This presentation is part of: Poster Session - CEA: Methods and Applications; Health Services Research
A TIME-DEPENDENT MARKOV MODEL TO EVALUATE THE COST EFFECTIVENESS OF LOSARTAN IN TREATING PATIENTS WITH HYPERTENSION AND LEFT VENTRICULAR HYPERTROPHY
Aslam H. Anis, PhD1, Huiying Sun, PhD2, Sonia Singh, MD2, John C. Woolcott, MA3, and Bohdan Nosyk, MA2. (1) University of British Columbia, Department of Health Care and Epidemiology, Vancouver, BC, Canada, (2) St. Paul's Hospital, Centre for Health Evaluation and Outcome Sciences, Vancouver, BC, Canada, (3) BC Centre for Disease Control, Vaccine and Pharmacy Services, Vancouver, BC, Canada
Purpose: A time-dependant Markov model was developed to perform an incremental cost effectiveness analysis of losartan (Cozaar™) versus atentolol as a first line anti-hypertensive agent in the prevention of cardiovascular morbidity and mortality. Methods: Using results from the Losartan Intervention for End Point Reduction in Hypertension (LIFE) trial as the source of treatment and effectiveness data, a Markov State Transition model was utilized to extrapolate the outcomes observed during the four-year trial to the patients′ lifetime. Four irreversible health states (hypertension, MI, stroke, and death) were defined to calculate costs and quality adjusted life years (QALYs) over patients′ projected lifetime. Costs and quality of life (QoL) estimates (utilities) for each of the given states were obtained from published studies The transition probability matrix for each cycle (cycle length 1 year) which allowed the transition probabilities to be time dependent and the state distribution at the end of each cycle were obtained. Moreover, the probability of patients newly transitioning into each state at each cycle was calculated. Similarly, costs were allowed to be time dependent. For example, costs incurred in the first cycle after a patient had a stroke were different from the cost incurred in the subsequent cycles. Costs associated with death due to MI or stroke were also considered. An incremental cost effectiveness ratio (ICER) for losartan versus atenolol, a first-line antihypertensive agent, assuming a discount rate of 3% for both cost and QoL were estimated. Extensive probabilistic sensitivity analyses were performed to examine the impact of a broad range of variation in our model parameters. A societal perspective was adopted. Result: The ICER of losartan versus atenolol in the treatment of patients commencing at age 67 with hypertension and left ventricular hypertrophy was CDN $1,337 (CND$1=US$0.75) per QALY gained. Probabilistic sensitivity analyses with 5000 simulations demonstrated a 50% probability that the ICER would be lower than $1,313 per QALY, a 34% probability that losartan was a dominant strategy (higher QALYs and lower cost) and a 95% probability that the ICER would be less than $18,884 per QALY. Conclusion: Losartan appears to be an effective and cost-effective alternative to traditional first-line therapies for the treatment of hypertension. The Markov model developed was appropriate because it allowed for time dependent transition probabilities, QoL, and costs.
