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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.

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Leaving Las Vegas

February 24th, 2013

The Journal of the National Cancer Institute recently published a curious article about what appears to be unpublished research that suggests a non-asbestos environmental cause of malignant mesothelioma in Clark County, Nevada. Leslie Harris O’Hanlon, “Researchers Explore Possible Link Between Mesothelioma and Dust Emissions in Southern Nevada,” J. Nat’l Cancer Instit., doi: 10.1093/jnci/djt033, published ahead of print (Feb. 12, 2013).

The researcher appears to have been Francine Baumann , an epidemiologist at the University of Hawaii Cancer Center, who has worked with Michele Carbone, on occasion. Analyzing Nevada’s cancer registry data from 1995 to 2008, Baumann found what she believed to be an increase in earlier age at diagnosis, and a reduced ratio of male-to-female cases for Clark County. She interpreted these data to show that an environmental exposure was at work, but she professed ignorance of what the exposure might be.

The article also quotes the Nevada state epidemiologist, Ihsan Azzam, M.D., Ph.D., as saying:

“We analyzed the data and used the same data set as the researcher and came to completely different conclusions and findings. Their interpretation of data and their representation of it is wrong.”

The article presents no data or statistical analysis. Given that Baumann’s work is unpublished, and apparently contradicted, it is curious that the Journal would publish any story about it. Some of the raw data can be found online at Nevada Central Cancer Registry, including an online database, and Reports From The Office of Public Health Informatics and Epidemiology.

The O’Hanlon article is even more curious considering the nature of the research. There are 16 counties in Nevada, so Baumann presumably was canvassing counties without a pre-specified hypothesis as to whether Clark County was different from the others, or from the national rates. This seems like post-hoc data dredging, but the Journal does not provide sufficient information to assess the validity of Baumann’s work.

The O’Hanlon article bizarrely talks about an unknown environmental cause in Clark County, but does not mention erionite, a zeolite. The article discusses erionite-associated mesothelioma in Turkey, and an investigation into erionite occurrences in the United States. Remarkably, O’Hanlon fails to mention that erionite occurs in Clark County, and in many other counties, throughout Nevada. The NIOSH Science Blog fills in the missing information by showing how widespread erionite deposits are throughout Nevada. See David Weissman, MD, and Max Kiefer, MS, CIH, “Erionite: An Emerging North American Hazard,” (Nov. 22, 2011). Of course, the widespread deposits argue against erionite as a causal explanation for the putative environmental trigger in Clark County. See also Arthur J. Gude & Richard Sheppard, “Wooly Erionite from the Reese River Zeolite Deposit, Lander County, Nevada, and its Relationship to Other Erionites,” 29 Clays and Clay Minerals, 378-384 (1981); Keith Papke, “Erionite and Other Associated Zeolites in Nevada,” Bulletin 79, Nevada Bureau of Mines and Geology (1972).

Erionite occurs in several mineralogical forms, including non-fibrous and various fibrous forms. The erionite associated with environmental cases in Turkey has been studied and found to be fibrous, but there are many variations in fibers, including length, and length-to-diameter aspect ratio. Erionite is a zeolite mineral and has the ability to absorb metal ions, including chromate, uranyl, and other ions, which may be an independent source of potential carcinogenicity.

There are many reasons to leave Las Vegas, but Dr. Baumann probably has not found a new one.

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Origins of the Relative Risk of Two Argument for Specific Causation

October 20th, 2012

In an unpublished paper, which Professor Susan Haack has presented several times over the last few years, she has criticized the relative risk [RR] >2 argument. In these presentations, Haack has argued that the use of RR to infer specific causation is an example of flawed “probabilism” in the law. Susan Haack, “Risky Business: Statistical Proof of Individual Causation,” in Jordi Ferrer Beltrán, ed., Casuación y atribución de responsibilidad (Madrid: Marcial Pons, forthcoming)[hereafter Risky Business]; Presentation at the Hastings Law School (Jan. 20, 2012); Presentation at University of Girona (May 24, 2011). Elsewhere, Haack has criticized the use of relative risks for inferring specific causation on logical grounds. See, e.g., Susan Haack, “Warrant, Causation, and the Atomism of Evidence Law,” 5 Episteme 253, 261 (2008)[hereafter “Warrant“]; “Proving Causation: The Holism of Warrant and the Atomism of Daubert,” 4 J. Health & Biomedical Law 273, 304 (2008)[hereafter “Proving Causation“]. (See Schachtman, “On the Importance of Showing Relative Risks Greater Than Two – Haack’s Arguments” (May 23, 2012) (addressing errors in Haack’s analysis).

In “Risky Business,” Haack describes the RR > 2 argument as the creation of government lawyers from the litigation over claims of Guillain-Barré syndrome (GBS), by patients who had received swine flu vaccine. Like her logical analyses, Haack’s historical description is erroneous. The swine flu outbreak of 1976, indeed, had led to a federal governmental immunization program, which in turn generated claims that the flu vaccine caused GBS. Litigation, of course, ensued. The origins of the RR > 2 argument, however, predate this litigation.

GBS is an auto-immune disease of the nervous system. The cause or causes of GBS are largely unknown. In the GBS vaccine cases, the government took the reasonable position that treating physicians or clinicians have little or nothing to contribute to understanding whether the swine-flu vaccine can cause GBS or whether the vaccine caused a particular patient’s case. Cook v. United States, 545 F. Supp. 306 (N.D. Cal. 1982); Iglarsh v. United States, No. 79 C 2148, 1983 U.S. Dist. Lexis 10950 (N.D. Ill. Dec. 9, 1983). The government did, however, concede that cases that arose within 10 weeks of vaccination were more likely than not related on the basis of surveillance data from the Centers for Disease Control. After 10 weeks, the relative risk dropped to two or less, and thus the plaintiffs who developed GBS 10 weeks, or more, after immunization were more likely than not idiopathic cases (or at least non-vaccine cases). See Michael D. Green, “The Impact of Daubert on Statistically Based Evidence in the United States,” Am. Stat. Ass’n, Proc. Comm. Stat. Epidem. 35, 37-38 (1998) (describing use of probabilistic evidence in the GBS cases).

Haack’s narrative of the evolution of the RR > 2 argument creates the impression that the government lawyers developed their defense out of thin air. This impression is false. By the time, the Cook and Iglarsh cases were litigated, the doubling of risk notion had been around for decades in the medical literature on radiation risks and effects. Ionizing radiation had been shown to have genetic effects, including cancer risk, in the 1920’s. By the time of the Manhattan project, radiation was a known cause of certain types of cancer. Although there was an obvious dose-response relationship between radiation and cancer, the nature of the relationship and the existence of thresholds were not well understood. Medical scientists, aware that there were background mutations and genetic mistakes, thus resorted to a concept of a “doubling dose” to help isolate exposures that would likely be of concern. See, e.g., Laurence L. Robbins, “Radiation Hazards: III. Radiation Protection in Diagnostic Procedures,” 257 New Engl. J. Med. 922, 923 (1957) (discussing doubling dose in context of the medical use of radiation).

By 1960, the connection between “doubling dose” and a legal “more likely than not” evidentiary standard was discussed in the law review literature. See, e.g., Samuel D. Estep, “Radiation Injuries and Statistics: The Need for a New Approach to Injury Litigation,” 59 Mich. L. Rev. 259 (1960). If the doubling dose concept was not obviously important for specific causation previously, Professor Estep made it so in his lengthy law review article. By 1960, the prospect of litigation over radiation-induced cancers, which had a baseline prevalence in the population, was a real threat. Estep described the implications of the doubling dose:

“This number is known technically as the doubling dose and has great legal significance under existing proof rules.”

Id. at 271.

* * *

“The more-probable-than-not test surely means simply that the trier of fact must find that the chances that defendant’s force caused the plaintiff’s injuries are at least slightly better than 50 percent; or, to put it the other way, that the chances that all other forces or causes together could have caused the injury are at least no greater than just short of 50 percent. Even if such an analysis is inapplicable to other types of cases, in those cases in which the only proof of causal connection is a statistical correlation between radiation dose and injury, the only just approach is to use a percentage formula. This is the case with all nonspecific injuries, including leukemia. Under existing rules the only fair place to draw the line is at 50 percent. These rules apply when the injury is already manifested as of the time of trial.”

Id. at 274.

The RR >2 argument was also percolating through the biostatistical and epidemiologic communities before the Cook and Iglarsh cases. For instance, Philip Enterline, a biostatistician at the University of Pittsburgh, specifically addressed the RR > 2 argument in a 1980 paper:

“The purpose of this paper is to illustrate how epidemiologic data can be used to make statements about causality in a particular case.”

* * *

“In summary, while in a given instance we cannot attribute an individual case of disease to a particular occupational exposure, we can, based on epidemiologic observation, make a statement as to the probability that a particular occupational exposure was the cause. Moreover, we can modify this probability by taking into consideration various aspects of a particular case.”

Philip Enterline, “Attributability in the Face of Uncertainty,” 78 (Supp.) Chest 377, 377, 378 (1980).

About the time of the Cook case, the scientific media discussed Enterline’s suggestion for using epidemiologic data to infer specific causation. See, e.g., Janet Raloff, “Compensating radiation victims,” 124 Science News 330 (1983). Dr. David Lilienfeld, son of the well-known epidemiologist Abraham Lilienfeld, along with a lawyer, further popularized the use of attributable risk, derived from a relevant RR to quantify the probability that an individual case is causally related to an exposure of interest. See David Lilienfeld & Bert Black, “The Epidemiologist in Court,” 123 Am. J. Epidem. 961, 963 (1986) (describing how a relative risk of 1.5 allows an inference of attributable risk of 33%, which means any individual case is less likely than not to causally related to the exposure).

In the meanwhile, the RR argument picked up support from other professional epidemiologists. In 1986, Dr. Otto Wong explained that for many common cancers, tied to multiple non-specific risk factors, probabilistic reasoning was the only way to make a specific attribution:

“In fact, all cancers have multiple causes. Furthermore, clinical features of cancer cases, caused by different risk factors, are seldom distinguishable from one another. Therefore, the only valid scientific way to address causation in a specific individual is through use of probability.”

Otto Wong, “Using Epidemiology to Determine Causation in Disease,” 3 Natural Resources & Env’t 20, 23 (1988). The attributable risk [AR], derived from the RR, was the only rational link that could support attribution in many cases:

“For AR [attributable risk] to be greater than 50% (more likely than not), RR has to be greater than 2. Thus, for any exposure with a RR of less than 2, the cancer cannot be attributed to that exposure according to the ‘more likely than not’ criterion. That is, that cancer is ‘more likely than not’ a background case.”

***

“The epidemiologic measure for probability of causation is attributable risk, which can be used to determine whether a particular cause in an individual case meets the ‘more likely than not’ criterion.”

Id. at 24.

In 1988, three Canadian professional epidemiologists described the acceptance of the use of epidemiologic data to attribute bladder cancer cases in the aluminum industry. Ben Armstrong, Claude Tremblay, and Gilles Theriault, “Compensating Bladder Cancer Victims Employed in Aluminum Reduction Plants,” 30 J. Occup. Med. 771 (1988).

The use of the RR > 2 argument was not a phenomenon limited to defense counsel or defense-friendly expert witnesses. In 1994, a significant textbook, edited by two occupational physicians who were then and now associated with plaintiffs’ causes, explicitly embraced the RR argument. Mark R. Cullen & Linda Rosenstock, “Principles and Practice of Occupational and Environmental Medicine,” chap. 1, in Linda Rosenstock & Marc Cullen, eds., Textbook of Clinical Occupational and Environmental Medicine 1 (Phila. 1994) [Cullen & Rosenstock].

The editors of this textbook were also the authors of the introductory chapter, which discussed the RR > 2 argument. The first editor-author, Mark R. Cullen, is now a Professor of Medicine in Stanford University’s School of Medicine. He is a member of the Institute of Medicine (IOM). Professor Cullen has been involved in several litigations, almost always on the plaintiffs’ side. In the welding fume litigation, Cullen worked on a plaintiff-sponsored study of Mississippi welders. Linda Rosenstock was the director for the National Institute for Occupational Safety and Health (NIOSH) from 1994 through 2000. Dr. Rosenstock left NIOSH to become the dean of the University of California, Los Angeles School of Public Health. She too is a member of the IOM. Here is how Cullen and Rosenstock treat the RR > 2 argument in their textbook:

“In most workers’ compensation and legal settings, one of the physician’s roles in OEM [occupational and environmental medicine] practice is to establish whether or not it is probable (greater, than 50% likelihood) that the patient’s injury or disease is occupationally or environmentally related. Physicians, whose standards of scientific certainty are usually considerably higher than those of the legal field (for example, often at the 95% level that an observed association did not occur by chance), need to appreciate that a disease may be deemed work related (i.e., in legal jargon, with medical certainty or more probable than not) even when there remains significant uncertainty (up to 50%) about this judgment.

Epidemiologic or population-based data may be used to provide evidence of both the causal relationship between an exposure and an outcome and the likelihood that the exposure is related to the outcome in an individual case. *** Although they are not fully conclusive, well-performed and interpreted epidemiologic studies can play an important role in determining the work-relatedness of disease in a person, using some of the additional guidelines below.”

***

“The concept of attributable fraction, known by many names, including attributable risk and etiologic fraction, has particular utility in determining the likelihood of importance of a hazardous exposure. Although these numbers refer to risks in groups, as shown in the following section, reasonable extrapolations from these numbers can often be made about risks in individuals.”

Cullen & Rosenstock at 13. Cullen & Rosenstock work through an easy example and discuss its implications:

“For example, if all the members of a population are exposed to a factor, and there is a RR of 5 of disease in relation to the factor, then the PAR = 80% (= (5 – 1)/5 X 100). If exposures and other population characteristics are similar in a second population, then it also can be assumed that this factor will account for 80% of cases of the disease. A short conceptual leap can be made to individual attribution: if an affected individual is similar (e.g., in age and gender) to those in the population and is similarly exposed (e.g., similar duration, intensity, and latency), then there is an 80% likelihood that the factor caused the disease in that individual.”

***

“By this reasoning of assuming that all in a population are exposed and the relative risk is greater that [sic] 2, then the PAR [population attributable risk] is greater than 50% (where PAR = (2 – 1)/2 X 100%). Accordingly, if an affected individual is similar to the population in a study that has demonstrated a RR ≥ 2, then the legal test (that there is a greater than 50% likelihood that the factor caused disease) can be met.”

***

“In cases in which the relative risks are stable (i.e., very narrow confidence intervals) and the patient is typical of the population studied, one can state these individual attributable risks with some assurance that they are valid estimates. When the studies are of limited power or give varying results, or if the patient’s exposure cannot be easily related to the study population., caution in using this method is appropriate.”

Cullen & Rosenstock at 13-14. Cullen and Rosenstock embraced probabilistic evidence because they understood that antipathy to probabilistic inference meant that there could be no rational basis for supporting recoveries in the face of known hazards that carried low relative risks (greater than 2). The “conceptual leap” these authors described is small compared to the unbridgeable analytical gaps that result from trying to infer specific causation from clinicians’ hunches.

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Eighth Circuit Holds That Increased Risk Is Not Cause

August 4th, 2012

The South Dakota legislature took it upon itself to specify the “risks” to be included in the informed consent required by state law for an abortion procedure:

(1) A statement in writing providing the following information:
* * *
(e) A description of all known medical risks of the procedure and statistically significant risk factors to which the pregnant woman would be subjected, including:
(i) Depression and related psychological distress;
(ii) Increased risk of suicide ideation and suicide;
* * *

S.D.C.L. § 34-23A-10.1(1)(e)(i)(ii). Planned Parenthood challenged the law on constitutional grounds, and the district court granted a preliminary injunction against the South Dakota statute, which a panel of the Eight Circuit affirmed, only to have that Circuit en banc reverse and remand the case for further proceedings. Planned Parenthood Minn. v. Rounds, 530 F.3d 724 (8th Cir. 2008) (en banc).

On remand, the parties filed cross-motions for summary judgment. The district court held that the so-called suicide advisory was unconstitutional. On the second appeal to the Eight Circuit, a divided panel affirmed the trial court’s holding on the suicide advisory. 653 F.3d 662 (8th Cir. 2011). The Circuit, however, again granted rehearing en banc, and reversed the summary judgment for Planned Parenthood on the advisory. Planned Parenthood Minnesota v. Rounds, Slip op. July 24, 2012 (en banc)[Slip op.].

In support of the injunction, Planned Parenthood argued that the state’s mandatory suicide advisory violated women’s abortion rights and physicians’ free speech rights. The en banc court rejected this argument, holding that the required advisory was “truthful, non-misleading information,” which did not unduly burden abortion rights, even if it might cause women to forgo abortion. See Planned Parenthood of Southeastern Pennsylvania v. Casey, 505 U.S. 833, 882-83 (1992).

Risk ≠ Cause

Planned Parenthood’s success in the trial court turned on its identification of risk (or increased risk) with cause, and its expert witness evidence that causation had not been accepted in the medical literature. In other words, Planned Parenthood argued that the advisory required disclosure of a conclusive causal “link” between abortion and suicide or suicidal ideation. See 650 F. Supp. 2d 972, 982 (D.S.D. 2009). The en banc court, on the second appeal, sought to save the statute by rejecting Planned Parenthood’s reading. The court parsed the statute to suggest that the term “increased risk” is more precise and limited than the umbrella term of “risk,” standing alone. Slip op. at 6. The statute does not define “increased risk,” which the en banc court noted had various meanings in medicine. Id. at 7.

Reviewing the medical literature, the en banc court held that the term “increased risk” does not refer to causation but to a much more modest finding of “a relatively higher probability of an adverse outcome in one group compared to other groups—that is, to ‘relative risk’.” Id. The en banc majority seemed to embroil itself in some considerable semantic confusion. One the hand, the majority, in a rhetorical rift proclaimed that:

“It would be nonsensical for those in the field to distinguish a relationship of ‘increased risk’ from one of causation if the term ‘risk’ itself was equivalent to causation.”

Id. at 9. The majority’s nonsensical labeling is, well, … nonsensical. There is a compelling difference in assessment of risk and causation. Risk is an ex ante concept, applied before the effect has occurred. Assessment or attribution of causation takes place after the effect. Of course, there is a sense of risk or “increased risk,” which is epistemologically more modest, but that hardly makes the more rigorous use of risk as an ex ante cause, nonsensical.

The majority, however, is not content to leave the matter alone. Elsewhere, the en banc court contradicts itself, and endorses a view that risk = causation. For instance, in citing to a civil action involving a claimed causal relationship between Bendectin and a birth defect, the Eighth Circuit reduces risk to cause. See Slip op. at 26 n. 9 (citing Brock v. Merrell Dow Pharms., Inc., 874 F.2d 307, 312 , modified on reh’g, 884 F.2d 166 (5th Cir. 1989)). The en banc court’s “explanatory” parenthetical explains the depths of its confusion:

“explaining that if studies establish, within an acceptable confidence interval, that those who use a pharmaceutical have a relative risk of greater than 1.0—that is, an increased risk—of an adverse outcome, those studies might be considered sufficient to support a jury verdict of liability on a failure-to-warn claim.”

This reading of Brock is wrong on two counts. First, the Fifth Circuit, in Brock, and consistently since, has required the relative risk greater than 1.0 to be statistically significant at the conventional significance probability, as well as other indicia of causality, such as the Bradford Hill factors. So Brock and its progeny did not confuse or conflate risk with cause, or dilute the meaning of cause such that it could be satisfied by a mere showing of an increased relative risk.

Second, Brock itself made a serious error in interpreting statistical significance and confidence intervals. The Bendectin studies at issue in Brock were not statistically significant, and the confidence intervals did not include a measure of no association (relative risk = one). Brock, however, in notoriously incorrect dicta claimed that the computation of confidence intervals took into account bias and confounding as well as sampling variability. Brock v. Merrill Dow Pharmaceuticals, Inc., 874 F.2d 307, 311-12 (5th Cir. 1989)(“Fortunately, we do not have to resolve any of the above questions [as to bias and confounding], since the studies presented to us incorporate the possibility of these factors by the use of a confidence interval.”)(emphasis in original). See, e.g., David H. Kaye, David E. Bernstein, and Jennifer L. Mnookin, The New Wigmore – A Treatise on Evidence: Expert Evidence § 12.6.4, at 546 (2d ed. 2011); Michael O. Finkelstein, Basic Concepts of Probability and Statistics in the Law 86-87 (2009)(criticizing the over-interpretation of confidence intervals by the Brock court); Schachtman, “Confidence in Intervals and Diffidence in the Courts” (Mar. 4, 2012).

The en banc majority’s discussion of the studies of abortion and suicidality make clear that the presence of bias and confounding in a study may prevent inference of causation, but they do not undermine the conclusion that the studies show an increased risk. A conclusion that the body of epidemiologic studies was inconclusive, and that it failed to “to disentangle confounding factors and establish relative risks of abortion compared to its alternatives,” did not, therefore, render the suicide advisory about risk or increased risk unsupported, untruthful, or misleading. Slip op. at 20. Indeed, the en banc court provided an example, outside the context of abortion, to illustrate its meaning. The en banc court’s use of the example of prolonged television viewing and “increased risk” of mortality suggests that the court took risk to mean any association, no matter how likely it was the result of bias or confounding. See id. at 10 n. 3 (citing Anders Grøntved, et al., “Television Viewing and Risk of Type 2 Diabetes, Cardiovascular Disease, and All-Cause Mortality, 305 J. Am. Med. Ass’n 2448 (2011). The en banc majority held that the advisory would be misleading only if Planned Parenthood could show that the available epidemiologic studies conclusively ruled out causation. Slip op. at 24-25.

The Suicide Advisory Has Little Content Because Risk Is Not Cause

The majority decision clarified that the mandatory disclosure does not require a physician to inform a patient that abortion causes suicide or suicidal thoughts. Slip op. at 25. The en banc court took solace in its realization that physicians’ reviewing the available studies could provide a disclosure that captures the difference between risk, relative risk, and causation. In other words, physicians are free to tell patients that this thing called increased risk is not concerning because the studies are highly confounded, and they do not show causation. Id. at 25-26. Indeed, it would be hard to imagine an ethical physician telling patients anything else.

Dissent

Four of the Eight Circuit judges dissented, pointing to evidence that the South Dakota legislators intended to mandate a disclosure about causality. Slip op. at 29. Putting aside whether the truthfulness of the suicide advisory can be saved by reverting to a more modest interpretation of risk or of increased risk, the dissenters appear to have the better argument that the advisory is misleading. The majority, however, by driving its wedge between causation and increased risk have allowed physicians to explain that the advisory has little or no meaning.

NOCEBO

The nocebo effect is the dark side of the placebo effect. As pointed out recently in the Journal of the American Medical Association, nocebos can induce harmful outcomes because of the expectation of injury from the “psychosocial context or therapeutic environment” affecting patients’ perception of their health. Luana Colloca & Damien Finniss, “Nocebo Effects, Patient-Clinician Communication, and Therapeutic Outcomes,” 307 J. Am. Med. Ass’n 567, 567 (2012). It is fairly well accepted that clinicians can inadvertently prejudice health outcomes by how they frame outcome information to patients. Colloca and Finniss note that the negative expectations created by nocebo communication can take place in the process of obtaining informed consent.

Unfortunately, there is no discussion of nocebo effects in the Eight Circuit’s decision. Planned Parenthood might well consider the role the nocebo effect has on the risk-benefit of an informed consent disclosure about a risk that really is not a risk, or is not a risk in the sense that it is a factor that will result in the putative cause, but rather only something that is under study and which cannot be separated from many confounding factors. Surely, physicians in South Dakota will figure out how to give truthful, non-misleading disclosures that incorporate the mandatory suicide advisory, as well as the scientific evidence.

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Another Confounder in Lung Cancer Occupational Epidemiology — Diesel Engine Fumes

June 13th, 2012

Researchers obviously need to be aware of, and control for, potential and known confounders. In the context of investigating the etiologies of lung cancer, there is a long list of potential confounding exposures, often ignored in peer-reviewed papers, which focus on one particular outcome of interest. Just last week, I wrote to emphasize the need to account for potential and known confounding agents, and how this need was particularly strong in studies of weak alleged carcinogens such as crystalline silica. See Sorting Out Confounded Research – Required by Rule 702. Yesterday, the World Health Organization (WHO) added another “known” confounder for lung cancer epidemiology: diesel fume.

According to the International Agency for Research on Cancer (IARC), a division of the WHO, a working group of international experts voted to reclassify diesel engine exhaust as a “Group I” carcinogen. IARC: Diesel engines exhaust carcinogenic (2012). This classification means, in IARC parlance, that ” there is sufficient evidence of carcinogenicity in humans. Exceptionally, an agent may be placed in this category when evidence of carcinogenicity in humans is less than sufficient but there is sufficient evidence of carcinogenicity in experimental animals and strong evidence in exposed humans that the agent acts through a relevant mechanism of carcinogenicity.” The Group was headed up by Dr. Christopher Portier, who is the director of the National Center for Environmental Health and the Agency for Toxic Substances and Disease Registry at the Centers for Disease Control and Prevention. Id.

The reclassification removes diesel exhaust from its previous categorization as a Group 2A carcinogen, which is interpreted “as probably carcinogenic to humans.” Diesel exhaust has been on a high-priority list for re-evaluation since 1998, as result of epidemiologic research from many countries. The Working Group specifically found that there was sufficient evidence to conclude that diesel exhaust is a cause of lung cancer in humans, and limited evidence to support an association with bladder cancer. The Group rejected any change in classification of gasoline engine exhaust from its current IARC rating as “possibly carcinogenic to humans. (Group 2B).”

Unlike other IARC Working Group decisions (such as crystalline silica), which were weakened by close votes and significant dissents, the diesel Group’s conclusion was unanimous. The diesel Group appeared to be impressed by two recent studies of lung cancer in underground miners, released in March 2012. One study was in a large cohort, conducted by NIOSH, and the other was a nested case-control study, conducted by the National Cancer Institute (NCI). See Debra T. Silverman, Claudine M. Samanic, Jay H. Lubin, Aaron E. Blair, Patricia A. Stewart , Roel Vermeulen, Joseph B. Coble, Nathaniel Rothman, Patricia L. Schleiff , William D. Travis, Regina G. Ziegler, Sholom Wacholder, Michael D. Attfield, “The Diesel Exhaust in Miners Study: A Nested Case-Control Study of Lung Cancer and Diesel Exhaust,” J. Nat’l Cancer Instit. (2012)(in press and open access); and Michael D. Attfield, Patricia L. Schleiff, Jay H. Lubin, Aaron Blair, Patricia A. Stewart, Roel Vermeulen, Joseph B. Coble, and Debra T. Silverman, “The Diesel Exhaust in Miners Study: A Cohort Mortality Study With Emphasis on Lung Cancer,” J. Nat’l Cancer Instit. (2012)(in press).

According to a story in the New York Times, the IARC Working Group described diesel engine exhaust as “more carcinogenic than secondhand cigarette smoke.” Donald McNeil, “W.H.O. Declares Diesel Fumes Cause Lung Cancer,” N.Y. Times (June 12, 2012). The Times also quoted Dr. Debra Silverman, NCI chief of environmental epidemiology, at length. Dr. Silverman, who was the lead author of the nested case-control study cited by the IARC Press Release, noted that her large study showed that long-term heavy exposure to diesel fumes increased lung cancer risk seven fold. Dr. Silverman described this risk as much greater than that thought to be created by passive smoking, but much smaller than smoking two packs of cigarettes a day. She stated that “totally” supported the IARC reclassification, and that she believed that governmental agencies would use the IARC analysis as the basis for changing the regulatory classification of diesel exhaust.

Silverman’s nested case-control study appears to have been based upon careful diesel exhaust exposure information, as well as smoking histories. The study also searched and analyzed for other potential confounders, which might be expected to be involved in underground mining:

“Other potential confounders [ie, duration of cigar smoking; frequency of pipe smoking; environmental tobacco smoke; family history of lung cancer in a first-degree relative; education; body mass index based on usual adult weight and height; leisure time physical activity; diet; estimated cumulative exposure to radon, asbestos, silica, polycyclic aromatic hydrocarbons (PAHs) from non-diesel sources, and respirable dust in the study facility based on air measurement and other data (14)] were evaluated but not included in the final models because they had little or no impact on odds ratios (ie, inclusion of these factors in the final models changed point estimates for diesel exposure by ≤ 10%).”

Silverman, et al., at 4. The absence of an association between lung cancer and silica exposure is noteworthy in a such a large study of underground miners.

Posted in Causation, Risk and Risk Factor, Rule 702, Scientific Evidence, Silica | Comments Off on Another Confounder in Lung Cancer Occupational Epidemiology — Diesel Engine Fumes

Exposure, Epidemiology, and External Validity under Rule 702

May 14th, 2012

Sometimes legal counsel take positions in court determined solely by the expediency of what expert witnesses are available, and what opinions are held by those witnesses.

Back in the early days of the asbestos litigation in Philadelphia, a hotbed of early asbestos litigation, plaintiffs and defendants each identified a pool of available expert witnesses on lung diseases. Each side found witnesses who held views on important issues, such as whether asbestos caused lung cancer, with or without pre-existing asbestosis, whether all types of asbestos caused mesothelioma, whether asbestos caused gastrointestinal cancers, and whether “each and every exposure was a substantial factor” in producing an asbestos-related disease. Some expert witnesses adopted opinions as a matter of convenience and malleability, but most witnesses expressed sincerely held opinions. Either way, each expert witness active in the asbestos litigation, came to be seen as a partisan of one side. Because of the volume of cases, there was the opportunity to be engaged in a large number of cases, and to earn sizable fees as an expert witness. Both side’s expert witnesses struggled to avoid being labeled hired guns.

A few expert witnesses, eager to avoid being locked in as either a “plaintiff’s” or a “defendant’s” expert witness, with perhaps some damage to their professional reputations, balanced their views in a way to avoid being classified as working exclusively for one side or the other. The late Paul Epstein, MD, adopted this strategy to great effect. Dr. Epstein had excellent credentials, and he was an excellent physician. He was on the faculty at the University of Pennsylvania, and he was a leader in the American College of Physicians, where he was the deputy editor of the Annals of Internal Medicine. Dr. Epstein exemplified gravitas and learning. He was not, however, above adopting views in such a way as to balance out his commitments to both the plaintiffs’ and defense bars. By doing so, Dr. Epstein made himself invaluable to both sides, and he made aggressive cross-examination difficult, if not impossible, when he testified. I suspect his positions had this strategic goal.

In his first testimonies, in the late 1970’s and early 1980’s, Dr. Epstein expressed the view that asbestos exposure caused parietal pleural plaques, but these plaques rarely interfered with respiration. Pleural plaques did not cause impairment or disability, and thus they were not an “injury.” Dr. Epstein’s views were very helpful in obtaining defense verdicts in cases of disputed pleural thickening or plaques, and they led to his being much sought after by defense counsel for their independent medical examinations. Dr. Epstein also strongly believed, based upon the epidemiologic evidence, that asbestos did not cause gastrointestinal or laryngeal cancer.

Dr. Epstein was wary of being labeled a “defendants’ expert” in the asbestos litigation, especially given the social opprobrium that attached to working for the “asbestos industry.” And so, by the mid-1980’s, Dr. Epstein surprised the defense bar by showing up in a plaintiff’s lung cancer case, without underlying asbestosis. Dr. Epstein took the position that if the plaintiff worked around asbestos, and later developed lung cancer, then asbestos caused his lung cancer, and “each and every exposure to asbestos” contributed substantially to the outcome. Risk was causation; ipse dixit. Dr. Epstein recited the Selikoff multiplicative “synergy” theory, with relative risks of 5 (for non-smoking asbestos workers), 10 (for smoking non-asbestos workers), and 50 (for smoking asbestos-exposed workers). Every worker was described with the same set of risk ratios. Remarkably, and unscientifically, Dr. Epstein gave the same risk figures in every plaintiff’s lung cancer case, regardless of the duration or level of exposure. In mesothelioma cases, Dr. Epstein took the unscientific position that all fiber types (chrysotile, amosite, crocidolite, and anthopyllite) contributed to any patient’s mesothelioma.

Dr. Epstein’s views made him off limits to plaintiffs in non-malignancy cases, and off limits to defendants in lung cancer and mesothelioma cases.

Because of his careful alignment with both plaintiffs’ and defense bars, Dr. Epstein’s views were never forcefully challenged. Of course, the Pennsylvania case law in the 1980’s and 1990’s was not particularly favorable to challenges to the validity of opinions about causation, but even as Rule 702 evolved in federal court, both plaintiffs’ and defense counsel were unable to antagonize Dr. Epstein. The inanity of “each and every exposure” was not seriously hurtful in the early asbestos litigation, when the defendants were almost all manufacturers of asbestos-containing insulation, and if a manufacturer had supplied insulation to a worksite, then the proportion of asbestos exposure for that manufacturer would likely have been “substantial.”

Today, the nature of the asbestos litigation has changed, but it when we examine Pennsylvania law and procedure, it is not surprising to see that Dr. Epstein’s views have had a long-lasting effect. Claimants with only pleural plaques have been relegated to an “inactive” docket. Plaintiffs’ expert witnesses still opine that each and every exposure was substantial, without any basis in evidence, and they still recite the same 5x, 10x, and 50x risk ratios, based upon Selikoff’s insulator studies, even though the Philadelphia Court of Common Pleas probably has not seen more than a handful of insulators’ cases in the last decade. Dozens of epidemiologic studies have shown that asbestos exposures of bystander trades, chrysotile factory workers, and other non-insulator, occupational exposures have lower risks of asbestos-related diseases.

The failure to challenge the Selikoff risk ratios is regrettable, especially considering that it was based upon politics, personalities, and not on scientific or legal evidentiary grounds.

As Irving Selikoff observed about his frequently cited statistics:

“These particular figures apply to the particular groups of asbestos workers in this study. The net synergistic effect would not have been the same if their smoking habits had been different; and it probably would have been different if their lapsed time from first exposure to asbestos dust had been different or if the amount of asbestos dust they had inhaled had been different.”

E. Cuyler Hammond, Irving Selikoff, and Herbert Seidman, “Asbestos Exposure, Cigarette Smoking and Death Rates,” 330 Ann. N.Y. Acad. Sci. 473, 487 (1979).

The Selikoff risk figures were unreliable even for insulators, given that the so-called non-smokers were admittedly occasional smokers, and the low relative risk for smokers in the general population came from an historical cohort of relatively healthy American Cancer Society volunteers. The updated risk figures for smokers in the general population placed their lung cancer risk closer to, and above, 20-fold, which raised doubts about Selikoff’s neat multiplicative theory.

The more important lesson though is that the Philadelphia courts, with acquiescence from most defense counsel, never challenged the use of Selikoff’s 5x, 10x, and 50x risk ratios to describe asbestos effects and smoking interactions. Dr. Epstein made such a challenge impolitic and imprudent. In Philadelphia, the Selikoff risk ratios gained a measure of respectability that they never deserved in science, or in the courtroom.

*****

Under Rule 702, the law has evolved to require reasonable exposure assessments of plaintiffs’ exposures, and supporting epidemiology that shows relevant increase risks at the level and the latency actual experienced by each plaintiff. This criterion does not come from a “sufficiency” review as some have suggested; it is clearly a requirement of external validity of the epidemiologic studies relied upon by expert witnesses.

The following cases excluded or limited expert witness opinion testimony with respect to epidemiological studies that the court concluded were not sufficiently similar to the facts of the case to warrant the admission of an expert’s opinion based on their results:

SUPREME COURT

General Electric Co. v. Joiner, 522 U.S. 136 (1997)(questioning the external validity of a study of massive injected doses of PCBs in baby mice, with an outcome unrelated to the cancer claimed by paintiff)

1st Circuit

Sutera v. Perrier Group of America Inc., 986 F. Supp. 655 (D. Mass. 1997)(occupational epidemiology of benzene exposure and benzene does not inform health effects from vanishingly low exposure to benzene in bottled water)

Whiting v. Boston Edison Co., 891 F. Supp. 12 (D. Mass. 1995) (excluding plaintiff’s expert witnesses; holding that epidemiology of Japanese atom bomb victims, and of patients treated with X-rays for spinal arthritis, and acute lymphocytic leukemia (ALL), was an invalid extrapolative model for plaintiff’s much lower exposure)

2d Circuit

Wills v. Amerada Hess Corp., 2002 WL 140542 (S.D. N.Y. 2002)(excluding plaintiff’s expert witness who attempted to avoid exposure assessment by arguing no threshold)(‘‘[E]ven though benzene and PAHs have been shown to cause some types of cancer, it is too difficult a leap to allow testimony that says any amount of exposure to these toxins caused squamous cell carcinoma of the head and neck in the decedent… . It is not grounded in reliable scientific methods, but only Dr. Bidanset’s presumptions. It fails all of the Daubert factors.’’), aff’d, 379 F.3d 32 (2d Cir. 2004)(Sotomayor, J.), cert. denied, 126 S.Ct. 355 (2005)

Amorgianos v. National RR Passenger Corp., 137 F. Supp. 2d 147 (E.D. N.Y. 2001), aff’d, 303 F.3d 256 (2d Cir. 2002);

Mancuso v. Consolidated Edison Co., 967 F.Supp. 1437, 1444 (S.D.N.Y. 1997)

3d Circuit

Magistrini v. One Hour Martinizing Dry Cleaning, 180 F. Supp. 2d 584(D.N.J. 2002), aff’d, 68 Fed. Appx. 356 (3d Cir. 2003);

In re W.R. Grace & Co., 355 B.R. 462 (Bankr. D. Del. 2006)

4th Circuit

White v. Dow Chemical Co., 321 F.Appx. 266, 273 (4th Cir. 2009)

Newman v. Motorola, Inc., 78 Fed. Appx. 292 (4th Cir. 2003)

Cavallo v. Star Enterprise, 892 F. Supp. 756, 764, 773 (E.D. Va. 1995) (excluding opinion of expert witness who failed to identify plaintiff ’s exposure levels to jet fuel, and failed to characterize the relevant dose-response relationship), aff’d in relevant part, 100 F.3d 1150, 1159 (4th Cir. 1996)

5th Circuit

LeBlanc v. Chevron USA, Inc., 396 Fed. Appx. 94 (5th Cir. 2010)

Knight v. Kirby Inland Marine Inc.,482 F.3d 347 (5th Cir. 2007);

Cotroneo v. Shaw Environmental & Infrastructure, Inc., 2007 WL 3145791 (S.D. Tex. 2007)

Castellow v. Chevron USA, 97 F. Supp. 2d 780, 796 (S.D. Tex. 2000) (‘‘[T]here is no reliable evidence before this court on the amount of benzene, from gasoline or any other source, to which Mr. Castellow was exposed.’’)

Moore v. Ashland Chemical Inc., 151 F.3d 269, 278 (5th Cir. 1998) (en banc);

Allen v. Pennsylvania Engineering Corp., 102 F.3d 194, 198-99 (5th Cir. 1996)

6th Circuit

Pluck v. BP Oil Pipeline Co., 640 F.3d 671 (6th Cir. 2011)(affirming district court’s exclusion of Dr. James Dahlgren; noting that he lacked reliable data to support his conclusion of heavy benzene exposure; holding that without quantifiable exposure data, the Dahlgren’s causation opinion was mere “speculation and conjecture”)

Nelson v. Tennessee Gas Pipeline Co., 243 F.3d 244, 252 (6th Cir. 2001)(noting ‘‘with respect to the question of dose, plaintiffs cannot dispute that [their expert] made no attempt to determine what amount of PCB exposure the Lobelvill subjects had received and simply assumed that it was sufficient to make them ill.’’)

Conde v. Velsicol Chemical Corp., 24 F.3d, 809, 810 (6th Cir. 1994)(excluding expert testimony that chlordane,although an acknowledged carcinogen that was applied in a manner that violated federal criminal law, caused plaintiff’s injuries when expert witness’s opinion was based upon high-dose animal studies as opposed to the low-exposure levels experienced by the plaintiffs)

7th Circuit

Cunningham v. Masterwear Corp., 2007 WL 1164832 (S.D. Ind., Apr. 19, 2007)(excluding plaintiff’s expert witnesses who opined without valid evidence of plaintiffs’ exposure to perchloroethylene (PCE)), aff’d, 569 F.3d 673 (7th Cir. 2009) (Posner, J.)(affirming exclusion of expert witness and grant of summary judgment)

Wintz v. Northrop Corp., 110 F.3d 508, 513 (7th Cir. 1997)

Schmaltz v. Norfolk & Western Ry. Co., 878 F. Supp. 1119, 1122 (N.D. Ill. 1995) (excluding expert witness opinion testimony that was offered in ignorance of plaintiff’s level of exposure to herbicide)

8th Circuit

Junk v. Terminix Intern. Co. Ltd. Partnership, 594 F. Supp. 2d 1062, 1073 (S.D. Iowa 2008).

Medalen v. Tiger Drylac U.S.A., Inc., 269 F. Supp. 2d 1118, 1132 (D. Minn. 2003)

National Bank of Commerce v. Associated Milk Producers, Inc., 22 F. Supp. 2d 942 (E.D. Ark. 1998)(excluding causation opinion that lacked exposure level data), aff’d, 191 F.3d 858 (8th Cir. 1999)

Bednar v. Bassett Furniture Mfg. Co., Inc.,147 F.3d 737, 740 (8th Cir. 1998) (“The Bednars had to make a threshold showing that the dresser exposed the baby to levels of gaseous formaldehyde known to cause the type of injuries she suffered”)

Wright v. Willamette Industries, Inc., 91 F.3d 1105, 1106 (8th Cir. 1996) (affirming exclusion; requiring evidence of actual exposure to levels of substance known to cause claimed injury)

National Bank of Commerce v. Dow Chemical Co., 965 F. Supp. 1490, 1502 (E.D. Ark., 1996)

9th Circuit

In re Bextra & Celebrex Marketing Sales Practices & Product Liab. Litig., 524 F. Supp. 2d 1166, 1180 (N.D. Cal. 2007)(granting Rule 702 exclusion of expert witness’s opinions with respect to low dose, but admitting opinions with respect to high dose Bextra and Celebrex)

Henricksen v. ConocoPhillips Co., 605 F. Supp. 2d 1142, 1157 (E.D. Wash. 2009)

Valentine v. Pioneer Chlor Alkali Co., Inc., 921 F. Supp. 666, 676 (D. Nev. 1996)

Abuan v. General Electric Co., 329 F.3d 329, 333 (9th Cir. 1993) (Guam)

10th Circuit

Maddy v. Vulcan Materials Co., 737 F.Supp. 1528, 1533 (D.Kan. 1990) (noting the lack of any scientific evidence of the level or duration of plaintiff’s exposure to specific toxins).

Estate of Mitchell v. Gencorp, Inc., 968 F. Supp. 592, 600 (D. Kan. 1997), aff’d,165 F.3d 778, 781 (10th Cir. 1999)

11th Circuit

Brooks v. Ingram Barge Co., 2008 WL 5070243 *5 (N.D. Miss. 2008)) (noting that plaintiff’s expert witness “acknowledges that it is unclear how much exhaust Brooks was exposed to, how much exhaust it takes to make developing cancer a probability, or how much other factors played a role in Brooks developing cancer.”)

Cuevas v. E.I. DuPont de Nemours & Co., 956 F. Supp. 1306, 1312 (S.D. Miss. 1997)

Chikovsky v. Ortho Pharmaceutical Corp., 832 F. Supp. 341, 345–46 (S.D. Fla. 1993)(excluding opinion of an expert witness who did not know plaintiff’s actual exposure or dose of Retin-A, and the level of absorbed Retin-A that is unsafe for gestating women)

Savage v. Union Pacific RR, 67 F. Supp. 2d 1021 (E.D. Ark. 1999)

STATE CASES

California

Jones v. Ortho Pharmaceutical Corp., 163 Cal. App. 3d 396, 404, 209 Cal. Rptr. 456, 461 (1985)(duration of use in relied upon studies not relevant to plaintiffs’ use)

Michigan

Nelson v. American Sterilizer Co., 566 N.W. 2d 671 (Mich. Ct. App. 1997)(affirming exclusion of expert witness who opined, based upon high-dose animal studies, that plaintiff’s liver disease was caused by low-level exposure to chemicals used in sterilizing medical equipment)

Mississippi

Watts v. Radiator Specialty Co., 2008 WL 2372694 *3 (Miss.2008);

Ohio

Valentine v. PPG Indus., Inc., 158 Ohio App. 3d 615, 821 N.E.2d 580 (2004)

Oklahoma

Christian v. Gray, 2003 Okla. 10, 65 P.3d 591, 601 (2003);

Holstine v. Texasco, 2001 WL 605137 (Okla. Dist. Ct. 2001)(excluding expert witness testimony that failed to assess plaintiff’s short-term, low-level benzene exposure as fitting the epidemiology relied upon to link plaintiff’s claimed injury with his exposure)

Texas

Merrell Dow Pharm., Inc. v. Havner, 953 S.W.2d 706, 720 (Tex. 1997) (“To raise a fact issue on causation and thus to survive legal sufficiency review, a claimant must do more than simply introduce into evidence epidemiological studies that show a substantially elevated risk. A claimant must show that he or she is similar to those in the studies.”).

Merck & Co. v. Garza, 347 S.W.3d 256 (Tex. 2011)

Frias v. Atlantic Richfield Co., 104 S.W.3d 925, 929 (Tex. App. Houston 2003)(holding that plaintiffs’ expert witness’s testimony was inadmissible for relying upon epidemiologic studies that involved much higher levels of exposure than experienced by plaintiff)

Daniels v. Lyondell-Citgo Refining Co, 99 S.W.3d 722 (Tex. App. 2003) (claim that benzene exposure caused plaintiff’s lung cancer had to be supported with studies of comparable exposure, and latency, as that observed and reported in the studies)

Austin v. Kerr-McGee Refining Corp., 25 S.W.3d 280, 292 (Tex. App. Texarkana 2000)

Posted in Causation, Conflicts of Interest, Risk and Risk Factor, Rule 702, Scientific Evidence | Comments Off on Exposure, Epidemiology, and External Validity under Rule 702

Relative of Risk > Two in the Courts – Updated

March 3rd, 2012

See Reference Manual on Scientific Evidence on Relative Risk Greater Than Two For Specific Causation Inference (April 25, 2015), for the updated the case law on the issue of using relative and attributable risks to satisfy plaintiff’s burden of showing, more likely than not, that an exposure or condition caused a plaintiff’s disease or injury.

Posted in Causation, Risk and Risk Factor, Rule 702, Scientific Evidence | 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.

*******************

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)

***************************

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 (5^th 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.

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