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

Statistical Analysis Requires an Expert Witness with Statistical Expertise

November 13th, 2016

Christina K. Connearne sued her employer, Main Line Hospitals, for age discrimination. Main Line charged Connearne with fabricating medical records, but Connearne replied that the charge was merely a pretext. Connearney v. Main Line Hospitals, Inc., Civ. Action No. 15-02730, 2016 WL 6569292 (E.D. Pa. Nov. 4, 2016) [cited as Connearney]. Connearne’s legal counsel engaged Christopher Wright, an expert witness on “human resources,” for a variety of opinions, most of which were not relevant to the action. Alas, for Ms. Connearne, the few relevant opinions proffered by Wright were unreliable. On a Rule 702 motion, Judge Pappert excluded Wright from testifying at trial.

Although not a statistician, Wright sought to offer his statistical analysis in support of the age discrimination claim. Connearney at *4. According to Judge Pappert’s opinion, Wright had taken just two classes in statistics, but perhaps His Honor meant two courses. (Wright Dep., at 10:3–4.) If the latter, then Wright had more statistical training than most physicians who are often permitted to give bogus statistical opinions in health effects litigation. In 2015, the Medical College Admission Test apparently started to include some very basic questions on statistical concepts. Some medical schools now require an undergraduate course in statistics. See Harvard Medical School Requirements for Admission (2016). Most medical schools, however, still do not require statistical training for their entering students. See Veritas Prep, “How to Select Undergraduate Premed Coursework” (Dec. 5, 2011); “Georgetown College Course Requirements for Medical School” (2016).

Regardless of formal training, or lack thereof, Christopher Wright demonstrated a profound ignorance of, and disregard for, statistical concepts. (Wright Dep., at 10:15–12:10; 28:6–14.) Wright was shown to be the wrong expert witness for the job by his inability to define statistical significance. When asked what he understood to be a “statistically significant sample,” Wright gave a meaningless, incoherent answer:

I think it depends on the environment that you’re analyzing. If you look at things like political polls, you and I wouldn’t necessarily say that serving [sic] 1 percent of a population is a statistically significant sample, yet it is the methodology that’s used in the political polls. In the HR field, you tend to not limit yourself to statistical sampling because you then would miss outliers. So, most HR statistical work tends to be let’s look at the entire population of whatever it is we’re looking at and go from there.”

Connearney at *5 (Wright Dep., at 10:15–11:7). When questioned again, more specifically on the meaning of statistical significance, Wright demonstrated his complete ignorance of the subject:

Q: And do you recall the testimony it’s generally around 85 to 90 employees at any given time, the ER [emergency room]?

A: I don’t recall that specific number, no.

Q: And four employees out of 85 or 90 is about what, 5 or 6 percent?

A: I’m agreeing with your math, yes.

Q: Is that a statistically significant sample?

A: In the HR [human resources] field it sure is, yes.

Q: Based on what?

A: Well, if one employee had been hit, physically struck, by their boss, that’s less than 5 percent. That’s statistically significant.”

Connearney at *5 n.5 (Wright Dep., at 28:6–14)

In support of his opinion about “disparate treatment,” Wright’s report contained nothing than a naked comparison of two raw percentages and a causal conclusion, without any statistical analysis. Even for this simplistic comparison of rates, Wright failed to explain how he obtained the percentages in a way that permitted the parties and the trial court to understand his computation and his comparisons. Without a statistical analysis, the trial court concluded that Wright had failed to show that the disparity in termination rates among younger and older employees was not likely consistent with random chance. See also Moultrie v. Martin, 690 F. 2d 1078 (4th Cir. 1982) (rejecting writ of habeas corpus when petitioner failed to support claim of grand jury race discrimination with anything other than the numbers of white and black grand jurors).

Although Wright gave the wrong definition of statistical significance, the trial court relied upon judges of the Third Circuit who also did not get the definition quite right. The trial court cited a 2010 case in the Circuit, which conflated substantive and statistical significance and then gave a questionable definition of statistical significance:

The Supreme Court has not provided any definitive guidance about when statistical evidence is sufficiently substantial, but a leading treatise notes that ‘[t]he most widely used means of showing that an observed disparity in outcomes is sufficiently substantial to satisfy the plaintiff’s burden of proving adverse impact is to show that the disparity is sufficiently large that it is highly unlikely to have occurred at random.’ This is typically done by the use of tests of statistical significance, which determine the probability of the observed disparity obtaining by chance.”

See Connearney at *6 & n.7, citing and quoting from Stagi v. National RR Passenger Corp., 391 Fed. Appx. 133, 137 (3d Cir. 2010) (emphasis added) (internal citation omitted). Ultimately, however, this was all harmless error on the way to the right result.

Benhaim v. St. Germain – Supreme Court of Canada Wrestles With Probability

November 11th, 2016

On November 10, 2016, the Supreme Court of Canada handed down a divided (four-to-three decision) in a medical malpractice case, which involved statistical evidence, or rather probabilistic inference. Benhaim v. St-Germain, 2016 SCC 48 (Nov. 10, 2016).  The case involved an appeal from a Quebec trial court, and the Quebec Court of Appeal, and some issues peculiar to Canadian lawyers. For one thing, Canadian law does not appear to follow lost-chance doctrine outlined in the American Law Institute’s Restatement. The consequence seems to be that negligent omissions in the professional liability context are assessed for their causal effect by the Canadian “balance of probabilities” standard.

The facts were reasonably clear, although their interpretation were disputed. In November 2005, Mr. Émond was 44 years old, a lifelong non-smoker, and in good health. At his annual physical with general practitioner Dr. Albert Benhaim, Émond had a chest X-ray (CXR). Benhaim at 11, 6. Remarkably, neither the majority nor the dissent commented upon the lack of reasonable medical necessity for a CXR in a healthy, non-smoking 40-something male. Few insurers in the United States would have paid for such a procedure. Maybe Canadian healthcare is more expansive than what we see in the United States.

The radiologist reviewing Mr. Émond’s CXR reported a 1.5 to 2.0 cm solitary lesion, and suggested a review with previous CXRs and a recommendation for a CT scan of the thorax. Dr. Benhaim did not follow the radiologist’s suggestions, but Mr. Émond did have a repeat CXR two months later, on January 17, 2006, which was interpreted as unchanged. A recommendation for a follow-up third CXR in four months was not acted upon. Benhaim at 11, 7. The trial court found that the defendant physicians deviated from the professional standard of care, a finding from which there was no appeal.

Mr. Émond did have a follow-up CXR at the end of 2006, on December 4, 2006, which showed that the solitary lung nodule had grown. Follow up CT and PET scans confirmed that Mr. Émond had Stage IV lung cancer. Id.

The issues in controversy turned on the staging of Mr. Émond’s lung cancer at the time of his first CXR, in November 2005, the medical consequences of the delay in diagnosis. Plaintiffs presented expert witness opinion testimony that Mr. Émond’s lung cancer was only Stage I (or at most IIA), at initial radiographic discovery of a nodule, and that he was at Stage III or IV in December 2006, when CT and PET scans confirmed the actual diagnosis of lung cancer. In the view of plaintiff’s expert witnesses, the delay in diagnosis, and the accompanying growth of the tumor and change from Stage I to IV, dramatically decreased Émond’s chance of survival. Id. At 13, 15-16. Indeed, plaintiff’s expert witnesses opined that had Mr. Émond been timely diagnosed and treated in November 2005, he probably would have been cured.

The defense expert witness, Dr. Ferraro, testified that Mr. Émond’s lung cancer was Stage III or IV in November 2005, when the radiographic nodule was first seen, and his chances of survival at that time were already quite poor. According to Dr. Ferraro, earlier intervention and treatment would probably not have been successful in curing Mr. Émond, and the delay in diagnosis was not a cause of his death.

The trial court rejected plaintiffs’ expert witnesses’ opinions on factual grounds. These witnesses had argued that Mr. Émond’s lung cancer was at Stage I in November 2005 because the lung nodule was less than 3 cm., and because Mr. Émond was asymptomatic and in good health. These three points of contention were clearly unreliable because they were all present in January 2007, when Mr. Émond was diagnosed with Stage IV cancer, according to all the expert witnesses. Every point cited by plaintiffs’ expert witnesses in support of their staging failed to discriminate Stage I from Stage III. In Her Honor’s opinion, the lung cancer was probably Stage III in November 2005, and this staging implied a poor prognosis on all the expert witnesses’ opinions. The failure to diagnose until late 2006 was thus not, on the “balance of probabilities” a cause of death. Id. At 15, ¶21.

The intermediate appellate court reversed on grounds of a presumption of causation, which comes into being when the defendant’s negligence interferes with plaintiff’s ability to show causation, and there is some independent evidence of causation to support the case. I will leave this presumption, which the Supreme Court of Canada held inappropriate on the facts of this case, to Canadian lawyers to debate. What was more interesting was the independent evidence adduced by plaintiffs. This evidence consisted of statistical evidence in the form of generality that 78 percent of fortuitously discovered lung cancers are at Stage I, which in turn is associated with a cure rate of 70 percent. Id. at 18 30.

The plaintiffs’ witnesses hoped to apply this generality to this case, notwithstanding that Émond’s nodule was close to 2 cm. on CXR, that the general statistic was based up more sensitive CT studies, and that Émond had been a non-smoker (which may have influenced tumor growth and staging). Furthermore, there was an additional, ominous finding in Mr. Émond’s first CXR, of hilar prominence, which supported the defense’s differentiation of his case from the generality of fortuitously discovered (presumably small, solitary lung nodules without hilar involvement). Id. at 44 83.

The trial court rejected the inference from the group statistic of 70% survival to the conclusion that Mr. Émond had a 70% probability of survival. Tellingly, there was no discussion of the variance for the 70% figure; nor any mention of relevant subgroups. The Court of Appeals, however, would have turned this statistic into a binding presumption by virtue of accepting the 78 percent as providing strong evidencec that the 70% survival figure pertained to Mr. Émond. The intermediate appellate court would then have taken the group survival rate as providing a more likely than not conclusion about Mr. Émond, while rejecting the defense expert witness’s statistics as mere speculation. Id. at 36 ¶67.

Adopting a skeptical stance with respect to probabilistic evidence, the Supreme Court reversed the Quebec Court of Appeal’s reversal of the trial court’s judgment. The Court cited Richard Wright and Jonathan Cohen’s criticisms of probabilistic evidence (and Cohen’s Gatecrasher’s Paradox), and urged caution in applying class or group statistics to generate probabilities that class members share the group characteristic.

Appellate courts should generally not interfere with a trial judge’s decision not to draw an inference from a general statistic to a particular case. Statistics themselves are silent about whether the particular parties before the court would have conformed to the trend or been an exception from it. Without an evidentiary bridge to the specific circumstances of the plaintiff, statistical evidence is of little assistance. For this reason, such general trends are not determinative in particular cases. What inferences follow from such evidence — whether the generalization that a statistic represents is instantiated in the particular case — is a matter for the trier of fact. This determination must be made with reference to the whole of the evidence.”

Benhaim at 39, 74, 75 (internal citations omitted).

To some extent, the Supreme Court’s comments about statistical evidence were rather wide of there mark. The 78% statistic was based upon a high level of generality, namely all cases, without regard for the size of the radiographically discovered lesion, the manner of discovery (CXR versus CT), presence or absence of hilar pathology, or group or individual’s smoking status. In the context of the facts of the case, however, the trial court clearly had a factual basis for resisting the application of the group statistic (78% fortuitously discovered tumors were Stage I with 70% five-year survival).

The Canadian Supreme Court seems to have navigated these probabilistic waters fairly adeptly, although the majority opinion contains broad brush generalities and inaccuracies, which will, no doubt, show up in future lower court cases. For instance:

This is because the law requires proof of causation only on a balance of probabilities, whereas scientific or medical experts often require a higher degree of certainty before drawing conclusions on causation (p. 330). Simply put, scientific causation and factual causation for legal purposes are two different things.”

Benhaim at 24, 47. The Court cited legal precedent for its observation, and not any scientific treatises. And then, the Supreme Court suggested that all one needs to prevail in a tort case in Canada is a medical expert witness who speculates:

Trial judges are empowered to make legal determinations even where medical experts are not able to express an opinion with certainty.

Benhaim at 37, 72Clearly dictum on the facts of Benhaim, but it seems that judges in Canada are like those in the United States. Black robes empower them to do what mere scientists could not do. If we were to ignore the holding of Benhaim, we might think that all one needs in Canada is a medical expert who speculates.

Talc Litigation – Stop the Madness

November 10th, 2016

Back in September, Judge Johnson, of New Jersey, wrapped up a talc ovarian cancer case in Kemp, and politely excused the case from any further obligations to show up in court. Carl v. Johnson & Johnson, No. ATL-L-6546-14, 2016 WL 4580145 (N.J. Super. Ct. Law Div., Atl. Cty., Sept. 2, 2016) [cited as Carl]. See “New Jersey Kemps Ovarian Cancer – Talc Cases” (Sept. 16, 2016).

In Giannecchini v. Johnson & Johnson, a Missouri jury returned a substantial verdict for plaintiff. The jury, by a 9 to 3 vote, awarded $575,000 for claimed economic loss, and $2 million for non-economic compensatory damages. The jury also found defendant Johnson & Johnson in need of punishment to the tune of $65,000,000, and Imerys Talc America Inc. for $2.5 million. Plaintiffs, having sought $285 million, were no doubt disappointed. The Giannecchini verdict was the third large verdict in the Missouri talc litigation. See Myron Levin, “Johnson & Johnson Hammered Again in Talc-Ovarian Cancer Verdict of $70 Million,” (Oct. 27, 2016); Brandon Lowrey, “J & J, Talc Co. Hit With $70M Baby Powder Cancer Verdict,” Law360 (Oct. 2016).

In his closing argument, Giannecchini’s lawyer, R. Allen Smith, reportedly accused Johnson & Johnson of having “rigged” regulatory agencies to ignore the dangers of talc, and of having “falsified” medical records to hide the problem. Smith implored the jury to “make them stop”; make them “stop this madness.”

Make them stop the madness, indeed. The November 2016 issue of Epidemiology features a publication of the “Sister Study,” which explored whether there was any association between perineal talc use and ovarian cancer. The authors acknowledged, as had Judge Johnson in the Carl case, that some prior case-control studies had found an increased risk of ovarian cancer, but that prospective cohort studies have not confirmed an association. Nicole L. Gonzalez, Katie M. O’Brien, Aimee A. D’Aloisio, Dale P. Sandler, and Clarice R. Weinberg, “Douching, Talc Use, and Risk of Ovarian Cancer,” 27 Epidemiology 797 (2016).

The Sister Study (2003–2009) followed a cohort of 50,884 women whose sisters had been diagnosed with breast cancer. Talc use was ascertained at baseline, before diagnosis of subsequent disease and before any chance for selective recall. The cohort was followed for a median of 6.6 years, in which time there were 154 cases of ovarian cancer during the follow up, available for analysis using Cox’s proportional hazards model. Perineal talc use at baseline was not associated with later ovarian cancer. The authors reported a hazard ratio of 0.73, less than expected, with a 95% confidence interval of 0.44, 1.2.

So, yes, make them stop this madness; close the gate.

Jersey Devil and the Occult (Asbestos)

November 7th, 2016

Amosite Mine in Collingswood, New Jersey

Amosite is a commercial term for the fibrous mineral grunerite (Fe7Si8O22(OH)2). Grunerite and its fibrous form, amosite, does not occur naturally in the sedimentary terrain of southern New Jersey.

And yet, my son and I encountered a treasure trove of amosite in the attic of a house on East Franklin Avenue, in Collingswood, New Jersey, not far from the Cooper River. We were within 24 hours of buying a house to renovate, when an astute building inspector called our attention to unusual attic insulation.1 Most houses built right after World War I have no insulation, or perhaps cork insulation between the attic joists. This house had loose, greyish-brown tufted fibrous material several inches thick spread across the entire attic floor. A local analytical laboratory confirmed that the loose mineral fiber was largely amosite.2

Asbestos in Attic1

The where, when, how, and why there were many cubic yards of amosite in the attic of a house in Collingswood is a mystery, but one clue is that there are several shipyards nearby, including what once was the New York Shipbuilding & Dry Dock, the Philadelphia Naval Shipyard, and Cramps Shipyard. My unverified hunch is that after World War II, these shipyards gave away, or sold, loose amosite asbestos, which was no longer needed, and the use of which was discouraged by Naval regulations in favor of molded, pre-formed asbestos-containing insulation. The presence of such loose, fibrous amphibole asbestos in residential construction raises serious issues for exposure assessment in epidemiologic studies and in litigation cases, both of which proceed on the glib assumption that workplace exposures are the only meaningful asbestos exposures to be measured. Occult exposure to amosite or even worse, crocidolite, may well explain any number of isolated “black swan” cases of mesothelioma among workers with limited exposure to chrysotile. The amosite in the house’s attic was truly occult – hidden and scary – to the sellers of the house and to use as potential buyers.3 The contract for the sale of the house fell apart over the sellers’ and buyers’ inability to agree upon what the appropriate remediation would be.

One of the serious disservices performed by Dr. Irving Selikoff was his conflation of the various asbestos mineral types as equally dangerous.4 His motivation was quite transparent. He and his staff were working closely with plaintiffs’ counsel, and other plaintiffs’ expert witnesses, in asbestos personal injury and property damages lawsuits. Although the amphibole asbestos minerals were known to be much more dangerous than chrysotile (white asbestos), the mining and distributing companies were mostly South African, and judgment proof in United States courts. The lawsuit industry required propagating the myth of equal risk in order to keep the chrysotile mining and milling companies from avoiding liability by drawing scientific comparisons between and among the different fiber Despicable Me 3

1 Inspections Plus, LLC, Clementon, New Jersey 08021.

EMSL Analytical, Inc., 200 Route 130 North, Cinnaminson, NJ 08077.

See alsoAsbestos isn’t just in old fibro sheeting it can be in everything from fences to carpets,” The Courier Mail (No. 28, 2015) (“Bulk loose fill insulation is now rarely found but may be encountered unexpectedly, e.g. DIY lost insulation and fire-stop packing around cables between floors.”).

SeeHide the Substantial Factors in Asbestos Litigation”; “Selikoff and the Mystery of the Disappearing Amphiboles.”