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基于人群的青光眼筛查在中国的成本效益和成本效用:决策分析马尔可夫模型。

Cost-effectiveness and cost-utility of population-based glaucoma screening in China: a decision-analytic Markov model.

机构信息

School of Agricultural Economics and Rural Development, Renmin University of China, Beijing, China; Centre for Public Health, Queen's University Belfast, Belfast, UK.

The Eye Hospital, School of Optometry and Ophthalmology, Wenzhou Medical University, Wenzhou, Zhejiang, China; Glaucoma Institute, Wenzhou Medical University, Wenzhou, Zhejiang, China.

出版信息

Lancet Glob Health. 2019 Jul;7(7):e968-e978. doi: 10.1016/S2214-109X(19)30201-3. Epub 2019 May 20.

Abstract

BACKGROUND

Glaucoma, particularly primary angle closure glaucoma (PACG), is a leading cause of global blindness. Nearly half of all people with PACG are of Chinese descent. Population-level glaucoma screening has generally not been found to be cost-effective in high-income countries; however, this assessment has rarely been done in low-income or middle-income countries. We aimed to assess the cost-effectiveness and cost-utility of population-level glaucoma screening in China.

METHODS

We developed decision-analytic Markov models for separate and combined screening for PACG and primary open angle glaucoma (POAG) to evaluate costs and benefits of community-level screening versus opportunistic case finding from a societal perspective. A cohort of individuals was followed in the model from age 50 years through a total of 30 1-year Markov cycles. Analyses were done separately for rural and urban settings. We did a meta-analysis of glaucoma prevalence studies in China to obtain prevalence estimates for PACG and POAG. Screening costs were taken from a Chinese screening programme and treatment costs from a tertiary Chinese eye hospital. Main outcomes were incremental cost-utility ratios (ICURs) using quality-adjusted life-years and incremental cost-effectiveness ratios (ICERs) using years of blindness avoided. We did one-way deterministic and simulated probabilistic sensitivity analyses to reflect uncertainty around ICURs and ICERs.

FINDINGS

Compared with no screening, combined screening of POAG and PACG in rural China is predicted to result in an ICUR of US$569 (95% CI 17 to 4180) and an ICER of $1280 (-58 to 7940), both of which are below the WHO cost-effectiveness threshold of one to three times rural gross domestic product. For the urban China setting, combined screening is predicted to result in fewer net costs and greater gain in health benefits than no screening. Findings were robust in all sensitivity analyses. Over 30 years, a total of 246 (95% CI 63 to 628) and 1325 (510 to 2828) years of blindness are predicted to be avoided for every 100 000 rural and urban residents screened, respectively.

INTERPRETATION

Population screening for glaucoma (POAG and PACG combined) is likely to be cost-effective in both urban and rural China. Future studies should investigate the effectiveness of interventions to improve acceptance of definitive care among people screened.

FUNDING

Ulverscroft Foundation, Wenzhou Medical University Research Fund, Zhejiang Province Health Innovation Talents Project, and Wenzhou's Ten Major Livelihood Issues 2015.

摘要

背景

青光眼,特别是原发性闭角型青光眼(PACG),是全球失明的主要原因之一。近一半的 PACG 患者为华裔。在高收入国家,人群水平的青光眼筛查一般被认为不具有成本效益;然而,在低收入和中等收入国家,这种评估很少进行。我们旨在评估在中国进行人群水平青光眼筛查的成本效益和成本效用。

方法

我们为 PACG 和原发性开角型青光眼(POAG)的单独和联合筛查开发了决策分析 Markov 模型,从社会角度评估社区水平筛查与机会性病例发现的成本和效益。该模型中,一个队列的个体从 50 岁开始,通过总共 30 个 1 年 Markov 周期进行随访。分别对农村和城市环境进行分析。我们对中国的青光眼患病率研究进行了荟萃分析,以获得 PACG 和 POAG 的患病率估计值。筛查成本来自中国的筛查计划,治疗成本来自中国的一家三级眼科医院。主要结果是使用质量调整生命年的增量成本效用比(ICUR)和使用避免失明年数的增量成本效益比(ICER)。我们进行了一次确定性和模拟概率敏感性分析,以反映对 ICUR 和 ICER 的不确定性。

结果

与不筛查相比,中国农村地区联合筛查 POAG 和 PACG 的预测结果为增量成本效用比为 569 美元(95%CI 17 至 4180 美元),增量成本效益比为 1280 美元(-58 至 7940 美元),均低于世界卫生组织成本效益阈值的一至三倍农村人均国内生产总值。对于中国城市地区,联合筛查预计将导致净成本减少,健康效益增加。所有敏感性分析的结果均稳健。在 30 年内,预计每筛查 10 万农村和城市居民,将分别避免 246 人(95%CI 63 至 628 人)和 1325 人(510 至 2828 人)失明。

解释

在中国的城市和农村地区,人群筛查(联合筛查 POAG 和 PACG)可能具有成本效益。未来的研究应调查干预措施的有效性,以提高被筛查人群对明确治疗的接受度。

资助

Ulverscroft 基金会、温州医科大学科研基金、浙江省卫生创新人才项目和温州市 2015 年十大民生问题。

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