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Bayesian Analysis for Medical Device Trials

Capsule endoscopy (CE) is rapidly growing in popularity and new studies are being published every month detailing its efficacy. Therefore being able to use CE in as broad a patient population as possible is important. Currently, the manufacturer recommends not using CE in patients with implantable defibrillators, pacemakers, and other implantable electronic devices. Leighton et al. have performed two important pilot studies to measure the safety of CE in patients with pacemakers (1) and now with defibrillators (2). In both studies, they performed CE in five patients and observed no adverse electrical events. Taken in isolation these data are weak. Standard statistical methods, which treat the empirical data in isolation, provide little insight into the current belief about the adverse event rate when using CE in patients with implantable defibrillators. Leighton et al. report a confidence interval of 0–52%. This is a very broad interval that contains much good news (0%) but much bad news also (any rate over 5% is probably bad news). We know more than just the raw empirical data. We have the results of other studies of implanted electrical devices, which report adverse event rates. While these devices are not the same there are similarities and there is information in these other results. We encourage a Bayesian analysis that incorporates all available information—especially in a case, such as this, where the empirical data are not extremely strong. We perform a Bayesian analysis of this scenario, combining sources of information together—including the data in Leighton et al. to capture the current knowledge of the adverse event rate when using CE in patients with implantable defibrillators. This editorial serves as an introduction to Bayesian analysis for medical devices. For additional discussion see (3–5).