Understanding preferences of patients with multivessel coronary artery disease towards revascularisation and optimal medical therapy: a protocol for a discrete choice experiment.

INTRODUCTION

The selection of the optimal treatment strategy remains one of the most challenging decisions in the management of coronary artery disease (CAD). Surgical and percutaneous coronary revascularisation are two widely used treatments for managing CAD and can result in improved outcomes compared with medications alone. Current practice guidelines recommend revascularisation for multivessel CAD for most patients. However, there remains uncertainty about whether revascularisation or medical therapy is optimal for managing multivessel disease for many patients, especially, in the elderly and those living with multimorbidity. Also, there is limited understanding of patient preferences towards candidate treatment options for multivessel disease. This study aims to quantify and characterise heterogeneity in patient preferences towards treatment options for multivessel CAD.

METHODS AND ANALYSIS

We have designed and will administer a discrete choice experiment to elicit and quantify preferences of people with multivessel CAD towards revascularisation and optimal medical therapy for managing multivessel CAD. Multinomial logit mixed effects and hierarchical Bayes models will be used to model the association between the participants' choices and the attributes and their different levels. The relative importance of the attributes will be assessed using the size of coefficients and marginal rate of substitution (MRS), a measure of the willingness to accept a trade-off among different options. Heterogeneity in patient preferences will be evaluated using latent class analysis.

ETHICS AND DISSEMINATION

Ethical approval for this study was granted by the University of Calgary Conjoint Health Research Ethics Board. Findings from this study will inform the development of clinical decision support tool that integrates patient preferences with clinical risk information to support patient-care provider discussion about optimal treatment for multivessel CAD management.