New Cancer Drug: Breakthrough or Just Hype?

Having just passed through Ontario’s Pearson International airport on route from eastern Canada, I was struck by an email from one of my patient’s mothers who shared with me a 6/20/2013 article from the Toronto Globe and Mail, “Take news of cancer breakthrough with a big grain of salt,” by staff writer André Picard.

The author describes an announcement by two prominent cancer researchers, Tak Mak, PhD, of Princess Margaret Hospital Toronto, CA and Denis Slamon, MD, from UCLA, who reported the results from a new class of compounds known as “polo-like kinase 4 inhibitors.” Picard goes on to note, “This seemingly miraculous ‘breakthrough’ drug has not been tested on a single person. The experimental drug CFI-400945 has ‘prevented cancer growth’ in a bunch of mice.”

What troubles the author (and should probably trouble us all), is the lack of substance in this report. After all, many drugs reveal activity in animal models, yet most seemingly promising drugs fail to provide clinical benefit. Only 8 percent of cancer chemotherapy drugs that enter the earliest form of human clinical trials (Phase I) ever achieve FDA approval. According to a study published in the New England Journal of Medicine, fully 50 percent of drugs that make it to the final stage (Phase III) of clinical testing nonetheless fail to gain approval. Thus, there is ample reason for concern when “breakthrough” drugs achieve this level of public recognition, because it is distinctly unlikely that they will ever deliver on their promises.

When I attend the AACR meetings, I’m impressed by the level of scientific discovery. When I then attend the ASCO meetings, I’m even more concerned by the lack of clinically relevant progress. The divide between clinicians and scientists seems to grow ever wider. While TIME magazine and The New York Times (to use Andre Picard’s term) genuflect before these scientists’ reports of dramatic advances, most cancer patients continue to suffer through largely ineffective toxic therapies. The disconnect is becoming painfully evident. What we need is a better pathway from discovery to clinical application. What we don’t need is more hype.

Evidence Based Medicine and the Cost of Cancer Care

Before I attended the ASCO meeting in Chicago, I penned a blog about a Forbes magazine article that described increasing restrictions placed on access to newer diagnostic tests for patients covered by Medicare.

Among the presentations that I attended at ASCO, (more to follow), was a study entitled “The cost per patient of deviations from evidence-based (EB) standards of oncology care.”  The presentation caught my eye as it addressed the cost of care associated with adherence to evidence-based guidelines versus treatment plans that varied from these guidelines. Utilizing a database developed to analyze the cost of treatment, these investigators explored costs incurred when physicians used treatments that were not within the confines of the evidence-based formulae.

A total of 2,775 consecutive patients had their treatment plans (TPS) submitted and 730 (26 percent) of these patients were described as receiving, “unjustified, non-Evidence Based Treatment Plans.” The authors then examined the costs associated with these treatments. Their phraseology for treatment that varied from guidelines was those “that did not confirm to Evidence Based standards or could not be medically justified.” Apparently the practice on the part of qualified, skilled oncologists of making drug choices that vary from evidence-based medicine is synonymous with “not being medically justified.” Their conclusion “conservative estimate(s) of the average per patient overspend (first order) on inappropriate treatment validates the potential for quality care to lower cost and deliver huge value to patients, physicians and payors.”

What’s wrong with this picture?

First, clinical oncology as it is practiced today through the available guidelines (NCCN, etc.) has failed to improve 5-year survival for advanced cancer in 50 years. Thus, this “regression to the mean” thinking, if followed, would increasingly demand that medical oncologists scrupulously adhere to largely ineffective therapy guidelines.

The second problem is that this analysis provides no data on response, time to progression, survival or toxicity. For all we know, the 26 percent of patients who received non-evidence based treatment plans may have been the best responders with better survivals and lower toxicities.

Finally, in keeping with the Forbes article previously described, medical oncologists are rapidly abdicating control of their cancer patients’ treatments in favor of econometric analyses.  Should this trend continue, patients may soon be forgoing the opinions of their MDs, in favor or the opinions of  MBAs.

The High Cost of Cancer Care

An article by Scott Gottlieb, MD, in Forbes (Medicare Nixes Coverage for New Cancer Tests), described Medicare reimbursement for new molecular diagnostics. As many readers are aware, there have been a growing number of diagnostic tests developed and marketed over recent years designed to identify and monitor the progress of cancer. Many of these tests are multiplexed gene or protein panels that identify prognostic groups using nomograms developed from prospective or retrospective analyses. The 21-gene Oncotype DX and related Mammoprint, are among the most widely used. Related tests for lung, colon, and other cancers are in development.

With the explosion of assays designed to personalize cancer care, comes the expense associated with conducting these analyses. Medicare, as the largest provider of medical insurance in the United States, is at the leading edge of cost containment. Not surprisingly, HHS has a jaundiced view of adding tests without clear cost benefit.

The issue is far broader than cost analysis. It goes to the very heart of what we describe as personalized medicine. Every patient wants the right treatment for their disease. Every laboratory company wants to sell their services. Where the supply and demand curve meet however, is no longer set by market forces. In this instance, third party reimbursers set the fee and the companies then need to determine whether they can provide their service at that cost.

The problem, as with all economic analysis, is meeting patient’s unlimited wants with limited resources. Two solutions can be envisaged. On the one hand, medical care progressively moves to a scenario of haves and have nots wherein only wealthier individuals can afford to obtain those drugs and interventions that are beyond the price range of most. On the other hand, care is rationed and only those treatments and interventions that rise to the highest level of evidence are made available.

While the subject of this article was sophisticated diagnostic tests, it will only be a matter of time before these same econometric analyses begin to limit the availability of costly drugs like highly expensive targeted agents. In a recent editorial published in blood, leading leukemia experts pointed out that 11 of the 12 recently approved drugs each cost $10,000 or more per month.

As we examine the rather grim prospect of unaffordable or rationed care, a glimmer of hope can be seen. Using expensive and relatively insensitive molecular diagnostic tests to select expensive targeted agents could be replaced by less expensive testing platforms. The dramatic, yet brief responses observed for many targeted agents reflect the shortcoming of linear thinking applied to the manifestly non-linear human biology, characterized by cross talk, redundancies and unrecognized hurdles. To address these complexities phenotypic analysis (the phenotype being the end product of genomic, transcriptomic and proteomic events) provide global assessments of tumor response to drugs, combinations and signal transduction inhibitors. These more discriminating results identify cellular response at the level of biology, not just informatics. While it is theoretically possible that high-throughput genomic analyses using neural networks and high throughput computer analyses may ultimately provide similar information, it is unlikely that most patients will have ready access to a Cray computer to decipher their results.

We need to stop working hard and start working smart. The answers to the many questions raised by the Forbes article regarding resource allocation in cancer treatment may already be at hand.