Last week, the Tufts Center for the Study of Drug Development unleashed the latest in their occasional series of dire pronouncements about the state of pharmaceutical clinical trials.
One particular factoid from the CSDD "study" caught my attention:
|Shocking performance stat: |
57% of these racers won't medal!
* 11% of sites in a given trial typically fail to enroll a single patient, 37% under-enroll, 39% meet their enrollment targets, and 13% exceed their targets.Many industry reporters uncritically recycled those numbers. Pharmalot noted:
Now, the bad news – 48 percent of the trial sites miss enrollment targets and study timelines often slip, causing extensions that are nearly double the original duration in order to meeting enrollment levels for all therapeutic areas.(Fierce Biotech and Pharma Times also picked up the same themes and quotes from the Tufts PR.)
There are two serious problems with the data as reported.
One: no one – neither CSDD nor the journalists who loyally recycle its press releases – seem to remember this CSDD release from less than two years ago. It made the even-direr claim that
According to Tufts CSDD, two-thirds of investigative sites fail to meet the patient enrollment requirements for a given clinical trial.If you believe both Tufts numbers, then it would appear that the number of under-performing sites has dropped almost 20% in just 20 months – from 67% in April 2011 to 48% in January 2013. For an industry as hidebound and slow-moving as drug development, this ought to be hailed as a startling and amazing improvement!
Maybe at the end of the day, 48% isn't a great number, but surely this would appear to indicate we're on the right track, right? Why would no one mention this?
Which leads me to problem two: I suspect that no one is connecting the 2 data points because no one is sure what it is we're even supposed to be measuring here.
In a clinical trial, a site's "enrollment target" is not an objectively-defined number. Different sponsors will have different ways of setting targets – in fact, the method for setting targets may vary from team to team within a single pharma company.
The simplest way to set a target is to divide the total number of expected patients by the number of sites. If you have 50 sites and want to enroll 500 patients, then viola ... everyone's got a "target" of 10 patients! But then as soon as some sites start exceeding their target, others will, by definition, fall short. That’s not necessarily a sign of underperformance – in fact, if a trial finishes enrollment dramatically ahead of schedule, there will almost certainly be a large number of "under target" sites.
Some sponsors and CROs get tricky about setting individual targets for each site. How do they set those? The short answer is: pretty arbitrarily. Targets are only partially based upon data from previous, similar (but not identical) trials, but are also shifted up or down by the (real or perceived) commercial urgency of the trial. They can also be influenced by a variety of subjective beliefs about the study protocol and an individual study manager's guesses about how the sites will perform.
If a trial ends with 0% of sites meeting their targets, the next trial in that indication will have a lower, more achievable target. The same will happen in the other direction: too-easy targets will be ratcheted up. The benchmark will jump around quite a bit over time.
As a result, "Percentage of trial sites meeting enrollment target" is, to put it bluntly, completely worthless as an aggregate performance metric. Not only will it change greatly based upon which set of sponsors and studies you happen to look at, but even data from the same sponsors will wobble heavily over time.
Why does this matter?
There is a consensus that clinical development is much too slow -- we need to be striving to shorten clinical trial timelines and get drugs to market sooner. If we are going to make any headway in this effort, we need to accurately assess the forces that help or hinder the pace of development, and we absolutely must rigorously benchmark and test our work. The adoption of, and attention paid to unhelpful metrics will only confuse and delay our effort to improve the quality of speed of drug development.
[Photo of "underperforming" swimmers courtesy Boston Public Library on flikr.]