Cost-utility analysis of antihypertensive medications in Nigeria: a decision analysis

The study employed decision analytic modeling. Interventions were obtained from a meta-analysis. The Markov process model calculated clinical outcomes and costs during a life cycle of 30 years of 1000 hypertensive patients stratified by 3 cardiovascular risk groups, under the alternative intervention scenarios. Quality adjusted life year (QALY) was used to quantify clinical outcome. The average cost of treatment for the 1000 patient was tracked over the Markov cycle model of the alternative interventions and results were presented in 2010 US Dollars. Probabilistic cost-effectiveness analysis was performed using Monte Carlo simulation, and results presented as cost-effectiveness acceptability frontiers. Expected value of perfect information (EVPI) and expected value of parameter perfect information (EVPPI) analyses were also conducted for the hypothetical population.Thiazide diuretic was the most cost-effective option across the 3 cardiovascular risk groups. Calcium channel blocker was the second best for Moderate risk and high risk with a willingness to pay of at least 2000$/QALY. The result was robust since it was insensitive to the parameters alteration.The result of this study showed that thiazide diuretic followed by calcium channel blocker could be a feasible strategy in order to ensure that patients in Nigeria with hypertension are better controlled.Hypertension is a disturbance in hemodynamic function in which there is persistent abnormal elevation of systemic blood pressure, whether it is diastolic or systolic above the level of normal pressure of 140/90 mmHg [1]. It is regarded as a silent killer. Hypertension has a relationship with other cardiovascular diseases. Increasing blood pressure increases the risk of developing other cardiovascular diseases like stroke or coronary heart disease (CHD) [2].There is growing evidence that prevalence of hypertension is on the increase in most sub-Saharan African countries including Nigeria [3]. A Meta analysis of prev