GRACE :: Cancer Basics

How much evidence is needed to change practice in cancer care? 8 key factors help set the bar.

The concept of statistical significance, a line drawn at the level of less than 5% probability that the effects of a new approach could be due to chance alone and not the intervention itself, implies that there’s a point of demarcation where we considera result positive. In truth, however, science and medicine are far messier than that, and we see adoption of new tests and new treatments adopted in a pattern more reminiscent of deciding to upgrade your mobile phone and television, in which there are bleeding edge people who are eager to pursue the latest approach with the first hint of potential value (called “innovators” and “early adopters” in technology, and in medicine they may be considered as “cowboys”), a much larger pool of people who need more evidence and comfort in something becoming a new standard of care, and a minority of “laggards” (the people for whom a phone upgrade today is focusing on whether to replace their rotary phone yet). 

technology-adoption-curve-Rogers(From the website

In truth, there are several variables that affect how eagerly or reluctantly members of the health care community adopt a new test or treatment. Here are the top 5 factors as I see them:

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Frogs in boiling water: On breaking the $10,000 barrier

Note: Novartis has provided funding to GRACE for our recent ALK-positive patient forum.

Last week, the FDA approved Zykadia (ceritinib), the second generation ALK inhibitor.  As I wrote in my post about this new agent its rapid approval as the first effective treatment for acquired resistance to a targeted therapy in advanced lung cancer, there should be little question that it provides a helpful new option.  A couple of days later, I learned the cost: $13,500/month.

I felt some sticker shock over this. After initially being shocked at the price of EGFR inhibitors at around $5000/month, then having then escalate every few years, we saw the approval of XALKORI (crizotinib), setting a new pace in lung cancer, at $9800/month. Though that represents a heady range, we cou;d also potentially justify the cost by saying this was a very limited population and that criotinib provided a profound benefit. 

I was shocked about the cost of Zykadia, at $13,500, which made the $9800/month cost of XALKORI seem quaint, like a relative bargain. I expressed my concerns to the folks at Novartis, saying that I thought the price was aggressive and approaching extortionate, especially after the FDA approved the drug just a couple of years after it began phase II testing, based on just 140 patients, not the typical requirement of large, expensive phase III trials over many years that provided the justification for the high cost of these drugs in the past.

To their credit, they were very responsive and got back to me about my concerns.  They made several points that made me feel as though the question of cost and value for cancer agents is a fair concern, but also that their pricing was a thoutful process, what they estimated as fair market value relative to other agents and not just a simple opportunity to demand the absolute most that could be obtained.

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The Spectrum of Cancer Progression (50 Shades of Progression)

Here’s a general summary of a thoughtful approach to how we might assess progression of disease, recognizing that it isn’t just a simple matter of a “yes/no” question of progression or not.  

And for those who want the pdf to print, here it is: 50 Shades of Cancer Progression

Feel free to leave questions. comments, objections, etc. here.I hope it’s helpful.



How a Cancer Adapts: Key Clinical Implications from the Evolution of an Advanced Cancer

Key Clinical Implications of how a Cancer Evolves from H. Jack West

The associated, printable pdf is here.

All about subgroups: Why do we value the results in some trial subgroups but not others?

Here’s an important summary of how to interpret results from cancer trials that are increasingly hyped to the general public. You need to be a knowledgeable consumer of this information.

Over the past decade, one of the biggest developments in lung cancer, and in fact many kinds of cancer, has been the identification of important subgroups within the broad categories. Where 10-12 years ago we categorized patients as “advanced NSCLC” and didn’t get much more granular than that, we now routinely look for differences depending on different tumor histologies (adenocarcinoma, squamous, or other), the presence or absence of driver mutations, perhaps even smoking status. We expect to see differences, and in many cases identification of specific subgroups within a larger trial has led to major changes in treatment recommendations. At other times, however, you may see/read cancer news highlights that describe results as being significantly different for one group or another in a trial that was otherwise negative. What makes the results of one subgroup analysis credible and practice-changing, while oncologists view others with far more skepticism?

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