Monitoring the introduction of a surgical intervention with long-term consequences

• Published in: Statistics in medicine Vol. 26; no. 3; pp. 512 - 531
• Main Authors: Gorst-Rasmussen, A., Spiegelhalter, D. J., Bull, C.
• Format: Journal Article
• Language: English
• Published: Chichester, UK John Wiley & Sons, Ltd 10.02.2007; Wiley Subscription Services, Inc
• Subjects: Bayes Theorem; Bayesian analysis; Bayesian monitoring; Cardiovascular disease; Cohort Studies; congenital heart disease; Decision making; Female; Heart surgery; Humans; Infant, Newborn; Innovations; Kaplan-Meier Estimate; learning curves; life expectancy; Male; Models, Statistical; Randomized Controlled Trials as Topic - methods; Surgical Procedures, Operative - methods; Surgical Procedures, Operative - standards; surgical trials; Transposition of Great Vessels - surgery; Treatment Outcome
• ISSN: 0277-6715; 1097-0258
• DOI: 10.1002/sim.2548

Surgical innovations are often introduced for their expected long‐term benefits, but the decision to abandon the existing treatment must be based on the available short‐term data and rational judgment. We present a framework for monitoring the introduction of a surgical intervention with long‐term consequences and failure‐time endpoints. The framework is based on Bayesian methods, and formally combines study data, clinical opinion, and external evidence to construct a posterior survival function from which intuitive summary statistics can be extracted to aid decision making. It incorporates learning effects and is adaptable to a wide variety of settings. The methods are illustrated on survival data from a cohort of 325 consecutive neonates treated for simple transposition of the great arteries with either the Senning or the Switch operation during the period 1978–1998. Copyright © 2006 John Wiley & Sons, Ltd.