The Magic Number – Audra K.

Out of everything Chapter 6 of Rigor Mortis talks about, the way that Harris reflects on how the OvaCheck blood tests were still promoted and recommended even after being questioned and proven inaccurate is one of the biggest parts that stuck with me. This connects back to failed trials, which are described in the first Chapter of Rigor Mortis, and how they lead to incorrect or even falsified results in the hope to make a major medical breakthrough. The OvaCheck made headlines and its researchers were on the TODAY show. It was published in scientific journals. It shows once again why researchers are so quick to hop onto an idea with minimal data backing it, in the hopes it may lead to a major breakthrough. OvaCheck was the first test to ever be able to test for Ovarian Cancer using proteins from the blood while being as minimally invasive as possible. This was a very big deal once it came out, as before many women did not find out that they had Ovarian cancer until it had already developed into advanced stages or metastasized to other parts of the body.

Unfortunately, data results during research phases of the OvaCheck caused a misread in the protein analysis which researchers were using to identify the difference between cancerous and non-cancerous proteins (there actually are not). According to Keith Baggerly, “‘We yelled about this and eventually made a bit of a stink,’” [pg 125]. Even after the fact that it was known that the Ovacheck test was not proven to work, it was still being promoted and marketed. This article from the New York Times more in-depth explains how the OvaCheck was still promoted and how the studies and papers were later retracted.

It all does still show that the medical research industry is driven by a need for results as a hope for publicity and future funding towards other projects, as opposed to driven by a need for results as a way to change people’s lives. It does shock me at how so many research trials have gone similarly. According to Harris, “Analytical errors alone account for almost one in four irreproducible results (..) researchers often follow the traditional practices of their fields, even when those practices are deeply problematic.” [pg 126]. Many trials end up being irreproducible due to these analytical errors. Many trials are too small to produce enough variety among results, however, large scale trials are harder to control and replicate all variables throughout the researching phases. Studies are set at an appropriate size to where it yields results which have only a 5% chance that results occurred by chance. This is leaving a large part of the research objectives up to chance.

While 5% does not seem like a large number, it can be when referring to the loss of expenses, time, and utilities towards studies which end up yielding false results. This isn’t just a problem with large studies. This is what happens to many small scale studies in the end because they jumped on a false lead from the get-go.