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Bayesian meta-analysis on medical devices: application to implantable cardioverter defibrillators

Bayesian meta-analysis on medical devices: application to implantable cardioverter defibrillators
Bayesian meta-analysis on medical devices: application to implantable cardioverter defibrillators
Objectives: The aim of this study is to describe and illustrate a method to obtain early estimates of the effectiveness of a new version of a medical device. Methods: In the absence of empirical data, expert opinion may be elicited on the expected difference between the conventional and modified devices. Bayesian Mixed Treatment Comparison (MTC) meta-analysis can then be used to combine this expert opinion with existing trial data on earlier versions of the device. We illustrate this approach for a new four-pole implantable cardioverter defibrillator (ICD) compared with conventional ICDs, Class III anti-arrhythmic drugs, and conventional drug therapy for the prevention of sudden cardiac death in high risk patients. Existing RCTs were identified from a published systematic review, and we elicited opinion on the difference between four-pole and conventional ICDs from experts recruited at a cardiology conference. Results: Twelve randomized controlled trials were identified. Seven experts provided valid probability distributions for the new ICDs compared with current devices. The MTC model resulted in estimated relative risks of mortality of 0.74 (0.60ââ?
Bayesian analysis, meta-analysis, medical devices, expert opinions, defibrillator, implantable
0266-4623
115-124
Youn, J.H.
62cc4e23-e98f-4f93-8dfd-41088fe77e3c
Lord, J.
fd3b2bf0-9403-466a-8184-9303bdc80a9a
Hemming, K.
d4db0561-9863-4d13-b322-07024a2af087
Girling, A.
51daa9c0-2d88-4d7d-b256-8d2ae1025310
Buxton, M.
2496fce8-7812-477d-bd26-0e30c1969613
Youn, J.H.
62cc4e23-e98f-4f93-8dfd-41088fe77e3c
Lord, J.
fd3b2bf0-9403-466a-8184-9303bdc80a9a
Hemming, K.
d4db0561-9863-4d13-b322-07024a2af087
Girling, A.
51daa9c0-2d88-4d7d-b256-8d2ae1025310
Buxton, M.
2496fce8-7812-477d-bd26-0e30c1969613

Youn, J.H., Lord, J., Hemming, K., Girling, A. and Buxton, M. (2012) Bayesian meta-analysis on medical devices: application to implantable cardioverter defibrillators. International Journal of Technology Assessment in Health Care, 28 (2), 115-124. (doi:10.1017/S0266462312000037). (PMID:22559753)

Record type: Article

Abstract

Objectives: The aim of this study is to describe and illustrate a method to obtain early estimates of the effectiveness of a new version of a medical device. Methods: In the absence of empirical data, expert opinion may be elicited on the expected difference between the conventional and modified devices. Bayesian Mixed Treatment Comparison (MTC) meta-analysis can then be used to combine this expert opinion with existing trial data on earlier versions of the device. We illustrate this approach for a new four-pole implantable cardioverter defibrillator (ICD) compared with conventional ICDs, Class III anti-arrhythmic drugs, and conventional drug therapy for the prevention of sudden cardiac death in high risk patients. Existing RCTs were identified from a published systematic review, and we elicited opinion on the difference between four-pole and conventional ICDs from experts recruited at a cardiology conference. Results: Twelve randomized controlled trials were identified. Seven experts provided valid probability distributions for the new ICDs compared with current devices. The MTC model resulted in estimated relative risks of mortality of 0.74 (0.60ââ?

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Published date: April 2012
Additional Information: ID: 46426; PMCID: PMC3339879
Keywords: Bayesian analysis, meta-analysis, medical devices, expert opinions, defibrillator, implantable
Organisations: Primary Care & Population Sciences

Identifiers

Local EPrints ID: 382154
URI: http://eprints.soton.ac.uk/id/eprint/382154
ISSN: 0266-4623
PURE UUID: 8475cc77-c751-40ee-8157-9372cff7ac71
ORCID for J. Lord: ORCID iD orcid.org/0000-0003-1086-1624

Catalogue record

Date deposited: 26 Oct 2015 13:08
Last modified: 21 Nov 2021 03:12

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Contributors

Author: J.H. Youn
Author: J. Lord ORCID iD
Author: K. Hemming
Author: A. Girling
Author: M. Buxton

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