Tuesday, April 07, 2020 9:32:54 PM
I've seen a few posts talk about Dr. Heinecke and his claim that the ApoB result for Kura is significant, and some discussion about how this might then become a situation where two experts are pitted against one another in the appeal.
I don't believe this is the case. This particular issue, statistical testing between baseline and a randomized group as opposed to between two randomized groups, is very very common, and the statistical community has litigated this thoroughly. The answer is, it's a big no-no.
Board member Piyao posted a couple of links that discuss this (Hat tip to Piyao). I am reposting one of them here, and pasting a few quotes from this article, quoting past articles from the statistical literature. The article is not behind a paywall and highly readable, so I encourage people to take a look:
https://www.nature.com/articles/s41393-018-0203-y
Quoted from the article above:
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Nonetheless, the practice persists. Here are some comments that should dampen enthusiasm for using p values in this way:
“….performing a significance test to compare baseline variables is to assess the probability of something having occurred by chance when we know that it did occur by chance. Such a procedure is clearly absurd.” p. 126 [2].
“P-values for baseline differences do not serve a useful purpose, since they are not testing a useful scientific hypothesis.” p. 2928 [3].
“With few exceptions, the statistical literature is uniform in its agreement on the inappropriateness of using hypothesis testing to compare the distribution of baseline covariates between treated and untreated subjects in RCTs.” p. 142 [4].
“Indeed the practice can accord neither with the logic of significance tests nor with that of hypothesis tests….I suspect that the practice has originated through confused and false analogies with significance and hypothesis tests in general.” p. 1716 [5].
Even if we ignore the criticisms of statistical testing for baseline differences, there is the added problem that an insignificant p value may merely reflect a small sample size. That is, there may be large differences that statistical testing fails to detect. And what if there is a significant difference on one baseline variable? It would be rather surprising if there was not given the high number of variables that are typically measured at baseline. A single p value less than 0.05 among many baseline statistical tests may just reflect a spurious finding.
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In summary, the error with Kura is not a topic that will be resolved by a debate between experts. It is an issue that has already been thoroughly examined and resolved by the community.
It may be that removing Kura as evidence for obviousness is not enough to tip the appeal Amarin's way. However, I find it very difficult to believe that Kura will not be removed as evidence for obviousness, as long as the legal team is aware of the mistake and the literature.
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