Lipitor MDL Cuts the Fat Out of Specific Causation

Ms. Juanita Hempstead was diagnosed with hyperlipidemia in March 1998. Over a year later, in June 1999, with her blood lipids still elevated, her primary care physician prescribed 20 milligrams of atorvastatin per day. Ms. Hempstead did not start taking the statin regularly until July 2000. In September 2002, her lipids were under control, her blood glucose was abnormally high, and she had gained 13 pounds since she was first prescribed a statin medication. Hempstead v. Pfizer, Inc., 2:14–cv–1879, MDL No. 2:14–mn–02502–RMG, 2015 WL 9165589, at *2-3 (D.S.C. Dec. 11, 2015) (C.M.O. No. 55 in In re Lipitor Marketing, Sales Practices and Products Liability Litigation) [cited as Hempstead]. In the fall of 2003, Hempstead experienced abdominal pain, and she stopped taking the statin for a few weeks, presumably because of a concern over potential liver toxicity. Her cessation of the statin led to an increase in her blood fat, but her blood sugar remained elevated, although not in the range that would have been diagnostic of diabetes. In May 2004, about five years after starting on statin medication, having gained 15 pounds since 1999, Ms. Hempstead was diagnosed with type II diabetes mellitus. Id.

Living in a litigious society, and being bombarded with messages from the litigation industry, Ms. Hempstead sued the manufacturer of atorvastatin, Pfizer, Inc. In support of her litigation claim, Hempstead’s lawyers enlisted the support of Elizabeth Murphy, M.D., D.Phil., a Professor of Clinical Medicine, and Chief of Endocrinology and Metabolism at San Francisco General Hospital. Id. at *6. Dr. Murphy received her doctorate in biochemistry from Oxford University, and her medical degree from the Harvard Medical School. Despite her graduations from elite educational institutions, Dr. Murphy never learned the distinction between ex ante risk and assignment of causality in an individual patient.

Dr. Murphy claimed that atorvastatin causes diabetes, and that the medication caused Ms. Hempstead’s diabetes in 2004. Murphy pointed to a five-part test for her assessment of specific causation:

(1) reports or reliable studies of diabetes in patients taking atorvastatin;

(2) causation is biological plausible;

(3) diabetes appeared in the patient after starting atorvastatin;

(4) the existence of other possible causes of the patient’s diabetes; and

(5) whether the newly diagnosed diabetes was likely caused by the atorvastatin.

Id. In response to this proffered testimony, the defendant, Pfizer, Inc., challenged the admissibility of Dr. Murphy’s opinion under Federal Rule of Evidence 702.

The trial court, in reviewing Pfizer’s challenge, saw that Murphy’s opinion essentially was determined by (1), (2), and (3), above. In other words, once Murphy had become convinced of general causation, she was willing to causally attribute diabetes to atorvastatin in every patient who developed diabetes after starting to take the medication. Id. at *6-7.

Dr. Murphy relied upon some epidemiologic studies that suggested a relative risk of diabetes to be about 1.5 in patients who had taken atorvastatin. Id. at *5, *8. Unfortunately, the trial court, as is all too common among judges writing Rule 702 opinions, failed to provide citations to the materials upon which plaintiff’s expert witness relied. A safe bet, however, is that those studies, if they had any internal and external validity at all, involved multivariate analyses to analyze risk ratios for diabetes at time t1, in patients at time who had no diabetes before starting use of atorvastatin at time t0, compared with patients who did not have diabetes at t0 but never took the statin. If so, then Dr. Murphy’s use of a temporal relationship between starting atorvastatin and developing diabetes is quite irrelevant because the relative risk (1.5) relied upon is generated in studies in which the temporality is present. Ms. Hempstead’s development of diabetes five years after starting atorvastatin does not make her part of a group with a relative risk any higher than the risk ratio of 1.5, cited by Dr. Murphy. Similarly, the absence or presence of putative risk factors other than the accused statin is irrelevant because the risk ratio of 1.5 was mostly likely arrived at in studies that controlled or adjusted for the other risk factors in the epidemiologic study by a multivariate analysis. Id. at *5 & n. 8.

Dr. Murphy acknowledged that there are known risk factors for diabetes, and that plaintiff Ms. Hempstead had a few. Plaintiff was 55 years old at the time of diagnosis, and advancing age is a risk factor. Plaintiff’s body mass index (BMI) was elevated and it had increased over the five years since beginning to take atorvastatin. Even though not obese, Ms. Hempstead’s BMI was sufficiently high to confer a five-fold increase in risk for diabetes. Id. at *9. Plaintiff also had hypertension and metabolic syndrome, both of which are risk factors (with the latter adding to the level of risk of the former). Id. at *10. Perhaps hoping to avoid the intractable problem of identifying which risk factors were actually at work in Ms. Hempstead to produce her diabetes, Dr. Murphy claimed that all risk factors were causes of plaintiff’s diabetes. Her analysis was thus not so much a differential etiology as a non-differential, non-discriminating assertion that any and all risk factors were probably involved in producing the individual case. Not surprisingly, Dr. Murphy, when pressed, could not identify any professional organizations or peer-reviewed publications that employed such a methodology of attribution. Id. at *6. Dr. Murphy had never used such a method of attribution in her clinical practice; instead she attempted to justify and explain her methodology by adverting to its widespread use by expert witnesses in litigation. Id.

Relative Risk and the Inference of Specific Causation

The main thrust of the Dr. Murphy’s and the plaintiff’s specific causation claim seems to have been based upon a simple, simplistic identification of ex ante risk with causation. The MDL court recognized, however, that in science and in law, risk is not the same as causation.[1]

The existence of general causation, with elevated relative risks not likely the result of bias, chance, or confounding, does not necessarily support the inference that every person exposed to the substance or drug and who develops the outcome of interest, had his or her outcome caused by the exposure.

The law requires each plaintiff to show that his or her alleged injury, the outcome in the relied upon epidemiologic studies, was actually caused by the alleged exposure under a preponderance of the evidence. Id. at *4 (citing Guinn v. AstraZeneca Pharm. LP, 602 F.3d 1245, 1249 n. 1 (11th Cir.2010))

The disconnect between risk and causation is especially strong when the nature of the causation involved results from the modification of the incidence rate of a disease as a function of exposure. Although the MDL court did not explicitly note the importance of a base rate, which gives rise to an “expected value” or “expected outcome” in an epidemiologic sample, the court’s insistence upon a relative risk greater than two, from studies of sample groups that are sufficiently similar to the plaintiff, implicitly affirms the principle. The MDL court did, however, call out Dr. Murphy’s reasoning that specific causation exists for every drug-exposed patient, in the face of studies that show general causation with associations of the magnitude less than risk ratios of two, was logically flawed. Id. at *8 (citing Guinn v. AstraZeneca Pharm. LP, 602 F.3d 1245, 1255 (11th Cir. 2010) (“The fact that exposure to [a substance] may be a risk factor for [a disease] does not make it an actual cause simply because [the disease] developed.”).

The MDL court acknowledged the obvious, that some causal relationships may be based upon risk ratios of two or less (but greater than 1.0). Id. at *4. A risk ratio greater than 1.0, but not greater than two, can result only when some of the cases with the outcome of interest, here diabetes, would have occurred anyway in the population that has been sampled. And with increased risk ratios at two or less, a majority of the study sample would have developed the outcome even in the absence of the exposure of interest. With this in mind, the MDL court asked how plaintiff could show specific causation, even assuming that general causation were established with the use of epidemiologic methods.

The court in Hempstead reasoned that if the risk ratio were greater than 2.0, a majority of the exposed sample would have developed the outcome of interest because of the exposure being studied. Id. at *5. If the sampled population has had the same level of exposure as the plaintiff, then a case-specific inference of specific causation is supported.[2] Of course, this inferential strategy presupposes that general causation has been established, by ruling out bias, confounding, and chance, with high-quality, statistically significant findings of risk ratios in excess of 2.0. Id. at *5.

To be sure, there are some statisticians, such as Sander Greenland, who have criticized this use of a sample metric to assess the probability of individual causation, in part because the sample metric is an average level of risk, based upon the whole sample. Greenland is fond of speculating that the risk may not be stochastically distributed, but as the Supreme Court has recently acknowledged, there are times when the use of an average is appropriate to describe individuals within a sampled population. Tyson Foods, Inc. v. Bouaphakeo, No. 14-1146, 2016 WL 1092414 (U.S. S. Ct. Mar. 22, 2016).

The Whole Tsumish

Dr. Murphy, recognizing that there are other known and unknown causes and risk factors for diabetes, made a virtue of foolish consistency by opining that all risk factors present in Ms. Hempstead were involved in producing her diabetes. Dr. Murphy did not, and could not, explain, however, how or why she believed that every risk factor (age, BMI, hypertension, recent weight gain, metabolic syndrome, etc.), rather than some subset of factors, or some idiopathic factors, were involved in producing the specific plaintiff’s disease. The MDL court concluded that Dr. Murphy’s opinion was an ipse dixit of the sort that qualified her opinion for exclusion from trial. Id. at *10.

Biological Fingerprints

Plaintiffs posited typical arguments about “fingerprints” or biological markers that would support inferences of specific causation in the absence of high relative risks, but as is often the case with such arguments, they had no factual foundation for their claims that atorvastatin causes diabetes. Neither Dr. Murphy nor anyone else had ever identified a biological marker that allowed drug-exposed patients with diabetes to be identified as having had their diabetes actually caused by the drug of interest, as opposed to other known or unknown causes.

With Dr. Murphy’s testimony failing to satisfy common sense and Rule 702, plaintiff relied upon cases in which circumstances permitted inferences of specific causation from temporal relationships between exposure and outcome. In one such case, the plaintiff developed throat irritation from very high levels of airborne industrial talc exposure, which abated upon cessation of exposure, and returned with renewed exposure. Given that general causation was conceded, and natural experimental nature of challenge, dechallenge, and rechallenge, the Fourth Circuit in this instance held that the temporal relationship of an acute insult and onset was an adequate basis for expert witness opinion testimony on specific causation. Id. at *11. (citing Westberry v. Gislaved Gummi AB, 178 F.3d 257, 265 (4th Cir.1999) (“depending on the circumstances, a temporal relationship between exposure to a substance and the onset of a disease or a worsening of symptoms can provide compelling evidence of causation”); Cavallo v. Star Enter., 892 F. Supp. 756, 774 (E.D. Va.1995) (discussing unique, acute onset of symptoms caused by chemicals). In the Hempstead case, however, the very nature of the causal relationship claimed did not involve an acute reaction. The claimed injury, diabetes, emerged five years after statin use commenced, and the epidemiologic studies relied upon were all based upon this chronic use, with a non-acute, latent outcome. The trial judge thus would not credit the mere temporality between drug use and new onset of diabetes as probative of anything.


[1] Id. at *8, citing Guinn v. AstraZeneca Pharm. LP, 602 F.3d 1245, 1255 (11th Cir.2010) (“The fact that exposure to [a substance] may be a risk factor for [a disease] does not make it an actual cause simply because [the disease] developed.”); id. at *11, citing McClain v. Metabolife Int’l, Inc., 401 F.3d 1233, 1243 (11th Cir.2005) (“[S]imply because a person takes drugs and then suffers an injury does not show causation. Drawing such a conclusion from temporal relationships leads to the blunder of the post hoc ergo propter hoc fallacy.”); see also Roche v. Lincoln Prop. Co., 278 F.Supp. 2d 744, 752 (E.D. Va.2003) (“Dr. Bernstein’s reliance on temporal causation as the determinative factor in his analysis is suspect because it is well settled that a causation opinion based solely on a temporal relationship is not derived from the scientific method and is therefore insufficient to satisfy the requirements of Rule 702.”) (internal quotes omitted).

[2] See Reference Manual on Scientific Evidence at 612 (3d ed. 2011) (noting “the logic of the effect of doubling of the risk”); see also Marder v.G.D. Searle & Co., 630 F. Supp. 1087, 1092 (D. Md.1986) (“In epidemiological terms, a two-fold increased risk is an important showing for plaintiffs to make because it is the equivalent of the required legal burden of proof-a showing of causation by the preponderance of the evidence or, in other words, a probability of greater than 50%.”).

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