In Cancer – If It Seems Too Good to Be True, It Probably Is
The panoply of genomic tests that have become available for the selection of chemotherapy drugs and targeted agents continues to grow. Laboratories across the United States are using gene platforms to assess what they believe to be driver mutations and then identify potential treatments.
Among the earliest entrants into the field and one of the largest groups, offers a service that examines patient’s tumors for both traditional chemotherapy and targeted agents. This lab service was aggressively marketed under the claim that it was “evidence-based.” A closer examination of the “evidence” however, revealed tangential references and cell-line data but little if any prospective clinical outcomes and positive and negative predictive accuracies.
I have observed this group over the last several years and have been underwhelmed by the predictive validity of their methodologies. Dazzled by the science however, clinical oncologists began sending samples in droves, incurring high costs for these laboratory services of questionable utility.
In an earlier blog, I had described some of the problems associated with these broad brush genomic analyses. Among the greatest shortcomings are Type 1 errors. These are the identification of the signals (or analytes) that may not predict a given outcome. They occur as signal-to-noise ratios become increasingly unfavorable when large unsupervised data sets are distilled down to recommendations, without anyone taking the time to prospectively correlate those predictions with patient outcomes.
Few of these companies have actually conducted trials to prove their predictive values. This did not prevent these laboratories from offering their "evidence-based" results.
In April of 2013, the federal government indicted the largest purveyor of these techniques. While the court case goes forward, it is not surprising that aggressively marketed, yet clinically unsubstantiated methodologies ran afoul of legal standards.
A friend and former professor at Harvard Business School once told me that there are two reasons why start-ups fail. The first are those companies that “can do it, but can’t sell it.” The other types are companies that “can sell it, but can’t do it.” It seems that in the field of cancer molecular biology, companies that can sell it, but can’t do it, are on the march.