A cost-utility analysis of a fixed-dose combination “polypill” for primary prevention of cardiovascular events

Problem

Cardiovascular diseases are the leading cause of morbidity and mortality worldwide, and a significant economic burden due to treatment costs and reduced productivity. Combination drug therapy in the form of a polypill has been proposed in terms of increased adherence and efficacy in the primary prevention of cardiovascular events. In addition to considering the efficacy of a polypill, it is necessary to establish its cost-effectiveness. We sought to establish the cost effectiveness of a polypill for the primary prevention of cardiovascular disease using UK utility and cost data based on a recent meta-analysis (n=18,162) of three randomised controlled trials (RCTs).

Approach

A Markov model was developed using the “heemod” package in R, to model the quality of life and healthcare costs of a polypill cohort and comparison group (the placebo arm in the trials) over a period of 5 and 10 years. Cost data was taken from event and long-term costs for cardiovascular events based on CPRD (Clinical Practice Research Datalink) data from 2006-2012. Utility values were taken from a systematic review of estimates for cardiovascular health states. The annual cost of a polypill, £382.64, was taken from a similar study by Ferket et al in 2016, which aids comparability. All costs were inflated to September 2021 prices. A discount rate of 3.5% on both costs and effects was applied in accordance with NICE guidance.

Findings

The polypill was cost-effective (incremental cost-effectiveness ratio between £10,000 and £15,000 per QALY) when the model was allowed to run for both 5 years and 10 years. A deterministic sensitivity analysis showed that the most influential factor in the model is the price of the polypill.

Consequences

This study shows that a polypill strategy for primary prevention for cardiovascular disease is cost effective for a British population aged between 50-70 years olds at intermediate cardiac risk. Further examination and sensitivity analyses will be presented around the model assumptions.