 579 (1993), and which did involve any Rule 702 challenge to the use of a flawed statistical analysis. In Bazemore v. Friday, 478 U.S. 385, 400 (1986), plaintiffs sued as a class for employment discrimination, and sought to show the discrimination through the use of a regression analysis. The defense challenged the plaintiffs’ regression on grounds that key variables were omitted. The Court rejected a sufficiency challenge to a finding of discrimination in plaintiffs’ class action, and noted:

Normally, failure to include variables will affect the analysis’ probativeness, not its admissibility.”

The lesson of the last two decades of judicial gatekeeping is that methodological infirmity will affect both probitiveness and admissibility7. Courts cannot escape their important gatekeeping duties by shifting their responsibility to juries under the guise of WOE.

2 See Schachtman, “Desultory Thoughts on Milward v. Acuity Specialty Products,” (Oct. 2015).

3 Carl F. Cranor, Toxic Torts: Science, Law, and the Possibility of Justice 146 (2d ed. 2016) (citing and selectively quoting from Schachtman, WOE-fully Inadequate Methodology – An Ipse Dixit By Another Name” (May 1, 2012)).

4 See Charles Menzie, Miranda Hope Henning, Jerome Cura, Kenneth Finkelstein, Jack Gentile, James Maughan, David Mitchell, Stephen Petron, Bonnie Potocki, Susan Svirsky & Patti Tyler, “A weight-of-evidence approach for evaluating ecological risks; report of the Massachusetts Weight-of-Evidence Work Group,” 2 Human Ecological Risk Assessment 277, 279 (1996) (“although the term ‘weight of evidence’ is used frequently in ecological risk assessment, there is no consensus on its definition or how it should be applied”); Sheldon Krimsky, “The weight of scientific evidence in policy and law,” 95 Am. J. Pub. Health S129 (2005) (“However, the term [WOE] is applied quite liberally in the regulatory literature, the methodology behind it is rarely explicated.”); V. H. Dale, G.R. Biddinger, M.C. Newman, J.T. Oris, G.W. Suter II, T. Thompson, et al., “Enhancing the ecological risk assessment process,” 4 Integrated Envt’l Assess. Management 306 (2008) (“An approach to interpreting lines of evidence and weight of evidence is critically needed for complex assessments, and it would be useful to develop case studies and/or standards of practice for interpreting lines of evidence.”);  Douglas L. Weed, “Weight of Evidence: A Review of Concept and Methods,” 25 Risk Analysis 1545 (2005) (noting the “lack of definition of the term weight of evidence, multiple uses of the term and a lack of consensus about its meaning, and the many different kinds of weights, both qualitative and quantitative which can be used in risk assessment”); R.G. Stahl Jr., “Issues addressed and unaddressed in EPA’s ecological risk guidelines,” 17 Risk Policy Report 35 (1998) (noting that U.S. Environmental Protection Agency’s guidelines for ecological weight-of-evidence approaches to risk assessment fail to provide guidance); Glenn W. Suter, Susan M. Cormier, “Why and how to combine evidence in environmental assessments:  Weighing evidence and building cases,” 409 Sci. Total Env’t 1406, 1406 (2011) (noting arbitrariness and subjectivity of WOE “methodology”).

5 See Igor Linkov, Drew Loney, Susan Cormier, F. Kyle Satterstrom, and Todd Bridges, “Weight-of-evidence evaluation in environmental assessment: review of qualitative and quantitative approaches,” 407 Sci. Total Env’t 5199, 5203 (2009).

6 See, e.g., People v. Collier, 146 A.D.3d 1146, 1147-48, 2017 NY Slip Op 00342 (N.Y. App. Div. 3d Dep’t, Jan. 19, 2017) (rejecting appeal based upon defendant’s claim that conviction was against “weight of the evidence”); Venson v. Altamirano, 749 F.3d 641, 656 (7th Cir. 2014) (noting “new trial is appropriate if the jury’s verdict is against the manifest weight of the evidence”).

7 David L. Faigman, Christopher Slobogin & John Monahan, “Gatekeeping Science: Using the Structure of Scientific Research to Distinguish Between Admissibility and Weight in Expert Testimony,” 110 Northwestern L. Rev. 859, 865 (2016) (“An expert economist in an employment discrimination case who admittedly fails to control for a key variable such as seniority or wage structure in a regression analysis has committed a general error that should lead to exclusion by a judge… .”).

Slemp Trial Part 5 – Daniel W. Cramer

July 24th, 2017

The case of talc and ovarian cancer is a difficult and close case on general causation. Although I do not believe that the plaintiffs have made their case, their causal claims do not have the usual earmarks of “junk science,” so readily visible in many other litigations, such as the Zoloft birth defects cases.

Dr. Daniel Cramer is a physician and an epidemiology. He holds the title of professor of epidemiology at the Harvard University Chan School Of Public Health, as well as a professor of obstetrics, gynecology, and reproductive biology, at the Harvard Medical School. The plaintiffs called Cramer to testify on causation issues.

Cramer could have been purely duplicative as a witness, but he was used primarily on specific causation with a big boost on general causation because of his many publications on talc and ovarian cancer (a subject generally missing from Graham Colditz’s C.V.). The planned testimony for Cramer was to try to present the causal attribution of Slemp’s tumor to talc, with the understanding that since specific implied general causation, the plaintiff would obtain corroborating testimony on general causation as well.

With respect to Slemp’s known risk factors, such as her massive obesity and heavy smoking history, Cramer attempted to quantify her ex ante risks based upon her medical chart and from using risk ratios from available epidemiologic studies. Predictably, Cramer tried to diminish these ex ante risks by a highly selective reading of Slemp’s charts, but he ably deflected cross-examination criticisms by characterizing questions as quibbles and volunteering that he was not trying to ascribe plaintiff’s ovarian cancer exclusively to talc. Similarly, Cramer attempted to present the highest ex ante risk ratio for Slemp’s talc exposure, through his characterizations of her case as involving bilateral tumors and other features. Cramer tried to diminish the risk factor of obesity by claiming that fat women use talc more and that there was “synergy” between obesity and talc use. Cramer never described the evidentiary basis for this claimed synergy, or whether it was multiplicative or something less dramatic.

Interestingly, risk ratios from groups (epidemiologic studies) were used to describe her individual risks. The defense did not actively challenge this procedure. The premise of Cramer’s approach was that if an individual patient had a previous exposure or lifestyle variable that has been causally associated with ovarian cancer, then those exposures and lifestyle variables all participating in actually causing the patient’s cancer. As noted in the summary of Graham Colditz’s testimony, this assumption by Cramer is disputed. Cramer never attempted to justify the assumption by reference to any body of scientific evidence, or text. For Mrs. Slemp, Cramer opined that talc (as well as obesity and smoking) caused her serous borderline ovarian tumors. This conclusion was driven by his assumption that if Slemp had an exposure to a known cause of ovarian cancer, then it must have played a “substantial” role in causing the cancer.


The defense vigorously challenged Cramer for having failed to discuss causation in his publications. Most of these publications were epidemiologic studies, which did not necessarily provide an opportunity for full-ranging discussions of causal conclusions. Cramer effectively parried by noting that causation is not established by a single study, and single-study reports were not an appropriate vehicle for a full review and analysis of causation. As for his reviews and opinion pieces, Cramer defended his failure to state a clear causal conclusion on grounds that he had urged warning labels for personal talc products, and that a causal conclusion was not needed to justify such a warning because even a potential risk of ovarian cancer outweighed the negligible benefit of using talc in personal hygiene.

The defense plowed on with its claim that many studies lacked statistical significance, but Cramer generally lost defense counsel in technical details. For Cramer’s estimation of Slemp’s ex ante risk ratio from talc exposure, the defense challenged Cramer’s use of a one-tailed test of significance1. Cramer offered a half-hearted defense of a one-sided test in this context, and used the questions as an opportunity to repeat how low the p-value was with respect to the general association between talc and ovarian cancer. Cramer muddied the water by claiming that this calculation was superseded by further refinement of his estimate, which took into account the bilaterality of Slemp’s tumors, which obviated his one-sided confidence interval calculation. Although the details were not entirely forthcoming, the jury would not likely have seen this exchange as anything other than a quibble. The defense’s claim that Cramer had violated the “rules of epidemiology” never got off the ground, and given that the defense never presented an epidemiologist, the claim of counsel never was grounded in actual evidence.

Counterfactual Causation

The most important cross-examination of Dr. Cramer came from both J & J’s and Imerys’ counsel on the issue of counterfactual causation. Defense counsel asked Cramer, in several different ways, whether Ms. Slemp would have avoided having ovarian cancer if she had not used talc. Cramer stridently and belligerently refused to answer the question. The trial judge showed no interest in obtaining an answer to these questions. In the last effort to obtain a response from Cramer on “but for” causation, Cramer simply refused:

“I am not going to opine on the topic because it is not the task I was charged with.”

In other words, plaintiffs’ counsel and Cramer had discussed his inability to answer the counterfactual question, and decided it was simply better not respond to the question altogether. Since Mr. Smith, plaintiffs’ counsel, did not “task” him with counterfactual causation, Cramer was not going to answer it. Cramer’s intransigence was remarkable because the counterfactual question is an important component to causal inference in epidemiologic science. See, e.g., Michael Höfler, “Causal inference based on counterfactuals,” 5 BMC Med. Research Methodology 28 (2005).

In law, as in science, the counterfactual questions put to Cramer, are essential. Conduct or a product cannot be a legal cause of harm unless that cause alone, or acting in concert with other causes, was enough to result in the injury. Although legal treatises speak of “substantial factor,” the American Law Institute (ALI) defined that phrase (outside the context of overdetermined effects) negatively to make clear that “the actor’s negligent conduct is not a substantial factor in bringing about harm to another if the harm would have been sustained even if the actor had not been negligent.” Restatement (Second) of Torts § 432 (1965).

Given the mischief generated by some courts and commentators2 with respect to “substantial factor,” the ALI abandoned the phrase altogether in its most recent Restatement of the law of torts. In the current Restatement, the ALI has emphasized that the imposition of liability require that the harm claimed is one that would not have occurred in the absence of (“but for”) the defendant’s negligent conduct. Restatement (Third) of Torts: Physical and Emotional Harm § 26 cmt. J (2010); see also June v. Union Carbide Corp., 577 F.3d 1234, 1244 (10th Cir. 2009) (no material difference between Second and Third Restatements; holding that ‘‘a defendant cannot be liable to the plaintiff unless its conduct is either (a) a but-for cause of the plaintiff’s injury or (b) a necessary component of a causal set that (probably) would have caused the injury in the absence of other causes.’’).

Dr. Cramer’s refusal to answer the key counterfactual question about talc and Ms. Slemp’s ovarian cancer points to a lawlessness, both scientific and legal, in the proceedings in St. Louis, Missouri.

1 SeeFAQ: What are the differences between one-tailed and two-tailed tests?” Institute for Digital Research and Education.

2 See David A. Fischer, “Insufficient Causes,” 94 Kent. L. J. 277, 277 (2005-06) (criticizing judicial obtuseness in misinterpreting the earlier Restatement’s use of “substantial factor”).

Slemp Trial Part 4 – Graham Colditz

July 22nd, 2017

The Witness

Somehow, in opposition to two epidemiologists presented by the plaintiff in Slemp, the defense managed to call none. The first of the plaintiffs’ two epidemiology expert witnesses was Graham A. Colditz, a physician with doctoral level training in epidemiology. For many years, Colditz was a professor at the Harvard School of Public Health. Colditz left Harvard to become the Niess-Gain Professor at Washington University St. Louis School of Medicine, where he is also the Associate Director for Prevention and Control at the Alvin J. Siteman Cancer Center.

Colditz is a senior epidemiologist, with many book and article publications to his credit. Although he has not published a causal analysis of ovarian cancer and talc, Colditz was an investigator on the well-known Nurses’ Health Study. One of Colditz’s publications on the Nurses’ cohort featured an analysis of talc use and ovarian cancer outcomes.

Although he is not a frequent testifying expert witness, Colditz is no stranger to the courtroom. He was a regular protagonist in the estrogen-progestin hormone replacement therapy (HRT) litigation, which principally involves claims of female breast cancer. Colditz has a charming Australian accent, with a voice tremor that makes him sound older than 63, and perhaps even more distinguished. He charges $1,500 per hour for his testimonial efforts, but is quick to point out that he has given thousands to charity. At his hourly rate, we can be sure he needs tax deductions of some kind.

In discussing his own qualifications, Colditz was low-key and modest except for what seemed like a strange claim that his HRT litigation work for plaintiffs led the FDA to require a boxed warning of breast cancer risk on the package insert for HRT medications. This claim is certainly false, and an extreme instance of post hoc ergo propter hoc. Colditz gilded the lilly by claiming that he does not get involved unless he believes that general causation exists between the exposure or medication and the disease claimed. Since he has only been a plaintiffs’ expert witness, this self-serving claim is quite circular.

The Examinations

The direct and cross-examinations of Dr. Colditz were long and tedious. Most lawyers are reluctant to have an epidemiologists testify at all, and try to limit the length of their examinations, when they must present epidemiologic testimony. Indeed, the defense in Slemp may have opted to present a clinician based upon the prejudice against epidemiologists testifying about quantitative data and analysis. In any event, Colditz’s direct examination went not hours, but days, as did the defense’s cross-examination.

The tedium of the direct examination was exacerbated by the shameless use of leading, loaded, and argumentative questions by plaintiff’s counsel, Allen Smith. A linguistic analysis might well show that Smith spoke 25 to 30 words for every one word spoken by Colditz on direct examination. Even aside from the niceties of courtroom procedure, the direct examination was lacking in aesthetic qualities. Still, it is hard to argue with a $110 million verdict, which cries out for explanation.

There were virtually no objections to Smith’s testifying in lieu of Colditz, with Colditz reduced to just “yes.” Sometimes, Colditz waxed loquacious, and answered, “yes, sir.” From judicial responses to other objections, however, it was clear that the trial court would have provided little control of the leading and argumentative questions.

Smith’s examination also took Colditz beyond the scope of his epidemiologic expertise in to ethics, social policy, and legal requirements of warnings, again without judicial management or control. We learned, over objection, from Colditz of all witnesses that the determination of causation has nothing to do with whether a warning should be given.

The Subject Matter

Colditz was clearly familiar with the subject matter, and allowed Smith to testify for him on a fairly simplistic level. The testimony was a natural outgrowth of his professional interests, and Colditz must have appeared to have been a credible expert witness, especially in a St. Louis courtroom, given that he was in a leadership role at the leading cancer center in that city.

With Smith’s lead, Colditz broached technical issues of bias evaluation, meta-analysis and pooling, which would never be addressed later by a defense expert witness at an equal level of expertise, sophistication, and credibility. Colditz offered criticisms of the Gonzalez (Sister Study) and the latency built into the observation period of that cohort, and he introduced the concept of Berkson bias in some of the case-control studies. Neither of these particular criticisms was rebutted in the defense case, again raising the question whether the defense expert witness, Dr. Huh, a clinician specializing in gynecologic oncology, was an appropriate foil for the line up of plaintiffs’ expert witness. Dr. Colditz was able to talk authoritatively (and in some cases misleadingly) about issues, which Dr. Huh could not contradict effectively, even if he were to have tried.

Colditz characterized his involvement in the talc cases as starting with his conducting a systematic review, undertaken for litigation, but still systematic. As a professor of epidemiology, Colditz should know what a systematic review is, although he never fully described the process on either direct or cross-examinations. No protocol for the systematic review was adduced into evidence. Sadly, the defense expert witness, Dr. Huh, never stated that he had done a systematic review; nor did he offer any criticisms of Dr. Colditz’s systematic review. Indeed, Huh admitted that he had not read Colditz’s testimony. In general, observing Colditz’s testimony after having watched Dr. Huh testify shouted MISMATCH.

The Issues

Statistical Significance

The beginning point of a case such as Slemp, involving a claim that talc causes ovarian cancer, and that it caused her ovarian cancer, is whether there is supporting epidemiology for the claim. As Sir Austin Bradford Hill put it over 50 years ago:

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

Austin Bradford Hill, “The Environment and Disease: Association or Causation?” 58 Proc. Royal Soc’y Med. 295, 295 (1965). Colditz, and plaintiff’s counsel, did not run away from the challenge; they embraced statistical significance and presented an argument for why the association was “clear-cut” (not created by bias or confounding).

In one of his lengthy, leading questions, plaintiffs’ counsel attempted to suggest that statistical significance, or a confidence interval that excluded a risk ratio of 1.0, excluded bias as well as chance. Colditz to his credit broke from the straight jacket of “yes, sirs,” and disagreed as to bias. Smith, perhaps chastised then took a chance and asked an open-ended question about what a confidence interval was. With the bit in his mouth, Colditz managed to describe the observed confidence interval incorrectly as providing the range within which the point estimate would fall 95% of the time if the same study were repeated many times! There is a distribution of 95% confidence intervals, which cover the true parameter 95% of the time, assuming a correct statistical model, random sampling, and no bias or confounding. For the observed confidence interval, the true value is either included or not. Perhaps Colditz was thinking of a prediction interval, but Smith had asked for a definition of a confidence interval, and the jury got non-sense.

Dose Response

Colditz parsed the remaining Bradford Hill factors, and opined that exposure-gradient or dose response was good to have but not necessary to support a causal conclusion. Colditz opined, with respect to whether the statistical assessment of a putative dose-response should include non-exposed women, that the non-exposed women should be excluded. This was one of the few technical issues that Dr. Huh engaged with, in the defense case, but Dr. Colditz was not confronted with any textbooks or writings that cast doubt on his preference for excluding non-users.


Plaintiff’s counsel spent a great deal of time, mostly reading lengthy passages of articles on this or that plausible mechanism for talc’s causing human ovarian cancer, only to have Colditz, with little or no demonstrated expertise in biological mechanism, say “yes.” Some articles discussed that talc use was a modifiable risk and that avoiding perineal talc use “may” reduce ovarian cancer risk. Smith would read (accurately) and then ask Colditz whether he agreed that avoiding talc use would reduce ovarian cancer in women. Colditz himself catches and corrects Smith, some times, but not others.

Smith read from an article that invokes a claim that asbestos (with definition as to what mineral) causes ovarian cancer. Colditz agreed. Smith testified that talc has asbestos in it, and Colditz agreed. Smith read from an article that stated vaguely that talc is chemically similar to asbestos and thus this creates plausibility for a causal connection between talc and cancer. Colditz agreed, without any suggestion that he understands whether or not talc is morphologically similar to asbestos. It seems unlikely that Colditz had any real expertise to offer here, but Smith could not resist touching all bases with Colditz; and the defense did not object or follow up on these excesses.

Smith and Colditz, well mostly Smith, testified that tubal ligation reduces the otherwise observed increased risk of ovarian cancer from talc use. Smith here entrusts Colditz with providing the common-sense explanation. There is no meaningful cross-examination on this “jury friendly” point.


Colditz testifed that the studies, both case-control and cohort studies, were consistent in showing an increased risk of ovarian cancer in association with talc use. Indeed, the studies are mostly consistent; the issue is whether they are consistently biased or consistently showing the true population risk. The defense chose to confront Colditz with the lack of statistical significance in some studies (with elevated risk ratios) as though these studies were inconsistent with the studies that found similar risk ratios, with p-values less than 5%. This confrontation did not go well for the defense, either on cross-examination of Colditz, or on direct examination of Dr. Huh. Colditz backed up his opinion on consistency with the available meta-analyses, which find very low p-values for the summary estimate of risk ratio for talc use and ovarian cancer.

Unlike the Zoloft case1, in which consistency was generated across different end points by cherry picking, the consistency in the talc case was evidenced by a consistent elevation of risk ratios for the same end point, across studies. When subgroups of ovarian cell or tumor types were examined, statistical significance was sometimes lost, but the direction of the risk ratio above one was maintained. Meta-analyses generated summary point estimates with very low p-values.

The Gold Standard

Colditz further gilded the consistency lilly by claiming that the Terry study2, a pooled analysis of available case-control studies, was the “gold standard” in this area of observational epidemiology. Smith and Colditz presented at some length as to how the Cochrane Collaboration has labeled combined “individual patient data” (IPD) analyses as the gold standard. Colditz skimmed over the Cochrane’s endorsement of IPD analyses as having been made in the context of systematic reviews, involving primarily randomized clinical trials, for which IPD analyses allow time-to-event measurements, which can substantially modify observed risk ratios, and even reverse their direction. The case-control studies in the Terry pooled analysis did not have anything like the kind of prospectively collected individual patient data, which would warrant holding the Terry paper up as a “gold standard,” and Terry and her co-authors never made such a claim for their analysis. Colditz’s claim about the Terry study cried out for strong rebuttal, which never came.

The defense should have known that this hyperbolic testimony would be forthcoming, but they seemed not to have a rebuttal planned, other than dismissing case-controls studies generally as smaller than cohort studies. Rather than “getting into the weeds” about the merits of pooled analyses of observational studies, as opposed to clinical trials, the defense continued with its bizarre stance that the cohort studies were better because larger, while ignoring that they are smaller with respect to number of ovarian cancer cases and have less precision than the case-control studies. SeeNew Jersey Kemps Ovarian Cancer – Talc Cases” (Sept. 16, 2016). The defense also largely ignored Colditz’s testimony that exposure data collected in the available cohort studies was of limited value because lacking in details about frequency and intensity of use, and in some cases, collected on only one occasion.

Specific Causation

Colditz disclaimed the ability or intention to offer a specific causation opinion about Ms. Slemp’s ovarian cancer. Nonetheless, Colditz volunteered that “cancer is multifactorial,” which says very little because it says so much. In plaintiffs’ counsel’s hands, this characterization became a smokescreen to indict every possible present risk factor as playing a part in the actual causation of a particular case, such as Ms. Slemp’s case. No matter that the plaintiff was massively obese, and a smoker; every risk factor present must be, by fiat, in the “causal pie.”

But this would seem not to be Colditz’s own opinion. Graham Colditz has elsewhere asserted that an increased risk of disease cannot be translated into the “but-for” standard of causation3:

Knowledge that a factor is associated with increased risk of disease does not translate into the premise that a case of disease will be prevented if a specific individual eliminates exposure to that risk factor. Disease pathogenesis at the individual level is extremely complex.”

Just because a risk factor (assuming it is real and causal) is present does not put in the causal set.


The direct examination of Graham Colditz included scurrilous attacks on J & J’s lobbying, paying FDA user fees, and other corporate conduct, based upon documents of which Colditz had not personal knowledge. Colditz was reduced to nothing more than a backboard, off which plaintiff’s counsel could make his shots. On cross, the defense carefully dissected this direct examination and obtained disavowals from Colditz that he had suggested any untoward conduct by J & J. The jury could have been spared their valuable time by a trial judge who did not allow the scurrilous, collateral attacks in the first place.

The defense also tried to diminish Dr. Colditz’s testimony as an opinion coming from a non-physician. The problem, however, was that Colditz is a physician, who understands the biological issues, even if he is not a pathologist, toxicologist, or oncologist. Colditz did not offer opinions about Slemp’s medical treatment, and there was nothing in this line of cross-examination that lessened the impact of Colditz’s general causation testimony.

Generally, the cross-examination did not hurt Dr. Colditz’s strongly stated opinion that talc causes ovarian cancer. The defense (and plaintiff’s counsel before them) spent an inordinate amount of time on why Dr. Colditz has not updated his website to state publicly that talc causes ovarian cancer. Colditz blamed the “IT” guys, a rather disingenuous excuse. His explanation on direct, and on cross, as to why he could not post his opinion on his public-service website was so convoluted, however, that there was no clear admission or inference of dereliction. Colditz was permitted to bill his opinion, never posted to his institution’s website, as a “consensus opinion,” endorsed by several researchers, based upon hearsay emails and oral conversations.

1 See In re Zoloft Prod. Liab. Litig., No. 16-2247 , __ F.3d __, 2017 WL 2385279, 2017 U.S. App. LEXIS 9832 (3d Cir. June 2, 2017) (affirming exclusion of dodgy opinion, which involved changing subgroup end points across studies of maternal sertraline use and infant cardiac birth defects ).

2 Kathryn L. Terry, et al., “Genital powder use and risk of ovarian cancer: a pooled analysis of 8,525 cases and 9,859 controls,” 6 Cancer Prev. & Research 811 (2013).

3 Graham A. Colditz, “From epidemiology to cancer prevention: implications for the 21st Century,” 18 Cancer Causes Control 117, 118 (2007).

Slemp Trial Part 3 – The Defense Expert Witness – Huh

July 9th, 2017

On June 19, 2017, the U.S. Supreme Court curtailed the predatory jurisdictional practices of the lawsuit industry in seeking out favorable trial courts with no meaningful connection to their claims. See Bristol-Myers Squib Co. v. Superior Court, No. 16-466, 582 U.S. ___ (June 19, 2017). The same day, the defendants in a pending talc cancer case in St. Louis filed a motion for a mistrial. Swann v. Johnson & Johnson, Case No. 1422-CC09326-01, Division 10, Circuit Court of St. Louis City, Missouri. Missouri law may protect St. Louis judges from having to get involved in gatekeeping scientific expert witness testimony, but when the Supreme Court speaks to the requirements of the federal constitution’s due process clause, even St. Louis judges must listen. Bristol-Myers held that the constitution limits the practice of suing defendants in jurisdictions unrelated to the asserted claims, and the St. Louis trial judge, Judge Rex Burlison, granted the requested mistrial in Swann. As a result, there will not be another test of plaintiffs’ claims that talc causes ovarian cancer, and the previous Slemp case will remain an important event to interpret.

The Sole Defense Expert Witness

Previous posts1 addressed some of the big picture issues as well as the opening statements in Slemp. This posts turns to the defense expert witness, Dr. Walter Huh, in an attempt to understand how and why the jury returned its egregious verdict. Juries can, of course, act out of sympathy, passion, or prejudice, but their verdicts are usually black boxes when it comes to discerning their motivations and analyses. A more interesting and fruitful exercise is to ask whether a reasonable jury could have reached the conclusion in the case. The value of this exercise is limited, however. A reasonable jury should have reasonable expertise in the subject matter, and in our civil litigation system, this premise is usually not satisfied.

Dr. Walter Huh, a gynecologic oncologist, was the only expert witness who testified for the defense. As the only defense witness, and as a clinician, Huh had a terrible burden. He had to meet and rebut testimony outside his fields of expertise, including pathology, toxicology, and most important, epidemiology. Huh was by all measures well-spoken, articulate, and well-qualified as a clinical gynecologic oncologist. Defense counsel and Huh, however, tried to make the case that Huh was qualified to speak to all issues in the case. The initial examination on qualifications was long and tedious, and seemed to overcompensate for the obvious gaps in Dr. Huh’s qualifications. In my view, the defense never presented much in the way of credible explanations about where Huh had obtained the training, experience, and expertise to weigh in on areas outside clinical medicine. Ultimately, the cross-examination is the crucial test of whether this strategy of one witness for all subjects can hold. The cross-examination of Dr. Huh, however, exposed the gaps in qualifications, and more important, Dr. Huh made substantive errors that were unnecessary and unhelpful to the defense of the case.

The defense pitched the notion that Dr. Huh somehow trumped all the expert witnesses called by plaintiff because Huh was the “only physician heard by the jury” in court. Somehow, I wonder whether the jury was so naïve. It seems like a poor strategic choice to hope that the biases of the jury in favor of the omniscience of physicians (over scientists) will carry the day.

There were, to be sure, some difficult clinical issues, on which Dr. Huh could address within his competence. Cancer causation itself is a multi-disciplinary science, but in the case of a disease, such as ovarian cancer, with a substantial base-rate in the general population and without any biomarker of a causal pathway between exposure and outcome, epidemiology will be a necessary tool. Huh was thus forced to “play” on the plaintiffs’ expert witnesses’ home court, much to his detriment.

General Causation

Don’t confuse causation with links, association, and risk factors

The defense strong point is that virtually no one, other than the plaintiffs’ expert witnesses themselves, and only in the context of litigation, has causally attributed ovarian cancer to talc exposure. There are, however, some ways that this point can be dulled in the rough and tumble of trial. Lawyers, like journalists, and even some imprecise scientists, use a variety of terms such as “risk,” “risk factor,” “increased risk,” and “link,” for something less than causation. Sometimes these terms are used deliberately to try to pass off something less than causation as causation; sometimes the speaker is confused; and sometimes the speaker is simply being imprecise. It seems incumbent upon the defense to explain the differences between and among these terms, and to stick with a consistent, appropriate terminology.

One instance in which Dr. Huh took his eye off the “causation ball,” arose when plaintiffs’ counsel showed him a study conclusion that talc use among African American women was statistically significantly associated with ovarian cancer. Huh answered, non-responsively, “I disagree with the concept that talc causes ovarian cancer.” The study, however, did not advance a causal conclusion and there was no reason to suggest to the jury that he disagreed with anything in the paper; rather it was the opportunity to repeat that association is not causation, and the article did not contradict anything he had said.

Similarly, Dr. Huh was confronted with several precautionary recommendations that women “may” benefit from avoiding talc. Remarkably, Huh simply disagreed, rather than making the obvious point that the recommendation was not stated as something that would in fact benefit women.

When witnesses answer long, involved questions, with a simple “yes,” then they may have made every implied proposition in the questions into facts in the case. In an exchange between plaintiff’s counsel and Huh, counsel asked whether a textbook listed talc as a risk factor.2 Huh struggled to disagree, which disagreement tended to impair his credibility, for disagreeing with a textbook he acknowledged using and relying upon. Disagreement, however, was not necessary; the text merely stated that “talc … may increase risk.” If “increased risk” had been defined and explained as something substantially below causation, then Huh could have answered simply “yes, but that quotation does not support a causal claim.”

At another point, plaintiffs’ counsel, realizing that none of the individual studies reached a causal conclusion, asked whether it would be improper for a single study to give such a conclusion. It was a good question, with a solid premise, but Dr. Huh missed the opportunity for explaining that the authors of all the various individual studies had not conducted systematic reviews that advanced the causal conclusion that plaintiffs would need. Certainly, the authors of individual studies were not prohibited from taking the next step to advance a causal conclusion in a separate paper with the appropriate analysis.

Bradford Hill’s Factors

Dr. Huh’s testimony provided the jury with some understanding of Sir Austin Bradford Hill’s nine factors, but Dr. Huh would have helped himself by acknowledging several important points. First, as Hill explained, the nine factors are invoked only after there is a clear-cut (valid) association beyond that which we care to attribute to chance. Second, establishing all nine factors is not necessary. Third, some of the nine factors are more important than others.

Study validity

In the epidemiology of talc and ovarian cancer, statistical power and significance are not the crucial issues; study validity is. It should have been the plaintiff’s burden to rule out bias, and confounding, as well as chance. Hours had passed in the defense examination of Dr. Huh before study validity was raised, and it was never comprehensively explained. Dr. Huh explained recall bias as a particular problem of case-control studies, which made up the bulk of evidence upon which plaintiffs’ expert witnesses relied. A more sophisticated witness on epidemiology might well have explained that the selection of controls can be a serious problem without obvious solutions in case-control studies.

On cross-examination, plaintiffs’ counsel, citing Kenneth Rothman, asked whether misclassification bias always yields a lower risk ratio. Dr. Huh resisted with “not necessarily,” but failed to dig in whether the conditions for rejecting plaintiffs’ generalization (such as polychotomous exposure classification) obtained in the relevant cohort studies. More importantly, Huh missed the opportunity to point out that the most recent, most sophisticated cohort study reported a risk ratio below 1.0, which on the plaintiffs’ theory about misclassification would have been even lower than 1.0 than reported in the published paper. Again, a qualified epidemiologist would not have failed to make these points.

Dr. Huh never read the testimony of one of the plaintiffs’ expert witnesses on epidemiology, Graham Colditz, and offered no specific rebuttal of Colditz’s opinions. With respect to the other of plaintiffs’ epidemiology expert witness, Dr. Cramer, Huh criticized him for engaging in post-hoc secondary analyses and asserted that Cramer’s meta-analysis could not be validated. Huh never attempted to validate the meta-analysis himself; nor did Huh offer his own meta-analysis or explain why a meta-analysis of seriously biased studies was unhelpful. These omissions substantially blunted Huh’s criticisms.

On the issue of study validity, Dr. Huh seem to intimate that cohort studies were necessarily better than case-control studies because of recall bias, but also because there are more women involved in the cohort studies than in the case-control studies. The latter point, although arithmetically correct, is epidemiologically bogus. There are often fewer ovarian cancer cases in the cohort study, especially if the cohort is not followed for a very long time. The true test comes in the statistical precision of the point estimate, relative risk or odds ratio, in the different type of study. The case-control studies often generate much more precise point estimates as seen from their narrower confidence intervals. Of course, the real issue is not precision here, but accuracy.  Still, Dr. Huh appeared to have endorsed the defense counsel misleading argument about study size, a consideration that will not help the defense when the contentions of the parties are heard in scientific fora.

Statistical Significance

Huh appeared at times to stake out a position that if a study does not have statistical significance, then we must accept the null hypothesis. I believe that most careful scientists would reject this position. Null studies simply fail to reject the null hypothesis.

Although there seems to be no end to fallacious reasoning by plaintiffs, there is a particular defense fallacy seen in some cases that turn on epidemiology. What if we had 10 studies that each found an elevated risk ratio of 1.5, with two-tailed 95 percent confidence intervals of 0.92 – 2.18, or so. Can the defense claim victory because no study is statistically significant? Huh seemed to suggest so, but this is clearly wrong. Of course, we might ask why no one conducted the 11th study, with sufficient power to detect a risk ratio of 1.5, at the desired level of significance. But parties go to trial with the evidence they have, not what they might want to have. On the above 10-study hypothetical, a meta-analysis might well be done (assuming the studies could be appropriately included), and the summary risk ratio for all studies would be 1.5, and highly statistically significant.

On the question of talc and ovarian cancer, there were several meta-analyses at issue, and so the role of statistical significance of individual studies was less relevant. The real issue was study validity. This issue was muddled by assertions that risk ratios such as 2.05 (95%, 0.94 – 4.47) were “chance findings.” Chance may not have been ruled out, but the defense can hardly assert that chance and chance alone produced the findings; otherwise, it will be sunk by the available meta-analyses.

Strength of Association

The risk ratios involved in most of the talc ovarian cancer studies are small, and that is obviously an important factor to consider in evaluating the studies for causal conclusions. Still, it is also obvious that sometimes real causal associations can be small in magnitude. Dr Huh could and should have conceded in direct that small associations can be causal, but explained that validity concerns about the studies that show small associations become critical. Examples would have helped, such as the body of observational epidemiology that suggested that estrogen replacement therapy in post-menopausal women provided cardiovascular benefit, only to be reversed by higher quality clinical trials. Similarly, observational studies suggested that lung cancer rates were reduced by Vitamin A intake, but again clinical trial data showed the opposite.

Consistency of Studies

Are studies that have statistically non-significant risk ratios above 1.0 inconsistent with studies that find statistically significant elevated risk ratios? At several points, Huh appears to say that such a group of studies is inconsistent, but that is not necessarily so. Huh’s assertion provoked a good bit of harmful cross-examination, in which he seemed to resist the notion that meta-analysis could help answer whether a group of studies is statistically consistent. Huh could have conceded the point readily but emphasized that a group of biased studies would give only a consistently biased estimate of association.


One of the cheapest tricks in the trial lawyers’ briefcase is the “learned treatise” exception to the rule against hearsay.”3 The lawyer sets up witnesses in deposition by obtaining their agreement that a particular author or text is “authoritative.” Then at trial, the lawyer confronts the witnesses with a snippet of text, which appears to disagree with the expert witnesses’ testimony. Under the rule, in federal and in some state courts, the jury may accept the snippet or sound bite as true, and also accept that the witnesses do not know what they are talking about when they disagree with the “authoritative” text.

The rule is problematic and should have been retired long ago. Since 1663, the Royal Society has sported the motto:  “Nullius in verba.”  Disputes in science are resolved with data, from high-quality, reproducible experimental or observational studies, not with appeals to the prestige of the speaker. And yet, we lawyers will try, and sometimes succeed, with this greasy kidstuff approach cross-examination. Indeed, when there is an opportunity to use it, we may even have an obligation to use so-called learned treatises to advance our clients’ cause.

In the Slemp trial, the plaintiff’s counsel apparently had gotten a concession from Dr. Huh that plaintiff’s expert witness on epidemiology, Dr. Daniel Cramer, was “credible and authoritative.” Plaintiff’s counsel then used Huh’s disagreement with Cramer’s testimony as well as his published papers to undermine Huh’s credibility.

This attack on Huh was a self-inflicted wound. The proper response to a request for a concession that someone or some publication is “authoritative,” is that this word really has no meaning in science. “Nullius in verba,” and all that. Sure, someone can be a respected research based upon past success, but past performance is no guarantee of future success. Look at Linus Pauling and Vitamin C. The truth of a conclusion rests on the data and the soundness of the inferences therefrom.

Collateral Attacks

The plaintiff’s lawyer in Slemp was particularly adept at another propaganda routine – attacking the witness on the stand for having cited another witness, whose credibility in turn was attacked by someone else, even if that someone else was a crackpot. Senator McCarthy (Joseph not Eugene) would have been proud of plaintiff’s lawyer’s use of the scurrilous attack on Paolo Boffetta for his views on EMF and cancer, as set out in Microwave News, a fringe publication that advances EMF-cancer claims. Now, the claim that non-ionizing radiation causes cancer has not met with much if any acceptance, and Boffetta’s criticisms of the claims are hardly unique or unsupported. Yet plaintiff’s counsel used this throw-away publication’s characterization of Boffetta as “the devil’s advocate,” to impugn Boffetta’s publications and opinions on EMF, as well as Huh’s opinions that relied upon some aspect of Boffetta’s work on talc. Not that “authority” counts, but Boffetta is the Associate Director for Population Sciences of the Tisch Cancer Institute and Chief of the Division of Cancer Prevention and Control of the Department of Oncological Sciences, at the Mt. Sinai School of Medicine in New York. He has published many epidemiologic studies, as well as a textbook on the epidemiology of cancer.4

The author from the Microwave News was never identified, but almost certainly lacks the training, experience, and expertise of Paolo Boffetta. The point, however, is that this cross-examination was extremely collateral, had nothing to do with Huh, or the issues in the Slemp case, and warranted an objection and admonition to plaintiff’s counsel for the scurrilous attack. An alert trial judge, who cared about substantial justice, might have shut down this frivolous, highly collateral attack, sua sponte. When Huh was confronted with the “devil’s advocate” characterization, he responded “OK,” seemingly affirming the premise of the question.

Specific Causation

Dr. Huh and the talc defendants took the position that epidemiology never informs assessment of individual causation. This opinion is hard to sustain. Elevated risk ratios reflect more individual cases than expected in a sample. Epidemiologic models are used to make individual predictions of risk for purposes of clinical monitoring and treatment. Population-based statistics are used to define range of normal function and to assess individuals as impaired or disabled, or not.

At one point in the cross-examination, plaintiffs’ counsel suggested the irrelevance of the size of relative risk by asking whether Dr. Huh would agree that a 20% increased risk was not small if you are someone who has gotten the disease. Huh answered “Well, if it is a real association.” This answer fails on several levels. First, it conflates “increased risk” and “real association” with causation. The point was for Huh to explain that an increased risk, if statistically significant, may be an association, but it is not necessary causal.

Second, and equally important, Huh missed the opportunity to explain that even if the 20% increased risk was real and causal, it would still mean that an individual patient’s ovarian cancer was most likely not caused by the exposure. See David H. Schwartz, “The Importance of Attributable Risk in Toxic Tort Litigation,” (July 5, 2017).


The defense strategy of eliciting all their scientific and medical testimony from a single witness was dangerous at best. As good a clinician as Dr. Huh appears to be, the defense strategy did not bode well for a good outcome when many of the scientific issues were outside of Dr. Huh’s expertise.

2 Jonathan S. Berek & Neville F. Hacker, Gynecologic Oncology at 231 (6th ed. 2014).

3 SeeTrust-Me Rules of Evidence” (Oct. 18 2012).

4 See, e.g., Paolo Boffetta, Stefania Boccia, Carol La Vecchia, A Quick Guide to Cancer Epidemiology (2014).