September 28, 2011- On Aug. 26, 2011, the Texas Supreme Court decided Merck v. Garza — one of the last Vioxx cases to be tried and a case that resulted in a $32 million verdict reduced to a $7.75 million judgment.

Leonel Garza, age 71, died of a heart attack, alone at his ranch near Rio Grande City, Texas, in 2001. Garza had a 20-year history of cardiovascular disease but had been taking Vioxx immediately before his death. The Garza family sued Merck & Co. Inc. on these facts and won, despite Merck challenging the scientific reliability of evidence that Vioxx caused Garza’s death. The court of appeals overturned the lower-court decision based on juror misconduct and remanded the case for a new trial. Merck appealed to the Texas Supreme Court.

The court’s relatively short opinion rolls along (1) reaffirming Havner (if you play the game of epidemiological causal inference, then you need to play by epidemiology's rules; and that if all you have is probabilistic evidence then that evidence had better show that defendant's product probably did it); (2) apparently adding the further requirement of a second well-done epidemiological study "statistically significant at the 95-percent confidence level" that shows a doubling of risk; (3) rejecting the "totality of the evidence" ipse dixit of plaintiff's expert; but then suddenly (4) utterly confounding us by holding "when parties attempt to prove general causation using epidemiological evidence, a threshold requirement of reliability is that the evidence demonstrate a statistically significant doubling of the risk." What?!

The whole purpose of the "doubling of the risk" requirement had been, we thought, to ensure that when a plaintiff has nothing but probabilistic evidence, such evidence must actually support a "more likely than not" causal inference as to her specific illness. There are numerous agents that produce small effects (i.e., relative risks less than 2.0) and which are nevertheless unquestionably causative of human disease. Hopefully, the court meant "specific" where it wrote "general" regarding risk doubling.

Yet there is another problem on the very next page. Apparently, courts are now to "examine the design and execution of epidemiological studies using factors like the Bradford Hill criteria to reveal any biases that might have skewed the results of the study." Again: What?!

We thought (and we are pretty sure we are right) that Hill's list of factors were his way of assessing a given claim of general causation. And anyway, that is not how you look for bias. Here is a good example of an effective way to look for bias: "Excess Significance Bias In The Literature On Brain Volume Abnormalities."

In sum, we liked, of course, the court's conclusion that when each piece of the plaintiff's supposedly supportive evidence is flawed, "a plaintiff cannot prove causation by presenting different types of unreliable evidence." Yet, recognizing that causal inference is hard (nearly maddening sometimes) and that statistical inference is complicated and counterintuitive, we wish the court had done a better job on this one. The deviations from standard analysis will only support those who complain that the current court is "merely results oriented."  

This column was originally posted in the September 28, 2011 editions of Product Liability Law360 and Texas Law360.