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Brendon Nafziger, DOTmed News Associate Editor | April 29, 2010
But the FDA believes the risk of clearing a defective device is too great to not have these error reports included.
"If the trial concludes, for example, that the device is effective when it's not, that's an error which has implications in terms of the public health.... So it is of concern for the agency to not make those kinds of errors very often, and one way to keep track of that is to ask companies who are doing Bayesian trials... to simulate the type 1 error characteristics in their trial," says Dr. Campbell.
FUTURE OF BAYESIANISM
So far, the method is catching on, but slowly. Crowe says Cambridge Consultants, which only publicly announced their program a few weeks ago, is still working to line up a customer for it.
The FDA hasn't seen too many applications yet, either. An FDA employee recently looked over the figures, and found around 24 pre-market applications using Bayesian designs, admittedly a "relatively small portion of the trials we see," acknowledges Dr. Campbell. But still, it's something that's likely to become more popular.
"[There's] probably a trend to seeing a little more activity in this area," says Dr. Campbell.
But Bayesian analyses have only really taken off over the last 20 years, after mathematicians developed better algorithms, such as the Markov Chain Monte Carlo (MCMC) method, and computing power increased to where the data-dense problems could be tackled. "If you go back 10 or 20 years, there were big mainframe computers that have speeds comparable to people's laptops now," says Dr. Campbell. "We can do things now, that 20 years ago would have been very hard to do."
Further reading: "US FDA Guidance on Using Bayesian Statistics in Medical Device Clinical Trials," Roger Sewell and Elisabeth Crowe,
Regulatory Affairs Journal Devices, March 10th 2010: http://www.rajdevices.com/productsector/medicaldevices/US-FDA-Guidance-on-Using-Bayesian-Statistics-in-Medical-Device-Clinical-Trials-200786?autnID=/contentstore/rajdevices/codex/c09b6183-2c48-11df-9a1d-43f7b12171c7.xml
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