Slemp Trial Part 3 – The Defense Expert Witness – Huh

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).

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