A Markov decision analysis model to aid the vascular surgeon in the management of a patient with an asymptomatic infra-renal abdominal aortic aneurysm

Abstract Introduction Despite increasing evidence regarding the safety and efficacy of endovascular (EVAR) and open abdominal aortic aneurysm repair, it is often unclear which technique is most appropriate for an individual patient. We have designed a decision analysis model that will predict survival, reintervention rates and other parameters for individual patients. Methods A Markov decision analysis model was developed in Microsoft Excel to simulate five management options; EVAR, open repair, best medical therapy or delayed EVAR or open repair at a threshold aneurysm diameter. Probabilities for the model were determined from systematic literature review. The user can assess the impact of adjusting patient-specific risk-factors including aneurysm size, threshold diameter for intervention, operative mortality, hazard ratios for general mortality, reintervention rate and aneurysm rupture rate. Results Patient and aneurysm specific variables are entered through a user-friendly data-input sheet and the model generates graphical and descriptive results regarding estimated survival and reintervention rates for the different management options. Individualised survival curves, both aneurysm-related and general mortality curves, cumulative reintervention rates and other key parameters are generated for each management option. The model has been validated against average data published from recent RCTs and examples have been generated based on real and hypothetical patient characteristics. Conclusions An easy-to-use computer model has been developed that will provide meaningful information relating to risks and benefits that could assist in shared decision making and obtaining informed consent from patients with aneurysms, and could help to guide policy decisions in respect to patient selection for EVAR.

Name dc:type.qualificationname

M.Phil

Level dc:type.qualificationlevel

masters

Grantor dc:publisher.institution

University of Sheffield

Year dc:date.issued

2010

Author dc:creator

• Drury, Duncan

Advisor dc:contributor.advisor

• Michaels, J