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Meta-Analysis of Observational Studies in Non-Pharmaceutical Litigations

February 26th, 2012

Yesterday, I posted on several pharmaceutical litigations that have involved meta-analytic studies.   Meta-analytic studies have also figured prominently in non-pharmaceutical product liability litigation, as well as in litigation over videogames, criminal recidivism, and eyewitness testimony.  Some, but not all, of the cases in these other areas of litigation are collected below.  In some cases, the reliability or validity of the meta-analyses were challenged; in some cases, the court fleetingly referred to meta-analyses relied upon the parties.  Some of the courts’ treatments of meta-analysis are woefully inadequate or erroneous.  The failure of the Reference Manual on Scientific Evidence to update its treatment of meta-analysis is telling.  See “The Treatment of Meta-Analysis in the Third Edition of the Reference Manual on Scientific Evidence” (Nov. 14, 2011).

 

Abortion (Breast Cancer)

Christ’s Bride Ministries, Inc. v. Southeastern Pennsylvania Transportation Authority, 937 F.Supp. 425 (E.D. Pa. 1996), rev’d, 148 F.3d 242 (3d Cir. 1997)

Asbestos

In re Joint E. & S. Dist. Asbestos Litig., 827 F. Supp. 1014, 1042 (S.D.N.Y. 1993)(“adding a series of positive but statistically insignificant SMRs [standardized mortality ratios] together does not produce a statistically significant pattern”), rev’d, 52 F.3d 1124 (2d Cir. 1995).

In Re Asbestos Litigation, Texas Multi District Litigation Cause No. 2004-03964 (June 30, 2005)(Davidson, J.)(“The Defendants’ response was presented by Dr. Timothy Lash.  I found him to be highly qualified and equally credible.  He largely relied on the report submitted to the Environmental Protection Agency by Berman and Crump (“B&C”).  He found the meta-analysis contained in B&C credible and scientifically based.  B&C has not been published or formally accepted by the EPA, but it does perform a valuable study of the field.  If the question before me was whether B&C is more credible than the Plaintiffs’ studies taken together, my decision might well be different.”)

Jones v. Owens-Corning Fiberglas, 288 N.J. Super. 258, 672 A.2d 230 (1996)

Berger v. Amchem Prods., 818 N.Y.S.2d 754 (2006)

Grenier v. General Motors Corp., 2009 WL 1034487 (Del.Super. 2009)

Benzene

Knight v. Kirby Inland Marine, Inc., 363 F. Supp. 2d 859 (N.D. Miss. 2005)(precluding proffered opinion that benzene caused bladder cancer and lymphoma; noting without elaboration or explanation, that meta-analyses are “of limited value in combining the results of epidemiologic studies based on observation”), aff’d, 482 F.3d 347 (5th Cir. 2007)

Baker v. Chevron USA, Inc., 680 F.Supp. 2d 865 (S.D. Ohio 2010)

Diesel Exhaust Exposure

King v. Burlington Northern Santa Fe Ry. Co., 277 Neb. 203, 762 N.W.2d 24 (2009)

Kennecott Greens Creek Mining Co. v. Mine Safety & Health Admin., 476 F.3d 946 (D.C. Cir. 2007)

Eyewitness Testimony

State of New Jersey v. Henderson, 208 N.J. 208, 27 A.3d 872 (2011)

Valle v. Scribner, 2010 WL 4671466 (C.D. Calif. 2010)

People v. Banks, 16 Misc.3d 929, 842 N.Y.S.2d 313 (2007)

Lead

Palmer Asarco Inc., 510 F.Supp.2d 519 (N.D. Okla. 2007)

PCBs

In re Paoli R.R. Yard PCB Litigation, 916 F.2d 829, 856-57 (3d Cir.1990) (‘‘There is some evidence that half the time you shouldn’t believe meta-analysis, but that does not mean that meta-analyses are necessarily in error. It means that they are, at times, used in circumstances in which they should not be.’’) (internal quotation marks and citations omitted), cert. denied, 499 U.S. 961 (1991)

Repetitive Stress

Allen v. International Business Machines Corp., 1997 U.S. Dist. LEXIS 8016 (D. Del. 1997)

Tobacco

Flue-Cured Tobacco Cooperative Stabilization Corp. v. United States Envt’l Protection Agency, 4 F.Supp.2d 435 (M.D.N.C. 1998), vacated by, 313 F.3d 852 (4th Cir. 2002)

Tocolytics – Medical Malpractice

Hurd v. Yaeger, 2009 WL 2516874 (M.D. Pa. 2009)

Toluene

Black v. Rhone-Poulenc, Inc., 19 F.Supp.2d 592 (S.D.W.Va. 1998)

Video Games (Violent Behavior)

Brown v. Entertainment Merchants Ass’n, ___ U.S.___, 131 S.Ct. 2729 (2011)

Entertainment Software Ass’n v. Blagojevich, 404 F.Supp.2d 1051 (N.D. Ill. 2005)

Entertainment Software Ass’n v. Hatch, 443 F.Supp.2d 1065 (D. Minn. 2006)

Video Software Dealers Ass’n v. Schwarzenegger, 556 F.3d 950 (9th Cir. 2009)

Vinyl Chloride

Taylor v. Airco, 494 F. Supp. 2d 21 (D. Mass. 2007)(permitting opinion testimony that vinyl chloride caused intrahepatic cholangiocarcinoma, without commenting upon the reasonableness of reliance upon the meta-analysis cited)

Welding

Cooley v. Lincoln Electric Co., 693 F.Supp.2d 767 (N.D. Ohio. 2010)

Posted in Meta-analysis, Reference Manual on Scientific Evidence, Rule 702, Scientific Evidence, statistical evidence | 72 Comments »

Unreported Decisions on Expert Witness Opinion in New Jersey

February 21st, 2012

In New Jersey, as in other states, unpublished opinions have a quasi-outlaw existence.  According to the New Jersey Rules of Court, unpublished opinions are not precedential.  By court fiat, the court system has declared that it can act a certain way in a given case, and not have to follow its own lead in other cases:

No unpublished opinion shall constitute precedent or be binding upon any court. Except for appellate opinions not approved for publication that have been reported in an authorized administrative law reporter, and except to the extent required by res judicata, collateral estoppel, the single controversy doctrine or any other similar principle of law, no unpublished opinion shall be cited by any court. No unpublished opinion shall be cited to any court by counsel unless the court and all other parties are served with a copy of the opinion and of all contrary unpublished opinions known to counsel.

New Jersey Rule of Court 1:36-3 (Unpublished Opinions).

Litigants down the road may feel that they are not being given the equal protection of the law, but never mind.  Res judicata and collateral estoppel are in, but stare decisis is out.  Consistency and coherence are so difficult, surely it is better to be free from having from these criteria of rationality unless we decide to “opt in” by publishing opinions with our decisions.  As many other scholars and commentators have noted, rules of this sort allow decisions from other states, and even other countries, to be potentially persuasive, whereas by court rule and fiat, an unpublished decision of the deciding court can not have any precedential value.  Why then permit unpublished cases to be cited at all?

Having tracked decisions, published and un-, in New Jersey for many years, I am left with an impression that the Appellate Division has a tendency to refuse to publish opinions of decisions in which it has reversed the trial court’s refusal to exclude expert witness testimony, or in which it has affirmed the trial court’s exclusion of expert testimony.  Opinions that explain the affirmance of a denial of expert witness exclusion or the reversal of a trial court’s grant of exclusion appear to be published more often.  Stated as a four-fold table:

  Trial Court Permits Expert Trial Court Bars Expert
Appellate Court Affirms Published Not Published
Appellate Court Reverses Not Published Publish

My impression is that there is an institutional bias against creating a body of law that illuminates the criteria for admission and for exclusion of expert witness opinion testimony. This is only an impression, and I do not have statistics, descriptive or inferential on these judicial behaviors.  From a jurisprudential perspective, the affirmance of an exclusion below, or the reversal of a denial of exclusion below, should be at least as important as publishing the reversal of an exclusion below.  The goal of announcing to the Bar and to trial judges the criteria for inclusion and exclusion would seem to suggest greater publication of the opinions, from the two unpublished cells, in the contingency table, above.

No citation and no precedent rules are deeply problematic, and have attracted a great deal of scholarly attention.  See Erica Weisgerber, “Unpublished Opinions: A Convenient Means to an Unconstitutional End,” 97 Georgetown L.J. 621 (2009);  Rafi Moghadam, “Judge Nullification: A Perception of Unpublished Opinions,” 62 Hastings L.J. 1397 (2011);  Norman R. Williams, “The failings of Originalism:  The Federal Courts and the Power of Precedent,” 37 U.C.. Davis L. Rev. 761 (2004);  Dione C. Greene, “The Federal Courts of Appeals, Unpublished Decisions, and the ‘No-Citation Rule,” 81 Indiana L.J. 1503 (2006);  Vincent M. Cox, “Freeing Unpublished Opinions from Exile: Going Beyond the Citation Permitted by Proposed Federal Rule of Appellate Procedure 32.1,” 44 Washburn L.J. 105 (2004);  Sarah E. Ricks, “The Perils of Unpublished Non-Precedential Federal Appellate Opinions: A Case Study of The Substantive Due Process State-Created Danger Doctrine in One Circuit,” 81 Wash. L.Rev. 217 (2006);  Michael J. Woodruff, “State Supreme Court Opinion Publication in the Context of Ideology and Electoral Incentives.” New York University Department of Politics (March 2011);   Michael B. W. Sinclair, “Anastasoff versus Hart: The Constitutionality and Wisdom of Denying Precedential Authority to Circuit Court Decisions.”  See generally The Committee for the Rule of Law (website) (collecting scholarship and news on the issue of unpublished and supposedly non-precedential opinions).

What would be useful is an empirical analysis of the New Jersey Appellate Division’s judicial behavior in deciding whether or not to publish decisions for each of the four cells, in the four-fold table, above.  If my impression is correct, the suggestion of institutional bias would give further support to the abandonment of N.J. Rule of Court 1:36-3.

Posted in Rule 702, Scientific Evidence, Trial Procedure | No Comments »

When There Is No Risk in Risk Factor

February 20th, 2012

Some of the terminology of statistics and epidemiology is not only confusing, but it is misleading.  Consider the terms “effect size,” “random effects,” and “fixed effect,” which are all used to describe associations even if known to be non-causal.  Biostatisticians and epidemiologists know that the terms are about putative or potential effects, but the sloppy, short-hand nomenclature can be misleading.

Although “risk” has a fairly precise meaning in scientific parlance, the usage for “risk factor” is fuzzy, loose, and imprecise.  Journalists and plaintiffs’ lawyers use “risk factor,” much as they another frequently abused term in their vocabulary:  “link.”  Both “risk factor” and “link” sound as though they are “causes,” or at least as though they have something to do with causation.  The reality is usually otherwise.

The business of exactly what “risk factor” means is puzzling and disturbing.  The phrase seems to have gained currency because it is squishy and without a definite meaning.  Like the use of “link” by journalists, the use of “risk factor” protects the speaker against contradiction, but appears to imply a scientifically valid conclusion.  Plaintiffs’ counsel and witnesses love to throw this phrase around precisely because of its ambiguity.  In journal articles, authors sometimes refer to any exposure inquired about in a case-control study to be a “risk factor,” regardless of the study result.  So a risk factor can be merely an “exposure of interest,” or a possible cause, or a known cause.

The author’s meaning in using the phrase “risk factor” can often be discerned from context.  When an article reports a case-control study, which finds an association with an exposure to some chemical the article will likely report in the discussion section that the study found that chemical to be a risk factor.  The context here makes clear that the chemical was found to be associated with the outcome, and that chance was excluded as a likely explanation because the odds ratio was statistically significant.  The context is equally clear that the authors did not conclude that the chemical was a cause of the outcome because they did not rule out bias or confounding; nor did they do any appropriate analysis to reach a causal conclusion and because their single study would not have justified reaching a causal association.

Sometimes authors qualify “risk factor” with an adjective to give more specific meaning to their usage.  Some of the adjectives used in connection with the phrase include:

– putative, possible, potential, established, well-established, known, certain, causal, and causative

The use of the adjective highlights the absence of a precise meaning for “risk factor,” standing alone.  Adjectives such as “established,” or “known” imply earlier similar findings, which are corroborated by the study at hand.  Unless “causal” is used to modify “risk factor,” however, there is no reason to interpret the unqualified phrase to imply a cause.

Here is how the phrase “risk factor” is described in some noteworthy texts and treatises.

Legal Treatises

Professor David Faigman, and colleagues, with some understatement, note that the term “risk factor is loosely used”:

“Risk Factor An aspect of personal behavior or life-style, an environmental exposure, or an inborn or inherited characteristic, which on the basis of epidemiologic evidence is known to be associated with health-related condition(s) considered important to prevent. The term risk factor is rather loosely used, with any of the following meanings:

1. An attribute or exposure that is associated with an increased probability of a specified outcome, such as the occurrence of a disease. Not necessarily a causal factor.

2. An attribute or exposure that increases the probability of occurrence of disease or other specified outcome.

3. A determinant that can be modified by intervention, thereby reducing the probability of occurrence of disease or other specified outcomes.”

David L. Faigman, Michael J. Saks, Joseph Sanders, and Edward Cheng, Modern Scientific Evidence:  The Law and Science of Expert Testimony 301, vol. 1 (2010)(emphasis added).

The Reference Manual on Scientific Evidence (2011) (RMSE3d) does not offer much in the way of meaningful guidance here.  The chapter on statistics in the third edition provides a somewhat circular, and unhelpful definition.  Here is the entry in that chapter’s glossary:

risk factor. See independent variable.

RMSE3d at 295.  If the glossary defined “independent variable” as a simply a quantifiable variable that was being examined for some potential relationship with the outcome, or dependent, variable, the RMSE would have avoided error.  Instead the chapter’s glossary, as well as its text, defines independent variables as “causes,” which begs the question why do a study to determine whether the “independent variable” is even a candidate for a causal factor?  Here is how the statistics chapter’s glossary defines independent variable:

“Independent variables (also called explanatory variables, predictors, or risk factors) represent the causes and potential confounders in a statistical study of causation; the dependent variable represents the effect. ***. “

RMSE3d at 288.  This is surely circular.  Studies of causation are using independent variables that represent causes?  There would be no reason to do the study if we already knew that the independent variables were causes.

The text of the RMSE chapter on statistics propagates the same confusion:

“When investigating a cause-and-effect relationship, the variable that represents the effect is called the dependent variable, because it depends on the causes.  The variables that represent the causes are called independent variables. With a study of smoking and lung cancer, the independent variable would be smoking (e.g., number of cigarettes per day), and the dependent variable would mark the presence or absence of lung cancer. Dependent variables also are called outcome variables or response variables. Synonyms for independent variables are risk factors, predictors, and explanatory variables.”

FMSE3d at 219.  In the text, the identification of causes with risk factors is explicit.  Independent variables are the causes, and a synonym for an independent variable is “risk factor.”  The chapter could have avoided this error simply by the judicious use of “putative,” or “candidate” in front of “causes.”

The chapter on epidemiology exercises more care by using “potential” to modify and qualify the risk factors that are considered in a study:

“In contrast to clinical studies in which potential risk factors can be controlled, epidemiologic investigations generally focus on individuals living in the community, for whom characteristics other than the one of interest, such as diet, exercise, exposure to other environmental agents, and genetic background, may distort a study’s results.”

FMSE3d at 556 (emphasis added).

 

Scientific Texts

Turning our attention to texts on epidemiology written for professionals rather than judges, we find that sometimes the term “risk factor” with a careful awareness of its ambiguity.

Herbert I. Weisberg is a statistician whose firm, Correlation Research Inc., specializes in the applied statistics in legal issues.  Weisberg recently published an interesting book on bias and causation, which is recommended reading for lawyers who litigate claimed health effects.  Weisberg’s book defines “risk factor” as merely an exposure of interest in a study that is looking for associations with a harmful outcome.  He insightfully notes that authors use the phrase “risk factor” and similar phrases to avoid causal language:

“We will often refer to this factor of interest as a risk factor, although the outcome event is not necessarily something undesirable.”

Herbert I. Weisberg, Bias and Causation:  Models and Judgment for Valid Comparisons 27 (2010).

“Causation is discussed elliptically if at all; statisticians typically employ circumlocutions such as ‘independent risk factor’ or ‘explanatory variable’ to avoid causal language.”

Id. at 35.

“Risk factor : The risk factor is the exposure of interest in an epidemiological study and often has the connotation that the outcome event is harmful or in some way undesirable.”

Id. at 317.   This last definition is helpful in illustrating a balanced, fair definition that does not conflate risk factor with causation.

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Lemuel A. Moyé is an epidemiologist who testified in pharmaceutical litigation, mostly for plaintiffs.  His text, Statistical Reasoning in Medicine:  The Intuitive P-Value Primer, is in places a helpful source of guidance on key concepts.  Moyé puts no stock in something’s being a risk factor unless studies show a causal relationship, established through a proper analysis.  Accordingly, he uses “risk factor” to signify simply an exposure of interest:

“4.2.1 Association versus Causation

An associative relationship between a risk factor and a disease is one in which the two appear in the same patient through mere coincidence. The occurrence of the risk factor does not engender the appearance of the disease.

Causal relationships on the other hand are much stronger. A relationship is causal if the presence of the risk factor in an individual generates the disease. The causative risk factor excites the production of the disease. This causal relationship is tight, containing an embedded directionality in the relationship, i.e., (1) the disease is absence in the patient, (2) the risk factor is introduced, and (3) the risk factor’s presence produces the disease.

The declaration that a relationship is causal has a deeper meaning then the mere statement that a risk factor and disease are associated. This deeper meaning and its implications for healthcare require that the demonstration of a causal relationship rise to a higher standard than just the casual observation of the risk factor and disease’s joint occurrence.

Often limited by logistics and the constraints imposed by ethical research, the epidemiologist commonly cannot carry out experiments that identify the true nature of the risk factor–disease relationship. They have therefore become experts in observational studies. Through skillful use of observational research methods and logical thought, epidemiologists assess the strength of the links between risk factors and disease.”

Lemuel A. Moyé, Statistical Reasoning in Medicine:  The Intuitive P-Value Primer 92 (2d ed. 2006)

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In A Dictionary of Epidemiology, which is put out by the International Epidemiology Association, a range of meanings is acknowledged, although the range is weighted toward causality:

“RISK FACTOR (Syn: risk indicator)

1. An aspect of personal behavior or lifestyle, an environmental exposure, or an inborn or inherited characteristic that, on the basis of scientific evidence, is known to be associated with meaningful health-related condition(s). In the twentieth century multiple cause era, a synonymous with determinant acting at the individual level.

2. An attribute or exposure that is associated with an increased probability of a specified outcome, such as the occurrence of a disease. Not necessarily a causal factor: it may be a risk marker.

3. A determinant that can be modified by intervention, thereby reducing the probability of occurrence of disease or other outcomes. It may be referred to as a modifiable risk factor, and logically must be a cause of the disease.

The term risk factor became popular after its frequent use by T. R. Dawber and others in papers from the Framingham study.346 The pursuit of risk factors has motivated the search for causes of chronic disease over the past half-century. Ambiguities in risk and in risk-related concepts, uncertainties inherent to the concept, and different legitimate meanings across cultures (even if within the same society) must be kept in mind in order to prevent medicalization of life and iatrogenesis.124–128,136,142,240”

Miquel Porta, Sander Greenland, John M. Last, eds., A Dictionary of Epidemiology 218-19 (5th ed. 2008).  We might add that the uncertainties inherent in risk concepts should be kept in mind to prevent overcompensation for outcomes not shown to be caused by alleged tortogens.

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One introductory text uses “risk factor” as a term to describe the independent variable, while acknowledging that the variable does not become a risk factor until after the study shows an association between factor and the outcome of interest:

“A case-control study is one in which the investigator seeks to establish an association between the presence of a characteristic (a risk factor).”

Sylvia Wassertheil-Smoller, Biostatistics and Epidemiology: A Primer for Health and Biomedical Professionals 104 (3d ed. 2004).  See also id. at 198 (“Here, also, epidemiology plays a central role in identifying risk factors, such as smoking for lung cancer”).  Although it should be clear that much more must happen in order to show a risk factor is causally associated with an outcome, such as lung cancer, it would be helpful to spell this out.  Some texts simply characterize risk factor as associations, not necessarily causal in nature.  Another basic text provides:

“Analytical studies examine an association, i.e. the relationship between a risk factor and a disease in detail and conduct a statistical test of the corresponding hypothesis … .”

Wolfgang Ahrens & Iris Pigeot, eds., Handbook of Epidemiology 18 (2005).  See also id. at 111 (Table describing the reasoning in a case-control study:    “Increased prevalence of risk factor among diseased may indicate a causal relationship.”)(emphasis added).

These texts, both legal and scientific, indicate a wide range of usage and ambiguity for “risk factor.”  There is a tremendous potential for the unscrupulous expert witness, or the uneducated lawyer, to take advantage of this linguistic latitude.  Courts and counsel must be sensitive to the ambiguity and imprecision in usages of “risk factor,” and the mischief that may result.  The Reference Manual on Scientific Evidence needs to sharpen and update its coverage of this and other statistical and epidemiologic issues.

Posted in Causation, Reference Manual on Scientific Evidence, Risk and Risk Factor, Rule 702, Scientific Evidence, statistical evidence | No Comments »

When Is Risk Really Risk?

February 14th, 2012

The term “risk” has a fairly precise meaning in scientific parlance.  The following is a typical definition:

RISK The probability that an event will occur, e.g., that an individual will become ill or die within a stated period of time or by a certain age. Also, a nontechnical term encompassing a variety of measures of the probability of a (generally) unfavorable outcome. See also probability.

Miquel Porta, ed., A Dictionary of Epidemiology 212-18 (5th ed. 2008)(sponsored by the Internat’l Epidemiological Ass’n).

In other words, a risk is an ex ante cause.  The probability is not a qualification about whether there is a causal relationship, but rather whether any person at risk will develop the outcome of interest.  Such is the nature of stochastic risks.

Regulatory agencies often use the term “risk” metaphorically, as a fiction to justify precautionary regulations.  Although there may be nothing wrong with such precautionary initiatives, regulators often imply a real threat of harm from what can only be a hypothetical harm.  Why?  If for no other reason, regulators operate with a “wish bias” in favor of the reality of the risk they wish to avert if risk it should be.  We can certainly imagine the cognitive slippage that results from the need to motivate the regulated actors to comply with regulations, and at times, to prosecute the noncompliant.

Plaintiffs’ counsel in personal injury and class action litigation have none of the regulators’ socially useful motives for engaging in distortions of the meaning of the word “risk.”  In the context of civil litigation, plaintiffs’ counsel use the term “risk,” borrowed from the Humpty-Dumpty playbook:

“When I use a word,” Humpty Dumpty said, in rather a scornful tone, “it means just what I choose it to mean—neither more nor less.”
“The question is,” said Alice, “whether you can make words mean so many different things.”
“The question is,” said Humpty Dumpty, “which is to be master — that’s all.”

Lewis Carroll, Through the Looking-Glass 72 (Raleigh 1872).

Undeniably, the word mangling and distortion have had some success with weak-minded judges, but Humpty-Dumpty linguistics had a fall recently in the Third Circuit.  Others have written about it, but I am only just getting around to read the analytically precise and insightful decision in Gates v. Rohm and Haas Co., 655 F.3d 255 (3d Cir. 2011).  See Sean Wajert, “Court of Appeals Rejects Medical Monitoring Class Action” (Aug. 31, 2011); Carl A. Solano, “Appellate Court Consensus on Medical Monitoring Class Actions Solidifies” (Sept. 12, 2011).

Gates was an attempted class action, in which the district court denied plaintiffs’ motion for certification of a medical monitoring and property damage class.  265 F.R.D. 208 (E.D.Pa. 2010)(Pratter, J.).  Plaintiffs contended that they were exposed to varying amounts of vinyl chloride exposure in air, and perhaps in water at levels too low to detect. Gates, 655 F.3d at 258-59.   The class’s request for medical monitoring foundered because plaintiffs were unable to prove that they were all exposed to a level of vinyl chloride that created a significant risk of serious latent disease for all class members. Id. at 267-68.

With no scientific evidence in hand, the plaintiffs tried to maintain that they were “at risk” on the basis of EPA regulations, which set a very low, precautionary threshold, but the district and circuit courts rebuffed this use of regulatory “risk” language:

The court identified two problems with the proposed evidence. First, it rejected the plaintiffs’ proposed threshold—exposure above 0.07µ/m3, developed as a regulatory threshold by the EPA for mixed populations of adults and children—as a proper standard for determining liability under tort law. Second, the court correctly noted, even if the 0.07 µ/m3 standard were a correct measurement of the aggregate threshold, it would not be the threshold for each class member who may be more or less susceptible to diseases from exposure to vinyl chloride.18 Although the positions of regulatory policymakers are relevant, their risk assessments are not necessarily conclusive in determining what risk exposure presents to specified individuals. See Federal Judicial Center, Reference Manual on Scientific Evidence 413 (2d ed.2000) (“While risk assessment information about a chemical can be somewhat useful in a toxic tort case, at least in terms of setting reasonable boundaries as to the likelihood of causation, the impetus for the development of risk assessment has been the regulatory process, which has different goals.”); id. at 423 (“Particularly problematic are generalizations made in personal injury litigation from regulatory positions…. [I]f regulatory standards are discussed in toxic tort cases to provide a reference point for assessing exposure levels, it must be recognized that  there is a great deal of variability in the extent of evidence required to support different regulations.”).

Thus, plaintiffs could not carry their burden of proof for a class of specific persons simply by citing regulatory standards for the population as a whole. Cf. Wright v. Willamette Indus., Inc., 91 F.3d 1105, 1107 (8th Cir.1996) (“Whatever may be the considerations that ought to guide a legislature in its determination of what the general good requires, courts and juries, in deciding cases, traditionally make more particularized inquiries into matters of cause and effect.”).

Plaintiffs have failed to propose a method of proving the proper point where exposure to vinyl chloride presents a significant risk of developing a serious latent disease for each class member.

Plaintiffs propose a single concentration without accounting for the age of the class member being exposed, the length of exposure, other individual factors such as medical history, or showing the exposure was so toxic that such individual factors are irrelevant. The court did not abuse its discretion in concluding individual issues on this point make trial as a class unfeasible, defeating cohesion.

Id. at 268.  For class actions, the inability to invoke a low threshold of “permissible” exposure may be the death knell of medical monitoring and personal injury class actions.  The implications of the Gates court’s treatment of “regulatory risk” is, however, more far reaching.  Sometimes risk is not really risk at all.  The ambiguity of the risk in risk assessment has confused judges from the lowest magistrate up to Supreme Court justices.  It is time to disambiguate.  See General Electric v. Joiner, 522 U.S. 136, 153-54 (1997) (Stevens, J., dissenting in part) (erroneously assuming that plaintiffs’ expert witness was justified in relying upon a weight-of-evidence methodology because such methodology is often used in risk assessment).

Posted in Causation, Medical monitoring, Scientific Evidence | No Comments »

Two Articles of Interest in JAMA – Nocebo Effects; Medical Screening

February 12th, 2012

Two articles in this week’s Journal of the American Medical Association (JAMA) are of interest to lawyers who litigate, or counsel about, health effects.

One article deals with the nocebo effect, which is the dark side of the placebo effect.  Placebos can induce beneficial outcomes because of the expectation of useful therapy; nocebos can induce harmful outcomes because of the expectation of injury. The viewpoint article in JAMA points out that nocebo effects, like placebo effects, result from the “psychosocial context or therapeutic environment” affecting a patient’s perception of his state of health or illness.  Luana Colloca, MD, PhD, and Damien Finniss, MSc Med., “Nocebo Effects, Patient-Clinician Communication, and Therapeutic Outcomes,” 307 J. Am. Med. Ass’n 567, 567 (2012).

The authors discuss how clinicians can inadvertently prejudice health outcomes by how they frame outcome information to patients.  Importantly, Colloca and Finniss also note that the negative expectations created by the nocebo communication can take place in the process of obtaining informed consent.

The litigation significance is substantial because the creation of negative expectations is not the exclusive domain of clinicians.  Plaintiffs’ counsel, support and advocacy groups, and expert witnesses, even when well meaning, can similarly create negative expectations for health outcomes.  These actors often enjoy undeserved authority among their audience of litigants or claimants.  The extremely high rate of psychogenic illness found in many litigations is the result.  The harmful communications, however, are not limited to plaintiffs’ lawyers and their auxiliaries.  As Colloca and Finniss point out, nocebo effects can be induced by well-meaning warnings and disclosure of information from healthcare providers to patients.  Id. at 567.  The potential to induce negative harms in this way has the obvious consequence for the tort system:  more warnings are not always beneficial.  Indeed, warnings themselves can bring about harm.  This realization should temper courts’ enthusiasms for the view that more warnings are always better.  Warnings about adverse health outcomes should be based upon good scientific bases.

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The other article from this week’s issue of JAMA addresses the harms of screening.  Steven H. Woolf, MD, MPH, and Russell Harris, MD, MPH, “The Harms of Screening: New Attention to an Old Concern,” 307 J. Am. Med. Ass’n 565 (2012).    As I pointed out on these pages, screening for medical illnesses carries significant health risks to patients and ethical risks for the healthcare providers.  See “Ethics and Daubert: The Scylla and Charybdis of Medical Monitoring” (Feb. 1, 2012).  Bayes’ Theorem teaches us that even very high likelihood ratios for screening tests will yield true positive cases swamped by false positive cases when the baseline prevalence is low.  See Jonathan Deeks and Douglas Altman, “Diagnostic tests 4: likelihood ratios,” 329 Brit. Med. J. 168 (2004) (Providing a useful nomogram to illustrate how even highly accurate tests, with high likelihood ratios, will produce more false than true positive cases when the baseline prevalence of disease is low).

The viewpoint piece by Woolf and Harris emphasizes the potential iatrogenic harms from screening:

  • physical injury from the test itself (as in colonic perforations from colonoscopy);
  • cascade of further testing, with further risk of harm, both physical and emotional;
  • anxiety and emotional distress over abnormal results;
  • overdiagnosis; and
  • the overtreatment of conditions that are not substantial threats to patients’ health

These issues should have an appropriately chilling effect on judicial enthusiasm for medical monitoring and surveillance claims.  Great care is required to fashion a screening plan for patients or claimants.  Of course, there are legal risks as well, as when plaintiffs’ counsel fail to obtain the necessary prescriptions or permits to conduct radiological screenings.  See Schachtman “State Regulators Impose Sanction for Unlawful Silicosis Screenings,” 17(13) Wash. Leg. Fdtn. Legal Op. Ltr. (May 25, 2007).  Caveat litigator.

Posted in Causation, Medical monitoring, Scientific Evidence | No Comments »

Federal Rule of Evidence 702 Requires Perscrutations — Samaan v. St. Joseph Hospital (2012)

February 4th, 2012

After the dubious decision in Milward, the First Circuit would seem an unlikely forum for perscrutations of expert witness opinion testimony.  Milward v. Acuity Specialty Products Group, Inc., 639 F.3d 11 (1st Cir. 2011), cert. denied, ___ U.S.___ (2012).  See “Milward — Unhinging the Courthouse Door to Dubious Scientific Evidence” (Sept. 2, 2011).  Late last month, however, a First Circuit panel of the United States Court of Appeals held that Rule 702 required perscrutation of expert witness opinion, and then proceeded to perscrutate perspicaciously, in Samaan v. St. Joseph Hospital, 2012 WL 34262 (1st Cir. 2012).

The plaintiff, Mr. Samaan suffered an ischemic stroke, for which he was treated by the defendant hospital and physician.  Plaintiff claimed that the defendants’ treatment deviated from the standard of care by failing to administer intravenous tissue plasminogen activator (t-PA).  Id. at *1.  The plaintiff’s only causation expert witness, Dr. Ravi Tikoo, opined that the defendants’ failure to administer t-PA caused plaintiffs’ neurological injury.  Id. at *2.   Dr. Tikoo’s opinions, as well as those of the defense expert witness, were based in large part upon data from a study done by one of the National Institutes of Health:  The National Institute of Neurological Disorders and Stroke rt-PA Stroke Study Group, “Tissue Plasminogen Activator for Acute Ischemic Stroke,” 333 New Engl. J. Med. 1581 (1995).

Both the District Court and the Court of Appeals noted that the problem with Dr. Tikoo’s opinions lay not in the unreliability of the data, or in the generally accepted view that t-PA can, under certain circumstances, mitigate the sequelae of ischemic stroke; rather the problem lay in the analytical gap between those data and Dr. Tikoo’s conclusion that the failure to administer t-PA caused Mr. Samaan’s stroke-related injuries.

The district court held that Dr. Tikoo’s opinion failed to satisfy the requirements of Rule 702. Id. at *8 – *9.  Dr. Tikoo examined odds ratios from the NINDS study, and others, and concluded that a patient’s chances of improved outcome after stroke increased 50% with t-PA, and thus Mr. Samaan’s healthcare providers’ failure to provide t-PA had caused his poor post-stroke outcome.  Id. at *9.  The appellate court similarly rejected the inference from an increased odds ratio to specific causation:

“Dr. Tikoo’s first analysis depended upon odds ratios drawn from the literature. These odds ratios are, as the term implies, ratios of the odds of an adverse outcome, which reflect the relative likelihood of a particular result.FN5 * * * Dr. Tikoo opined that the plaintiff more likely than not would have recovered had he received the drug.”

Id. at *10.

The Court correctly identified the expert witness’s mistake in inferring specific causation from an odds ratio of about 1.5, without any additional information.  The Court characterized the testimonial flaw as one of “lack of fit,” but it was equally an unreliable inference from epidemiologic data to a conclusion about specific causation.

While the Court should be applauded for rejecting the incorrect inference about specific causation, we might wish that it had been more careful about important details.  The Court misinterpreted the meaning of an odds ratio to be a relative risk.  The NINDS study reported risk ratio results both as an odds ratio and as a relative risk.  The Court’s sloppiness should be avoided; the two statistics are different, especially when the outcome of interest is not particularly rare.

Still, the odds ratio is interesting and important as an approximation for the relative risk, and neither measure of risk can substitute for causation, especially when the magnitude of the risk is small, and less than two-fold.  The First Circuit recognized and focused in on this gap between risk and causal attribution in an individual’s case:

“[Dr. Tikoo’s] reasoning is structurally unsound and leaves a wide analytical gap between the results produced through the use of odds ratios and the conclusions drawn by the witness. When a person’s chances of a better outcome are 50% greater with treatment (relative to the chances of those who were not treated), that is not the same as a person having a greater than 50% chance of experiencing the better outcome with treatment. The latter meets the required standard for causation; the former does not.  To illustrate, suppose that studies have shown that 10 out of a group of 100 people who do not eat bananas will die of cancer, as compared to 15 out of a group of 100 who do eat bananas. The banana-eating group would have an odds ratio of 1.5 or a 50% greater chance of getting cancer than those who eschew bananas. But this is a far cry from showing that a person who eats bananas is more likely than not to get cancer.

Even if we were to look only at the fifteen persons in the banana-eating group who did get cancer, it would not be likely that any particular person in that cohort got it from the consumption of bananas. Correlation is not causation, and a substantial number of persons with cancer within the banana-eating group would in all probability have contracted the disease whether or not they ate bananas.FN6

We think that this example exposes the analytical gap between Dr. Tikoo’s methods and his conclusions.  Although he could present figures ranging higher than 50%, those figures were not responsive to the question of causation. Let us take the “stroke scale” figure from the NINDS study as an example. This scale measures the neurological deficits in different parts of the nervous system. Twenty percent of patients who experienced a stroke and were not treated with t-PA had a favorable outcome according to this scale, whereas that figure escalated to 31% when t-PA was administered.

Although this means that the patients treated with t-PA had over a 50% better chance of recovery than they otherwise would have had, 69% of those patients experienced the adverse outcome (stroke-related injury) anyway.FN7  The short of it is that while the odds ratio analysis shows that a t-PA patient may have a better chance of recovering than he otherwise would have had without t-PA, such an analysis does not show that a person has a better than even chance of avoiding injury if the drug is administered. The odds ratio, therefore, does not show that the failure to give t-PA was more likely than not a substantial factor in causing the plaintiff’s injuries. The unavoidable conclusion from the studies deemed authoritative by Dr. Tikoo is that only a small number of patients overall (and only a small fraction of those who would otherwise have experienced stroke-related injuries) experience improvement when t-PA is administered.”

*11 and n.6 (citing Milward).

The court in Samaan thus suggested, but did not state explicitly, that the study would have to have shown better than a 100% increase in the rate of recovery for attributability to have exceeded 50%.  The Court’s timidity is regrettable. Yes, Dr. Tikoo’s confusing the percentage increased risk with the percentage of attributability was quite knuckleheaded.  I doubt that many would want to subject themselves to Dr. Tikoo’s quality of care, at least not his statistical care.  The First Circuit, however, stopped short of stating what magnitude increase in risk would permit an inference of specifc causation for Mr. Samaan’s post-stroke sequelae.

The Circuit noted that expert witnesses may present epidemiologic statistics in a variety of forms:

“to indicate causation. Either absolute or relative calculations may suffice in particular circumstances to achieve the causation standard. See, e.g., 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, 176 L.Ed.2d 111 (2010).”

 Id. at *11.

Although the citation to Texas law with its requirement of a doubling of a relative risk is welcome and encouraging, the Court seems to have gone out of its way to muddle its holding.  First, the Young case involved t-PA and a claimed deviation from the standard of care in a stroke case, and was exactly on point.  The Fifth Circuit’s reliance upon Texas substantive law left unclear to what extent the same holding would have been required by Federal Rule of Evidence 702.

Second, the First Circuit, with its banana hypothetical, appeared to confuse an odds ratio with a relative risk.  The odds ratio is different from a relative risk, and typically an odds ratio will be higher than the corresponding relative risk, unless the outcome is rare.  See Michael O. Finkelstein & Bruce Levin, Statistics for Lawyers at 37 (2d ed. 2001). In studies of medication efficacy, however, the benefit will not be particularly rare, and the rare disease assumption cannot be made.

Third, risk is not causation, regardless of magnitude.  If the magnitude of risk is used to infer specific causation, then what is the basis for the inference, and how large must the risk be?  In what way can epidemiologic statistics be used “to indicate” specific causation?  The opinion tells us that Dr. Tivoo’s reliance upon an odds ratio of 1.5 was unhelpful, but why?  The Court, which spoke so clearly and well in identifying the fallacious reasoning of Dr. Tivoo, faltered in identifying what use of risk statistics would permit an inference of specific causation in this case, where general causation was never in doubt.

The Fifth Circuit’s decision in Young, supra, invoked a greater than doubling of risk required by Texas law.  This requirement is nothing more than a logical, common-sense recognition that risk is not causation, and that small risks alone cannot support an inference of specific causation.  Requiring a relative risk greater than two makes practical sense despite the apoplectic objections of Professor Sander Greenland.  See “Relative Risks and Individual Causal Attribution Using Risk Size” (Mar. 18, 2011).

Importantly, the First Circuit panel in Samaan did not engage in the hand-waving arguments that were advanced in Milward, and stuck to clear, transparent rational inferences.  In footnote 6, the Samaan Court cited its earlier decision in Milward, but only with double negatives, and for the relevancy of odds ratios to the question of general causation:

“This is not to say that the odds ratio may not help to prove causation in some instances.  See, e.g., Milward v. Acuity Specialty Prods. Group, Inc., 639 F.3d 11, 13–14, 23–25 (1st Cir.2011) (reversing exclusion of expert prepared to testify as to general rather than specific causation using in part the odds ratio).”

Id. at n.6.

The Samaan Court went on to suggest that inferring specific causation from the magnitude of risk was “theoretically possible”:

“Indeed, it is theoretically possible that a particular odds ratio calculation might show a better-than-even chance of a particular outcome. Here, however, the odds ratios relied on by Dr. Tikoo have no such probative force.“

Id. (emphasis added).  But why and how? The implication of the Court’s dictum is that when the risk ratio is small, less than or equal to two, the ratio cannot be taken to have supported the showing of “better than even chance.” In Milward, one of the key studies relied upon by plaintiff’s expert witness reported an increased risk of only 40%.  Although Milward presented primarily a challenge on general causation, the Samaan decision suggests that the low-dose benzene exposure plaintiffs are doomed, not by benzene, but by the perscrutation required by Rule 702.

Posted in Causation, Rule 702, Scientific Evidence, statistical evidence | No Comments »

Ethics and Daubert: The Scylla and Charybdis of Medical Monitoring

February 1st, 2012

Build a courtroom and they will come. The floodgates argument, all too quickly rejected by the judiciary, proved all too true in West Virginia. West Virginia built a courtroom that would entertain multiple claims from virtually every West Virginian. This jurisprudential hospitality offers medical monitoring that requires no predicate present injury. Bower v. Westinghouse Electric Corp., 522 S.E.2d 424 (W.Va. 1999).

Everyone is exposed to hazardous substances and to medications with potential side effects. In West Virginia, almost everyone is a potential plaintiff in a medical monitoring case.

Universal health care may be attainable, after all, funded by the manufacturers of predominately beneficial products. Almost heaven West Virginia, indeed. Type 2 diabetes mellitus, or adult-onset diabetes, is a devastating disease that results from uncontrolled blood sugars. The medical complications of diabetes are extensive and well known: blindness, gangrene, kidney failure, heart attack, stroke, liver disease, and others. The costs of this medical care are staggering, and diabetics are among the neediest patients in our health care system. Imagine if the “compensation goals” of the tort system could be subverted to provide medical monitoring to diabetic patients. If possible anywhere, it would seem West Virginia would be the most likely candidate.

Between March 1997 and March 2000, many Type 2 diabetics achieved control of their blood sugars with the help of a new oral medication, Troglitazone (Rezulin®).  Troglitazone modifies the Type 2 diabetic patient’s resistance to insulin. The drug effectively reduces blood sugar, and it avoids the need for exogenous insulin. Most life-saving drugs have side effects, and Troglitazone is no exception. Physicians, knowledgeable about Troglitazone’s efficacy and its potential for rare, idiosyncratic liver toxicity, prescribed the drug to help their patients gain control over their blood sugar levels and to avoid the serious complications of diabetes. In March 2000, the manufacturer of Troglitazone voluntarily withdrew the drug from the market. Adverse publicity over liver toxicity and the availability of two other more recent glitazones, which initially had the appearance of a safer adverse event profile, had shifted the risk-benefit balance against Troglitazone.

No one can be surprised that Rezulin plaintiffs sought class certification in West Virginia state court; nor can anyone, in view of Bower, be surprised that asymptomatic plaintiffs sought medical monitoring as a remedy, within the context of the class action. Observers unfamiliar with the weakness of the Rezulin plaintiffs’ scientific proofs might, however, be surprised at the plaintiffs’ failure, initially at the trial court level, to win class certification in West Virginia, for a medical monitoring class. In re West Virginia Rezulin Litigation, W.Va. Cir.Ct., Civil Action No. 00-C-1180H, Amended Order Denying Class Certification (Dec. 12, 2001) (Hutchison, J.), 2001 WL 1818442 (Dec 13, 2001).

The West Virginia trial court’s rejection of the proposed Rezulin medical monitoring class is remarkable for many reasons. Some commentators regard West Virginia law as the outer limits of medical monitoring jurisprudence.  In the Rezulin case, however, Judge John Hutchison delivered a thorough, analytical opinion, which demonstrated that the liberal West Virginia criteria for a medical monitoring remedy cannot be satisfied as easily as once thought. Among the notable holdings were the trial court’s insistence that:

(1) the monitoring proponents adduce epidemiologic evidence that the exposure at issue can actually cause the latent injury for which monitoring is sought;

(2) the proponents of monitoring identify highly sensitive tests, which when deployed on the exposed population that has a relatively high prevalence of the latent injury, will have a high predictive value; and

(3) the proposed monitoring will allow for early preventive care.

In determining whether the class plaintiffs had met the criteria for medical monitoring, Judge Hutchison did not face any significant evidentiary gatekeeping responsibility. The trial court did not have to ponder the contours of any reliable epidemiologic studies. The court found no epidemiologic studies to show that Rezulin can cause latent injury months or years after the drug is discontinued.

Similarly, the court did not have to delve into any evidentiary thicket of contradictory scientific proof to determine whether the proposed medical monitoring program was based upon reliable scientific and medical methods. The court found that most of the proposed tests had low sensitivity, and that there were no diagnostic tests that can determine whether any liver injury was caused by Rezulin. Given the many other causes of liver diseases among the plaintiff class members, there was no evidence of any prevalence of latent injury from Rezulin. Without an assessment of prevalence of latent injury, any proposed test would have little or no positive predictive value. The proposed program failed for lack of substantial evidentiary support.

The court was further impressed by the riskiness of the proposed monitoring program. The proposed tests, lacking sensitivity and specificity, were likely to result in many “false positives,” which in turn would lead to liver biopsies.  (Indeed, false positives would likely swamp any true positives if any there should be). Liver biopsies, however, are painful, invasive, and carry a small, but definite, risk of death. Furthermore, the court found that the proposed tests would not facilitate medical interventions that could prevent or resolve the detected problem.

This failure to obtain class certification for medical monitoring is noteworthy for more than the narrow case holdings. There is intriguing obiter dictum. The court noted that one of the plaintiffs’ expert witnesses admitted that the proposed monitoring program was an “experiment.” The court found this admission directly relevant to the plaintiffs’ failure to produce epidemiologic evidence that the substance at issue could actually cause latent injury. Apparently, the plaintiffs’ witness was advocating implementation of the monitoring program so it might yield the evidence that the class must proffer before it could obtain the monitoring remedy. The court readily dismissed this Alice in Wonderland insistence upon “[s]entence first—verdict afterwards.” The court showed little patience for the “stuff and nonsense” of trying to satisfy the criterion of epidemiologic evidence with the anticipated results that would come from the proposed monitoring program itself.

Implicit in the trial court’s rejection of evidentiary bootstrapping is a larger, ethical concern. There is something unsettling about a court-ordered medical monitoring program that is an “experiment.” Class certification decisions are complicated enough without having to endorse experimentation on human beings. Perhaps the suggestion of human experimentation chilled any residual enthusiasm for the notion that medical monitoring might otherwise be a suitable judicial remedy for achieving corrective justice in a mass tort case.

And yet there is an “experimental” aspect to many, if not most, proposed monitoring programs. Little or no clinical experience is available to support the claimed benefits of many proposed large, lifelong monitoring regimes. Indeed, such programs are not wholly benign. The potential harms of monitoring, some of which were acknowledged in Judge Hutchison’s opinion, are significant.

The imposition of potentially harmful monitoring should, indeed, trouble our courts and cause their reticence in embracing monitoring as a remedy. Courts need to confront the ethical implications that flow from the experimental nature of many medical monitoring proposals.

Proposals for monitoring differ from expert witness opinion that is typically offered in personal injury cases involving present injuries. Physician witnesses, at the request of the parties, usually examine claimants, evaluate and diagnose their conditions, and opine about prognosis and etiology. Although such witnesses use their medical experience, training, and knowledge, they generally are not acting within the context of a patient-physician relationship. Adams v. Harron, 191 F.3d 447, 1999 WL 710326 (4th Cir. 1999). In the usual personal injury case, physician witnesses are not advocating medical interventions; at most, they are endorsing or criticizing the reasonable medical necessity of medical plans of treating physicians.  In medical monitoring class actions, however, physician expert witnesses advocate medical interventions for people they have often never met and have never evaluated.

Recommendations for preventive health measures carry risks of harm, and these risks must provoke ethical scrutiny of the proposed monitoring. The offering of an opinion that a plaintiff, or a class of plaintiffs, should receive medical monitoring is the practice of medicine. As part of medical practice, the presentation of such opinions is subject to ethical constraints, which courts should observe and foster. Medico-legal opinions that recommend preventive interventions represent a significant involvement in the claimant’s actual medical care. Screening or monitoring recommendations must acknowledge and avoid the highly individualized risks of harm and the essential need for informed consent to protect individual autonomy.

Physicians who prepare medical monitoring litigation plans cannot absolve themselves of ethical and professional responsibility by disclaiming the existence of physician-patient relationships. Such physicians are not practicing mere courthouse medicine; they are engaged in medical practice, as defined by the American Medical Association, AMA Policy H-265.993, and in the sense that they are seeking to control future medical interventions for the class members.  Physicians who propose medical monitoring or screening for claimants thus operate under the ethical constraints of avoiding harm, providing benefits, and respecting individual patient autonomy. The medical community recognizes that good intentions notwithstanding, monitoring can be harmful. “[P]reventive therapies can give rise to anticipatory anxiety, side effects, the stress of false-positive results and an unhealthy preoccupation with disease.” Huston, “The Perils of Prevention,” 154 Canadian Med. Ass’n J. 1463 (1996). Other potential adverse effects of monitoring include deriving false assurances of health and being labeled as “sick.” Marshall, “Prevention. How Much Harm? How Much Benefit? 3. Physical, Psychological and Social Harm,” 155 Canadian Med. Ass’n J. 169 (1996).

Furthermore, some screening programs will detect true-positive results with little or no clinical significance.  For example, in cancer screening, some nodules detected will be benign. Other nodules may be extremely indolent malignancies, which would never become aggressive, metastatic growths. Indeed, such masses, picked up in screening, might regress before they would have been otherwise detectable. Screening programs must come to grips with the vagaries of the diseases and conditions that are the subject of the monitoring. The potential for harm, from monitoring, may be increased by the litigation setting, in which people are encouraged to become invested in illness seeking behaviors.

Given the potential for harm, physician witnesses who advocate monitoring face ethical and evidentiary burdens to establish the efficacy and benefit of the planned screening. At a minimum, class members will have to be properly advised, and will have to be given informed consent. The process of obtaining consent must accommodate the intensely personal and individualized judgments about the risks of monitoring.

Well-established criteria for evaluating public health interventions are available and employed by such agencies and groups as the United States Preventive Task Force, the Canadian Task Force on the Periodic Health Examination, the Cochrane Collaboration, and others.  The existence of generally accepted evaluative criteria has obvious implications for determining the admissibility of monitoring proposals under either Daubert or Frye standards. Expert witnesses, in this ethically sensitive area, must be held to the same intellectual rigor that would be employed to evaluate monitoring or screening programs in the field of public health. Pitfalls, fallacies, and methodological error are abundant in the field of preventive medicine. Marshall, “Prevention. How Much Harm? How Much Benefit? 2. Ten Potential Pitfalls in Determining the Clinical Significance of Benefits,” 154 Canadian Med. Ass’n J. 1837 (1996). Even well-intentioned advice, such as counseling routine mammography in women, has been the subject of heated controversy and intense methodological debate. Ernster, “Mammograms and Personal Choice,” The New York Times (Feb. 14, 2002).   Courts must acknowledge that if a proposed preventive program does not satisfy generally accepted criteria for medical interventions and does not have proven benefits that clearly outweigh the potential harms, medical monitoring becomes a court-sanctioned human experiment.

The guiding principles and corollaries for human experimental research can be found in several sources, including The Nuremberg Code, Permissible Medical Experiments, World Medical Association, “Declaration of Helsinki’s Ethical Principles for Medical Research Involving Human Subjects,” 284 J. Am. Med. Ass’n 3043 (Dec. 20, 2000), as restated on several occasions, regulations of the Food and Drug Administration, Protection of Human Subjects, 21 C.F.R. § 50.25; and the Department of Health and Human Services, 45 C.F.R. § 46.

Informed consent is the absolute requirement for any human medical experimentation. Regulations and guidelines of various federal and state agencies and medical organizations, however, place further limitations on the course of permissible experimental design.  The Declaration of Helsinki, for instance, requires that the research design be clearly set out in an experimental protocol, which has been approved by an independent ethical review committee. The proposed medical research

“must conform to generally scientific principles, [and] be based on a thorough knowledge of the scientific literature….”

Declaration of Helsinki, ¶11 (2000). Permissible Medical Experiments, supra. Daubert and Frye thus become ethical imperatives, as well as legal requirements, before any serious consideration can be given to a medical monitoring program.

In all likelihood, no court, if it really thought about the matter, would want to serve as an Institutional Review Board, and to sit in judgment of an experimental protocol. The realization that the proposed remedy is itself an experiment should suffice to quash any advocacy for the result. Indeed, an awareness of the ethical problems entailed by poorly supported medical monitoring programs must guide and propel courts to be vigilant in their gatekeeping responsibilities.  Much of the earlier case law on monitoring developed before the principles and implications of Daubert could be realized in monitoring cases, and these older judgments must be questioned in the light of these ethical and evidentiary concerns.

Judge Hutchison’s decision to deny certification for a Rezulin medical monitoring class obviated consideration of the ethical and evidentiary problems posed by monitoring remedies. The clear absence of proof to support the remedy for the Rezulin plaintiffs avoided debate over how to protect the informed consent process when the personal perception of the risks of monitoring will be perceived differently by each class member.

The paradisiacal Appalachian dream, however, did not last very long.

The Supreme Court of West Virginia did not appear to be concerned by the ethics of human experimentation or the need for showing a basis in evidence for the reliability or accuracy of screening tests.  Chief Justice Starcher, writing for a unanimous court, reversed and remanded the case to proceed as a class action.  The Supreme Court’s opinion was a mechanical recitation of class action rules, interpreted to disallow any preliminary inquiry into the merits of the suit. In re West Virginia Rezulin Litig., 585 S.E.2d 52 (W.Va. 2003).  The word “ethics” does not appear in the Supreme Court’s opinion. The Nuremberg Code was nowhere in sight.

Perhaps most medical monitoring class action battles are now behind us, given that federal courts have come to their senses and have generally disallowed class actions for this remedy.  The cases on the book, however, represent ethically dubious judgments, which call for condemnation from the medical and legal community.  Courts must take stock of the certainty that many medical monitoring schemes will produce far more false positive cases than true positive cases, and widespread fear, anxiety, and harm from unnecessary medical interventions.  See generally Christopher P. Guzelian, Bruce E. Hillner, and Philip S. Guzelian, “A Quantitative Methodology for Determining the Need for Exposure-Prompted Medical Monitoring,” 79 Indiana L. J. 57 (2004).

[An earlier version of this post was published under the same title in Industrywide Liability News (Spring 2002)]

Posted in Medical monitoring, Rule 702, Scientific Evidence | No Comments »

Ethics and Statistics

January 21st, 2012

Chance magazine has started a new feature, the “Ethics and Statistics column, which is likely to be of interest to lawyers and to statisticians who work on litigation issues.  The column is edited by Andrew Gelman.  Judging from the Gelman’s first column, I think that the column may well become a valuable forum for important scientific and legal issues arising from studies used in public policy formulation, and in reaching conclusions that are the bases for scientific expert witnesses’ testimony in court.

Andrew Gelman is a professor of statistics and political science in Columbia University.  He is also the director of the University’s Applied Statistics Center.   Gelman’s inaugural column touches on some issues of great importance to legal counsel who litigate scientific issues involving scientific studies:  access to underlying data in the studies that are the bases for expert witness opinions.  See Andrew Gelman, “Open Data and Open Methods,” 24 Chance 51 (2011).

Gelman acknowledges that conflicts are not only driven by monetary gain; they can be potently raised by positions or causes espoused by the writer:

“An ethics problem arises when you are considering an action that

(a) benefits you or some cause you support,

(b) hurts or reduces benefits to others, and

(c) violates some rule.”

Id. at 51a.

Positional conflicts among scientists whose studies touch upon policy issues give rise to “the ethical imperative to share data.”  Id. at 51c.  Naming names, Professor Gelman relates an incident in which he wrote to an  EPA scientist, Carl Blackman, who had presented a study on the supposed health effects of EMF radiation.   Skeptical of how Blackman had analyzed data, Gelman wrote to Blackman to request his data to carry out additional, alternative statistical analyses.  Blackman answered that he did not think these other analyses were needed, and he declined to share his data.

This sort of refusal is all too common, and typical of the arrogance of scientists who do not want others to be able to take a hard look at how they arrived at their conclusions.  Gelman reminds us that:

“Refusing to share your data is improper… .”

* * * *

“[S]haring data is central to scientific ethics.  If you really believe your results, you should want your data out in the open. If, on the other hand, you have a sneaking suspicion that maybe there’s something there you don’t want to see, and then you keep your raw data hidden, it’s a problem.”

* * * *

“Especially for high-stakes policy questions (such as the risks of electric power lines), transparency is important, and we support initiatives for automatically making data public upon publication of results so researchers can share data without it being a burden.”

Id. at 53.

To be sure, there are some problems with sharing data, but none that is insuperable, and none that should be an excuse for withholding data.  The logistical, ethical, and practical problems of data sharing should now be anticipated long before publication and the requests for data sharing arrive.

Indeed, the National Institutes of Health requires data sharing plans to be part of a protocol for a federally funded study.  See Final NIH Statement on Sharing Research Data (Feb. 26, 2003). Unfortunately, the NIH’s implementation and enforcement of its data-sharing policy is as spotty as a Damien Hirst painting.  See “Seeing Spots” The New Yorker (Jan. 23, 2012).

Posted in Conflicts of Interest, Data Sharing, Rule 702, Scientific Evidence, statistical evidence | No Comments »

Defendants’ Petition for Certiorari in Milward – DENIED

January 9th, 2012

The Supreme Court reported this morning that the defendants petition for certiorari in U.S. Steel Corp. v. Milward, Docket No.. 11-316, was denied.

While unfortunate for the parties involved, the denial was not a surprise.  The Supreme Court does not sit to review factual errors and distortions, such as those that pervaded the First Circuit’s decision below.  Furthermore, most of the justices are at sea when it comes to scientific evidence, as shown by Justice Sotomayor’s incredible discussion of causal concepts, in Mattrix Initiatives v. Siracusano, ___ U.S. ___, 131 S.Ct. 1309 (2011).  See “Matrixx Unloaded.”

Indeed, there were great dangers involved in seeking this discretionary review in the Supreme Court.  As I have written, the SKAPP-a-lites have larded up the most recent edition of the Reference Manual on Scientific Evidence with language that could easily be marshaled in favor of a loosey-goosey interpretation of Rule 702.  See “Reference Manual on Scientific Evidence v3.0 – Disregarding Study Validity in Favor of the ‘Whole Gamish’.”

What is needed is not Supreme Court review, but a thorough dismemberment of the philosophy behind the Circuit’s decision in Milward, and the wayward, or the Milward, trend towards anything goes in the latest edition of the Reference Manual on Scientific Evidence.  See “Milward — Unhinging the Courthouse Door to Dubious Scientific Evidence.”

It was shame and humiliation that drove the Daubert decision in the Supreme Court, and ultimately the revision of Federal Rule of Evidence 702.   When the Courts suddenly realized that the scientific community was looking at their aberrant judgments,  they changed up.  The silicone gel breast implant litigation illustrates the phenomenon of how the courts react to the medical and scientific communties’ condemnation.

The Milward decision calls for a similar collateral attack on the unprincipled use of so-called “weight of the evidence” thinking.  Some evidence, after all, is a mere feather’s weight, and not an appropriate basis for a scientific conclusion.

FW: Defendants’ Petition for Certiorari in Milward – DENIED

Inbox
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Nathan A. Schachtman
11:37 AM (12 minutes ago)
to me

From: Nathan A. Schachtman [mailto:Nathan@SchachtmanLaw.com]
Sent: Monday, January 09, 2012 11:22 AM
To: ‘Nathan A. Schachtman’
Subject: Defendants’ Petition for Certiorari in Milward – DENIED

The Supreme Court reported this morning that the defendants petition for certiorari in U.S. Steel Corp. v. Milward, Docket No.. 11-316, was denied.

While unfortunate for the parties involved, the denial was not a surprise.  The Supreme Court does not sit to review factual errors and distortions, such as those that pervaded the First Circuit’s decision below.  Furthermore, most of the justices are at sea when it comes to scientific evidence, as shown by Justice Sotomayor’s incredible discussion of causal concepts, in Mattrix Initiatives v. Siracusano, ___ U.S. ___, 131 S.Ct. 1309 (2011).  See “Matrixx Unloaded.”

http://www.supremecourt.gov/opinions/10pdf/09-1156.pdf

http://schachtmanlaw.com/matrixx-unloaded/

Indeed, there were great dangers involved in seeking this discretionary review in the Supreme Court.  As I have written, the SKAPP-a-lites have larded up the most recent edition of the Reference Manual on Scientific Evidence with language that could easily be marshaled in favor of a loosey-goosey interpretation of Rule 702.

What is needed is not Supreme Court review, but a thorough dismemberment of the philosophy behind the Circuit’s decision in Milward, and the wayward, or the Milward, trends towards anything goes in the latest edition of the Reference Manual on Scientific Evidence.  See “Milward — Unhinging the Courthouse Door to Dubious Scientific Evidence.”

http://schachtmanlaw.com/milward-unhinging-the-courthouse-door-to-dubious-scientific-evidence/

The courts need to be made to feel ashamed of their judgments with respect to scientific matters.

It was the shame and humiliation of Bendectin litigation and others that moved the Court in Daubert, and later Joiner.

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Posted in Rule 702, Scientific Evidence | No Comments »

The Continuing Saga of Bad-Faith Assertions of Conflicts of Interest

December 28th, 2011

Conflicts of interest (COI), real or potential, have become a weapon used to silence the manufacturing industry in various scientific debates and discussions.  Other equally “interested” parties, labor unions, advocacy groups, and consultants to the other industry – the litigation industry – have used conflicts and ethical claims to silence the manufacturing industry and to engage in unfettered false scientific speech. The public, unwilling and untrained to look at evidence on the merits, is conditioned to accepting an allegation of COI as the end of the discussion on scientific issues.

Recently, journalist Shannon Brownlee criticized the FDA for its suggestion that the agency was having difficulty in finding experts who cleared the agency’s conflict-of-interest prohibitions.  Brownlee explicitly contended that she could easily find “unbiased” scientists who could advise the agency on drug and device issues.

Shannon Brownlee, “Is There an Independent Unbiased Expert in the House” (Aug. 3, 2011).

Indeed, Brownlee sent FDA Commissioner Margaret Hamburg a list of allegedly neutral experts who could advise the agency.  Brownlee gave everyone on her list a clean bill of ethical health, and has published the list on multiple occasions, both on the website Healthnewsreview.org, and a few years ago, in the British Medical Journal:  Jeanne Lenzer & Shannon Brownlee, “Is there an (unbiased) doctor in the house?” 337 Brit. Med. J. 206 (2008).

Brownlee tells us that journalists from respectable print media, including the New York Times, and the Wall Street Journal, have requested the list, apparently to contact the “unbiased” experts to help investigate news stories about drugs and medical devices.  What the gullible may not appreciate is that the list fallaciously is based upon only one exclusionary criterion:  having consulted for the pharmaceutical industry.  The list omits other important COI exclusionary criteria, such as having consulted for the litigation industry, or having taken erroneous, unwarranted, and ideologically driven positions on scientific issues.

What litigation industry?  Brownlee may have missed the fact that plaintiffs’ lawyers represent a huge financial interest in obtaining compensation for others, with 40 percent of the proceeds going to themselves.  This litigation industry thrives, even with Dickie Scruggs in prison, and Stanley Chesley in disrepute.

In today’s litigation environment, with aggregation of claims in federal multi-district cases, plaintiffs’ counsel stand to profit in the billions from scientific positions espoused by their expert witnesses.

Who are the litigation industry expert witnesses on Brownlee’s list?  Here are some obvious candidates:

Peter R. Breggin, MD, psychiatrist, clinical psychopharmacologist, independent author and scientist; Founder and Director Emeritus, International Center for the Study of Psychiatry and Psychology

Adriane Fugh-Berman, MD, Professor, Department of Physiology and Biophysics, Georgetown University Medical Center; Director, PharmedOut.org

Curt Furberg, MD, PhD, Professor of Public Health Sciences, Wake Forest University School of Medicine

Joseph Glenmullen, MD, Clinical instructor in psychiatry, Harvard Medical School

Bruce Psaty, MD, PhD, Professor, Medicine & Epidemiology, University of Washington Cardiovascular Health Research Unit

Also on the list were well-known anti-industry zealots, who focus almost exclusively on the manufacturing industry, while ignoring or endorsing the excesses and unwarranted claims of the litigation industry:

Lisa Bero, PhD, Professor, University of California, San Francisco U.S.

Sheldon Krimsky, PhD, Tufts University & Council for Responsible Genetics

Sidney Wolfe, MD, Director, Health Research Group of Public Citizen.

Now some people may claim that the litigation industry consultants, and the anti-industry zealots, take their positions not to please their sponsors, or to pursue lucrative opportunity, but because they fervently believe the positions that they take. But then why not give the pharmaceutical industry consultants the same benefit of the doubt?  Indeed, why not move beyond COI allegations to creating lists of scientists and physicians who have demonstrated proficiency in advancing evidence-based judgments that have withstood the test of time?

This anti-industry hypocrisy manifests not only in assertions of conflicts of interest, but also in calls for industry to disclose all underlying data from industry-funded or sponsored studies, while taking a protectionist stance on all other underlying data.

Let’s hope that in 2012, industry fights back, and evidence regains its primary role in resolving scientific disputes.

Posted in Conflicts of Interest, Scientific Evidence | No Comments »

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