title: The Cost-Effectiveness of Low-Cost Essential Antihypertensive Medicines for Hypertension Control in China: A Modelling Study.
abstract: BACKGROUND
  Hypertension is China's leading cardiovascular disease risk factor. Improved hypertension control in China would result in result in enormous health gains in the world's largest population. A computer simulation model projected the cost-effectiveness of hypertension treatment in Chinese adults, assuming a range of essential medicines list drug costs.
  
  
  RESULTS
  The Cardiovascular Disease Policy Model-China, a Markov-style computer simulation model, simulated hypertension screening, essential medicines program implementation, hypertension control program administration, drug treatment and monitoring costs, disease-related costs, and quality-adjusted life years (QALYs) gained by preventing cardiovascular disease or lost because of drug side effects in untreated hypertensive adults aged 35-84 y over 2015-2025. Cost-effectiveness was assessed in cardiovascular disease patients (secondary prevention) and for two blood pressure ranges in primary prevention (stage one, 140-159/90-99 mm Hg; stage two, ≥160/≥100 mm Hg). Treatment of isolated systolic hypertension and combined systolic and diastolic hypertension were modeled as a reduction in systolic blood pressure; treatment of isolated diastolic hypertension was modeled as a reduction in diastolic blood pressure. One-way and probabilistic sensitivity analyses explored ranges of antihypertensive drug effectiveness and costs, monitoring frequency, medication adherence, side effect severity, background hypertension prevalence, antihypertensive medication treatment, case fatality, incidence and prevalence, and cardiovascular disease treatment costs. Median antihypertensive costs from Shanghai and Yunnan province were entered into the model in order to estimate the effects of very low and high drug prices. Incremental cost-effectiveness ratios less than the per capita gross domestic product of China (11,900 international dollars [Int$] in 2015) were considered cost-effective. Treating hypertensive adults with prior cardiovascular disease for secondary prevention was projected to be cost saving in the main simulation and 100% of probabilistic simulation results. Treating all hypertension for primary and secondary prevention would prevent about 800,000 cardiovascular disease events annually (95% uncertainty interval, 0.6 to 1.0 million) and was borderline cost-effective incremental to treating only cardiovascular disease and stage two patients (2015 Int$13,000 per QALY gained [95% uncertainty interval, Int$10,000 to Int$18,000]). Of all one-way sensitivity analyses, assuming adherence to taking medications as low as 25%, high Shanghai drug costs, or low medication efficacy led to the most unfavorable results (treating all hypertension, about Int$47,000, Int$37,000, and Int$27,000 per QALY were gained, respectively). The strengths of this study were the use of a recent Chinese national health survey, vital statistics, health care costs, and cohort study outcomes data as model inputs and reliance on clinical-trial-based estimates of coronary heart disease and stroke risk reduction due to antihypertensive medication treatment. The limitations of the study were the use of several sources of data, limited clinical trial evidence for medication effectiveness and harms in the youngest and oldest age groups, lack of information about geographic and ethnic subgroups, lack of specific information about indirect costs borne by patients, and uncertainty about the future epidemiology of cardiovascular diseases in China.
  
  
  CONCLUSIONS
  Expanded hypertension treatment has the potential to prevent about 800,000 cardiovascular disease events annually and be borderline cost-effective in China, provided low-cost essential antihypertensive medicines programs can be implemented.
authors.affiliation: Department of Epidemiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; National Center for Cardiovascular Diseases, Beijing, China.
authors.forename: Dongfeng
authors.initials: D
authors.lastname: Gu
authors.affiliation: Department of Epidemiology, Tulane University School of Public Health and Tropical Medicine, New Orleans, Louisiana, United States of America; Department of Medicine, Tulane University School of Medicine, New Orleans, Louisiana, United States of America.
authors.forename: Jiang
authors.initials: J
authors.lastname: He
authors.affiliation: Division of General Medicine, University of California at San Francisco, San Francisco, California, United States of America.
authors.forename: Pamela G
authors.initials: PG
authors.lastname: Coxson
authors.affiliation: Division of General Medicine, Columbia University Medical Center, New York, New York, United States of America.
authors.forename: Petra W
authors.initials: PW
authors.lastname: Rasmussen
authors.affiliation: Department of Epidemiology, Fuwai Hospital, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, China; National Center for Cardiovascular Diseases, Beijing, China.
authors.forename: Chen
authors.initials: C
authors.lastname: Huang
authors.affiliation: Division of General Medicine, Columbia University Medical Center, New York, New York, United States of America.
authors.forename: Anusorn
authors.initials: A
authors.lastname: Thanataveerat
authors.affiliation: Division of General Medicine, Columbia University Medical Center, New York, New York, United States of America.
authors.forename: Keane Y
authors.initials: KY
authors.lastname: Tzong
authors.affiliation: School of Medicine and Health Management, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
authors.forename: Juyang
authors.initials: J
authors.lastname: Xiong
authors.affiliation: Department of Epidemiology, Capital Medical University Beijing Anzhen Hospital and Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, China.
authors.forename: Miao
authors.initials: M
authors.lastname: Wang
authors.affiliation: Department of Epidemiology, Capital Medical University Beijing Anzhen Hospital and Beijing Institute of Heart, Lung and Blood Vessel Diseases, Beijing, China.
authors.forename: Dong
authors.initials: D
authors.lastname: Zhao
authors.affiliation: Columbia University College of Physicians and Surgeons, New York, New York, United States of America.
authors.forename: Lee
authors.initials: L
authors.lastname: Goldman
authors.affiliation: Division of General Medicine, Columbia University Medical Center, New York, New York, United States of America; Columbia University College of Physicians and Surgeons, New York, New York, United States of America.
authors.forename: Andrew E
authors.initials: AE
authors.lastname: Moran
mesh_terms: D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D000959:Antihypertensive Agents / Q000191:economics*; D002681:China; D003198:Computer Simulation; D003362:Cost-Benefit Analysis; D016903:Drug Monitoring; D005260:Female; D006801:Humans; D006973:Hypertension / Q000188:drug therapy* / Q000191:economics*; D008297:Male; D008390:Markov Chains; D008875:Middle Aged
chemical_list: D000959:Antihypertensive Agents