The skyrocketing cost of cancer therapy has become a popular topic of discussion as a recent article in the Wall Street Journal made abundantly clear (Policy Shift Is a Win for Drug-makers: Joseph Walker, Business & Finance, Friday, 03/23/2018).
In the article, under the subheading “Costly Therapy” a graph reveals that in 2015 just 10 drugs made up nearly half of all Medicare’s Part B (outpatient) spending. Eight of these 10 are the so called “biologics”, mostly monoclonal antibodies, and 7 of these 8 are cancer therapies.
Of the total $23 billion spent in 2015 by Medicare for part B drugs, $6.62 was spent on these 7 cancer treatments.
With so much of the expenses coming from “biologics “ there is hope that new generic formulations, known as bio-similars, may bring down costs
This is already being seen with the bone marrow stimulants known as granulocyte colony stimulating factors (GCSF) and some others. However, many of the proprietary drugs remain expensive and for most of them there are no generic alternatives.
If the cost of drugs continues to rise and patient (and physician) desire to use these drugs continues unabated, how can we curtail medical care costs from spiraling out of control?
One answer is to better select candidates for therapy.
While pharmaceutical companies, governmental agencies and university investigators spend an inordinate amount of time, energy and money developing “new drugs” there is almost no expenditure on technologies that can accurately select drugs. The term “accurately” is used advisedly.
The academic community will opine that we are in the midst of a genomic revolution that will, in the near future, enable us to use next generation sequencing (NGS) and gene-based tests to select candidates for treatments, with the proverbial “flick of a switch”.
While NGS testing has become very popular and, for some, highly profitable, the ability of these platforms to select candidates for therapy beyond a handful of well-established targets like EGFR and ALK, has been virtually non-existent.
One study known as the SHIVA trial (Le Tourneau, C. Lancet Oncology, October, 2015) compared the outcomes of patients who received “genomically selected” drugs against “physician choice”. After conducting genomic analysis on each patient’s tumor their DNA mutations were used to select the “best” drug.
Those patients randomized to “physician choice” received whatever the doctor considered best, without the benefit of a DNA study. For some of these patients, the “physician choice” was no therapy at all.
The results: There was no difference whatsoever.
The trial was an abject failure.
Nonetheless, tens of millions of dollars are spent every year by unwitting patients and their physicians on these techniques.
If we are to meaningfully curtail the rapidly rising cost of cancer therapy, it is likely that future answers will come from the intelligent application of clinically validated laboratory platforms that accurately identify candidates for drugs before they are administered.
Phenotypic platforms like EVA-PCD analyses are meeting these needs every day.
As always, I appreciate your thoughts and comments.
Dr. Robert Nagourney, has been internationally recognized as a pioneer in cancer research and personalized cancer treatment for over 20 years. He is a TEDX SPEAKER, author of the book OUTLIVING CANCER, a practicing oncologist and triple board certified in Internal Medicine, Medical Oncology and Hematology helping cancer patients from around the world at his Nagourney Cancer Institute in Long Beach, California. For more info go to NAGOURNEYCANCERINSTITUTE.COM