Evidence map›Paper›PMID 32713271›Full record

ArticleHypertension (Dallas, Tex. : 1979)2020

Cost-Effectiveness of Drug Treatment for Chinese Patients With Stage I Hypertension According to the 2017 Hypertension Clinical Practice Guidelines.

Yan-Feng Zhou, Na Liu, Pei Wang, Jae Jeong Yang, Xing-Yue Song, Xiong-Fei Pan, Xiaomin Zhang, Meian He, Honglan Li, Yu-Tang Gao and 4 more

Open access · bronzeAbstract read
In one paragraph

Article in Hypertension (Dallas, Tex. : 1979), 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
16citing papers in PubMed, 4 pooled it
1.6field-weighted citation impact, top 14% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

16 citing papers in PubMed, 4 syntheses or guidelines pooled it, 21 citations in OpenAlex.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

14 authors at 4 institutions in 2 countries.

Yan-Feng ZhouFrom the Department of Epidemiology and Biostatistics (Y.-F.Z., N.L., X.-Y.S., X.-F.P., A.P.), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Na LiuFrom the Department of Epidemiology and Biostatistics (Y.-F.Z., N.L., X.-Y.S., X.-F.P., A.P.), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Pei WangDepartment of Health Economics, School of Public Health, Fudan University, Shanghai, China (P.W.).
Jae Jeong YangVanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN (J.J.Y., D.Y.).
Xing-Yue SongFrom the Department of Epidemiology and Biostatistics (Y.-F.Z., N.L., X.-Y.S., X.-F.P., A.P.), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xiong-Fei PanFrom the Department of Epidemiology and Biostatistics (Y.-F.Z., N.L., X.-Y.S., X.-F.P., A.P.), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Xiaomin ZhangDepartment of Occupational and Environmental Health (X.Z., M.H., T.W.), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Meian HeDepartment of Occupational and Environmental Health (X.Z., M.H., T.W.), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Honglan LiState Key Laboratory of Oncogene and Related Genes and Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China (H.L., Y.-T.G., Y.-B.X.).
Yu-Tang GaoState Key Laboratory of Oncogene and Related Genes and Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China (H.L., Y.-T.G., Y.-B.X.).
Yong-Bing XiangState Key Laboratory of Oncogene and Related Genes and Department of Epidemiology, Shanghai Cancer Institute, Renji Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China (H.L., Y.-T.G., Y.-B.X.).
Tangchun WuDepartment of Occupational and Environmental Health (X.Z., M.H., T.W.), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Danxia YuVanderbilt Epidemiology Center, Vanderbilt University Medical Center, Nashville, TN (J.J.Y., D.Y.).
An PanFrom the Department of Epidemiology and Biostatistics (Y.-F.Z., N.L., X.-Y.S., X.-F.P., A.P.), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, China.
Huazhong University of Science and Technology · CNState Key Laboratory of Oncogene and Related Genes · CNVanderbilt University Medical Center · USFudan University · CN

Funding

Cohort Study of Cancer inhibitory Factors in MenR01CA082729 · NCI · VANDERBILT UNIVERSITY · PI SHU, XIAO-OU · 2001 to 2011
$6.3M
Shanghai Womens Health StudyUM1CA182910 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI ZHENG, WEI · 2014 to 2018
$5.9M
Shanghai Men's Health StudyUM1CA173640 · NCI · VANDERBILT UNIVERSITY MEDICAL CENTER · PI SHU, XIAO-OU · 2013 to 2017
$4.9M
NCI NIH HHS R01 CA082729NCI NIH HHS UM1 CA173640NCI NIH HHS UM1 CA182910
6 · The paper itself

Abstract

Systolic/diastolic blood pressure of 130 to 139/80 to 89 mm Hg has been defined as stage I hypertension by the 2017 Hypertension Clinical Practice Guidelines. Drug treatment is recommended for stage I hypertensive patients aged ≥65 years without cardiovascular disease in the 2017 Hypertension Clinical Practice Guidelines but not in the 2018 Chinese guidelines. However, the cost-effectiveness of drug treatment among this subgroup of Chinese patients is unclear. This study developed a microsimulation model to compare costs and effectiveness of drug treatment and nondrug treatment for the subgroup of stage I hypertensive patients over a lifetime horizon from a government affordability perspective. Event rates of mortality and cardiovascular complications were estimated from 3 cohorts in the Chinese population. Costs and health utilities were obtained from the national statistics report and published literature. The model predicted that drug treatment generated quality-adjusted life-years of 13.52 and associated with expected costs of $6825 in comparison with 13.81 and $7328 produced by nondrug treatment over a lifetime horizon among stage I hypertensive patients aged ≥65 years without cardiovascular disease. At a willingness-to-pay threshold of $8836/quality-adjusted life-year (the GDP per capita in 2017), drug treatment only had a 1.8% probability of being cost-effective compared with nondrug treatment after 10 000 probabilistic simulations. Sensitivity analysis of treatment costs, benefits expected from treatment, health utilities, and discount rates did not change the results. Our results suggested that drug treatment was not cost-effective compared with nondrug treatment for stage I hypertensive patients aged ≥65 years without cardiovascular disease in China.

Indexed as

Antihypertensive AgentsHypertensionAgedChinaCost-Benefit AnalysisFemaleHealth Care CostsHumansMaleModels, EconomicPatient Care PlanningPractice Guidelines as TopicQuality-Adjusted Life YearsSeverity of Illness IndexAntihypertensive AgentsAmerican Heart AssociationAsian continental ancestry groupcost-benefit analysisquality-adjusted life-years

Identifiers

PMID32713271
PMCPMC7429361
OpenAlexW3045345078

What OpenQuestion holds

Textmetadata
LicenceTDM
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.