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Pharmacoeconomic Evaluation of Irbesartan and Bisoprolol Using Markov Model for Hypertension with Heart Failure / 中国药学杂志
Chinese Pharmaceutical Journal ; (24): 2209-2213, 2017.
Article in Chinese | WPRIM | ID: wpr-858486
ABSTRACT

OBJECTIVE:

To analyze the cost-effectiveness of irbesartan and bisoprolol using Markov model for the purpose of choosing a secure and effective therapy for hypertension with heart failure.

METHODS:

Markov state transition model was built to simulate the dynamic changes of the four states (event free, non-fatal myocardial infarction, non-fatal stoke and death) in the hypertension with heart failure patients who received the irbesartan or bisoprolol treatment. Markov model was applied using roll back analysis, Markov cohort simulation to project the costs and effectiveness for the hypertension with heart failure who had been long-term treated with irbesartan or bisoprolol. One way sensitivity analysis was carried out to determine the robustness of this baseline results.

RESULTS:

The results of cost-effectiveness analysis showed that patients receiving irbesartan cumulative costs and effects were 60 635.48 yuan and 6.22 quality-adjusted life years gained. Patients receiving bisoprolol cumulative costs and effects were 58 185.12 yuan and 6.17 quality-adjusted life years gained and the ICER was 49 007.20 yuan/QALYs. According to the sensitivity analysis, the change of key parameters in the set range did not affect the model results.

CONCLUSION:

Bisoprolol treatment is more economical than irbesartan treatment for hypertension with heart failure patients. This study could be used as methodology reference of pharmacoeconomics on the hypertension with heart failure diseases for Chinese pharmacoeconomist.

Full text: Available Index: WPRIM (Western Pacific) Type of study: Health economic evaluation Language: Chinese Journal: Chinese Pharmaceutical Journal Year: 2017 Type: Article

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Full text: Available Index: WPRIM (Western Pacific) Type of study: Health economic evaluation Language: Chinese Journal: Chinese Pharmaceutical Journal Year: 2017 Type: Article