title: Incorporation of stochastic engineering models as prior information in Bayesian medical device trials.
abstract: Evaluation of medical devices via clinical trial is often a necessary step in the process of bringing a new product to market. In recent years, device manufacturers are increasingly using stochastic engineering models during the product development process. These models have the capability to simulate virtual patient outcomes. This article presents a novel method based on the power prior for augmenting a clinical trial using virtual patient data. To properly inform clinical evaluation, the virtual patient model must simulate the clinical outcome of interest, incorporating patient variability, as well as the uncertainty in the engineering model and in its input parameters. The number of virtual patients is controlled by a discount function which uses the similarity between modeled and observed data. This method is illustrated by a case study of cardiac lead fracture. Different discount functions are used to cover a wide range of scenarios in which the type I error rates and power vary for the same number of enrolled patients. Incorporation of engineering models as prior knowledge in a Bayesian clinical trial design can provide benefits of decreased sample size and trial length while still controlling type I error rate and power.
authors.affiliation: a Medtronic, plc, Mounds View , Minnesota , USA.
authors.forename: Tarek
authors.initials: T
authors.lastname: Haddad
authors.affiliation: a Medtronic, plc, Mounds View , Minnesota , USA.
authors.forename: Adam
authors.initials: A
authors.lastname: Himes
authors.affiliation: b Center for Devices and Radiological Health , U.S. Food and Drug Administration , Silver Spring , Maryland , USA.
authors.forename: Laura
authors.initials: L
authors.lastname: Thompson
authors.affiliation: b Center for Devices and Radiological Health , U.S. Food and Drug Administration , Silver Spring , Maryland , USA.|c Center for Biologics Evaluation and Research , U.S. Food and Drug Administration , Silver Spring , Maryland , USA.
authors.forename: Telba
authors.initials: T
authors.lastname: Irony
authors.affiliation: b Center for Devices and Radiological Health , U.S. Food and Drug Administration , Silver Spring , Maryland , USA.
authors.forename: Rajesh
authors.initials: R
authors.lastname: Nair
authors.affiliation: d Medical Device Innovation Consortium Clinical Trials Powered by Bench and Simulation Working Group.|e See online supplement for a complete list of participants.
mesh_terms: D001499:Bayes Theorem; D001698:Biomedical Engineering / Q000592:standards / Q000706:statistics & numerical data*; D002986:Clinical Trials as Topic / Q000592:standards / Q000706:statistics & numerical data*; D004864:Equipment and Supplies / Q000592:standards / Q000706:statistics & numerical data*; D006801:Humans; D015233:Models, Statistical; D013269:Stochastic Processes
keywords: Bayesian; clinical trial; medical devices; virtual patient