TORTINI

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

Differential Etiology and Other Courtroom Magic

June 23rd, 2014

ITERATIVE DISJUNCTIVE SYLLOGISM

Basic propositional logic teaches that the disjunctive syllogism (modus tollendo ponens) is a valid argument, in which one of its premises is a disjunction (P v Q), and the other premise is the negation of one of the disjuncts:

P v Q

~P_____

∴ Q

See Irving Copi & Carl Cohen Introduction to Logic at 362 (2005). If we expand the disjunctive premise to more than one disjunction, we can repeat the inference (iteratively), eliminating one disjunct at a time, until we arrive at a conclusion that is a simple, affirmative proposition, without any disjunctions in it.

P v Q v R

~P_____

∴ Q v R

~Q_____

∴ R

Hence, the term, “iterative disjunctive syllogism.” Fans of Sir Arthur Conan Doyle will recognize that iterative disjunctive syllogism is nothing other than the process of elimination, as explained by Doyle’s fictional detective, Sherlock Holmes. See, e.g., Doyle, The Blanched Soldier (“…when you have eliminated all which is impossible, then whatever remains, however improbable, must be the truth.”); Doyle, The Beryl Coronet (“It is an old maxim of mine that when you have excluded the impossible, whatever remains, however improbable, must be the truth.”); Doyle, The Hound of the Baskervilles (1902) (“We balance probabilities and choose the most likely. It is the scientific use of the imagination.”); Doyle, The Sign of the Four, ch 6 (1890)(“‘You will not apply my precept’, he said, shaking his head. ‘How often have I said to you that when you have eliminated the impossible, whatever remains, however improbable, must be the truth? We know that he did not come through the door, the window, or the chimney. We also know that he could not have been concealed in the room, as there is no concealment possible. When, then, did he come?”)

The process of elimination sometimes surfaces in court cases in which expert witnesses attempt to attribute a health outcome in a specific person to that person’s prior environmental, occupational, or lifestyle exposures. A few general conclusions can be advanced about this mode of reasoning:

1. Differential Etiology NOT Differential Diagnosis

Although courts and expert witnesses sometimes refer to this process of ruling out as “differential diagnosis,” their terminology is a misnomer. Their usage is not an innocent diction error because diagnosis is almost never involved, and the usage attempts to suggest that the causal attribution is part of a process typically conducted by a treating physician, when in fact, the treating physician rarely determines the actual cause in the person. Etiology is usually not needed to determine the nature of the disease or the proper course of treatment. Biomarkers, other than diagnostic criteria, rarely point to a specific cause(s) in a given case. The “differential diagnosis” misnomer tends to obscure clear reasoning about physician witnesses, who are often not experts in epidemiology or other sciences needed to assess general causation, not familiar with systematic reviews, not published on the scientific issue of general causation. The specific causal attribution is analogous to differential diagnosis, in its process of ruling in, and then ruling out, and therefore is sometimes called differential etiology. See, e.g., Michael D. Green, D. Michal Freedman, and Leon Gordis, Reference Guide on Epidemiology 549, 617 & n.211, in Reference Manual on Scientific Evidence (3ed ed. 2011)[RMSE].

2. Differential Etiology Assumes, and Cannot Establish, General Causation

The differential etiology process assumes that each disjunct – each putative specific cause – has itself been established as a known cause of the disease in general. Id. at 618 (“Although differential etiologies are a sound methodology in principle, this approach is only valid if general causation exists … .”). In the case of a novel putative cause, the case may give rise to a hypothesis that the putative cause can cause the outcome, in general, and did so in the specific case. That hypothesis must, of course, then be tested and supported by appropriate analytical methods before it can be accepted for general causation and as a putative specific cause in a particular individual.

3. Differential etiology typically fails when a substantial percentage of cases are idiopathic in origin

When one of the disjuncts is “no known cause,” then it will be virtually impossible to negate and remove from the disjunction. If very few cases have idiopathic causes, the error rate may be low, and tolerable. Take for example, asbestosis, a diffuse interstitial lung disease caused by chronic, excessive inhalation of asbestos. Clinically asbestosis will look similar to idiopathic pulmonary fibrosis (IPF), a lung disease of unknown origin. IPF may remain a differential diagnosis in every case because it cannot be ruled out, clinically. The likelihood of IPF, however, will be relatively low in a cohort of asbestos miners, and thus not a serious source of error. In a study of household exposure cases, in which the exposure resulted from a family member’s bringing home dust from work, IPF may be a much likelier alternative, and the failure to rule it out may invalidate conclusions about the asbestosis diagnosis in every case in the cohort.

With respect to differential etiology, the same principle applies: the iterative disjunctive syllogism requires ruling out “unknown,” or at least minimizing the number of cases in the unknown disjunct that are not ruled out. See RMSE at 618 (“Although differential etiologies are a sound methodology in principle, this approach is only valid if … a substantial proportion of competing causes are known. Thus, for diseases for which the causes are largely unknown, such as most birth defects, a differential etiology is of little benefit.”)(internal citations omitted). Accordingly, many cases reject proffered expert witness testimony on differential etiology, when the witnesses fail to rule out idiopathic causes in the case at issue. What is a substantial proportion? Unfortunately, the RMSE does not attempt to quantify or define “substantial.” The inability to rule out unknown etiologies remains the fatal flaw in much expert witness opinion testimony on specific causation.

More Nonsense on Differential Diagnosis

The Supreme Court recently addressed differential etiology in Matrixx Initiatives, in stunningly irrelevant and errant dicta:

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

Matrixx Initiatives, Inc. v. Siracusano, 131 S. Ct. 1309, 1319 (2011). The citation to Wells was clearly wrong in that the plaintiffs in that case had, in fact, relied upon studies that were nominally statistically significant, and so the Wells court could not have held that statistical significance was unnecessary.[1]

The two other cases cited by the Supreme Court, however, were both about “differential diagnosis,” and had nothing to do with statistical significance. Both cases assumed that general causation was established, and inquired into whether expert witnesses could reasonably attribute the health outcome in the case to the exposures that were established causes of such outcomes. The Court’s selection of these cases, quite irrelevant to its discussion, appears to have come from the Solicitor General’s amicus brief in Matrixx.[2]

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

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

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

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

and

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

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

Of course, a physicians rarely use this iterative process to arrive at causes of diseases in an individual; they use it to identify the disease or disease process that is responsible for the patient’s signs and symptoms. See generally Harold C. Sox, Michael C. Higgins, and Douglas K. Owens, Medical Decision Making (2d ed. 2014). The Best court’s description does not make sense in that it characterizes the process as ruling in “one or more” causes, and then ruling out alternative causes. If an expert had ruled in only one cause, then there would be no need or opportunity to rule out an alternative cause. If the one ruled-in cause was ruled out for other reasons, then the expert witness would be left with a case of idiopathic disease.[3]

We can take some solace in the Supreme Court’s disclaimer that it was not attempting reliable evidence of causation. Differential etiology, however, is irrelevant to general causation, which is the context in which statistical significance arises. The issue of statistical significance was not addressed; nor could it have been addressed in either Best or Westberry.

What follows is an incomplete selection of cases on differential etiology, good and bad.

Differential Etiology for Specific Causation

FIRST CIRCUIT

Baker v. Dalkon Shield Claimaints Trust, 156 F.3d 248, 252-53 (1st Cir. 1998) (stating that “ ‘differential diagnosis’ is a standard medical technique”)

District Courts within 1st Circuit

Whiting v. Boston Edison Co., 891 F. Supp. 12, 21 n.41 (D. Mass. 1995) (noting that differential diagnosis cannot be used to support conclusion of specific causation when 90% disease cases are idiopathic)

Polaino v. Bayer Corp., 122 F. Supp. 2d 63, 70 & n.7 (D. Mass. 2000) (“differential diagnosis is a useful means of distinguishing one disease from another with similar symptoms, it is not a technique typically used to investigate the cause of an illness”)

Plourde v. Gladstone, 190 F. Supp. 2d 708, 722-723 (D. Vt. 2002) (excluding testimony where expert failed to rule out causes of plaintiff’s illness other than exposure to herbicides)

Allen v. Martin Surfacing, 263 F.R.D. 47, 56 (D. Mass. 2008) (admitting general and specific causation testimony of ALS, to be tested by adversary process, rather than excluded altogether, despite paucity of epidemiologic evidence)

Milward v. Acuity Specialty Products Group, Inc., Civil Action No. 07–11944–DPW, 2013 WL 4812425 (D. Mass. Sept. 6, 2013)

SECOND CIRCUIT

McCullock v. H.B. Fuller Co., 61 F.3d 1038, 1043–44 (2d Cir.1995) (defining differential etiology as an analysis “which requires listing possible causes, then eliminating all causes but one”) (affirming admission of a treating doctor’s testimony despite his inability to “point to a single piece of medical literature that says glue fumes cause throat polyps”) (upholding admission of treating physician who relied upon his “care and treatment of McCullock; her medical history (as she related it to him and as derived from a review of her medical and surgical reports); pathological studies; review of [Defendant] Fuller’s [Material Safety Data Sheet], his training and experience, use of a scientific analysis known as differential etiology (which requires listing possible causes, then eliminating all causes but one); and reference to various scientific and medical treatises”)

United States v. Zuchowitz, 140 F.3d 381, 385-87 (2d Cir. 1998) (“[d]isputes as to . . . faults in [the] use of differential etiology as a methodology, or lack of textual authority for [an] opinion, go to the weight, not the admissibility of [the] testimony”)

Wills v. Amerada Hess Corp., 379 F. 3d 32, 45-46 (2d Cir. 2004)(noting that expert witness failed to account for other possible causes), cert. denied, 126 S.Ct. 355 (2005)

Ruggiero v. Warner-Lambert Co., 424 F.3d 249, 254 (2d Cir. 2005) (“Where an expert employs differential diagnosis to ‘rule out other potential causes’ for the injury at issue, he must also ‘rule in the suspected cause’ and do so using ‘scientifically valid methodology’.”) (quoting Cavallo v. Star Enter., 892 F. Supp. 756, 771 (E.D. Va. 1995), aff’d on this ground, rev’d on other grounds, 100 F.3d 1150 (4th Cir. 1996))

District Courts within 2d Circuit

Becker v. National Health Products, 896 F.Supp. 100 (N.D.N.Y. 1995).

Mancuso v. Consolidated Edison Co. of New York, Inc., 967 F. Supp. 1437, 1450 (S.D.N.Y. 1997)(“it is improper for an expert to presume that the plaintiff ‘must have somehow been exposed to a high enough dose to exceed the threshold [necessary to cause the illness], thereby justifying his initial diagnosis.’ This is circular reasoning.”)

Zwillinger v. Garfield Slope Hous. Corp., 1998 WL 623589, at *20 (E.D.N.Y. Aug. 17, 1998) (excluding testimony and granting summary judgment where expert failed to rule out alternative causes of plaintiff’s immunotoxicity syndrome)

Prohaska v. Sofamor, S.N.C., 138 F. Supp. 2d 422, 439 (W.D.N.Y. 2001) (excluding expert’s opinion and granting summary judgment where expert “was unable to rule out, to a reasonable degree of medical certainty, [plaintiff’s] pre-existing condition, scoliosis, as a current cause of her pain”)

Martin v. Shell Oil Co., 180 F. Supp. 2d 313, 320 (D. Conn. 2002)

Figueroa v. Boston Scientific Corp., 254 F.Supp. 2d 361, 368 (S.D.N.Y. 2003)(“failure to rule out alternative causes is not determinative of admissibility of evidence but goes to weight, which is for a jury to decide”)

Perkins v. Origin Medsystems, Inc., 299 F. Supp. 2d 45, 57-61 (D. Conn. 2004)

In re Rezulin Prods. Liab. Litig., No. MDL 1348, 00 Civ. 2843(LAK), 2004 WL 2884327, at *3-4 (S.D.N.Y. Dec. 10, 2004) (holding that differential etiology may not be used to prove general causation) (“differential diagnosis does not ‘speak to the issue of general causation. [It] assumes that general causation has been proven for the list of possible causes’ that it rules in and out in coming to a conclusion.”)

In re Ephedra Prods. Liab. Litig., 393 F. Supp. 2d 181, 187 (S.D.N.Y. 2005) (Rakoff, J.)

THIRD CIRCUIT

In re Paoli R.R. Yard PCB Litig., 916 F.2d 829, 862 (3d Cir.1990)

In re Paoli R.R. Yard PCB Litig., 35 F.3d 717, 758 (3d Cir. 1994) (“[D]ifferential diagnosis generally is a technique that has widespread acceptance in the medical community, has been subject to peer review, and does not frequently lead to incorrect results …. )

Wade-Greaux v. Whitehall Labs., Inc., 874 F. Supp. 1441 (D.V. I.), aff’d, 46 F.3d 1120 (3d Cir. 1994) (excluding testimony of expert who failed to rule out alternative causes of plaintiff’s birth defects)

Kannankeril v. Terminex Int’l, Inc., 128 F.3d 802, 807 (3d Cir. 1997)

Heller v. Shaw Indus., Inc., 167 F.3d 146, 154 (3d Cir. 1999) (a medical expert need not “always cite published studies on general causation in order to reliably conclude that a particular object caused a particular illness” so long as there are good grounds, such as differential diagnosis, for the conclusion)

District Courts within 3d Circuit

Diaz v. Matthey, Inc., 893 F. Supp. 358, 376-377 (D.N.J. 1995) (excluding testimony and granting summary judgment where expert failed to rule out alternative causes for plaintiff’s asthma)

Rutigliano v. Valley Bus. Forms, 929 F. Supp. 779, 787 (D.N.J. 1996) (excluding expert’s testimony and granting summary judgment where the “record is replete with evidence, including [the expert’s] own admissions, that [plaintiff’s] symptoms could be attributable to medical conditions other than formaldehyde sensitization”)

Reiff v. Convergent Technologies, 957 F. Supp. 573, 582-83 (D.N.J. 1997) (excluding expert’s testimony and granting summary judgment where expert failed to rule out alternative causes of plaintiff’s carpal tunnel syndrome)

O’Brien v. Sofamor, 1999 WL 239414, at *5 (E.D. Pa. Mar. 30, 1999) (excluding expert’s testimony and granting summary judgment where plaintiff “offer[ed] no evidence that [plaintiff’s experts] performed a differential diagnosis, or even considered other potential causes” of plaintiff’s back condition)

Kent v. Howell Elec. Motors, 1999 WL 517106, at * 5 (E.D. Pa. July 20, 1999) (excluding expert testimony and granting summary judgment because expert could “not rule out reasonable alternative theories of what caused the retaining ring to fail”)

Schmerling v. Danek Med., Inc., 1999 WL 712591, at *9 (E.D. Pa. Sept. 10, 1999) (excluding expert’s testimony and granting summary judgment on the grounds that expert’s failure to rule out alternative causes “alone warrants a determination that the expert’s methodology is unreliable”)

Turbe v. Lynch Trucking Inc., 1999 WL 1087026, at *6 (D.V.I. Oct. 7, 1999) (excluding expert’s testimony where expert “expressed awareness of obvious alternative causes” yet “did not investigate any other possible causes”)

In re Paoli R.R. Yard PCB Litig., 2000 WL 274262, at *5 (E.D. Pa. March 1, 2000) (expert’s opinion should be excluded “because she failed to rule out alternative causes” of plaintiff’s injuries)

Magistrini v. One Hour Martinizing Dry Cleaning, 180 F. Supp. 2d 584, 608-610 (D.N.J. 2002) (excluding testimony of expert who sought to testify that dry cleaning fluid caused leukemia, but failed to rule out smoking as an alternative cause) (holding expert witness’s differential methodology unreliable when objection to the opinion points to a plausible alternative cause, and the expert witness offers no explanation for his conclusion that the exposure was a substantial factor in causing plaintiff’s injury)

Yarchak v. Trek Bicycle Corp., 208 F. Supp. 2d 470, 498 (D.N.J. 2002)

Soldo v. Sandoz Pharms. Corp., 244 F.Supp. 2d 434, 554-56, 567 (W.D. Pa. 2003) (excluding experts’ specific causation testimony based on a differential diagnosis because the witnesses “did not demonstrate any valid diagnostic methodology–any ‘sufficient diagnostic technique’–for excluding” other plausible causes as the sole cause of the plaintiff’s injury) (holding that the differential “diagnostic” process is not reliable, and not admissible, unless it reliably rules out reasonable alternative causes or idiopathic causes of the alleged harm); see id. at 524 (differential diagnosis cannot establish general causation)

Perry v. Novartis, 564 F. Supp. 2d 452, 469 (E.D. Penn. 2008)(Dalzell, J.) (“Standing alone, the presence of a known risk factor is not a sufficient basis for ruling out idiopathic origin in a particular case, particularly where most of the cases of the disease have no known cause.”)

FOURTH CIRCUIT

Benedi v. McNeil-P.P.C. Inc., 66 F.3d 1378, 1384 (4th Cir. 1995) (upholding admission of differential diagnosis , reasoning circularly that diagnosing physicians use it)

Cavallo v. Star Enter., 892 F. Supp. 756, 771, (E.D. Va. 1995) (noting that it is not sufficient for an expert to rule out other possible causes if he has no sound evidence that allows him to “rule in” the purported cause), aff’d in relevant part, rev’d in part on other grounds, 100 F.3d 1150 (4th Cir. 1996)

Oglesby v. General Motors Corp., 190 F.3d 244, 250 (4th Cir. 1999) (affirming exclusion of testimony where “as a matter of logic, [the expert] could not eliminate other equally plausible causes” of cracked plastic inlet)

Westberry v. Gislaved Gummi AB, 178 F.3d 257, 262-263 (4th Cir. 1999) (“Differential diagnosis, or differential etiology, is a standard scientific technique of identifying the cause of a medical problem by eliminating the likely causes until the most probable one is isolated”)

Cooper v. Smith & Nephew, Inc., 259 F.3d 194, 202 (4th Cir.2001) (holding that an expert’s opinion based on a differential diagnosis is generally admissible but that there must be adequate evidence that the differential is a cause of the disease)

District Courts within 4th Circuit

Higgins v. Diversey Corp., 998 F. Supp. 598, 603 (D. Md. 1997), aff’d, 135 F.2d 769 (4th Cir. 1998) (excluding expert’s testimony that the accidental inhalation of a bleach caused plaintiff’s injuries, where expert “admit[ted] that he [could] not rule out several other possible causes”)

Driggers v. Sofamor, S.N.C., 44 F. Supp. 2d 760, 765 (M.D.N.C. 1998) (excluding expert’s testimony and granting summary judgment where “expert failed to rule out other possible causes of [plaintiff’s back] pain”)

Aldridge v. Goodyear Tire & Rubber Co., 34 F. Supp. 2d 1010, 1024 (D. Md. 1999), vacated on other grounds, 223 F.3d 263 (4th Cir. 2000) (excluding testimony of plaintiffs’ experts where they “failed to adequately address possible alternative causes of plaintiffs’ illnesses”)

Fitzerald v. Smith & Nephew Richards, Inc., 1999 WL 1489199 (D. Md. Dec. 30, 1999) (excluding expert’s testimony and granting summary judgment where expert “failed to rule out what could have been another cause of [plaintiff’s] condition”)

Shreve v. Sears, Robuck & Co., 166 F. Supp. 2d 378, 397-98 (D. Md. 2001) (excluding testimony where expert failed to rule out other causes of plaintiff’s injury other than an alleged defect in snow thrower)

Smith v. Wyeth-Ayerst Laboratories Co., 278 F.Supp. 2d 684, 692 (W.D.N.C. 2003)(inexplicably rejecting argument that idiopathic causes prevent the use of “differential etiology” method to ascertain specific causation)

Roche v. Lincoln Property Co., 278 F.Supp. 2d 744 (E.D. Va. 2003) (excluding in part expert witness’s testimony that mold caused the plaintiffs’ allergy-like symptoms because he failed “to rule out the Roches’ significant allergies to cats, dust mites, grasses, weeds, and trees as potential causes for the Roches’ symptoms,” which pre-existed moving to the defendant’s apartment)

Doe v. Ortho-Clinical Diagnostics, Inc., 440 F.Supp. 2d 465, 476-78 (M.D.N.C. 2006) (excluding improperly conducted differential diagnosis in thimerosal vaccine autism case)

Hines v. Wyeth, Inc., 2011 WL 2792436, at *3 (S.D.W.V. July 14, 2011) (excluding expert witness who failed properly to rule out alternative causes of breast cancer in hormone therapy case)

FIFTH CIRCUIT

Moore v. Ashland Chem. Inc., 151 F.3d 269, 278-79 (5th Cir. 1998)(en banc), cert. denied, 526 U.S. 1064 (1999)(holding that trial court has discretion to conclude that an expert’s differential diagnosis was insufficiently reliable to be submitted to the jury)

Curtis v. M&S Petroleum, Inc., 174 F.3d 661, 670 (5th Cir. 1999)

Michaels v. Avitech, Inc., 202 F.3d 746, 753 (5th Cir. 2000) (excluding testimony when “plaintiff’s experts wholly fail[ed] to address and rule out the numerous other potential causes” of an aircraft disaster)

Black v Food Lion, Inc, 171 F3d 308 (5th Cir 1999) (expert witness, purporting to use a differential diagnosis, testified that plaintiff’s slip in the supermarket caused fibromyalgia, which is largely idiopathic) (“This analysis amounts to saying that because [the physician] thought she had eliminated other possible causes of fibromyalgia, even though she does not know the real ‘cause,’ it had to be the fall at Food Lion. This is not an exercise in scientific logic but in the fallacy of post-hoc propter-hoc reasoning, which is as unacceptable in science as in law.”)

Johnson v. Arkema, Inc., 685 F.3d 452, 467–68 (5th Cir. 2012) (suggesting that a proper differential diagnosis may be admissible)

District Courts within 5th Circuit

Bennett v. PRC Public Sector, 931 F. Supp. 484, 492 (S.D. Tex. 1996) (excluding testimony of expert who failed to consider and rule out alternative causes of plaintiff’s repetitive motion disorders)

Conger v. Danek Med., Inc., 1998 WL 1041331, at *5-6 (N.D. Tex. Dec. 14, 1998) (excluding expert’s testimony and granting summary judgment when expert “had not attempted to rule out [other potential sources] as causes for [plaintiff’s back] pain”);

Nobles v. Sofamor, 1999 WL 1129661 (S.D. Tex June 30, 1999) (Rosenthal, J.)

Leigh v. Danek Med., Inc., 1998 WL 1041329, at *4-5 (N.D. Tex. Dec. 14, 1998) (excluding expert’s testimony and granting summary judgment where expert failed to rule out alternative causes of plaintiff’s back pain)

In re Propulsid Products Liability Litigation, 261 F. Supp. 2d 603, 618 (E.D. La. 2003)(“They also cannot rule out other explanations for the measurements that form the predicate of the QTc, the heart rate, or heart rate variability)

Cano v. Everest Minerals Corp., 362 F. Supp. 2d 814, 844-46 (W.D. Tex. 2005) (addressing specific causation in context of known carcinogen (radiation), and holding that expert witness’s methodology of concluding that any cause that could have been a cause was in fact a cause and a substantial factor was invalid)

Ridgeway v. Pfizer Inc., No. 2:09-cv-02794, 2010 WL 1729187, *4 (E.D.La. April 27, 2010) (using “differential diagnosis,” or res ipsa loquitur, the proponent bears the burden of “excluding reasonable explanations for the accident other than defendant’s negligence”)

SIXTH CIRCUIT

Glaser v. Thompson Med. Co., 32 F.3d 969, 978 (6th Cir. 1994) (differential diagnosis defined as “standard diagnostic tool used by medical professionals to diagnose the most likely cause or causes of illness, injury and disease”)

Hardyman v. Norfolk & W. Ry. Co., 243 F.3d 255, 260 (6th Cir.2001) (“Differential diagnosis … is a standard scientific technique of identifying the cause of a medical problem”)

Downs v. Perstorp Components, Inc., 26 F. Appx. 472, 476–77 (6th Cir. 2002) (holding that exclusion of expert’s opinion was appropriate when arrived at by a “methodology primarily [that] involved reasoning backwards from Downs’ condition and, through a process of elimination, concluding that [defendant’s product] must have caused it”)

Best v. Lowe’s Home Centers, Inc., 563 F. 3d 171, 178-80 (6th Cir. 2009)

Gass v. Marriott Hotel Servs., 558 F.3d 419, 426 (6th Cir. 2009) (“the ability to diagnose medical conditions is not remotely the same as the ability to deduce … in a scientifically reliable manner the causes of those medical conditions”)(internal citations omitted)

Tamraz v. BOC Group Inc., No. 1:04-CV-18948, 2008 WL 2796726 (N.D. Ohio July 18, 2008) (denying Rule 702 challenge to treating physician’s causation opinion), rev’d sub nom., Tamraz v. Lincoln Elec. Co., 620 F.3d 665, 673 (6th Cir. 2010) (carefully reviewing record of trial testimony of plaintiffs’ treating physician; reversing judgment for plaintiff based in substantial part upon treating physician’s speculative causal assessment created by plaintiffs’ counsel; “Getting the diagnosis right matters greatly to a treating physician, as a bungled diagnosis can lead to unnecessary procedures at best and death at worst. But with etiology, the same physician may often follow a precautionary principle: If a particular factor might cause a disease, and the factor is readily avoidable, why not advise the patient to avoid it? Such advice—telling a welder, say, to use a respirator—can do little harm, and might do a lot of good. This low threshold for making a decision serves well in the clinic but not in the courtroom, where decision requires not just an educated hunch but at least a preponderance of the evidence.”) (internal citations omitted), cert. denied, ___ U.S. ___ , 131 S. Ct. 2454, 2011 WL 863879 (2011)

Thomas v. Novartis Pharm. Corp., 443 Fed. App’x 58, 61-62 (6th Cir. 2011) (excluding expert witnesses in cases involving osteonecrosis of the jaw, allegedly caused by bisphosphonate medication, for failing to conduct proper differential analysis; emphasizing “the importance of correctly determining the cause of the osteonecrosis … does nothing to establish that [the doctor] can in fact, reliably determine the cause of a patient’s [osteonecrosis]”)

District Courts within 6th Circuit

Nelson v. Tennessee Gas Pipeline Co., 1998 WL 1297690, at *6 (W.D. Tenn. Aug. 1, 1998) (excluding testimony of expert who “failed to engage in adequate techniques to rule out alternative causes and offers no good explanation as to why his opinion is nevertheless reliable in light of other potential causes of the alleged injuries”)

Downs v. Perstorp Components, 126 F. Supp. 2d 1090, 1127 (E.D. Tenn. 1999) (excluding expert testimony as to whether exposure to chemicals caused plaintiff’s injuries where expert failed to rule out alternative causes)

Huffman v. SmithKline Beecham Clinical Lab., Inc., 111 F. Supp. 2d 921, 930 (N.D. Ohio 2000)

Asad v. Continental Airlines, Inc., 314 F. Supp. 2d 726 (N.D. Ohio 2004)

SEVENTH CIRCUIT

O’Connor v. Commonwealth Edison, 13 F.3d 1090, 1106 (7th Cir. 1994) (holding that physician’s testimony that cataracts were caused by radiation exposure based upon visual examination of the plaintiff’s was not reliably supported by clinical examination), cert. denied, 114 S.Ct. 2711 (1994).

Ervin v. Johnson & Johnson, Inc., 492 F.3d 901, 904 (7th Cir.2007)(noting that “[a] differential diagnosis satisfies a Daubert analysis if the expert uses reliable methods”) (excluding differential etiological testimony that was based upon ruling a particular potential specific cause based on temporal proximity)

District Courts within 7th Circuit

Schmaltz v. Norfolk & Western Ry., 878 F.Supp. 1122 (N.D. Ill. 1995)

Lennon v. Norfolk & Western Ry., 123 F.Supp.2d 1143, 1153 (N.D.Ind. 2000) (excluding neurologist’s unreliable causal attribution of multiple sclerosis to fall)

Eve v. Sandoz Pharm. Corp., No. IP 98-1429, 2001 U.S. Dist. LEXIS 4531 (S.D. Ind. 2001)

Caraker v. Sandoz Pharms., 188 F. Supp. 2d 1026, 1030 (S.D. Ill. 2001) (when a differential diagnosis is employed “in the practice of science (as opposed to its use by treating physicians in the practice of medicine out of necessity) it must reliably ‘rule in’ a potential cause”)

Bickel v. Pfizer, Inc., 431 F.Supp. 2d 918, 923 (N.D. Ind. 2006) (“the Plaintiff cannot rely on [differential] diagnosis to establish general causation”)

EIGHTH CIRCUIT

National Bank of Commerce v. Assoc. Milk Producers, 22 F. Supp. 2d 942, 963 (E.D. Ark. 1998), aff’d, 191 F.3d 858 (8th Cir.1999) (excluding testimony and granting summary judgment where expert did “not successfully rule out other possible alternative causes” for cancer)

Turner v. Iowa Fire Equip. Co., 229 F.3d 1202, 1208-09 (8th Cir. 2000) (“[A] medical opinion about causation, based upon a proper differential diagnosis, is sufficiently reliable to satisfy Daubert.”)(“If a properly qualified medical expert performs a reliable differential diagnosis through which, to a reasonable degree of medical certainty, all other possible causes of the victims’ condition can be eliminated, leaving only the toxic substance as the cause, a causation opinion based on that differential diagnosis should be admitted.”)

Bonner v. ISP Technologies, Inc., 259 F.3d 924, 1208 (8th Cir. 2001)

Glastetter v. Novartis Pharms. Corp., 252 F.3d 986, 989 (8th Cir. 2001) (per curiam) (“[T]he district court excluded the differential diagnoses performed by Glastetter’s expert physicians because they lacked a proper basis for ‘ruling in’ Parlodel as a potential cause of [an intracerebral hemorrhage] in the first place. . . . We agree with the district court’s conclusion.”)

Jazairi v. Royal Oaks Apts., 217 Fed. Appx. 895 (8th Cir. 2007) (excluding differential etiological testimony that was based upon ruling a particular potential specific cause based on temporal proximity)

Bland v. Verizon Wireless, L.L.C., 538 F.3d 893, 897 (8th Cir. 2008) (affirming exclusion of treating physician’s differential diagnosis)

District Courts within 8th Circuit

Stover v. Eagle Products, 1996 WL 172972, at *11 (D. Kan. Mar. 19, 1996) (excluding testimony of expert who “[did] not explain in any meaningful detail how he [was] able to exclude the numerous multiple alternative causes” of injury to plaintiff’s dogs) (excluding expert testimony for failing to rule out alternative causes)

Bruzer v. Danek Med., Inc., 1999 WL 613329, at *8 (D. Minn. Mar. 8, 1999) (excluding expert’s testimony and granting summary judgment where expert did “not attempt to rule out any alternative potential causes for [plaintiff’s] continuing and increasing [back] pain”) (excluding expert testimony for failing to rule out alternative causes)

Thurman v. Missouri Gas Energy, 107 F. Supp. 2d 1046, 1058 (W.D. Mo. 2000) (expert’s opinion “that the pipeline failed because of corrosion” was excluded and summary judgment granted where expert reached the conclusion “without eliminating other causes”) (excluding expert testimony for failing to rule out alternative causes)

Jisa Farms, Inc. v. Farmland Indus., No. 4:99CV3294, 2001 U.S. Dist. LEXIS 26084 (D. Neb. 2001) (excluding expert testimony for failing to rule out alternative causes)

In re Viagra Prod. Liab. Litig., 658 F. Supp. 2d 950, 957 (D. Minn. 2009)

NINTH CIRCUIT

Kennedy v. Collagen Corp., 161 F.3d 1226, 1228-30 (9th Cir. 1998)

Clausen v. M/V NEW CARISSA, 339 F.3d 1049, 1057 (9th Cir. 2003)

Messick v. Novartis Pharms., ___ F.3d. ___, 2014 WL 1328182 (9th Cir. 2014)

District Courts within 9th Circuit

Hall v. Baxter Healthcare Corp., 947 F.Supp. 1387, 1413 (D.Ore. 1996) (explaining that differential diagnosis assumes general causation has been established) (“differential diagnosis does not by itself prove the cause, even for the particular patient. Nor can the technique speak to the issue of general causation.”)

TENTH CIRCUIT

Hollander v. Sandoz Pharms. Corp., 289 F.3d 1193, 1211 (10th Cir. 2002) (stating that “experts would need to present reliable evidence that the drug can cause strokes” before differential diagnosis could be admissible)

Goebel v. Denver & Rio Grande W. RR., 346 F.3d 987, 999 (10th Cir. 2003)

Tingey v. Radionics, 193 Fed. Appx. 747, 763 (10th Cir. 2006)

District Courts within 10th Circuit

In re Breast Implant Lit., 11 F. Supp. 2d 1217, 1230, 1234 (D. Colo. 1998) (excluding expert testimony where expert failed to “explain what alternative causes he considered, or how he ruled out other possible causes” of plaintiffs’ auto- immune disease) (“Differential diagnosis may be utilized by a clinician to determine what recognized disease or symptom the patient has, but it is incapable of determining whether exposure to a substance caused disease in the legal sense.”)

ELEVENTH CIRCUIT

McClain v. Metabolife Int’l, Inc., 401 F.3d 1233, 1252-53 (11th Cir.2005) (detailing a reliable differential diagnostic process)(“A valid differential diagnosis, however, only satisfies a Daubert analysis if the expert can show the general toxicity of the drug by reliable methods.”)

Rink v. Cheminova, Inc., 400 F.3d 1286, 1295 (11th Cir. 2005) (holding that a differential diagnosis alone does not support a finding of causation where no expert testimony from a treating physician or toxicologist is presented, or any toxicological evidence produced; specifically rejecting the Westberry) (“[I]n the context of summary judgment . . . differential diagnosis evidence by itself does not suffice for proof of causation.”)

Guinn v. AstraZeneca Pharms. LP, 602 F.3d 1245 (11th Cir. 2010), aff’g 598 F. Supp. 2d 1239, 1243 (M.D. Fla. 2009) (excluding expert witness’s specific causation opinion for failing “to articulate any scientific methodology for assessing whether, and to what extent, Seroquel contributed to Guinn’s weight gain and diabetes”)

Hendrix v. Evenflo Co., 609 F.3d 1183, 1194-95 (11th Cir. 2010), aff’g, 255 F.R.D. 568, 596 (N.D. Florida, 2009)(differential etiology not diagnosis)

Kilpatrick v. Breg, Inc., 613 F.3d 1329, 1342 (11th Cir. 2010) (noting that differential diagnosis “assumes the existence of general causation”)

District Courts within 11th Circuit

Coleman v. Danek Med., Inc., 43 F. Supp. 2d 637, 650 n. 23 (S.D. Miss. 1999) (stating that “in reaching his conclusion that these plaintiffs were injured by Danek’s product, Dr. Aldreti did not rule out other causes of their alleged injuries. Thus, his conclusion that their injuries were caused by Danek’s product is based on pure speculation – and is not a valid differential diagnosis.”)

Siharath v. Sandoz Pharms. Corp., 131 F. Supp. 2d 1347, 1356-71 (N.D. Ga. 2001) (holding that differential diagnosis cannot rule in a general causal factor, and noting in Parlodel case that “[e]xperts must do something more than just ‘rule out’ other possible causes. They must explain how they were able to ‘rule in’ the product in question”), aff’d sub nom., Rider v. Sandoz Pharm. Corp., 295 F.3d 1194 (11th Cir. 2002).

D.C. CIRCUIT

Ambrosini v. Labarraque, 101 F.3d 129, 140 (D.C.Cir.1996) (describing the appropriate use of differential diagnosis to prove specific causation)

Meister v. Med. Eng’g Corp., 267 F.3d 1123, 1129, 347 U.S. App. D.C. 361 (D.C. Cir. 2001)(“whatever factors remain after other alternative causes have been eliminated [must be] at least capable of causing the disease in question”)

STATE COURT CASES

ALASKA

John’s Heating Service v. Lamb, 46 P.3d 1024 (Alaska 2002) (“[a] differential diagnosis that fails to take serious account of other potential causes may be so lacking that it cannot provide a reliable basis for an opinion on causation,” but not in this case involving carbon monoxide poisoning)

ARIZONA

Lofgren v. Motorola, No. CV 93-05521, 1998 WL 299925, at *24 (Ariz. Super. Ct. June 1, 1998) (differential diagnosis as a method of determining the cause of disease has been “unequivocally rejected by the scientific community”)

IOWA

Ranes v. Adams Labs., Inc., 778 N.W.2d 677, 690 (Iowa 2010)(general causation for each differential should be established by adequate evidence)

KANSAS

Kuhn v. Sandoz Pharms., 14 P.3d 1170, 1173-78 (Kan. 2000) (Frye test not applicable to “pure opinion” testimony such as differential diagnosis)

LOUISIANA

Keener v. Mid-Continent Cas., 817 So. 2d 347 (La. Ct. App. 5th Cir. 2002), writ denied, 825 So. 2d 1175 (La. 2002)

MINNESOTA

Zandi v. Wyeth, 2009 Minn. App. Unpub. LEXIS 785, at *17-18 (Minn. Ct. App. July 21, 2009), petition denied, 2009 Minn. LEXIS 648 (Minn. Sept. 29, 2009)

NEW JERSEY

Creanga v. Jardal, 185 N.J. 345, 886 A.2d 633 (2005) (holding that properly conducted differential diagnosis was admissible; reversing exclusion of physician testimony in case)

OHIO

Terry v. Ottawa Cty. Bd. of Mental Retardation & Developmental Delay, 658, 847 N.E.2d 1246 (Ohio Ct. App. 2006) (“We agree with the trial court: Dr. Bernstein did not conduct a scientifically valid differential diagnosis, because his method relied primarily upon temporal relationships and because he did not rule out other possible causes. He was properly barred from testifying to specific causation.”)

TEXAS

Mitchell Energy Corp. v. Bartlett, 958 S.W.2d 430, 448 (Tex. App.–Fort Worth 1997, pet. denied) (“Dr. Basset’s failure to rule out other causes of the presence of hydrogen sulfide in appellees’ water renders his opinion ‘little more than speculation.’”)

Weiss v. Mechanical Associated Services, Inc., 989 S.W.2d 120, 126 (Tex. App.– San Antonio 1999, pet. denied) (affirming summary judgment for the defendants in a case involving injuries allegedly caused by exposure to a chemical, because “none of Weiss’ experts were able to rule out other potential causes of Weiss’ illness with reasonable certainty”)

Williams v. NGF, Inc., 994 S.W.2d 255, 257 (Tex. App.–Texarkana 1999, no pet. h.) (affirming summary judgment for defendant because plaintiffs “failed to produce evidence which excluded the possibility that . . . other flowers or chemical agents used on them were the cause of her injuries”)

Austin v. Kerr-McGee Refining Corp., 25 S.W.3d 280, 293 (Tex. App.-Texarkana 2000, no pet.) (affirming summary judgment for defendants; trial court properly excluded plaintiffs’ scientific evidence because, among other reasons, plaintiffs “failed to exclude other plausible causes with reasonable certainty”)

Martinez v. City of San Antonio, 40 S.W.3d 587, 595 (Tex. App.–San Antonio 2001, no pet.) (“The opinions of Matson and Baynes, when offered to prove Alamodome site lead caused appellants’ injuries, constitute no evidence because Matson, in arriving at his lead calculation, failed to rule out alternative sources of the lead contamination.”)

Neal v. Dow Agrosciences L.L.C., 74 S.W.3d 468, 473 n. 3 (Tex. App. – Dallas 2002, no pet.)(describing “differential diagnosis” as a patient-specific process of elimination) (citing Minnesota Min. And Mfg. Co. v. Atterbury, 978 S.W.2d 183, 194 n. 9 (Tex. App. – Texarkana 1998, pet. denied)

Coastal Tankships, USA, Inc. v. Anderson, 87 S.W.3d 591, at 609-10 (2002)(“In the toxic-tort context, a plaintiff must establish general causation for a differential diagnosis to be relevant to show specific causation.”)

UTAH

Alder v. Bayer Corp., AGFA Div., 61 P.3d 1068, 1084–85 (Utah 2002)

VERMONT

Blanchard v. Goodyear Tire & Rubber Co., 2011 Vt. 85, 30 A.3d 1271 (2011)(holding that plaintiff’s claim that his NHL was caused by benzene was not reliably supported by differential diagnosis when a large percentage of NHL cases have no known cause)

WYOMING

Easum v. Miller, 92 P.3d 794, 802 (Wyo. 2004) (“Most circuits have held that a reliable differential diagnosis satisfies Daubert and provides a valid foundation for admitting an expert opinion. The circuits reason that a differential diagnosis is a tested methodology, has been subjected to peer review/publication, does not frequently lead to incorrect results, and is generally accepted in the medical community.”) (quoting Turner v. Iowa Fire Equip. Co., 229 F.3d 1202, 1208 (8th Cir. 2000)

COMMENTATORS

Conley & Garver, “William C. Keady and the Law of Scientific Evidence,” 68 Miss. L.J. 39, 51 (1998) (differential diagnosis is “a mixture of science and art, far too complicated for its accuracy to be assessed quantitatively or for a meaningful error rate to be calculated”)

Wendy Michelle Ertmer, “Just What the Doctor Ordered: The Admissibility of Differential Diagnosis in Pharmaceutical Product Litigation,” 56 Vand. L. Rev. 1227 (2003)

Joe G. Hollingsworth & Eric G. Lasker, “The Case Against Differential Diagnosis: Daubert, Medical Causation Testimony, and the Scientific Method,” 37 J. Health Law 85, 98 (2004)

Edward J. Imwinkelried,, “The Admissibility and Legal Sufficiency of Testimony about Differential Diagnosis (Etiology): Of Under‑ and Over‑Estimations,” 56 Baylor L. Rev. 391, 406 (2004)

Michael B. Kent Jr., “Daubert, Doctors and Differential Diagnosis: Treating Medical Causation Testimony as Evidence,” 66 Def. Couns. J. 525 (1999)

Joseph Sanders, “Applying Daubert Inconsistently? Proof of Individual Causation in Toxic Tort and Forensic Cases,” 75 Brooklyn L. Rev. 1367 (2010)

Joseph Sanders & Julie Machal-Fulks, “The Admissibility of Differential Diagnosis Testimony to Prove Causation in Toxic Tort Cases: The Interplay of Adjective and Substantive Law,” 64 Law & Contemp. Prob. 107 (2001)

Ian S. Spechler, “Physicians at the Gates of Daubert: A Look at the Admissibility of Differential Diagnosis Testimony to Show External Causation in Toxic Tort Litigation,” 26 Rev. Litig. 739 (2007)

Teratology Society, Public Affairs Committee, “Teratology Society Public Affairs Committee Position Paper Causation in Teratology-Related Litigation,” 73 Birth Defects Research (Part A) 421, 423 (2005) (“7. Biologic plausibility is an essential element in establishing causation. *** The consideration of alternative explanations is sometimes misused by expert witnesses to mean that failure to find an alternative explanation for an outcome is proof that the exposure at issue must have caused the outcome. A conclusion that an exposure caused an outcome is, however, based on positive evidence rather than on lack of an alternative explanation.”)

[1] Wells involved a claim of birth defects caused by the use of spermicidal jelly contraceptive, which had been the subject of several studies, one of which at least yielded a statistically significant increase in detected birth defects over what was expected. Wells v. Ortho Pharmaceutical Corp., 615 F. Supp. 262 (N.D.Ga. 1985), aff’d and rev’d in part on other grounds, 788 F.2d 741 (11^th Cir.), cert. denied, 479 U.S.950 (1986). The problematic aspect of the evidence in Wells lay in its involving spermicidal compounds different from the one at issue in the litigation, and the multiple testing that eroded the usual interpretation of the significance probability.

[2] Brief for the United States as Amicus Curiae Supporting Respondents, in Matrixx Initiatives, Inc. v. Siracusano, 2010 WL 4624148, at *16 (“Best v. Lowe’s Home Centers, Inc., 563 F.3d 171, 178 (6th Cir. 2009) (“an ‘overwhelming majority of the courts of appeals’ agree” that differential diagnosis, a process for medical diagnosis that does not entail statistical significance tests, informs causation) (quoting Westberry v. Gislaved Gummi AB, 178 F.3d 257, 263 (4th Cir. 1999)).”

[3] In the Rule 702 hearings before Judge Jones in Hall v. Baxter Healthcare, Dr. Eric Gershwin defined idiopathic disease as what a pathetic patient suffers from when she has an idiot for a physician.

Posted in Causation | Comments Off on Differential Etiology and Other Courtroom Magic

Substituting Risk for Specific Causation

June 15th, 2014

Specious, Speculative, Spurious, and Sophistical

Some legal writers assert that all evidence is ultimately “probable,” but that assertion appears to be true only to the extent that the evidentiary support for any claim can be mapped on scale from 0 to 1, much as probability is. Probability thus finds its way into discussions of burdens of persuasion as requiring the claim to be shown more probably than not, and expert witness certitude as requiring “reasonable degree of scientific probability.”

There is a contrary emphasis in the law on “actual truth,” which is different from “mere probability.” The rejection of probabilism can be seen in some civil cases, in which courts have emphasized the need for individualistic data and conclusions, beyond generalizations that might be made about groups that clearly encompass the individual at issue. For example, the Supreme Court has held that charging more for funding a woman’s pension than a man’s is discriminatory because not all women will outlive all men, or the men’s average life expectancy. City of Los Angeles Dep’t of Water and Power v. Manhart, 435 U.S. 702, 708 (1978) (“Even a true generalization about a class is an insufficient reason for disqualifying an individual to whom the generalization does not apply.”). See also El v. Southeastern Pennsylvania Transportation Authority, 479 F.3d 232, 237 n.6 (3d Cir. 2007) (“The burden of persuasion … is the obligation to convince the factfinder at trial that a litigant’s necessary propositions of fact are indeed true.”).

Specific causation is the soft underbelly of the toxic tort world, in large measure because courts know that risk is not specific causation. In the context of risk of disease, which is usually based upon a probabilistic group assessment, courts occasionally distinguish between risk and specific causation. See “Probabilism Case Law” (Jan. 28, 2013) (collecting cases for and against probabilism).

In In re Fibreboard Corp., 893 F. 2d 706, 711-12 (5th Cir. 1990), the court rejected a class action approach to litigating asbestos personal injury claims because risk could not substitute for findings of individual causation:

“That procedure cannot focus upon such issues as individual causation, but ultimately must accept general causation as sufficient, contrary to Texas law. It is evident that these statistical estimates deal only with general causation, for ‘population-based probability estimates do not speak to a probability of causation in any one case; the estimate of relative risk is a property of the studied population, not of an individual’s case.’ This type of procedure does not allow proof that a particular defendant’s asbestos ‘really’ caused a particular plaintiff’s disease; the only ‘fact’ that can be proved is that in most cases the defendant’s asbestos would have been the cause.”

Id. at 711-12 (citing Steven Gold, “Causation in Toxic Torts: Burdens of Proof, Standards of Persuasion, and Statistical Evidence,” 96 Yale L.J. 376, 384, 390 (1986). See also Guinn v. AstraZeneca Pharms., 602 F.3d 1245, 1255 (11th Cir. 2010) (“An expert, however, cannot merely conclude that all risk factors for a disease are substantial contributing factors in its development. ‘The fact that exposure to [a substance] may be a risk factor for [a disease] does not make it an actual cause simply because [the disease] developed.’”) (internal citation omitted).

Specific causation is the soft underbelly of the toxic tort world, in large measure because courts know that risk is not specific causation. The analytical care of the Guinn case and others is often abandoned when it will stand in the way of compensation. The conflation of risk and (specific) causation is prevalent precisely because in many cases there is no scientific or medical way to discern what antecedent risks actually played a role in causing an individual’s disease. Opinions about specific causation are thus frequently devoid of factual or logical support, and are propped up solely by hand waving about differential etiology and inference to the best explanation.

In the scientific world, most authors recognize that risk, even if real and above baseline, regardless of magnitude, does not support causal attribution in a specific case.[1] Sir Richard Doll, who did so much to advance the world’s understanding of asbestosis as a cause of lung cancer, issued a caveat about the limits of specific causation inference. Richard Doll, “Proof of Causality: Deduction from Epidemiological Observation,” 45 Perspectives in Biology & Medicine 499, 500 (2002) (“That asbestos is a cause of lung cancer in this practical sense is incontrovertible, but we can never say that asbestos was responsible for the production of the disease in a particular patient, as there are many other etiologically significant agents to which the individual may have been exposed, and we can speak only of the extent to which the risk of the disease was increased by the extent of his or her exposure.”)

Similarly, Kenneth Rothman, a leading voice among epidemiologists, cautioned against conflating epidemiologic inferences about groups with inferences about causes in individuals. Kenneth Rothman, Epidemiology: An Introduction 44 (Oxford 2002) (“An elementary but essential principal that epidemiologists must keep in mind is that a person may be exposed to an agent and then develop disease without there being any causal connection between exposure and disease.” … “In a courtroom, experts are asked to opine whether the disease of a given patient has been caused by a specific exposure. This approach of assigning causation in a single person is radically different from the epidemiologic approach, which does not attempt to attribute causation in any individual instance. Rather, the epidemiologic approach is to evaluate the proposition that the exposure is a cause of the disease in a theoretical sense, rather than in a specific person.”) (emphasis added).

The late David Freedman, who was the co-author of the chapters on statistics in all three editions of the Reference Manual on Scientific Evidence, was also a naysayer when it came to transmuting risk into cause:

“The scientific connection between specific causation and a relative risk of two is doubtful. *** Epidemiologic data cannot determine the probability of causation in any meaningful way because of individual differences.”

David Freedman & Philip Stark, “The Swine Flu Vaccine and Guillaine-Barré Syndrome: A Case Study in Relative Risk and Specific Causation,” 64 Law & Contemporary Problems 49, 61 (2001) (arguing that proof of causation in a specific case, even starting with a relative risk of four, was “unconvincing”; citing Manko v. United States, 636 F. Supp. 1419, 1437 (W.D. Mo. 1986) (noting relative risk of 3.89–3.92 for GBS from swine-flu vaccine), aff’d in part, 830 F.2d 831 (8th Cir. 1987)).

Graham Colditz, who testified for plaintiffs in the hormone therapy litigation, similarly has taught that an increased risk of disease cannot be translated into the “but-for” standard of causation. Graham A. Colditz, “From epidemiology to cancer prevention: implications for the 21st Century,” 18 Cancer Causes Control 117, 118 (2007) (“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.”)

Another epidemiologist, who wrote the chapter in the Federal Judicial Center’s Reference Manual on Scientific Evidence, on epidemiology, put the matter thus:

“However, the use of data from epidemiologic studies is not without its problems. Epidemiology answers questions about groups, whereas the court often requires information about individuals.”

Leon Gordis, Epidemiology 362 (5th ed. 2014) (emphasis in original).

=========================================================

In New Jersey, an expert witness’s opinion that lacks a factual foundation is termed a “net opinion.” Polzo v. County of Essex, 196 N.J. 569, 583 (2008) (explaining New Jersey law’s prohibition against “net opinions” and “speculative testimony”). Under federal law, Rule 702, such an opinion is simply called inadmissible.

Here is an interesting example of a “net opinion” from an expert witness, in the field of epidemiology, who has testified in many judicial proceedings:

November 12, 2008

George T. Brugess, Esq.

Hoey & Farina, Attorneys at Law

542 South Dearborn Street, Suite 200

Chicago, IL 60605

Ref: Oscar Brooks v. Ingram Barge and Jantran Inc.

* * * *

Because [the claimant] was employed 28 years, he falls into the greater than 20 years railroad employment category (see Table 3 of Garshick’s 2004 paper) which shows a significant risk for lung cancer that ranges from 1.24 to 1.50. This means that his diesel exposure was a significant factor in his contracting lung cancer. His extensive smoking was also a factor in his lung cancer, and diesel exposure combined with smoking is an explanation for the relatively early age, 61 years old, of his diagnosis.

Now assuming that diesel exposure truly causes lung cancer, what was the basis for this witness (David F. Goldsmith, PhD) to opine that diesel exposure was a “significant factor” in the claimant’s developing lung cancer? None really. There was no basis in the report, or in the scientific data, to transmute an exposure that yielded a risk ratio of 1.24 to 1.50 for lung cancer, in a similarly exposed population to diesel emissions, into a “significant factor.” The claimant’s cancer may have arisen from background, baseline risk. The cancer may have arisen from the risk due to smoking, which would have been on the order of a 2,000% increase, or so. The cancer may have arisen from the claimed carcinogenicity of diesel emissions, on the order of 25 to 50%, which was rather insubstantial compared with his smoking risk. Potentially, the cancer arose from a combination of the risk from both diesel emissions and tobacco smoking. In the population of men who looked like Mr. Oscar Brooks, by far, the biggest reduction in incidence would be achieved by removing tobacco smoking.

There were no biomarkers that identified the claimant’s lung cancer as having been caused by diesel emissions. The expert witness’s opinion was nothing more than an ipse dixit that equated a risk, and a rather small risk, with specific causation. Notice how a 24% increased risk from diesel emissions was a “significant factor,” but the claimant’s smoking history was merely “a factor.”

Goldsmith’s report on specific causation was a net opinion that exemplifies what is wrong with a legal system that encourages and condones baseless expert witness testimony. In Agent Orange, Judge Weinstein pointed out that the traditional judicial antipathy to probabilism would mean no recovery in many chemical and medicinal exposure cases. If the courts lowered their scruples to permit recovery on a naked statistical inference of greater than 50%, from relative risks greater than two, some cases might remain viable (but alas not the Agent Orange case itself). Judge Weinstein was, no doubt, put off by the ability of defendants, such as tobacco companies, to avoid liability because plaintiffs would never have more than evidence of risk. In the face of relative risks often in excess of 30, with attributable risks in excess of 95%, this outcome was disturbing.

Judge Weinstein’s compromise was a pragmatic solution to the problem of adjudicating specific causation on the basis of risk evidence. Although as noted above, many scientists rejected any use of risk to support specific causation inferences, some scientists agreed with this practical solution. Ironically, David Goldsmith, the author of the report in the Oscar Brooks case, supra, was one such writer who had embraced the relative risk cut off:

“A relative risk greater than 2.0 produces an attributable risk (sometimes called attributable risk percent¹⁰) or an attributable fraction that exceeds 50%. An attributable risk greater than 50% also means that ‘it is more likely than not’, or, in other words, there is a greater than 50% probability that the exposure to the risk factor is associated with disease.”

David F. Goldsmith & Susan G. Rose, “Establishing Causation with Epidemiology,” in Tee L. Guidotti & Susan G. Rose, eds., Science on the Witness Stand: Evaluating Scientific Evidence in Law, Adjudication, and Policy 57, 60 (OEM Press 2001).

In the Brooks case, Goldsmith did not have an increased risk even close to 2.0. The litigation industry ultimately would not accept anything other than full compensation for attributable risks greater than 0%.

[1] See, e.g., Sander Greenland, “Relation of the Probability of Causation to Relative Risk and Doubling Dose: A Methodologic Error that Has Become a Social Problem,” 89 Am. J. Pub. Health 1166, 1168 (1999)(“[a]ll epidemiologic measures (such as rate ratios and rate fractions) reflect only the net impact of exposure on a population”); Joseph V. Rodricks & Susan H. Rieth, “Toxicological Risk Assessment in the Courtroom: Are Available Methodologies Suitable for Evaluating Toxic Tort and Product Liability Claims?” 27 Regulatory Toxicol. & Pharmacol. 21, 24-25 (1998)(noting that a population risk applies to individuals only if all persons within the population are the same with respect to the influence of the risk on outcome); G. Friedman, Primer of Epidemiology 2 (2d ed. 1980)(epidemiologic studies address causes of disease in populations, not causation in individuals)

Posted in Causation, Expert Witnesses, Risk and Risk Factor, Rule 702 | Comments Off on Substituting Risk for Specific Causation

Goodman v Viljoen – Meeting the Bayesian Challenge Head On

June 11th, 2014

Putting Science On Its Posterior

Plaintiffs’ and Defendants’ counsel both want the scientific and legal standard to be framed as a very high posterior probability of the truth of a claim. Plaintiffs want the scientific posterior probability to be high because they want to push the legal system in the direction of allowing weak or specious claims that are not supported by sufficient scientific evidence to support a causal conclusion. By asserting that the scientific posterior probability for a causal claim is high, and that the legal and scientific standards are different, they seek to empower courts and juries to support judgments of causality that are deemed inconclusive, speculative, or worse, by scientists themselves.

Defendants want the scientific posterior probability to be high, and claim that the legal standard should be at least as high as the scientific standard.

Both Plaintiffs and Defendants thus find common cause in committing the transposition fallacy by transmuting the coefficient of confidence, typically 95%, into a minimally necessary posterior probability for scientific causal judgments. “One wanders to the left, another to the right ; both are equally in error, but are seduced by different delusions.”[1]

In the Goodman v. Viljoen[2] case, both sides, plaintiffs and defendants, embraced the claim that science requires a high posterior probability, and that the p-value provided evidence of the posterior probability of the causal claim at issue. The error came mostly from the parties’ clinical expert witnesses and from the lawyers themselves; the parties’ statistical expert witnesses appeared to try to avoid the transposition fallacy. Clearly, no text would support the conflation of confidence with certainty. No scientific text, treatise, or authority was cited for the notion that scientific “proof” required 95% certainty. This notion was simply an opinion of testifying witnesses.

The principal evidence that antenatal corticosteroid (ACS) therapy can prevent cerebral palsy (CP) came from a Cochrane review and meta-analysis[3] of clinical trials. The review examined a wide range of outcomes, only one of which was CP. The trials were apparently not designed to assess CP risk, and they varied significantly in case definition, diagnostic criteria, and length of follow up for case ascertainment. Of the five included studies, four ascertained CP at follow up from two to six years, and the length of follow up was unknown in the fifth study.

Data were sparse in the Cochrane review, as expected for a relatively rare outcome. The five studies encompassed 904 children, with 490 in the treatment group, and 414 in the control group. There was a total of 48 CP cases, with 20 in the treatment, and 28 in the control, groups. Blinding was apparently not maintained over the extended reporting period.

Professor Andrew Willan, plaintiffs’ testifying expert witness on statistics, sponsored a Bayesian statistical analysis, with which he concluded that there was between a 91 and 97% probability that there was an increased risk of CP from not providing ACS in pre-term labor (or, a decreased risk of CP from administering ACS).[4] Willan’s posterior probabilities was for any increased risk, based upon the Cochrane data. Willan’s calculations were not provided in his testimony, and no information about his prior probability, was given. The data came from clinical trials, but the nature of the observations and the analyses made these trials little more than observational studies conducted within the context of clinical trials designed to look at other outcomes. The Bayesian analysis did not account for the uncertainty in the case definitions, variations in internal validity and follow up, and biases in the clinical trials. Willan’s posterior probabilities thus described a maximal probability for general causation, which surely needed to be discounted for validity and bias issues.

There was a further issue of external validity. The Goodman twins developed CP from having sustained periventricular leukomalacia (PVL), which is one among several mechanistic pathways by which CP can develop in pre-term infants. The Cochrane data did not address PVL, and the included trials were silent as to whether any of the CP cases involved PVL mechanisms. There was no basis for assuming that ACS reduced risk of CP from all mechanisms equally, or even at all.[5] The Willan posterior probabilities did not address the external validity issues as they pertained to the Goodman case itself.

Although Dr. Viljoen abandoned the challenge to the Bayesian analysis at trial, his statistical expert witness, Dr. Robert Platt went further to opine that he agreed with Willan’s calculations. To agree with his calculations, and the posterior probabilities that came out of those calculations, Platt had to have agreed with the analyses themselves. This agreement seems ill considered given that elsewhere in his testimony, Platt appears to advance important criticisms of the Cochrane data in the form of validity and bias issues.

Certainly, Platt’s concession about the correctness of Willan’s calculations greatly undermined Dr. Viljoen’s position with the trial and appellate court. Dr. Viljoen maintained those criticisms throughout the trial, and on appeal. See, e.g., Defendant (Appellant) Factum, 2012 CCLTFactum 20936, at ¶14(a)

(“(a) antenatal corticosteroids have never been shown to reduce the incidence or effect of PVL”); id. at ¶14(d)(“at best, even taking the Bayesian approach at face value, the use of antenatal corticosteroids showed only a 40% reduction in the incidence of cerebral palsy, but not PVL”).

How might have things gone better for Dr. Vijoen? For one thing, Platt’s concession about the correctness of Willan’s calculations had to be explained and qualified as conceding only the posterior probability on the doubtful and unproven assumptions made by Willan. Willan’s posterior, as big as it was, represented only an idealized maximal posterior probability, which in reality had to be deeply discounted by important uncertainties, biases, and validity concerns. The inconclusiveness of the data were “provable” on either a frequentist or a Bayesian analysis.

[1] Horace, in Wood, Dictionary of Quotations 182 (1893).

[2] Goodman v. Viljoen, 2011 ONSC 821 (CanLII), aff’d, 2012 ONCA 896 (CanLII), leave appeal den’d, Supreme Court of Canada No. 35230 (July 11, 2013).

[3] Devender Roberts & Stuart R Dalziel “Antenatal corticosteroids for accelerating fetal lung maturation for women at risk of preterm birth,” Cochrane Database of Systematic Reviews, at 8, Issue 3. Art. No. CD004454 (2006)

[4] Notes of Testimony of Andrew Willan at 34 (April 9, 2010) (concluding that ACS reduces risk of CP, with a probability of 91 to 97 percent, depending upon whether random effects or fixed effect models are used).

[5] See, e.g., Olivier Baud, Laurence Laurence Foix l’Hélias, et al., “Antenatal Glucocorticoid- Treatment and Cystic Periventricular Leukomalacia in Very Premature Infants,” 341 New Engl. J. Med. 1190, 1194 (1999) (“Our results suggest that exposure to betamethasone but not dexamethasone is associated with a decreased risk of cystic periventricular leukomalacia.”).

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Goodman v Viljoen – Statistical Fallacies from Both Sides

June 8th, 2014

There was a deep irony to the Goodman[1] case. If a drug company, in 1995, marketed antenatal corticosteroid (ACS) for the prevention of cerebral palsy (CP) in the United States, the government might well have prosecuted the company for misbranding. The company might also be subject to a False Claims Act case as well. No clinical trial had found ACS efficacious for the prevention of CP at the significance level typically required by the FDA; no meta-analysis had found ACS statistically significantly better than placebo for this purpose. In the Goodman case, however, failure to order a full course of ACS was malpractice with respect to the claimed causation of CP in the Goodman twins.

The Goodman case also occasioned a well-worn debate over the difference between scientific and legal evidence, inference, and standards of “proof.” The plaintiffs’ case rested upon a Cochrane review of ACS with respect to various outcomes. For CP, the Cochrane meta-analyzed only clinical trial data, and reported:

“a trend towards fewer children having cerebral palsy (RR 0.60, 95% CI 0.34 to 1.03, five studies, 904 children, age at follow up two to six years in four studies, and unknown in one study).”[2]

The defendant, Dr. Viljoen, appeared to argue that the Cochrane meta-analysis must be disregarded because it did not provide a showing of efficacy for ACS in preventing CP, at a significance probability less than 5 percent. Here is the trial court’s characterization of Dr. Viljoen’s argument:

“[192] The argument that the Cochrane data concerning the effects of ACS on CP must be ignored because it fails to reach statistical significance rests on the flawed premise that legal causation requires the same standard of proof as medical/scientific causation. This is of course not the case; the two standards are in fact quite different. The law is clear that scientific certainty is not required to prove causation to the legal standard of proof on a balance of probabilities (See: Snell v. Farrell, [1990] 2 S.C.R. 311, at para. 34). Accordingly, the defendant’s argument in this regard must fail and for the purposes of this court, I accept the finding of the Cochrane analysis that ACS reduces the instance [sic] of CP by 40%.”

“Disregard” seems extreme for a meta-analysis that showed a 40% reduction in risk of a serious central nervous system disorder, with p = 0.065. Perhaps Dr. Viljoen might have tempered his challenge some by arguing that the Cochrane analysis was insufficient. One problem with Dr. Viljoen’s strident argument about statistical significance was that it overshadowed the more difficult, qualitative arguments about threats to validity in the Cochrane finding from loss to follow up in the aggregated trial data. These threats were probably stronger arguments against accepting the Cochrane “trend” as a causal conclusion. Indeed, the validity and the individual studies and the meta-analyses, along with questions about the accuracy of data, were not reflected in Bayesian analysis.

Another problem is that Dr. Viljoen’s strident assertion that p < 0.05 was absolutely necessary fed plaintiffs’ argument that the defendant was attempting to change the burden of proof for plaintiffs from greater than 50% to 95% or greater. Given the defendant’s position, great care was required to prevent the trial court from committing the transposition fallacy.

Justice Walters rejected the suggestion that a meta-analysis with a p-value of 6.5% should be disregarded, but the court’s discussion skirts the question whether and how the Cochrane data can be sufficient to support a conclusion of ACS efficacy. Aside from citing a legal case, however, Justice Walters provided no basis for suggesting that the scientific standard of proof was different from the legal standard. From the trial court’s opinion, the parties or their expert witnesses appeared to conflate “confidence,” a technical term when used to describe intervals or random error around sample statistics, with “level of certainty” in the obtained result.

Justice Walters is certainly not the first judge to fall prey to the fallacious argument that the scientific burden of proof is 95%.[3] The 95% is, of course, the coefficient of confidence for the confidence interval that is based upon a p-value of 5%. No other explanation for why 95% is a “scientific” standard of proof was offered in Goodman; nor is it likely that anyone could point to an authoritative source for the claim that scientists actually adjudge facts and theories by this 95 percent probability level.

Justice Walters’ confusion was led by the transposition fallacy, which confuses posterior and significance probabilities. Here is a sampling from Her Honor’s opinion, first from Dr. Jon Barrett, one of the plaintiffs’ expert witnesses, an obstetrician and fetal maternal medicine specialist at Sunnybrook Hospital, in Toronto, Ontario:

“[85] Dr. Barrett’s opinion was not undermined during his lengthy cross-examination. He acknowledged that the scientific standard demands 95% certainty. He is, however, prepared to accept a lower degree of certainty. To him, 85 % is not merely a chance outcome.

* * *

[87] He acknowledged that scientific evidence in support of the use of corticosteroids has never shown statistical significance with respect to CP. However, he explained it is very close at 93.5%. He cautioned that if you use a black and white outlook and ignore the obvious trends, you will falsely come to the conclusion that there is no effect.”

Dr. Jon (Yoseph) Barrett is a well-respected physician, who specializes in high-risk pregnancies, but his characterization of a black-white outlook on significance testing as leading to a false conclusion of no effect was statistically doubtful.[4] Dr. Barrett may have to make divinely inspired choices in surgery, but in a courtroom, expert witnesses are permitted to say that they just do not know. Failure to achieve statistical significance, with p < 0.05, does support a conclusion that there is no effect.

Professor Andrew Willan was plaintiffs’ testifying expert witness on statistics. Here is how Justice Walters summarized Willan’s testimony:

“[125] Dr. Willan described different statistical approaches and in particular, the frequentist or classical approach and the Bayesian approach which differ in their respective definitions of probability. Simply, the classical approach allows you to test the hypothesis that there is no difference between the treatment and a placebo. Assuming that there is no difference, allows one to make statements about the probability that the results are not due to chance alone.

To reach statistical significance, a standard of 95% is required. A new treatment will not be adopted into practice unless there is less than a 5% chance that the results are due to chance alone (rather than due to true treatment effect).

[127] * * * The P value represents the frequentist term of probability. For the CP analysis [from the Cochrane meta-analysis], the P value is 0.065. From a statistical perspective, that means that there is a 6.5% chance that the differences that are being observed between the treatment arm versus the non-treatment arm are due to chance rather than the treatment, or conversely, a 93.5% chance that they are not.”

Justice Walters did not provide transcript references for these statements, but they are clear examples of the transposition fallacy. The court’s summary may have been unfair to Professor Willan, who seems to have taken care to avoid the transposition fallacy in his testimony:

“And I just want to draw your attention to the thing in parenthesis where it says, “P = 0.065.” So, basically that is the probability of observing data this extremely, this much in favor of ACS given, if, if in fact the no [sic, null] hypothesis was true. So, if, if the no hypothesis was true, that is there was no difference, then the probability of observing this data is only 6.5 percent.”

Notes of Testimony of Andrew Willan at 26 (April , 2010). In this quote, Professor Willan might have been more careful to point out that the significance probability of 6.5% is a cumulative probability by describing the data observed “this extremely” and more. Nevertheless, Willan certainly made clear that the probability measure was based upon assuming the correctness of the null hypothesis. The trial court, alas, erred in stating the relevant statistical concepts.

And then there was the bizarre description by Justice Walters, of the Cochrane data, as embodying a near-uniform distribution represented by the Cochrane data:

“[190] * * * The Cochrane analysis found that ACS reduced the risk of CP (in its entirety) by 40%, 93.5% of the time.”

The trial court did not give the basis for this erroneous description of the Cochrane ACS/CP data.[5] To be sure, if the Cochrane result were true, then 40% reduction might be the expected value for all trials, but it would be a remarkable occurrence for 93.5% of the trials to obtain the same risk ratio as the one observed in the meta-analysis.

The defendant’s expert witness on statistical issues, Prof. Robert Platt, similarly testified that the significance probability reported by the Cochrane was dependent upon an assumption of the null hypothesis of no association:

“What statistical significance tells us, and I mentioned at the beginning that it refers to the probability of a chance finding could occur under the null-hypothesis of no effect. Essentially, it provides evidence in favour of there being an effect. It doesn’t tell us anything about the magnitude of that effect.”

Notes of Testimony of Robert Platt at 11 (April 19, 2010)

Perhaps part of the confusion resulted from Prof. Willan’s sponsored Bayesian analysis, which led him to opine that the Cochrane data permitted him to state that there was a 91 to 97 percent probability of an effect, which might have appeared to the trial court to be saying the same thing as interpretation of the Cochrane’s p-value of 6.5%. Indeed, Justice Walters may have had some assistance in this confusion from the defense statistical expert witness, Prof. Platt, who testified:

“From the inference perspective the p-value of 0.065 that we observe in the Cochrane review versus a 91 to 97 percent probability that there is an effect, those amount to the same thing.”

Notes of Testimony of Robert Platt at 50 (April 19, 2010). Now the complement of the p-value, 93.5%, may have fallen within the range of posterior probabilities asserted by Professor Willan, but these probabilities are decidedly not the same thing.

Perhaps Prof. Platt was referring only to the numerical equivalence, but his language, “the same thing,” certainly could have bred misunderstanding. The defense apparently attacked the reliability of the Bayesian analysis before trial, only to abandon the challenge by the time of trial. At trial, defense expert witness Prof. Platt testified that he did not challenge Willan’s Bayesian analysis, or the computation of posterior probabilities. Platt’s acquiescence in Willan’s Bayesian analysis is unfortunate because the parties never developed testimony exactly as to how Willan arrived at his posterior probabilities, and especially as to what prior probability he employed.

Professor Platt went on to qualify his understanding of Willan’s Bayesian analysis as providing a posterior probability that there is an effect, or in other words, that the “effect size” is greater than 1.0. At trial, the parties spent a good deal of time showing that the Cochrane risk ratio of 0.6 represented the decreased risk for CP of administering a full course of ACS, and that this statistic could be presented as an increased CP risk ratio of 1.7, for not having administered a full course of ACS. Platt and Willan appeared to agree that the posterior probability described the cumulative posterior probabilities for increased risks above 1.0.

“[T]he 91% is a probability that the effect is greater than 1.0, not that it is 1.7 relative risk.”

Notes of Testimony of Robert Platt at 51 (April 19, 2010); see also Notes of Testimony of Andrew Willan at 34 (April 9, 2010) (concluding that ACS reduces risk of CP, with a probability of 91 to 97 percent, depending upon whether random effects or fixed effect models are used).[6]

One point on which the parties’ expert witnesses did not agree was whether the failure of the Cochrane’s meta-analysis to achieve statistical significance was due solely to the sparse data aggregated from the randomized trials. Plaintiffs’ witnesses appeared to have testified that had the Cochrane been able to aggregate additional clinical trial data, the “effect size” would have remained constant, and the p-value would have shrunk, ultimately to below the level of 5 percent. Prof. Platt, testifying for the defense, appropriately criticized this hand-waving excuse:

“Q. and the probability factor, the P value, was 0.065, which the previous witness had suggested is an increase in probability of our reliability on the underlying data. Is it reasonable to assume that this data that a further increase in the sample size will achieve statistical significance?

A. No, that’s not a reasonable assumption….”

Notes of Testimony of Robert Platt at 29 (April 19, 2010).

Positions on Appeal

Dr. Viljoen continued to assert the need for significance on appeal. As appellant, he challenged the trial court’s finding that the Cochrane review concluded that there was a 40% risk reduction. See Goodman v. Viljoen, 2011 ONSC 821, at ¶192 (CanLII) (“I accept the finding of the Cochrane analysis that ACS reduces the instance of CP by 40%”). Dr. Viljoen correctly pointed out that the Cochrane review never reached such a conclusion. Appellant’s Factum, 2012 CCLTFactum 20936, ¶64. It was the plaintiffs’ expert witnesses, not the Cochrane reviewers, who reached the conclusion of causality from the Cochrane data.

On appeal, Dr. Viljoen pressed the point that his expert witnesses described statistical significance in the Cochrane analysis would have been “a basic and universally accepted standard” for showing that ACS was efficacious in preventing CP or PVL. Id. at ¶40. The appellant’s brief then commits to the very error that Dr. Barrett complained would follow from a finding that did not have statistical significance; Dr. Viljoen maintained that the “trend” of reduced CP reduced CD rates from ACS administration “is the same as a chance occurrence.” Defendant (Appellant), 2012 CCLTFactum 20936, at ¶40; see also id. at ¶14(e) (arguing that the Cochrane result for ACS/CP “should be treated as pure chance given it was not a statistically significant difference”).

Relying upon the Daubert decision from the United States, as well as Canadian cases, Dr. Viljoen framed one of his appellate issues as whether the trial court had “erred in relying upon scientific evidence that had not satisfied the benchmark of statistical significance”:

“101. Where a scientific effect is not shown to a level of statistical significance, it is not proven. No study has demonstrated a reduction in cerebral palsy with antenatal corticosteroids at a level of statistical significance.

102. The Trial Judge erred in law in accepting that antenatal corticosteroids reduce the risk of cerebral palsy based on Dr. Willan’s unpublished Bayesian probability analysis of the 48 cases of cerebral palsy reviewed by Cochrane—an analysis prepared for the specific purpose of overcoming the statistical limitations faced by the Plaintiffs on causation.”

Defendant (Appellant), 2012 CCLTFactum 20936. The use of the verb “proven” is problematic because it suggests a mathematical demonstration, which is never available for empirical propositions about the world, and especially not for the biological world. The use of a mathematical standard begs the question whether the Cochrane data were sufficient to establish a scientific conclusion of the efficacy of ACS in preventing CP.

In opposing Dr. Viljoen’s appeal, the plaintiffs capitalized upon his assertion that science requires a very high level of posterior probability for establishing a causal claim, by simply agreeing with it. See Plaintiffs’ (Respondents’) Factum, 2012 CCLTFactum 20937, at ¶31 (“The scientific method requires statistical significance at a 95% level.”). By accepting the idealized notion that science somehow requires 95% certainty (as opposed to 95% confidence levels as a test for assessing random error), the plaintiffs made the defendant’s legal position untenable.

In order to keep the appellate court thinking that the defendant was imposing an extra-legal, higher burden of proof upon plaintiffs, the plaintiffs went so far as to misrepresent the testimony of their own expert witness, Professor Willan, as having committed the transposition fallacy:

“49. Dr. Willan provided the frequentist explanation of the Cochrane analysis on CP:

a. The risk ratio (RR) is .060 which means that there is a 40% risk reduction in cerebral palsy where there has been administration of antenatal corticosteroids;

b. The upper limit of the confidence interval (CI) barely crosses 1 so it just barely fails to meet the rigid test of statistical significance;

c. The p value represents the frequentist term of probability;

d. In this case the p value is .065;

e. From a statistical perspective that means that there is a 6.5% chance that the difference observed in CP rates is due to chance alone;

f. Conversely there is a 93.5% chance that the result (the 40% reduction in CP) is due to a true treatment effect of ACS.”

2012 CCLTFactum 20937, at ¶49 (citing Evidence of Dr. Willan, Respondents’ Compendium, Tab 4, pgs. 43-52).

Although Justice Doherty dissented from the affirmance of the trial court’s judgment, he succumbed to the parties’ misrepresentations about scientific certainty, and their prevalent commission of the transposition fallacy. Goodman v. Viljoen, 2012 ONCA 896 (CanLII) at ¶36 (“Scientists will draw a cause and effect relationship only when a result follows at least 95 per cent of the time. The results reported in the Cochrane analysis fell just below that standard.”), leave appeal den’d, Supreme Court of Canada No. 35230 (July 11, 2013).

The statistical errors on both sides redounded to the benefit of the plaintiffs.

[1] Goodman v. Viljoen, 2011 ONSC 821 (CanLII), aff’d, 2012 ONCA 896 (CanLII), leave appeal den’d, Supreme Court of Canada No. 35230 (July 11, 2013).

[2] Devender Roberts & Stuart R Dalziel “Antenatal corticosteroids for accelerating fetal lung maturation for women at risk of preterm birth,” Cochrane Database of Systematic Reviews, at 8, Issue 3. Art. No. CD004454 (2006).

[3] See, e.g., In re Ephedra Prods. Liab. Litig., 393 F.Supp. 2d 181, 191, 193 (S.D.N.Y. 2005) (fallaciously arguing that the use of a critical value of less than 5% of significance probability increased the “more likely than not” burden of proof upon a civil litigant. Id. at 188, 193. See also Michael O. Finkelstein, Basic Concepts of Probability and Statistics in the Law 65 (2009) (criticizing the Ephedra decision for confusing posterior probability with significance probability).

[4] I do not have the complete transcript of Dr. Barrett’s testimony, but the following excerpt from April 9, 2010, at page 100, suggests that he helped lead Justice Walters into error: “When you say statistical significance, if you say that something is statistically significance, it means you’re, for the scientific notation, 95 percent sure. That’s the standard we use, 95 percent sure that that result could not have happened by chance. There’s still a 5 percent chance it could. It doesn’t mean for sure, but 95 percent you’re sure that the result you’ve got didn’t happen by chance.”

[5] On appeal, the dissenting judge erroneously accepted Justice Walters’ description of the Cochrane review as having supposedly reported a 40% reduction in CP incidence, 93.5% of the time, from use of ACS. Goodman v. Viljoen, 2012 ONCA 896 (CanLII) at ¶36, leave appeal den’d, Supreme Court of Canada No. 35230 (July 11, 2013).

[6] The Bayesian analysis did not cure the attributability problem with respect to specific causation.

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Goodman v Viljoen – Subterfuge to Circumvent Relative Risks Less Than 2

June 6th, 2014

Back in March, I wrote about a “Black Swan” case, in which litigants advanced a Bayesian analysis to support their claims. Goodman v. Viljoen, 2011 ONSC 821 (CanLII), aff’d, 2012 ONCA 896 (CanLII), leave appeal den’d, Supreme Court of Canada No. 35230 (July 11, 2013).

Goodman was a complex medical practice case in which Mrs. Goodman alleged that her obstetrician, Dr. Johan Viljoen, deviated from the standard of care by failing to prescribe antenatal corticosteroids (ACS) sufficiently in advance of delivery to reduce the risks attendant early delivery for her twin boys, of early delivery. Both boys developed cerebral palsy (CP). The parties and their experts agreed that the administration of ACS reduced the risks of respiratory distress and other complications of pre-term birth, but they disputed the efficacy of ACS to avoid or diminish the risk of CP.

According to the plaintiffs, ACS would have, more probably than not, prevented the twins from developing cerebral palsy, or would have diminished the severity of their condition. Dr. Viljoen disputed both general and specific causation. Evidence of general causation came from both randomized clinical trials (RCTs) and observational studies.

Limitations Issue

There were many peculiar aspects to the Goodman case, not the least of which was that the twins sued Dr. Viljoen over a decade after they were born. Dr. Viljoen had moved his practice in the passage of time, and he was unable to produce crucial records that supported his account of how his staff responded to Mrs. Goodman’s telephone call about signs and symptoms of labor. The prejudice to Dr. Viljoen illustrates the harshness of broad tolling statutes, the unfairness of which could be reduced by requiring infant plaintiffs to give notice of their intent to sue, even if they wait until the age of majority before filing their complaints.

State of the Art Issue

Dr. Viljoen suffered perhaps a more serious prejudice in the form of hindsight bias that resulted from the evaluation of his professional conduct by evidence that was unavailable when the twins were born in 1995. The following roughly contemporaneous statement from the New England Journal of Medicine is typical of serious thinking at the time of the alleged malpractice:

“Antenatal glucocorticoid therapy decreases the incidence of several complications among very premature infants. However, its effect on the occurrence of cystic periventricular leukomalacia, a major cause of cerebral palsy, remains unknown.”

Olivier Baud, Laurence Laurence Foix l’Hélias, et al., “Antenatal Glucocorticoid- Treatment and Cystic Periventricular Leukomalacia in Very Premature Infants,” 341 New Engl. J. Med. 1190, 1190 (1999) (emphasis added). The findings of this observational study illustrate some of the difficulties with the claim that Dr. Viljoen failed to prevent an avoidable consequence of pre-term delivery:

“Our results suggest that exposure to betamethasone but not dexamethasone is associated with a decreased risk of cystic periventricular leukomalacia.”

Id. at 1194. Results varied among various corticosteroids, among doses, among timing regimens. There hardly seemed enough data in 1995 to dictate a standard of care.

Meta-Analysis Issues

Over ten years after the Goodman twins were born, the Cochrane collaboration published a meta-analysis that was primarily concerned with the efficacy of ACS for lung maturation. Devender Roberts & Stuart R Dalziel “Antenatal corticosteroids for accelerating fetal lung maturation for women at risk of preterm birth,” Cochrane Database of Systematic Reviews Issue 3. Art. No. CD004454 (2006). The trials included mostly post-dated the birth of the twins, and the alleged malpractice. The relevance of the trials to address the causation of CP in infants who experienced periventricular leukomalacia (PVL) was hotly disputed, but for now, I will gloss over the external validity problem of the Cochrane meta-analysis.

The Cochrane Collaboration usually limits its meta-analyses to the highest quality evidence, or RCTs, but in this instance, the RCTs did not include CP in its primary pre-specified outcomes. Furthermore, the trials were generally designed to ascertain short-term benefits from ACS, and the data in the trials were uncertain with respect to longer-term outcomes, which may have been ascertained differentially. Furthermore, the trials were generally small and were plagued by sparse data. None of the individual trials was itself statistically significant at the 5 percent level. The meta-analysis did not show a statistically significant decrease in CP from ACS treatment. The authors reported:

“a trend towards fewer children having cerebral palsy (RR 0.60, 95% CI 0.34 to 1.03, five studies, 904 children, age at follow up two to six years in four studies, and unknown in one study).”

Id. at 8 (emphasis added).

The Cochrane authors were appropriately cautious in interpreting the sparse data:

“Results suggest that antenatal corticosteroids result in less neurodevelopmental delay and possibly less cerebral palsy in childhood.”

Id. at 13-14 (emphasis added).

The quality of the trials included in the Cochrane meta-analysis varied, as did the trial methodologies. Despite the strong clinical heterogeneity, the Cochrane authors performed their meta-analysis with a fixed-effect model. The confidence interval, which included 1.0, reflected a p-value of 0.065, but that p-value would have certainly increased if a more appropriate random-effects model had been used.

Furthermore, the RCTs were often no better than observational studies on the CP outcome. The RCTs here perhaps should not have been relied upon to the apparent exclusion of observational epidemiology.

Relative Risk Less Than Two

There is much to be said about the handling of statistical significance, the Bayesian analysis, the arguments about causal inference, but for now, let us look at one of the clearest errors in the case: the inference of specific causation from a relative risk less than two. To be sure, the Cochrane meta-analysis reported a non-statistically significant 40% decrease, but if we were to look at this outcome in terms of the increase in risk of CP from the physician’s failure to administer ACS timely, then the risk ratio would be 1.67, or a 67% increase. On either interpretation, fewer than half the cases of CP can be attributed to the failure to administer ACS fully and timely in the case.

The parties tried their case before Justice Walters, in St. Catherines, Ontario. Goodman v. Viljoen, 2011 ONSC 821 (CanLII). Justice Walters recognized that specific causation was essential and at the heart of the parties’ disagreement:

“[47] In order to succeed, the plaintiffs must establish that the failure to receive a full course of ACS materially affected the twins’ outcome. That is, they must establish that “but for” the failureto receive a full course of ACS, the twins would not have suffered from the conditions they now do, or that the severity of these afflictions would have been materially reduced.

[48] Not surprisingly, this was the most contentious issue at trial and the court heard a good deal of evidence with respect to the issue of causation.”

One of the defendant’s expert witnesses, Robert Platt, a professor of statistics at McGill University School of Medicine, testified, according to Justice Walters:

“[144] Dr. Platt also stated that the absolute risk in and of itself does not tell us anything about what might have happened in a specific case absent clinical and mechanistic explanations for that specific case.”

The plaintiffs’ expert witnesses apparently conceded the point. Professor Andrew Willan, a statistician, testifying for the plaintiffs, attempted to brush Platt’s point aside by suggesting it would render clinical research useless, but that was hardly the point. Platt embraced clinical research for what it could show about the “averages” in a sample of the population, even if we cannot discern causal efficacy retrospectively in a specific patient:

“[133] Dr. Willan also responded to Dr. Platt’s criticism that it was impossible to determine the distribution of the effect across the population. Professor Willan felt this issue was a red herring, and if it were valid, it would render most clinical research useless. There is really no way of knowing who will benefit from a treatment and who will not. Unless there are reasons to believe otherwise, it is best to apply the population average effect to each person.”

Although Willan labeled Platt’s point as cold-blooded and fishy, he ultimately concurred that the population average effect should be applied to each person in the absence of evidence of risk being sequestered in a subgroup.

A closer look at Willan’s testimony at trial is instructive. Willan acknowledged, on direct examination, that the plaintiffs were at increased risk, even if their mother had received a full course of ACS. All he would commit to, on behalf of the plaintiffs, was that their risk would have been less had the ACS been given earlier:

“All we can say is that there’s a high probability that that risk would be reduced and that this is probably the best estimate of the excess risk for not being treated and I would say that puts that in the 70 percent range of excess risk and I would say the probability that the risk would have been reduced is into the 90 percentage points.”

Notes of Testimony of Andrew Willan at 62 (April 6, 2010). The 90 percentage points reference here was Willan’s posterior probability that the claimed effect was real.

On cross-examination, the defense pressed the point:

Q. What you did not do in this, in this report, is provide any quantification for the reduction in the risk, true?

A. That’s correct.

Notes of Testimony of Andrew Willan at 35 (April 9, 2010)

Q. And you stated that there is no evidence that the benefits of steroids is restricted to any particular subgroup of patients?

A. I wasn’t given any. I haven’t seen any evidence of that.

Id. at 43.

Q. And what you’re suggesting with that statement, is that the statistics should be generally, should be considered by the court to be generally applicable, true?

A. That’s correct.

Id. at 44.

Q. But given your report, you can’t offer assistance on the clinical application to the statistics, true?

A. That’s true.

Id. at 46.

With these concessions in hand, defense counsel elicited the ultimate concession relevant to the “but for” standard of causation:

Q. And to do that by looking at an increase in risk, the risk ratio from the data must achieve 2 in order for there to be a 50 percent change in the underlying data, true?

A. Yeah, to double the risk, the risk ratio would have to be 2, to double the risk.

Id. at 63.

* * *

Q. So, none of this data achieves the threshold of a 50 percent change in the underlying data, whether you look at it as an increase in risk or …

A. Sure.

Q …. a decrease in risk …

A. Yeah.

Id. at 66.

Leaping Inferences

The legal standard for causation in Canada is the same counterfactual requirement that applies in most jurisdictions in the United States. Goodman v. Viljoen, 2011 ONSC 821 (CanLII), at ¶14, 47. The trial court well understood that the plaintiffs’ evidence left them short of showing that their CP would not have occurred but for the delay in administering ACS. Remarkably, the court permitted the plaintiffs to use non-existing evidence to bridge the gap.

According to Dr. Max Perlman, plaintiffs’ expert witness on neonatology and pediatrics, CP is not a dichotomous condition, but a spectrum that is manifested on a continuum of signs and symptoms. The RCTs relied upon had criteria for ascertaining CP and including it as an outcome. The result of these criteria was that CP was analyzed as a binary outcome. Dr. Perlman, however, held forth that “common sense and clinical experience” told him that CP is not a condition that is either present or not, but rather presented on a continuum. Id. at [74].

Without any evidence, Perlman testified that when CP is not avoided by ACS, “it is likely that it is less severe for those who do go on to develop it.” Id. [75]. Indeed, Perlman made the absence of evidence a claimed virtue; with all his experience and common sense, he “could not think of a single treatment which affects a basic biological process that has a yes or no effect; they are all on a continuum.” Id. From here, Perlman soared to his pre-specified conclusion that “that it is more likely than not that the twins would have seen a material advantage had they received the optimal course of steroids.” Id. at [76].

Perlman’s testimony is remarkable for inventing a non-existing feature of biological evidence: everything is a continuum. Justice Walters could not resist this seductive testimony:

“[195] The statistical information is but one piece of the puzzle; one way of assessing the impact of ACS on CP. Notably, the 40% reduction in CP attributable to ACS represents an all or nothing proposal. In other words, 93.5% of the time, CP is reduced in its entirety by 40%. It was the evidence of Dr. Perlman, which I accept, that CP is not a black and white condition, and, like all biological processes, it can be scaled on a continuum of severity. It therefore follows that in those cases where CP is not reduced in its entirety, it is likely to be less severe for those who go on to develop it. Such cases are not reflected in the Cochrane figure.

[196] Since the figure of 40% represents an all or nothing proposal, it does not accurately reflect the total impact of ACS on CP. Based on this evidence, it is a logical conclusion that if one were able to measure the total effect of ACS on CP, the statistical measure of that effect would be inflated beyond 40%.

[197] Unfortunately, this common sense conclusion has never and can never be tested by science. As Dr. Perlman testified, such a study would be impossible to conduct because it would require pre-identification of those persons who go on to develop CP. Furthermore, because the short term benefits of ACS are now widely accepted, it would be unethical to withhold steroids to conduct further studies on long term outcomes.”

Doubly unfortunate, because Perlman’s argument was premised on a counterfactual assumption. Many biological phenomena are dichotomous. Pregnancy, for instance, does not admit of degrees. Disease states are frequently dichotomous, and no evidence was presented that CP was not dichotomous. Threshold effects abound in living organisms. Perlman’s argument further falls apart when we consider that the non-experimental arm of the RCTs would also have had additional “less-severe” CP cases, with no evidence that they occurred disproportionately in the control arms of these RCTs. Furthermore, high-quality observational studies might have greater validity than post-hoc RCTs in this area, and there have been, and likely will continue to be, such studies to attempt better understanding of the efficacy of ACS, as well as differing effects among the various corticosteroids, doses, and patterns of administration.

On appeal, the Justice Walters’ verdict for plaintiffs was affirmed, but over a careful, thoughtful dissent. Goodman v. Viljoen, 2012 ONCA 896 (CanLII) (Doherty, J., dissenting). Justice Doherty caught the ultimate futility of Dr. Perlman’s opinion based upon non-existent evidence: even if there were additional sub-CP cases in the treatment arms of the RCTs, and if they occurred disporportionately more often in the treatment than in the placebo arms, we are still left guessing about the quantitative adjustment to make to the 40% decrease, doubtful as it was, which came from the Cochrane review.

Posted in Causation, Scientific Evidence, statistical evidence | Comments Off on Goodman v Viljoen – Subterfuge to Circumvent Relative Risks Less Than 2

Recrudescence of Traumatic Cancer Claims

June 4th, 2014

In 1991, Peter Huber, discussing traumatic cancer claims, wrote:

“After years of floundering in the junk science morass of traumatic cancer, judges slowly abandoned sequence-of-events logic, turned away from the sympathetic speculations of family doctors, and struggled on to the higher and firmer ground of epidemiology and medical science. Eventually, the change of heart among appellate judges was communicated back down to trial judges and worker’s compensation boards, and traumatic cancer went into almost complete remission.”

Peter W. Huber, Galileo’s Revenge: Junk Science in the Courtroom 55-56 (1991).

With the advent of Daubert and meaningful gatekeeping of expert witness opinion testimony, the traumatic cancer claims did recede. For a while. Plaintiffs’ counsel, and stalwart opponent of epistemic standards for scientific claims in court, Kenneth Chesebro attacked Huber’s précis of the traumatic cancer law and science. Kenneth J. Chesebro, “Galileo’s Retort: Peter Huber’s Junk Scholarship,” 42 Am. Univ. L. Rev. 1637 (1993). Defenses of the dubious science continue to appear, although mostly in non-peer-reviewed publications.[1]

One of the more disturbing implications of the West Virginia Supreme Court’s decision in Harris v. CSX Transportation, Inc., 232 W.Va. 617, 753 S.E.2d 275 (2013), was the Court’s reliance upon its own, recent approval of traumatic cancer claims. The Harris Court cited, with approval, a 2002 traumatic cancer case, State ex rel. Wiseman v. Henning, 212 W.Va. 128, 569 S.E.2d 204 (2002). The Wiseman case involved a specious claim that a traumatic rib injury caused multiple myeloma, a claim at odds with scientific method and observation. The West Virginia Supreme Court blinked at the challenge to the physician expert witness who advanced the causal claim in Wiseman; and in Harris, the Court made clear that blinking is what trial courts should do when confronted with methodological challenges to far-fetched causal opinions.

A couple of years ago, the New York Times ran an article about traumatic cancer. C. Claiborne Ray, “Injury and Insult” (Nov. 5, 2012), responding to the question “Is it possible for cancer to develop as a result of an injury?” Here is how Times science reporter responded:

A. “It’s a common myth that injuries can cause cancer,” the American Cancer Society says on its Web site. Until the 1920s, some doctors believed trauma did cause cancer, “despite the failure of injury to cause cancer in experimental animals.” But most medical authorities, including the cancer society and the National Cancer Institute, see no such link. The more likely explanation, the society suggests, is that a visit to the doctor for an injury could lead to finding an existing cancer.

Other possibilities are that scar tissue from an old trauma could look like a cancerous lesion and that an injured breast or limb would be more closely watched for cancer to develop.

Ms. Ray went on to note a published study, in which would-be myth-busters presented observational data purportedly showing a relationship between physical injury and subsequent breast cancer. The paper cited by Ms. Ray was a report on a small case-control study done by investigators at the Department of Geography, Lancaster University. See Jan Rigby, et al., “Can physical trauma cause breast cancer?” 11 Eur. J. Cancer. Prev. 307 (2002). The study consisted of 67 breast cancer cases and 134 controls, matched on age, family history, age of menarche, parity, age at first birth, and menopausal status.

Not surprisingly, considering its small size, the Rigby study reported no statistically significant differences for several factors known to be associated with breast cancer: social class, education, residence, smoking and alcohol consumption. Although lacking power to detect differences of known risk factors, this study turned up a large, statistically significant association between physical trauma and breast cancer:

“Women with breast carcinoma were more likely to report physical trauma to the breast in the previous 5 years than were the controls (odds ratio (OR) 3.3, 95% confidence interval (CI) 1.3-10.8, P < 0.0001).”

* * * * *

“More likely to [self-]report” hardly implies causation, but the authors jumped not only to a causal explanation but to a causal conclusion:

* * * * *

“In conclusion, recall bias is an unlikely explanation for these results in view of the nature and severity of physical trauma. Models of epithelial cell generation indicate that a causal link between physical trauma and cancer is plausible. A latent interval between cancer onset and presentation of under 5 years is also plausible. The most likely explanation of the findings is that physical trauma can cause breast cancer.”

Rigby at 307.

The Rigby study is a valuable demonstration of how malleable researchers can be in discovering plausible explanations for their data. The authors fail to discuss the natural history of breast carcinoma, such as tumor doubling time, which would make their five-year window decidedly implausible. The Rigby paper also demonstrates how strident researchers can be in claiming that they have produced a study that has eliminated bias in observational research, when they have barely scratched the surface of bias or confounding. Magical thinking is not the exclusive domain of lawyers.

Until reading the Harris and Wiseman cases, I had thought that the legal system had graduated from the “mythology” of traumatic cancer cases.[2] To be sure, in the past, any number of physicians have supported traumatic cancer claims, in print and in the courtroom.[3] Some authors attempted to put some rational limits on the extent of the traumatic cancer claims.[4] By 1947, at least, the trauma theory was criticized in leading texts.[5] In 1974, the Mayo Clinic published a review that emphasized the lack of experimental evidence to support the claim that uncomplicated trauma causes cancer.[6] The law review literature attempted to make sense of the compensation-frenzied courts, without much success.[7]

Many cases from most jurisdictions have approved traumatic cancer claims. Some are set out below. Some courts heroically resisted the pro-compensation Zeitgeist, usually on case-specific evidentiary issues.[8]

In New York, judges seem to be well aware that post hoc ergo propter hoc is a fallacy. Cassano v. Hagstrom, 5 N.Y.2d 643, 159 N.E.2d 348, 187 N.Y.S.2d 1 (1959) (affirming dismissal of case based because of plaintiffs’ attempt to use fallacious reasoning in the form of “post hoc ergo propter hoc”); Holzberg v. Flower & Fifth Ave. Hosps., 39 AD 2d 526 (N.Y. 1st Dep’t 1972). Still, the New York courts struggled with traumatic cancer claims, and appeared to oscillate wildly without clear guidance on whether or to what extent the courts could reject specious claiming supported by speculative or unreliable expert witness opinion testimony.[9] Given the current hostility to gatekeeping of expert witness opinion, a recrudescence of traumatic cancer claims is likely.

Opinions Approving Causation in Traumatic Cancer Cases

California

Santa Ana Sugar Co. v. Industrial Accid. Comm’n, 170 P. 630, 630 (Cal. Dist. Ct. App. 1917)

Colorado

Canon Reliance Coal Co. v. Indus. Comm’n, 72 Colo. 477, 211 P. 868, 869-70 (1922) (cancer caused by being hit on cheek with a lump of coal)

Georgia

National Dairy Prods. Corp. v. Durham, 154 S.E.2d 752, 753-54 (Ga. Ct. App. 1967)

Kentucky

Louisville Ry v. Steubing’s Adm’r, 136 S.W. 634, 634 (Ky. Ct. App. 1911)

Louisiana

Reed v. Mullin Wood Co., 274 So. 2d 845, 846-47 (La. Ct. App. 1972), cert. denied, 275 So. 2d 729, 791 (La. 1973);

Thompson v. New Orleans Ry. & Light Co., 83 So. 19, 20 (La. 1919)

Michigan

Wilson v. Doehler-Jarvis Div. of Nat’l Lead Co., 353 Mich. 363, 91 N.W.2d 538, 539-40 (1958) (blow to lip caused cancer)

Mooney v. Copper Range RR, 27 N.W.2d 603, 604 (Mich. 1947)

Minnesota

Daly v. Bergstedt, 267 Minn. 244, 126 N.W.2d 242, 247–48 (1964) (affirming jury finding of causation between traumatic leg fracture and breast cancer; six physicians testified against causation; one stated cancer “could” result from trauma; imagining that scientific and legal standards of causation differ)

Pittman v. Pillsbury Flour Mills, Inc., 48 N.W.2d 735, 736 (Minn. 1951)

Hertz v. Watab Pulp & Paper Co., 237 N.W. 610, 611 (Minn. 1931)

Austin v. Red Wing Sewer Pipe Co., 163 Minn. 397, 204 N.W. 323, 323-24 (Minn. 1925) (cancer developed one year after worker was hit in the face with coal)

Gaetz v. City of Melrose, 193 N.W. 691, 692 (Minn. 1923)

Missouri

Vitale v. Duerbeck, 338 Mo. 536, 92 S.W.2d 691, 695 (1936)

New Hampshire

Jewell v. Grand Trunk Ry, 55 N.H. 84 (1874) (reversing traumatic cancer verdict on other grounds)

New Mexico

White v. Valley Land Co., P.2d 707, 708-10 (N.M. 1957)

Ohio

Hanna v. Aetna Ins., 24 Ohio Misc. 27, 52 Ohio Op. 2d 316, 259 N.E.2d 177, 177-79 (Ohio Mun. Ct. Dayton 1970)(breast lump found three months after car accident)

Glenn v. National Supply, 129 N.E.2d 189, 190-91 (Ohio Ct. App. 1954)

Oregon

Devine v. Southern Pacific Co., 207 Or. 261, 295 P.2d 201 (1956) (holding that physician’s testimony as to “probable” causation between shoulder fracture and lung cancer was sufficient; jury verdict for plaintiff reversed on other grounds).

Pennsylvania

Baker v. DeRosa, 413 Pa. 164, 196 A.2d 387, 389–90 (Pa. 1964)

Menarde v. Philadelphia Transp. Co., 376 Pa. 497, 103 A.2d 681, 684(1954) (the fact that breast cancer was found in the same place as the injury-caused bruise helped establish causation);

Southern S.S. Co. v. Norton, 41 F. Supp. 103 (E.D. Pa. 1940) (trauma to skull and lower back held to have caused lung cancer)

Tennessee

Koehring-Southern & Am. Mut. Ins. Co. v. Burnette, 464 S.W.2d 820, 821 (Tenn. 1970)

Boyd v. Young, 193 Tenn. 272, 246 S.W.2d 10, 10 (Tenn. 1951)

Rhode Island

Valente v. Bourne Mills, 77 R.I. 274, 278-79, 75 A.2d 191, 193-94 (1950) (adopting house of cards position in which any rational inference suffices even if not supported by expert medical opinion)

Emma v. A.D. Julliard & Co., 75 R.I. 94, 63 A.2d 786, 787-89 (R.I. 1949)(plaintiff had malignant tumor removed from her breast seven weeks after being hit with a can of juice)

Texas

Traders & General Insur. Co. v. Turner, 149 S.W.2d 593, 597-98 (Tex. Civ. App. 1941) (testicular cancer)

Virginia

Ellis v. Commonwealth Dep’t of Highways, 28 S.E.2d 730, 731-32, 735 (Va. 1944) (accepting post-hoc reasoning “[f]acts prevail over possibilities or probabilities”)

Winchester Milling Corp. v. Sencindiver, 138 S.E. 479, 480-81 (Va. 1927)

[1] See, e.g., Melvin A. Shiffman, Can Trauma Cause or Accelerate the Growth of Cancer? Forensic Examiner 6 (Fall 2004).

[2] See Manasco v. Insurance Co. of State of Pennsylvania, 89 S.W.3d 239 (Tex. App. Texarkana 2002) (affirming denial of benefits to worker who claimed head injury caused brain tumor; citing to epidemiological studies that failed to show an association between trauma and brain tumors).

[3] See, e.g., George R. Parsons, “Sufficiency of Proof in Traumatic Cancer Cases,” 2 Tort & Med. Year Book 335 (1962); Stoll & Crissey, “Epithelioma from Single Trauma,” 62 N.Y. St. J. Med. 496 (Feb. 15, 1962); Wilhelm C. Hueper, Trauma and Cancer (1959); Arden R. Hedge, “Can a Single Injury Cause Cancer?” 90 Calif. Med. 55 (1959); R. Crane, “The Relationship of a Single Act of Trauma to Subsequent Malignancy,” in Alan R. Moritz & David S. Helberg, eds., Trauma and Disease 147 (1959); Shields Warren, M.D., “Minimal criteria required to prove causation of traumatic or occupational neoplasms,” Ann. Surgery 585 (1943); Bishop, “Cancer, Trauma, and Compensation,” 32 So. Med. J. 302 (1939); Knox, “Trauma and Malignant Tumors, 26 Am. J. Surg. 66, 69-70 (1934); William B. Coley & Norman L. Higinbotham, “Injury as a causative factor in the development of malignant tumors,” 98 Ann. Surg. 991 (1933); Wainwright, “Single Trauma, Carcinoma and Workman’s Compensation,” 5 Am. J. Surg. 433 (1928); Alson R. Kilgore & Curtis E. Smith, “Industrial liability for cancer,” 25 Calif. & Western Med. 70 (1926); Charles Phelps, “The relation of trauma to cancer formation,” 51 Ann. Surgery 609 (1910).

[4] James Ewing, “Modern Attitudes Toward Traumatic Cancer,” 19 Arch. Path. 690, 692 (1935); James Ewing, “The Relation of Trauma to Malignant Tumors,” Am. J. Surg. 30, 31-34 (Feb. 1926).

[5] See, e.g., James A. Tobey, Public Health Law 321 (3ed 1947) (“Although there is little, if any, scientific evidence to prove conclusively that malignant growths such as carcinoma, sarcoma, and other forms of cancer are ever caused by single blows, wounds, injuries, or other forms of trauma, the courts have awarded damages in a number of instances to persons who have developed cancers following single injuries.”) (internal citations omitted).

[6] George R. Monkman, Gregg Orwoll & John C. Ivins, “Trauma and Oncogenesis,” 49 Mayo Clinic Proc. 157 (1974).

[7] The trauma theory of carcinogenesis was discussed and questioned in several law review articles. See, e.g., Orrin E. Tilevitz, “Judicial Attitudes Towards Legal and Scientific Proof of Cancer Causation,” 3 Colum. J. Envt’l L. 344 (1977); Donald J. Ladanyi, “Impact Trauma As ‘Legal Cause’ of Cancer,” 20 Cleveland State L. Rev. 409 (1971); Theodore Dyke, “Traumatic Cancer?” 15 Clev.-Marshall L. Rev. 472 (1966); Jerry G. Elliott, “Traumatic cancer and ‘an old misunderstanding between doctors and lawyers’,” 13 U. Kan. L. Rev. 79 (1964); Comment, Sufficiency of Proof in Traumatic Cancer: A Medico-Legal Quandary, 16 Ark. L. Rev. 243 (1962); Comment, “Sufficiency of Proof in Traumatic Cancer Cases,” 46 Cornell L.Q. 581 (1961); Adelson, Injury and Cancer, 5 Western Res. L. Rev. 150 (1954).

[8] State Compensation Ins. Fund v. Kindig, 445 P.2d 72 (Colo. 1968) (head injury held not to have caused leukemia 68 days later); Slack v. C.L. Percival Co., 198 Iowa 54, 199 N.W. 323, 326 (1924) (anticipating Daubert by rejecting expert witness opinion that was “wholly in the realm of conjecture, speculation, and surmise”); Ortner v. Zenith Carburetor Co., 207 Mich. 610, 175 N .W. 122 (1919) (holding that 30 months was too long for a claim that accident that crushed worker’s fingers caused blood poisoning and penile cancer); Stordahl v. Rush Implement Co., 417 P.2d 95 (Mont. 1966) (rejecting traumatic causation of malignant tumor); Tonkovich v. Dep’t of Lab. & Indus., 31 Wash. 2d 220, 195 P.2d 638 (1948) (injury to foot held not to have caused abdominal cancer)

[9] See Dennison v. Wing, 279 App. Div. 494, 110 N.Y.S.2d 811, 813 (1952) (rejecting cancer claim when latency was two months on grounds that cancer took longer to develop); Sikora v. Apex Beverage Corp., 282 App. Div. 193, 196-97 (1953) (reversing judgment for plaintiff based upon jury’s finding that slip and fall accelerated breast cancer based upon lack of evidentiary support), aff’d, 306 N.Y. 917, 119 N.E.2d 601 (1954); Frankenheim v. B. Altman & Co., 13 Misc. 2d 1079, 1080-81, 177 N.Y.S.2d 2 (Bronx Cty. S.Ct. 1958) (granting motion to set aside verdict for plaintiff based upon traumatic cancer claim on grounds of insufficient evidence), app. dism’d, 8 App. Div. 2d 809 (First Dep’t 1959). But see McGrath v. Irving, 24 App. Div. 2d 236, 265 N.Y.S.2d 376 (1965) (affirming jury verdict based upon claim that plaintiff’s swallowing glass in car accident caused or accelerated development of laryngeal cancer); Mattfield v. Ward Baking Co., 14 App. Div. 2d 942, 221 N.Y.S.2d 224, 224 (1st Dep’t 1961) (affirming award for traumatic cancer based upon the “usual” conflicting expert witness testimony) Mattfield v. Ward Baking Co., 14 App. Div. 2d 942, 942 (1961) (affirming workman’s compensation award for “aggravation” of cancer, which resulted after “the usual conflict of medical opinion”); Pezzolanti v. Green Bus Lines, 114 App. Div. 2d 553, 553-54, 494 N.Y.S.2d 168, 169 (1985) (affirming workman’s compensation award for disability to wrist, which resulted from “trauma” of hitting pothole, which in turn injured asymptomatic wrist destabilized by pre-existing cancer).

Posted in Causation, Expert Witnesses, Rule 702, Scientific Evidence | Comments Off on Recrudescence of Traumatic Cancer Claims

Intellectual Due Process in West Virginia and Beyond

June 1st, 2014

Harris v. CSX Transportation

I have borrowed and modified the phrase “Intellectual Due Process” from earlier writers because of its obvious implications for the presentation, interpretation, synthesis, and evaluation of scientific evidence in court. See Scott Brewer, “Scientific Expert Testimony and Intellectual Due Process,” 107 Yale L. J. 1535 (1998). The major reason courts write opinions is to explain and justify their decisions to litigants, present and future, and to a wider audience of lawyers, scholars, and the general public. Judicial opinions involving scientific evidence, whether in legislation, regulation, or litigation must satisfy the societal need to explain and justify the acceptance and rejection of scientific claims. Despite a great deal of hand waving that law and science are somehow different, in the end, when courts describe their acceptance or rejection of scientific claims, they are addressing the same epistemic warrant that scientists themselves employ. Even a cursory review of the judicial output reveals an unsatisfactory state of affairs in which many courts mangle scientific and statistical evidence and inference. There is much that is needed to correct the problem.

One proposal would be to require that the parties file proposed findings of facts in connection with Rule 702 gatekeeping challenges. Courts should file detailed findings of facts that underlie their decisions to admit or to exclude expert witness opinion testimony. Another proposal would require courts to cite properly the scientific studies that they discuss in reaching a legal conclusion about sufficiency or admissibility. These are small steps, but ones that would help reduce the gross inaccuracies and the glib generalizations, while increasing the opportunity for public scrutiny and criticism.

We do not think anything is amiss with special courts for tax, patent, family law, national security, equity, or commercial matters. There is an even greater need for scientific skill, knowledge, and aptitude in a specialized science court. The time has come for special courts to hear cases involving scientific claims in health effects and other litigation.

* * * * * * *

A decision of the West Virginia Supreme Court, late last year, illustrates the need for substantial reform of how claiming based upon “scientific evidence” is permitted and evaluated in court. Mrs. Harris sued the railroad for the wrongful death of her husband, who died of multiple myeloma. Mr. Harris had been exposed, in his railroad workplace, to diesel exhaust, which Mrs. Harris claimed caused his cancer. See Harris v. CSX Transportation, Inc., 232 W.Va. 617, 753 S.E.2d 275 (2013). The trial court excluded Mrs. Harris’s expert witnesses. Harris v. CSX Transportation, Inc., No. 12-1135, 2012 WL 8899119 (Cir. Ct. Marshall Cty., W.Va. Aug. 21, 2012).

1. The West Virginia Supreme Court reversed the trial court’s exclusion of witnesses on the basis of an asymmetrical standard of review, which would allow de novo review of trial court decisions to exclude expert witness opinions, but which would privilege trial court decisions to admit opinions by limiting appellate review to abuse of discretion. This asymmetry was, of course, the same dodge that the Third and Eleventh Circuits had used to keep the “gates open,” regardless of validity or reliability concerns, and the same dodge that the Supreme Court shut down in General Electric v. Joiner. A single judge dissented in Harris, Justice Loughry, who took the majority to task for twisting facts and law to get to a desired result.

2. The Harris Court cited a federal court case for dicta that “Rule 702 reflects an attempt to liberalize the rules governing the admissibility of expert testimony.” See Harris, 753 S.E.2d at 279 (citing and quoting from Weisgram v. Marley Co., 169 F.3d 514, 523 (8th Cir.1999). Remarkably, the Harris Court omitted reference to the United States Supreme Court’s unanimous affirmance of Weisgram, which saw Justice Ginsburg write that “[s]ince Daubert, moreover, parties relying on expert evidence have had notice of the exacting standards of reliability such evidence must meet.” Weisgram v. Marley Co., 528 U.S. 440, 442 (2000). The Harris Court’s lack of scholarship is telling.

3. Meta-analysis appeared to play a role in the case, but the judicial decisions in Harris fail to describe the proffered evidence. The majority in Harris noted that one of plaintiff’s expert witnesses, Dr. Infante, relied upon a meta-analysis referred to as “Sonoda 2001.” Harris, 753 S.E.2d at 309. Neither the Court nor the dissent cited the published meta-analysis in a way that would help an interested reader in finding the paper. One could imagine the hue and cry if courts cited judicial cases or statutes by short-hand names without providing enough information to access the relied upon source. In this case, a PubMed search reveals the source so perhaps the error is harmless. Tomoko Sonoda, Yoshie Nagata, Mitsuru Mori, Tadao Ishida & Kohzoh Imai, “Meta-analysis of multiple myeloma and benzene exposure,” 11. J. Epidemiol. 249 (2001). Still, the time has come for courts to describe and report the scientific evidence with the same care and detail that they would use in a car collision case.

4. A quick read shows that the Sonoda meta-analysis supports the dissent’s assessment:

“‘Dr. Infante testified on direct examination that Sonoda 2001 considered 8 case-control studies specific to engine exhaust and stated it concluded that diesel and non-diesel engine exhaust causes multiple myeloma.’ Yet, as the trial court found, ‘[o]n cross examination Dr. Infante acknowledged that none of the 8 papers included in the Sonoda meta-analysis mention diesel exhaust’.”

Harris, 753 S.E.2d at 309. The dissent would have been considerably more powerful had it actually adverted to the language of Sonoda 2001:

“These results suggested that benzene exposure itself was not likely to be a risk factor of MM [multiple myeloma]. It is thought that several harmful chemical agents in engine exhaust, other than benzene, could be etiologically related to the risk of MM. Further case-control studies on MM are needed to obtain more information about detailed occupational exposure to toxic substances.”

Sonoda at 249 (2001) (emphasis added). Contrary to Infante’s asseveration, Sonoda and colleagues never concluded that diesel exhaust causes multiple myeloma. The state of scholarship and “intellectual due process” makes it impossible to tell whether or not Dr. Infante was telling the truth or the Harris Court badly misunderstood the record. Either way, something must give.

The dissent went on to note that Dr. Infante conducted his own meta-analysis, which included studies that did not mention diesel exhaust. Harris, 753 S.E.2d at 309. The railroad complained that some of the studies were small and had limited power, but that is exactly why a meta-analysis would be appropriate. The more disturbing complaints were that the meta-analysis left out important studies, and that it included irrelevant studies of benzene exposure and myeloma, which raised insuperable problems of external validity.

5. A half empty glass that is always full. According to the Harris Court, the West Virginia shadow of Rule 702 is a rule of “admissibility rather than exclusion.” Harris, 753 S.E.2d at 279 (citing and quoting from In re Flood Litig. Coal River Watershed, 222 W.Va. 574, 581, 668 S.E.2d 203, 210 (2008), which in turn quoted a federal case, Arcoren v. United States, 929 F.2d 1235, 1239 (8th Cir. 1991), decided before the Supreme Court decided Daubert.) This is just silly hand waving and blatant partisanship. A rule that sets out criteria or bases for admissibility also demarcates the inadmissible.

6. Cherry Picking. Dr. Infante was permitted by the Harris Court to aggregate data from studies that did not observe diesel exposure, while he failed to include, or he deliberately excluded data from, a large, powerful, exonerative study conducted by scientists from the National Cancer Institute, the International Agency for Research on Cancer (IARC), and the Karolinska Institute. See Paolo Boffetta, Mustafa Dosemeci, Gloria Gridley, Heather Bath, Tahere Moradi and Debra Silverman, “Occupational exposure to diesel engine emissions and risk of cancer in Swedish men and women,” 12 Cancer Causes Control 365 (2001). Dr. Infante inexplicably excluded this study, which found a risk ratio for men exposed to diesel exhaust that was below one, 0.98, with a very narrow 95% confidence interval, 0.92-1.05. Boffetta at 368, Table 2.

7. The West Virginia articulated an incohorent definition of “reliable,” designed to give itself the ability to reject gatekeeping completely. Citing its earlier decision in Flood, the Court offered its own ipse dixit:

“The assessment of whether scientifically-based expert testimony is “reliable,” as that term is used in [Daubert v. Merrell Dow Pharmaceuticals, Inc., 509 U.S. 579 (1993), and Wilt v. Buracker, 191 W.Va. 39, 443 S.E.2d 196 (1993)], does not mean an assessment of whether the testimony is persuasive, convincing, or well-founded. Rather, assessing ‘reliability’ is a shorthand term of art for assessing whether the testimony is to a reasonable degree based on the use of knowledge and procedures that have been arrived at using the methods of science — rather than being based on irrational and intuitive feelings, guesses, or speculation. If the former is the case, then the jury may (or may not, in its sole discretion) ‘rely upon’ the testimony. In re Flood Litig., 222 W.Va. at 582 n. 5, 668 S.E.2d at 211 n. 5.”

Harris, 753 S.E.2d at 279-80. Surely, this is circular or vacuous or both. Opinions not “well-founded” will be ones that are based upon guesses or speculation. Opinions arrived at by the “methods of science” will be ones that have an epistemic warrant that will survive a claim that they are not “well-founded.”

8. The Harris Court evidenced its hostility to scientific evidence by dredging up one of its own decisions involving a multiple myeloma causation claim, State ex rel. Wiseman v. Henning, 212 W.Va. 128, 569 S.E.2d 204 (2002). Wiseman involved a specious claim that a traumatic rib injury caused multiple myeloma, a claim at odds with scientific method and observation:

“Some research has suggested that people in some jobs may have an increased risk of developing multiple myeloma because they are exposed to certain chemicals. But the International Agency for Research on Cancer (IARC) states that the evidence is limited overall. It has been suggested that people may have an increased risk if they work in the petrol or oil industry, farming, wood working, the leather industry, painting and decorating, hairdressing, rubber manufacturing or fire fighting. But there is no evidence to prove that any of these occupations carry an increased risk of myeloma.”

Cancer Research UK, “Myeloma risks and causes” (last visited May 28, 2014). Even the most non-progressive jurisdictions have generally eradicated specious claiming for trauma-induced cancers, but West Virginia has carved out a place second to none in its race to the bottom.

9. WOE. Not surprisingly, the Harris Court relied heavily on the First Circuit’s “weight of the evidence” end-run around the notion of epistemic warrant for scientific claims, citing Milward v. Acuity Specialty Products Group, Inc., 639 F.3d 11 (1st Cir.2011), cert. denied sub nom., U.S. Steel Corp. v. Milward, ___ U.S. ___, 2012 WL 33303 (2012). The Harris Court went on to conflate and confuse WOE with Bradford Hill, and cited a recent New York case that confidently saw through WOE hand waving, while ignoring its devasting critique of expert witnesses’ attempts to pass off WOE for scientific, epistemic warrant. Reeps ex rel. Reeps v. BMW of N. Am., LLC, No. 100725/08,

2013 WL 2362566, at *3, 2012 N.Y. Misc. LEXIS 5788; 2012 NY Slip Op 33030U (N.Y. Sup. Ct. May 10, 2013).

10. Link. Dr. Infante links a lot, even when his sources do not:

“Dr. Infante testified that the International Agency for Research on Cancer issued Technical Publication Number 42 in 2009, and that the publication stated that diesel exhaust exposures have been linked to multiple myeloma and leukemia.”

Harris, 753 S.E.2d at 294. The Harris Court neglected to give the title of the publication, which tells a different story. Identification of research needs to resolve the carcinogenicity of high-priority IARC carcinogens. The dissent was willing to go behind the conclusory and false characterization that Dr. Infante and plaintiff gave to this publication. Harris, 753 S.E.2d at 309. The trial court’s finding (and the dissent’s assertion) that the IARC Technical Publication 42 intended to express a research agenda, not to make a causation statement, seems unassailable. Furthermore, it appears to be precisely the sort of specious claim that a court should keep from a jury. The cited IARC source actually notes that the then current IARC classification of diesel exhaust was of inadequate evidence for human carcinogenicity, with a focus on lung cancer, and barely a mention of multiple myeloma.

11. The Benzene Connection. Plaintiffs’ expert witnesses, including Dr. Infante, argued that benzene was a component of diesel exhaust, and benzene caused multiple myeloma. This move ignored not only the lack of evidence to implicate benzene in the causation of multiple myeloma, but it also ignored the large quantitative differences between the benzene occupational exposure studies and the very small amounts of benzene in diesel exhaust. The Harris Court held that the trial court acted improperly by inquiring into and finding the following facts, which were “exclusively” for the jury:

“There is substantially more benzene in cigarette smoke than diesel exhaust.

Benzene is present only in trivial doses in diesel exhaust.

The hypothesis that diesel exhaust causes multiple myeloma is confounded by the fact that cigarette smoking does not.”

The Harris majority further chastised the trial court for adverting to the ten or so studies that failed to find a statistically significant association between benzene exposure and multiple myeloma. Harris, 753 S.E.2d at 305-06. This inquiry directly calls into question, however, Dr. Infante’s methodology.

If these facts, found by the trial court, were reasonably established, then Dr. Infante’s argument was less than bogus, and a major underpinning for inclusion of benzene studies in his meta-analysis was refuted. These are precisely the sort of foundational facts that must be part of an inquiry into the methodological grounds of an expert witness’s opinion.

12. The Harris Court confused “proving causation” with “showing a methodology that provides an epistemic warrant for concluding.” Harris, 753 S.E.2d at 300. The Harris Court asserted that the trial court exceeded its gatekeeping function by inquiring into whether Mrs. Harris’s expert witnesses “proved” causation. Harris, 753 S.E.2d at 300. Speaking of “proof of” or “proving” causation is an affectation of lawyers, who refer to their evidence as their “proofs.” Epidemiologic articles and meta-analyses do not end with quod erat demonstrandum. Beyond the curious diction, there is a further issue in the majority’s suggestion that the trial court set the bar too high in declaring that the plaintiff failed to “prove” causation. Even if we were to accept the continuous nature of strength of evidence for a causal conclusion, Dr. Infante and the other plaintiff’s witnesses, would be fairly low on the curve, and their lowly position must of necessity speak to the merits of the defense motion to exclude under Rule 702.

13. Purely Matters for Jury. The Harris Court criticized the trial court for conducting a “mini-trial,” which set out to “resolve issues that were purely matters for jury consideration.” Harris, 753 S.E.2d at 305. In holding that the matters addressed in the pre-trial hearing were “exclusively grist for the jury and which had no relevancy to the limited role the trial court had under the facts of this case,” the Harris Court displayed a profound disregard for what facts would be relevant for a challenge to the plaintiff’s expert witnesses’ methodology. Many of the facts found by the trial court were directly relevant to “general acceptance,” validity (internal and external) of studies relied upon, and reliability of reasoning and inferences drawn. Aside from the lack of general acceptance and peer review of the plaintiff’s claimed causal relationship, the proffered testimony was filled with gaps and lacunae, which are very much at issue in methodological challenges to an opinion of causality.

* * * * * * *

The Harris case has taken its place next to Milward in the litigation industry’s arsenal of arguments for abandoning meaningful judicial supervision and gatekeeping of expert witness opinion testimony. See Andrew S. Lipton, “Proving Toxic Harm: Getting Past Slice and Dice Tactics,” 45 McGeorge L. Rev. 707, 731 (2014) (plaintiffs’ bar cheerleading for the Harris decision as “a lengthy and thoughtful analysis”, and for the Milward case as roadmap to evade meaningful judicial oversight). Not all was perfect with the trial court’s opinion. The defense seemed to have misled the court by asserting that “a difference between a case group and control group is not statistically significant then there is no difference at all.” See Respondent’s Brief at 5, Harris v. CSX Transportation, Inc., 2013 WL 4747999 (filed (Feb. 4, 2013) (citing App. 169, 228-230 (Shields) as having explained that the p-values greater than 0.05 do not support a causal association).

This is hardly true, and indeed, the lack of statistical significance does not lead to a claim that the null hypothesis of no association between exposure and outcome is correct. The defense, however, did not have a burden of showing the null to be correct; only that there was no reliable method deployed to reject the null in favor an alternative that the risk ratio for myeloma was raised among workers exposed to diesel exhaust.

Still, the trial court did seem to understand the importance of replication, in studies free of bias and confounding. Courts generally will have to do better at delineating what are “positive” and “negative” studies, with citations to the data and the papers, so that judicial opinions provide a satisfactory statement of reasons for judicial decisions.

Posted in Causation, Expert Witnesses, Meta-analysis, Rule 702, Scientific Evidence | Comments Off on Intellectual Due Process in West Virginia and Beyond

The Fallacy of Cherry Picking As Seen in American Courtrooms

May 3rd, 2014

After a long winter, the cherry trees are finally managing to blossom. Before we know it, it will be cherry-picking time.

Cherry picking is a good thing; right? Cherry picking yields cherries, and cherries are good. Selective cherry picking yields the best, ripest, sweetest, tastiest cherries. Cherry picking data no doubt yields the best, unbiased, unconfounded, most probative data to be had. Well, maybe not.

What could be wrong with picking cherries? At the end of the process you have cherries, and if you do it right, you have all ripe, and no rotten, cherries. Your collection of ripe cherries, however, will be unrepresentative of the universe of cherries, but at least we understand how and why your cherries were selected.

Elite colleges cherry pick the best high school students; leading law schools cherry pick the top college students; and top law firms and federal judges cherry pick the best graduates from the best law schools. Lawyers are all-too-comfortable with “cherry picking.” Of course, the cherry-picking process here has at least some objective criteria, which can be stated in advance of the selection.

In litigation, each side is expected to “cherry pick” the favorable evidence, and ignore or flyblow the contrary evidence. Perhaps this aspect of the adversarial system induces complacency in judges about selectivity in the presentation of evidence by parties and their witnesses. In science, this kind of adversarial selectivity is a sure way to inject bias and subjectivity into claims of knowledge. And even in law, there are limits to this adversarial system. Undue selectivity in citing precedent can land a lawyer in a heap of trouble. See Thul v. OneWest Bank, FSB, No. 12 C 6380, 2013 WL 212926 (N.D. Ill. Jan. 18, 2013) (failure to cite relevant judicial precedent constitutes an ethical offense)

In science, the development of the systematic review, in large measure, has been supported by the widespread recognition that studies cannot be evaluated with post hoc, subjective evaluative criteria. See generally Matthias Egger, George Davey Smith, and Douglas Altman, Systematic Reviews in Health Care: Meta-Analysis in Context (2001).

Farmers pick the cherries they want to go to market, to make money and satisfy customers. The harvesters’ virtue lies in knowing what to pick to obtain the best crop. The scientist’s virtue lies in the disinterested acquisition of data pursuant to a plan, and the evaluation of the data pursuant to pre-specified criteria.

The scientist’s virtue is threatened by motivations that are all-too human, and all-too common. The vice in science is wanting data that yields marketable publications, grants, promotions, awards, prizes, and perhaps a touch of fame. Picking data based upon a desired outcome is at the very least scientific fallacy if not scientific fraud. Cherry picking does not necessarily imply scienter, but in science, it is a strict liability offense.

The metaphor of cherry picking, mixed as it may be, thus gives us a label for fallacy and error. Cherry picking incorporates sampling bias, selection bias, confirmation bias, hasty generalization, and perhaps others as well. As explained recently, in Nature:

“Data can be dredged or cherry picked. Evidence can be arranged to support one point of view. * * * The question to ask is: ‘What am I not being told?’”

William J. Sutherland, David Spiegelhalter & Mark Burgman, “Policy: Twenty tips for interpreting scientific claims,” 503 Nature 335, 337 (2013).

Cherry picking in the orchard may be a good thing, but in the scientific world, it refers to the selection of studies or data within studies to yield results desired results, however misleading or counterfactual. See Ben Goldacre, Bad Science 97-99 (2008). The selective use of evidence is not a fallacy unique to science. Cherry picking is widely acknowledged to seriously undermine the quality of public debate See Gary Klass, “Just Plain Data Analysis: Common Statistical Fallacies in Analyses of Social Indicator Data” (2008). See generally Bradley Dowden, “Fallacies,” in James Fieser & Bradley Dowden, eds., Internet Encyclopedia of Philosophy.

The International Encyclopedia of Philosophy describes “cherry picking” as a fallacy, “a kind of error in reasoning.” Cherry-picking the evidence, also known as “suppressed evidence,” is:

“[i]ntentionally failing to use information suspected of being relevant and significant is committing the fallacy of suppressed evidence. This fallacy usually occurs when the information counts against one’s own conclusion. * * * If the relevant information is not intentionally suppressed but rather inadvertently overlooked, the fallacy of suppressed evidence also is said to occur, although the fallacy’s name is misleading in this case.”

Bradley Dowden, “Suppressed Evidence,” International Encyclopedia of Philosophy (Last updated: December 31, 2010). See also “Cherry picking (fallacy),” Wikipedia (describing cherry picking as the pointing to data that appears to confirm one’s opinion, while ignoring contradictory data).

In 1965, in his landmark paper, Sir Austin Bradford Hill described some important factors to consider in determining whether a clear-cut association, beyond that which we would attribute to chance, was a causal association. Hill, Austin Bradford Hill, “The Environment and Disease: Association or Causation?” 58 Proc. Royal Soc’y Med. 295, 295 (1965).

One of the key Hill factors is, of course, consistent, replicated results. Surely, an expert witness should not be permitted to manufacture a faux consistency by conducting a partial review. In birth defects litigation, the problem of “cherry picking” is so severe that one of the leading professional societies concerned with birth defects has issued a position paper to remind its members, other scientists, and the public that “[c]ausation determinations are made using all the scientific evidence”:

“Causation determinations are made using all the scientific evidence. This evidence is derived from correctly interpreted papers that have been published in the peer-reviewed literature. Unpublished data may be useful if available in sufficient detail for an evaluation and if derived from a source that is known to use reliable internal or external review standards. A National Toxicology program report would be an example of an unpublished source that is typically reliable. All available papers are considered in a scientific deliberation; selective consideration of the literature is not a scientific procedure.”

The Public Affairs Committee of the Teratology Society, “Teratology Society Public Affairs Committee Position Paper Causation in Teratology-Related Litigation,” 73 Birth Defects Research (Part A) 421, 422 (2005) (emphasis added).

* * * * * *

Cherry picking is a main rhetorical device for the litigator. Given the pejorative connotations of “cherry picking,” no one should be very surprised that lawyers and judges couch their Rule 702 arguments and opinions in terms of whether expert witnesses engaged in this fulsome fruitful behavior.

The judicial approach to cherry picking is a just a little schizophrenic. Generally, in the context of exercising its gatekeeping function for expert witnesses, the elimination of cherry picking is an important goal. Lust v. Merrell Dow Pharmaceuticals, Inc., 89 F.3d 594, 596-98 (9th Cir. 1996) (affirming exclusion of Dr. Done in a Chlomid birth defects case; district court found that “Dr. Done has seen fit to ‘pick and chose’ [sic] from the scientific landscape and present the Court with what he believes the final picture looks like. This is hardly scientific.”) (internal citation omitted); Barber v. United Airlines, Inc., 17 Fed. Appx. 433, 437 (7th Cir. 2001) (holding that a “selective use of facts fails to satisfy the scientific method and Daubert”). See also Crawford v. Indiana Harbor Belt Railroad Co., 461 F.3d 844 (7th Cir. 2006) (affirming summary judgment in disparate treatment discharge case, and noting judicial tendency to require “comparability” between plaintiffs and comparison group as a “natural response to cherry-picking by plaintiffs”); Miller v. Pfizer, Inc., 196 F. Supp. 2d 1062, (D. Kan. 2002) (excluding, with aid of independent, court-appointed expert witnesses, a party expert witness, David Healy, who failed to reconcile the fact that other research is contrary to his conclusion), aff’d, 356 F.3d 1326 (10th Cir.), cert denied, 125 S. Ct. 40 (2004).

In Ellis v. Barnhart, the Eighth Circuit affirmed a district court’s reversal of an Administrative Law Judge for “cherry picking” the record in a disability case. 392 F.3d 988 (8th Cir. 2005). Clearly cherry picking was a bad thing for a judicial officer to do when charged with the administration of justice. Several years later, however, the Eighth Circuit held that a trial court erred in excluding an expert witness for having offered an opinion that ignored the witness’s own prior, contrary opinions, a key National Institutes of Health clinical trial, and multiple other studies. The adversary’s charges of “cherry picking” were to no avail. Kuhn v. Wyeth, Inc., 686 F.3d 618, 633 (8th Cir. 2012) (“There may be several studies supporting Wyeth’s contrary position, but it is not the province of the court to choose between the competing theories when both are supported by reliable scientific evidence.”), rev’g Beylin v. Wyeth, 738 F.Supp. 2d 887, 892 (E.D.Ark. 2010) (MDL court) (Wilson, J. & Montgomery, J.) (excluding proffered testimony of Dr. Jasenka Demirovic who appeared to have “selected study data that best supported her opinion, while downplaying contrary findings or conclusions.”).

But wait, the court in Kuhn did not cite its own published opinion on cherry picking in Ellis. Some might say that the Circuit cherry picked its own precedents to get to a desired result. Anthony Niblett, “Do Judges Cherry Pick Precedents to Justify Extralegal Decisions?: A Statistical Examination,” 70 Maryland L. Rev. 234 (2010) (reviewing charges of cherry picking, and examining data [cherry picked?] from California).

The situation in the federal trial courts is chaotic. Most of the caselaw recognizes the fallacy of an expert witness’s engaging in ad hoc selection of studies upon which to rely. Federal courts, clear on their gatekeeping responsibilities and aware of the selection fallacy, have condemned cherry-picking expert witnesses. Judge Lewis Kaplan, in the Southern District of New York, expressed the proper judicial antipathy to cherry picking:

“[A]ny theory that fails to explain information that otherwise would tend to cast doubt on that theory is inherently suspect,” and “courts have excluded expert testimony ‘where the expert selectively chose his support from the scientific landscape.’”

In re Rezulin Prod. Liab. Litig., 369 F. Supp. 2d 398, 425 & n.164 (S.D.N.Y. 2005) (citation omitted).

Judge Breyer, of the Northern District of California, expressed similar sentiments in ruling on Rule 702 motions in the Celebrex personal injury litigation:

“these experts ignore the great weight of the observational studies that contradict their conclusion and rely on the handful that appear to support their litigation-created opinion.”

In re Bextra & Celebrex Mktg. Sales Pracs. & Prods. Liab. Litig., 524 F. Supp. 2d 1166, 1181 (N.D. Cal. 2007). The “cherry-picking” of favorable data “does not reflect scientific knowledge, is not derived by the scientific method, and is not ‘good science.’” Id. at 1176.

Other illustrative federal cases include:

In re Bausch & Lomb, Inc., 2009 WL 2750462 at *13-14 (D.S.C. 2009) (“Dr. Cohen did not address [four contradictory] studies in her expert reports or affidavit, and did not include them on her literature reviewed list [. . .] This failure to address this contrary data renders plaintiffs’ theory inherently unreliable.”)

Rimbert v. Eli Lilly & Co., No. 06-0874, 2009 WL 2208570, *19 (D.N.M. July 21, 2009) )(“Even more damaging . . . is her failure to grapple with any of the myriad epidemiological studies that refute her conclusion.”), aff’d, 647 F.3d 1247 (10th Cir. 2011) (affirming exclusion but remanding to permit plaintiff to find a new expert witness)

LeClercq v. The Lockformer Co., No. 00C7164, 2005 WL 1162979, at *4, 2005 U.S. Dist. LEXIS 7602, at *15 (N.D. Ill. Apr. 28, 2005) (“failure to discuss the import of, or even mention … material facts in [expert] reports amounts to ‘cherry-pick[ing]’ … and such selective use of facts fail[s] to satisfy the scientific method and Daubert.”) (internal citations and quotations omitted)

Contractors Ass’n of E. Pa. Inc. v. City of Philadelphia, 893 F. Supp. 419, 436 (E.D. Pa., 1995) (holding that expert witness opinion was unreliable when witness’s conclusions rested on incomplete factual data)

Galaxy Computer Servs. Inc. v. Baker, 325 B.R. 544 (E.D. Va. 2005) (excluding expert witness when witness relied upon incomplete data in reaching a valuation assessment).

Dwyer v. Sec’y of Health & Human Servs., No. 03-1202V, 2010 WL 892250, at *14 (Fed. Cl. Spec. Mstr. Mar. 12, 2010)(recommending rejection of thimerosal autism claim)(“In general, respondent’s experts provided more responsive answers to such questions. Respondent’s experts were generally more careful and nuanced in their expert reports and testimony. In contrast, petitioners’ experts were more likely to offer opinions that exceeded their areas of expertise, to “cherry-pick” data from articles that were otherwise unsupportive of their position, or to draw conclusions unsupported by the data cited… .”)

Holden Metal & Aluminum Works, Ltd. v. Wismarq Corp., No. 00C0191, 2003 WL 1797844, at *2 (N.D. Ill. Apr. 3, 2003) (“Essentially, the expert ‘cherrypicked’ the facts he considered to render his opinion, and such selective use of facts failed to satisfy the scientific method and Daubert.”) (internal citation omitted).

Flue-Cured Tobacco Cooperative Stabilization Corp. v. EPA, 4 F. Supp. 2d 435, 459 – 60 (M.D.N.C. 1998) (finding that EPA’s selection of studies for inclusion in a meta-analysis to be “disturbing,” and that agency’s selective, incomplete inclusion of studies violated its own guidelines for conducting risk assessments), rev’d on other grounds, 313 F.3d 852, 862 (4th Cir. 2002) (Widener, J.) (holding that the issuance of the report was not “final agency action”)

Fail-Safe, LLC v. AO Smith Corp., 744 F. Supp. 2d 870, 889 (E.D. Wis. 2010) (“the court also finds the witness’s methodology unreliable because of how Dr. Keegan uniformly treated all evidence that undermined his underlying conclusion: unwarranted dismissal of the evidence or outright blindness to contrary evidence. … In fact, it is readily apparent that Dr. Keegan all but ‘cherry picked’ the data he wanted to use, providing the court with another strong reason to conclude that the witness utilized an unreliable methodology. * * * Dr. Keegan’s two reports are rich with examples of his ‘cherry picking’ of the evidence.”)

As noted, however, there are federal trial courts that are all too willing to suspend judgment and kick the case to the jury. Here is a sampler of cases that found cherry picking to be an acceptable methodology, or at least a methodology sufficient to require that the case be submitted to the finder of fact.

In Berg v. Johnson & Johnson, the district court noted the defendants’ argument that proffered testimony is unreliable because witness “cherry-picked” data in order to form an opinion solely for purposes of litigation. 940 F.Supp. 2d 983, 991-92 (D.S.D. 2013). The trial judge, however, was not willing to look particularly closely at what was excluded or why:

“The only difference between his past and present research seems to exist in how he categorized his data. Defendants label this ‘cherry-picking’. The court views it as simply looking at the existing data from a different perspective.”

Id. Of course, expert witnesses on opposite sides look at the case from different perspectives, but the question begged was whether the challenged expert witness had categorized data in an unprincipled way. Other cases of this ilk include:

United States v. Paracha, 2006 WL 12768, at *20 (S.D. N.Y. Jan. 3, 2006) (rejecting challenge to terrorism expert witness on grounds that he cherry picked evidence in conspiracy prosecution involving al Queda)

In re Chantix (Varenicline) Products Liab. Litig., 889 F. Supp. 2d 1272, 1288 (N.D. Ala. 2012) (“Why Dr. Kramer chose to include or exclude data from specific clinical trials is a matter for cross-examination, not exclusion under Daubert.“)

Bouchard v. Am. Home Prods. Corp., 2002 WL 32597992 at *7 (N.D. Ohio May 24, 2002) (“If Bouchard believes that [the expert]… ignored evidence that would have required him to substantially change his opinion, that is a fit subject for cross-examination, not a grounds for wholesale rejection of an expert opinion.”)

In re Celexa & Lexapro Prods. Liab. Litig., 927 F. Supp. 2d 758, 2013 WL 791780, at *5, *7, *8 (E.D. Mo. 2013) (Sippel, J.) (rejecting challenge to David Healy in antidepressant suicide case)

Allen v. Takeda Pharms., MDL No. 6:11-md-2299, No. 12-cv-00064, 2013 WL 6825953, at *11 (W.D. La. Dec. 20, 2013) (challenged expert witness in Actos litigation sufficiently explained his choices to be exonerated from charges of cherry picking)

In re NuvaRing Prods. Liab. Litig., No. 4:08–MD–1964 RWS, 2013 WL 791787 (E.D. Mo. Mar. 4, 2013) (“As to cherry picking data, the Eighth Circuit has recently made clear that such allegations should be left for crossexamination.”)

McClellan v. I-Flow Corp., 710 F. Supp. 2d 1092, 1114 (D. Ore. 2010) (“Defendants are correct that plaintiffs’ experts must elucidate how the relevant evidence lends support to their opinions by explaining…..”) (rejecting cherry picking but denying Rule 702 challenge based in part upon alleged cherry picking)

Rich v. Taser Internat’l, Inc., No. 2:09–cv–02450–ECR–RJJ, 2012 WL 1080281, at *6 (D. Nev. March 30, 2012) (noting the objection to cherry picking but holding that it was an issue for cross-examination)

In re Urethane Antitrust Litig., No. 04-1313-JWL, MDL No. 1616, 2012 WL 6681783, at *3 (D. Kan. Dec. 21, 2012) (allowing expert testimony that “certain events are consistent with collusion”; “the extent to which [an expert] considered the entirety of the evidence in the case is a matter for cross-examination.”)

In re Titanium Dioxide Antitrust Litig., No. RDB-10-0318, 2013 WL 1855980, 2013 U.S. Dist. LEXIS 62394 (D. Md. May 1, 2013) (rejecting Rule 702 cherry-picking challenge to an expert who cherry picked; witness’s selection of documents upon which to rely from a record that exceeded 14 million pages was not unreliable. “ If important portions of the record were overlooked, then the Defendants may address that issue at trial.”)

STATE COURTS

The situation in state courts is similarly chaotic and fragmented.

In Lakey v. Puget Sound Energy, Inc., the Washington Supreme Court resoundingly rejected “cherry picking” by expert witnesses in a public and private nuisance case against a local utility for fear of future illnesses from exposure to electro-magnetic frequency radiation (EMF). Lakey v. Puget Sound Energy, Inc., 176 Wn.2d 909 (2013). The court held that the plaintiffs’ expert witnesses’ cherry-picking approach to data and studies was properly excluded under Rule 702. Their selective approach vitiated the reliability of his opinion with the consequence of :

“seriously tainting his conclusions because epidemiology is an iterative science relying on later studies to refine earlier studies in order to reach better and more accurate conclusions. Carpenter refused to account for the data from the toxicological studies, which epidemiological methodology requires unless the evidence for the link between exposure and disease is unequivocal and strong, which is not the case here. Carpenter also selectively sampled data within one of the studies he used, taking data indicating an EMF-illness link and ignoring the larger pool of data within the study that showed no such link, Carpenter’s treatment of this data created an improper false impression about what the study actually showed.”

Id.; see also “Washington Supreme Court Illustrates the Difference Between Frye and Rule 702” (April 15, 2013).

Other state Supreme Courts have recognized and rejected the gerrymandering of scientific evidence. Betz v. Pneumo Abex LLC, 2012 WL 1860853, *16 (May 23, 2012 Pa. S. Ct.)(“According to Appellants, moreover, the pathologist’s self-admitted selectivity in his approach to the literature is decidedly inconsistent with the scientific method. Accord Brief for Amici Scientists at 17 n.2 (“‘Cherry picking’ the literature is also a departure from ‘accepted procedure’.”)); George v. Vermont League of Cities and Towns, 2010 Vt. 1, 993 A.2d 367, 398 (Vt. 2010)(expressing concern about how and why plaintiff’s expert witnesses selected some studies to include in their “weight of evidence” methodology. Without an adequate explanation of selection and weighting criteria, the choices seemed “arbitrary” “cherry picking.”); Bowen v. E.I. DuPont de Nemours & Co., 906 A.2d 787, 797 (Del. 2006) (noting that expert witnesses cannot ignore studies contrary to their opinions).

Lower state courts have also quashed the cherry-picking harvest. Scaife v. AstraZeneca LP, 2009 WL 1610575, at *8 (Del. Super. June 9, 2009) (“Simply stated, the expert cannot accept some but reject other data from the medical literature without explaining the bases for her acceptance or rejection.”); see also In re Bextra & Celebrex Prod. Liab. Litig., No. 762000/2006, 2008 N.Y. Misc. LEXIS 720, at *47 (Sup. Ct. N.Y. Co. Jan 7, 2008) (stating that plaintiffs must show that their experts “do not ignore contrary data”).

The Nebraska Supreme Court appears to recognize the validity of considering the existence of cherry-picking in expert witness gatekeeping. In practice, however, that Court has shown an unwillingness to tolerate close scrutiny into what was included and excluded from the expert witness’s consideration. King v. Burlington No. Santa Fe Ry, ___N.W.2d___, 277 Neb. Reports 203, 234 (2009)(noting that the law does “not preclude a trial court from considering as part of its reliability inquiry whether an expert has cherry-picked a couple of supporting studies from an overwhelming contrary body of literature,” but ignoring the force of the fallacious expert witness testimony by noting that the questionable expert witness (Frank) had some studies that showed associations between exposure to diesel exhaust or benzene and multiple myeloma).

“Of all the offspring of time, Error is the most ancient, and is so old and familiar an acquaintance, that Truth, when discovered, comes upon most of us like an intruder, and meets the intruder’s welcome.”

Charles MacKay, Extraordinary Popular Delusions and the Madness of Crowds (1841)

Posted in Causation, Rule 702 | Comments Off on The Fallacy of Cherry Picking As Seen in American Courtrooms

Relative Risk of Two in Medical Malpractice Cases

April 14th, 2014

Counsel for plaintiffs and defendants in toxic tort cases are well aware of the need to show a sufficiently large relative risk, greater than two, to have sufficient evidence to satisfy the burden of proof on proximate causation between a known causal exposure and a specific plaintiff’s injury. As Judge Jack Weinstein wrote 30 years ago, “[a] government administrative agency may regulate or prohibit the use of toxic substances through rulemaking, despite a very low probability of any causal relationship. A court, in contrast, must observe the tort law requirement that a plaintiff establish a probability of more than 50% that the defendant’s action injured him. … This means that at least a two-fold increase in incidence of the disease attributable to Agent Orange exposure is required to permit recovery if epidemiological studies alone are relied upon.” In re Agent Orange Product Liab. Litig., 597 F. Supp. 740, 785, 836 (E.D.N.Y. 1984), aff’d 818 F.2d 145, 150-51 (2d Cir. 1987)(approving district court’s analysis), cert. denied sub nom. Pinkney v. Dow Chemical Co., 487 U.S. 1234 (1988).

In toxic tort cases, the risk ratio at issue allegedly results from a higher incidence of the disease in exposed persons compared to the incidence in unexposed persons. A similar risk ratio issue occurs in medical malpractice cases when a healthcare provider negligently fails to administer a therapy, or fails to administer a therapy in a timely fashion, to the detriment of the plaintiff. In instances in which the therapy is almost always efficacious, the risk ratio of a bad patient outcome will be very high, and the corresponding probability that the bad outcome would have been avoided by proper or timely therapy will be close to 100 percent. On the other hand, for some therapies, even timely administration is efficacious in a limited number of cases, less often than the 50-plus percent of cases that would support a proximate cause opinion between the allegedly negligent failure to administer therapy and the patient’s bad health outcome.

Unfortunately, the relative risk issue goes unlitigated in many cases, in New York and elsewhere. One recurring malpractice claim involves the alleged failure to administer clot-busting drugs to ischemic stroke patients. One such drug, tissue plasminogen activator (t-PA), which was approved by the Food and Drug Administration in 1996, can substantially reduce brain damage if administered within three hours of stroke onset. Even if administered within the crucial therapeutic time window, however, t-PA will benefit only about 30 percent of patients, and there is no medical “fingerprint”that identifies who has benefitted from the t-PA. In Samaan v. St. Joseph Hospital, 670 F.3d 21 (1st Cir. 2012), the First Circuit acted on its gatekeeping responsibilities to perscrutate the risk evidence and found that it fell short of what is required by Federal Rule of Evidence 702, and the “more likely than not” standard for civil cases. See also Smith v. Bubak, 643 F.3d 1137, 1141–42 (8th Cir.2011) (rejecting relative benefit testimony and suggesting in dictum that absolute benefit “is the measure of a drug’s overall effectiveness”); Young v. Mem’l Hermann Hosp. Sys., 573 F.3d 233, 236 (5th Cir.2009) (holding that Texas law requires a doubling of the relative risk of an adverse outcome to prove causation), cert. denied, ___ U.S. ___, 130 S.Ct. 1512 (2010).

Samaan and the cases cited by the First Circuit are hardly unique; the size of the relative risk issue has helped the defense prevail in other t-PA and similar malpractice cases around the country. Kava v. Peters, 450 Fed.Appx. 470, 478-79 (6th Cir. 2011) (affirming summary judgment for defendants when plaintiffs expert witnesses failed to provide clear testimony that plaintiff specific condition would have been improved by timely administration of therapy); Bonesmo v. The Nemours Foundation, 253 F.Supp. 2d 801, 809 (D.Del. 2003); Joshi v. Providence Health System of Oregon Corp., 342 Or. 152, 156, 149 P. 3d 1164, 1166 (2006) (affirming directed verdict for defendants when expert witness testified that he could not state, to a reasonable degree of medical probability, beyond 30%, that administering t-PA, or other anti-coagulant would have changed the outcome and prevented death); Ensink v. Mecosta County Gen. Hosp., 262 Mich.App. 518, 687 N.W.2d 143 (Mich.App. 2004) (affirming summary judgment for hospital and physicians when patient could not greater than 50% probability of obtaining a better result had emergency physician administered t-PA within three hours of stroke symptoms); Merriam v. Wanger, 757 A.2d 778, 2000 Me. 159 (2000) (reversing judgment on jury verdict for plaintiff on grounds that plaintiff failed to show that defendant failure to act were, more likely than not, a cause of harm). In Michigan, the holding of the t-PA and similar medical malpractice cases has been codified by statute:

“In an action alleging medical malpractice, the plaintiff has the burden of proving that he or she suffered an injury that more probably than not was proximately caused by the negligence of the defendant or defendants. In an action alleging medical malpractice, the plaintiff cannot recover for loss of an opportunity to survive or an opportunity to achieve a better result unless the opportunity was greater than 50%.”

Mich. Comp. Laws § 600.2912a(2) (2009). But see O’Neal v. St. John Hosp. & Med. Ctr., 487 Mich. 485, 791 N.W.2d 853 (Mich. 2010) (affirming denial of summary judgment when failure to administer therapy (not t-PA) in a timely fashion more than doubled the risk of stroke). In one unpublished Kentucky case, involving t-PA, the court seemed to acknowledge the general principle, but became confused as to whether 30 percent, was a reasonable probability. Lake Cumberland, LLC v. Dishman, 2007 WL 1229432, *5 (Ky. Ct. App. 2007) (unpublished) (citing without critical discussion an apparently innumerate opinion of expert witness Dr. Lawson Bernstein).

Despite the success of medical malpratice defense counsel in litigating dispositive motions in t-PA cases, the issue seems to go unnoticed in New York cases. For instance, in Gyani v. Great Neck Medical Group, a stroke victim sued on various allegations of medical malpractice, including failure to administer t-PA. N.Y. S.Ct. for Nassau Cty, 2011 WL 1430037 (April 4, 2011). The trial court denied summary judgment on proximate cause grounds, and noted that

“[t]he plaintiffs’ expert ultimately opines that the failure to administer t-PA allowed Gyani’s stroke to go untreated and progress to the point of her being locked-in permanently which would not have happened had t-PA been administered.”

From the court’s opinion, it would appear that defense counsel never pressed beyond this conclusory opinion, devoid of quantified relative risk. Behind the curtain of “ultimate” opinion is an expert without a meaningful basis for his opinion. It is time to pull the curtain.

Posted in Causation, Expert Witnesses, Risk and Risk Factor, Rule 702 | Comments Off on Relative Risk of Two in Medical Malpractice Cases

A Black Swan Case – Bayesian Analysis on Medical Causation

March 15th, 2014

Last month, I posted about an article that Professor Greenland wrote several years ago about his experience as a plaintiffs’ expert witness in a fenfluramine case. “The Infrequency of Bayesian Analyses in Non-Forensic Court Decisions (Feb. 16, 2014).” Greenland chided a defense expert for having declared that Bayesian analyses are rarely or never used in analyzing clinical trials or in assessments of pharmaco-epidemiologic data. Greenland’s accusation of ludicrousness appeared mostly to blow back on him, but his stridency for Bayesian analyses did raise the question, whether such analyses have ever moved beyond random-match probability analyses in forensic evidence (DNA, fingerprint, paternity, etc.) or in screening and profiling cases. I searched Google Scholar and Westlaw for counter-examples and found none, but I did solicit references to “Black Swan” cases. Shortly after I posted about the infrequency of Bayesian analyses, I came across a website that was dedicated to collecting legal citations of cases in which Bayesian analyses were important, but this website appeared to confirm my initial research.

Some months ago, Professor Brian Baigrie, of the Jackman Humanities Institute, at the University of Toronto, invited me to attend a meeting of an Institute working group on The Reliability of Evidence in Science and the Law. The Institute fosters interdisciplinary scholarship, and this particular working group has a mission statement close to my interests:

“The object of this series of workshops is to formulate a clear set of markers governing the reliability of evidence in the life sciences. The notion of evidence is a staple in epistemology and the philosophy of science; the notion of this group will be the way the notion of ‘evidence’ is understood in scientific contexts, especially in the life sciences, and in judicial form as something that ensures the objectivity of scientific results and the institutions that produce these results.”

The Reliability of Evidence in Science and the Law. The faculty on the working group represent disciplines of medicine (Andrew Baines), philosophy (James R. Brown, Brian Baigrie), and law (Helena Likwornik, Hamish Stewart), with graduate students in the environmental science (Amy Lemay), history & philosophy of science and technology (Karolyn Koestler, Gwyndaf Garbutt ), and computer science (Maya Kovats).

Coincidentally, in preparation for the meeting, Professor Baigrie sent me links to a Canadian case, Goodman v. Viljoen, which turned out to be a black swan case! The trial court’s decision, in this medical malpractice case focused mostly on a disputed claim of medical causation, in which the plaintiffs’ expert witnesses sponsored a Bayesian analysis of the available epidemiologic evidence; the defense experts maintained that causation was not shown, and they countered with the unreliability of the proffered Bayesian analysis. The trial court resolved the causation dispute in favor of the plaintiffs, and their witnesses’ Bayesian approach. Goodman v. Viljoen, 2011 ONSC 821 (CanLII), aff’d, 2012 ONCA 896 (CanLII). The Court of Appeals’ affirmance was issued over a lengthy, thoughtful dissent. The Canadian Supreme Court denied leave to appeal.

Goodman was a medical practice case. Mrs. Goodman alleged that her obstetrician deviated from the standard of care by failing to prescribe corticosteroids sufficiently early in advance of delivery to avoid or diminish the risk of cerebral palsy in her twins. Damages were stipulated, and the breach of duty turned on a claim that Mrs. Goodman, in distress, called her obstetrician. Given the decade that passed between the event and the lawsuit, the obstetrician was unable to document a response. Duty and breach were disputed, but were not the focus of the trial.

The medical causation claim, in Goodman, turned upon a claim that the phone call to the obstetrician should have led to an earlier admission to the hospital, and the administration of antenatal corticosteroids. According to the plaintiffs, the corticosteroids would have, more probably than not, prevented the twins from developing cerebral palsy, or would have diminished the severity of their condition. The plaintiffs’ expert witnesses relied upon studies that suggested a 40% reduction and risk, and a probabilistic argument that they could infer from this risk ratio that the plaintiffs’ condition would have been avoided. The case thus raises the issue whether evidence of risk can substitute for evidence of causation. The Canadian court held that risk sufficed, and it went further, contrary to the majority of courts in the United States, to hold that a 40% reduction in risk sufficed to satisfy the more-likely-than-not standard. See, e.g., Samaan v. St. Joseph Hosp., 670 F.3d 21 (1st Cir. 2012) (excluding expert witness testimony based upon risk ratios too small to support opinion that failure to administer intravenous tissue plasminogen activator (t-PA) to a patient caused serious stroke sequelae); see also “Federal Rule of Evidence 702 Requires Perscrutations — Samaan v. St. Joseph Hospital (2012)” (Feb. 4, 2012).

The Goodman courts, including the dissenting justice on the Ontario Court of Appeals, wrestled with a range of issues that warrant further consideration. Here are some that come to mind from my preliminary read of the opinions:

1. Does evidence of risk suffice to show causation in a particular case?

2. If evidence of risk can show causation in a particular case, are there requirements that the magnitude of risk be quantified and of a sufficient magnitude to support the inference of causation in a particular case?

3. The judges and lawyers spoke of scientific “proof.” When, if ever, is it appropriate to speak of scientific proof of a medical causal association?

4. Did the judges incorrectly dichotomize legal and scientific standards of causation?

5. Did the judges, by rejecting the need for “conclusive proof,” fail to articulate a meaningful standard for scientific evidence in any context, including judicial contexts?

6. What exactly does the “the balance of probabilities” mean, especially in the face of non-quantitative evidence?

7. What is the relationship between “but for” and “substantial factor” standards of causation?

8. Can judges ever manage to define “statistical significance” correctly?

9. What is the role of “common sense” in drawing inferences by judges and expert witnesses in biological causal reasoning? Is it really a matter of common sense that if a drug did not fully avert the onset of a disease, it would surely have led to a less severe case of the disease?

10. What is the difference between “effect size” and the measure of random or sampling error?

11. Is scientific certainty really a matter of being 95% certain, or is this just another manifestation of the transposition fallacy?

12. Are Bayesian analyses acceptable in judicial settings, and if so, what information about prior probabilities must be documented before posterior probabilities can be given by expert witnesses and accepted by courts?

13. Are secular or ecological trends sufficiently reliable data for expert witnesses to rely upon in court proceedings?

14. Is the ability to identify biological plausibility sufficient to excuse the lack of statistical significance and other factors that are typically needed to support the causality of a putative association?

15. What are the indicia of reliability of meta-analyses used in judicial proceedings?

16. Should courts give full citations to scientific articles that are heavily relied upon as part of the requirement that they publicly explain and justify their decisions?

These are some of the questions that come to mind from my first read of the Goodman case. The trial judge attempted to explain her decision in a fairly lengthy opinion. Unfortunately, the two judges, of the Ontario Court of Appeals, who voted to affirm, did not write at length. Justice Doherty wrote a thoughtful dissent, but the Supreme Court denied leave to appeal. Many of the issues are not fully understandable from the opinions, but I hope to be able to read the underlying testimony before commenting.

Thanks to Professor Baigrie for the reference to this case.

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