Saturday, 21 October 2017

Are new cancer treatments improving survival or quality of life?

This is the question that a recent study in BMJ by Davis et al. (2017) attempts to answer.  They use data from 48 cancer drugs for 68 indications that were approved by the European Medicines Agency (EMA) between 2009 and 2013.  Among these 68 indications, they found that:

only 35 (51%) were associated with significant improvement in survival or quality of life over alternative treatment options, placebo, or as add on treatment. For 33 (49%), uncertainty remains over whether the drugs extend survival or improve quality of life.

Now clearly we need to mention (citing Carl Sagan) that “Absence of evidence is not evidence of absence!”  In other words, the evidence did not show that overall survival (OS) and quality of life (QoL) did not improve, rather that this information was not collected.  The authors argue that the lack of evidence is a clear issue.  While as I researcher I would of course prefer more evidence on OS and QoL, creating studies that measure OS and QoL are costly and time-consuming.  Thus, how big an issue is it that the EMA is using surrogate outcomes to estimate treatment benefits?

One factor is how closely surrogate and OS/QoL outcomes are correlated. One of my studies showed that real-world OS benefits were about 16% lower in the real-world compared to the benefits shown using surrogate endpoints.  Thus, we see that the correlation–at least for the tumors studies–is fairly strong but far from perfect.

Second, we need to look at the cost of collecting the OS and QoL data.  If the cost of very high, it is better to rely on surrogate outcomes.  If the cost is low, then regulators or payers should incentivize the collection of OS and QoL data.

Third, we need to look at the benefits of early access to medicines relative to the cost or approving treatments that not likely to have OS or QoL benefits.  There clearly is a tradeoff, but patients have been shown to have preferences for treatments with some positive chance of long-term durable survival gains.  The authors look at median gains in survival and also median survival gains across treatments, however.

Thus, I agree with Davis and co-authors that more data on overall survival and quality of life would be good.  The relevant policy question, however, is whether collecting this additional information is worth the cost.  This clearly is an area for further research.

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