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北京大学学报（医学版） ›› 2021, Vol. 53 ›› Issue (3): 460-466. doi: 10.19723/j.issn.1671-167X.2021.03.004

• 论著 • 上一篇    下一篇

基于马尔可夫模型的社区人群心血管病筛查策略的效果评价

刘秋萍1,陈汐瑾2,王佳敏1,刘晓非2,司亚琴1,梁靖媛1,沈鹏3,林鸿波3,唐迅1,Δ(),高培1,2,Δ()   

  1. 1.北京大学公共卫生学院流行病与卫生统计学系,北京 100191
    2.北京大学临床研究所真实世界证据评价中心,北京 100191
    3.宁波市鄞州区疾病预防控制中心,浙江宁波 315101
  • 收稿日期:2021-02-27 出版日期:2021-06-18 发布日期:2021-06-16
  • 通讯作者: 唐迅,高培 E-mail:tangxun@bjmu.edu.cn;peigao@bjmu.edu.cn
  • 基金资助:
    国家自然科学基金(81973132);国家自然科学基金(81961128006);国家重点研发计划(2020YFC2003503)

Effectiveness of different screening strategies for cardiovascular diseases prevention in a community-based Chinese population: A decision-analytic Markov model

LIU Qiu-ping1,CHEN Xi-jin2,WANG Jia-min1,LIU Xiao-fei2,SI Ya-qin1,LIANG Jing-yuan1,SHEN Peng3,LIN Hong-bo3,TANG Xun1,Δ(),GAO Pei1,2,Δ()   

  1. 1. Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
    2. Center for Real-world Evidence Evaluation, Peking University Clinical Research Institute, Beijing 100191, China
    3. Yinzhou District Center for Disease Control and Prevention, Ningbo 315101, Zhejiang, China
  • Received:2021-02-27 Online:2021-06-18 Published:2021-06-16
  • Contact: Xun TANG,Pei GAO E-mail:tangxun@bjmu.edu.cn;peigao@bjmu.edu.cn
  • Supported by:
    National Natural Science Foundation of China(81973132);National Natural Science Foundation of China(81961128006);National Key Research and Development Program of China(2020YFC2003503)

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摘要：

目的: 在中国鄞州电子健康档案研究(Chinese electronic health records research in Yinzhou, CHERRY)的队列人群中,评估我国不同指南最新推荐的心血管病筛查策略的效果。方法: 研究对象为2010年1月1日基线未患心血管病的40~74岁的202 179名我国沿海经济发达地区的社区人群。本研究比较的筛查策略包括:策略1,在40~74岁人群中采用2020年《中国心血管病一级预防指南》推荐的风险流程图的定性筛查策略;策略2,在40~74岁人群中采用2019年《中国心血管病风险评估和管理指南》推荐的中国动脉粥样硬化性心血管病风险预测研究(prediction for atherosclerotic cardiovascular disease risk in China, China-PAR)风险评估模型的定量筛查策略;策略3,在50~74岁人群中采用China-PAR模型的定量筛查策略。根据指南推荐,采用上述不同的筛查策略进行风险分层后,对中危及以上人群进行生活方式干预,对高危人群额外进行药物治疗干预。使用马尔可夫模型仿真,研究期限为10年,比较的效果指标包括获得的生命年、质量调整生命年(quality-adjusted life year, QALY)、可预防的心血管病发病数、心血管病死亡数与全因死亡数以及对应的需筛查人数。马尔可夫模型的参数主要来源于CHERRY队列人群、公开发表的中国人群研究数据、Meta分析及系统综述。采用单因素敏感性分析探讨一般人群心血管病发病率的不确定性对结果的影响,采用概率敏感性分析探讨风险比参数的不确定性。结果: 与不筛查相比,采用策略1、2、3获得的增量QALYs分别为1 433年[95%不确定性区间(uncertainty interval, UI): 969~1 831]、1 401年(95%UI: 936~1 807)和716年(95%UI: 265~1 111),每获得1个QALY的需筛查人数分别为141人(95%UI: 110~209)、144人(95%UI: 112~216)和198人(95%UI: 127~529)。在40~74岁人群采用风险流程图的定性筛查策略与China-PAR模型的定量筛查策略效果相似,采用China-PAR模型的定量筛查策略在40~74岁人群进行筛查比在50~74岁人群筛查能够获得更多的健康收益。单因素敏感性分析和概率敏感性分析的结果与主要分析结果一致。结论: 在我国沿海经济发达地区的40岁以上社区人群中开展心血管病筛查能够获得更多的健康收益,采用2020年《中国心血管病一级预防指南》推荐的风险流程图的定性筛查策略与2019年《中国心血管病风险评估和管理指南》推荐的China-PAR模型的定量筛查策略可获得相似的筛查效果。

关键词: 心血管疾病, 筛查, 马尔可夫模型

Abstract:

Objective: To evaluate the potential effectiveness of different screening strategies for cardiovascular diseases prevention in a community-based Chinese population from economically developed area of China. Methods: Totally 202 179 adults aged 40 to 74 years without cardiovascular diseases at baseline (January 1, 2010) were enrolled from the Chinese electronic health records research in Yinzhou (CHERRY) study. Three scenarios were considered: the screening strategy based on risk charts recommended by the 2020 Chinese guideline on the primary prevention of cardiovascular diseases in Chinese adults aged 40-74 years (Strategy 1); the screening strategy based on the prediction for atherosclerotic cardiovascular disease risk in China (China-PAR) models recommended by the 2019 Guideline on the assessment and management of cardiovascular risk in China in Chinese adults aged 40-74 years (Strategy 2); and the screening strategy based on the China-PAR models in Chinese adults aged 50-74 years (Strategy 3). According to the guidelines, individuals who were classified into medium- or high-risk groups after cardiovascular risk assessment by the corresponding strategies would be introduced to lifestyle intervention, while high-risk population would take medication in addition. Markov model was used to simulate different screening scenarios for 10 years (cycles), using parameters mainly from the CHERRY study, as well as published data, Meta-analyses and systematic reviews for Chinese populations. The life year gained, quality-adjusted life year (QALY) gained, number of cardiovascular disease events/deaths could be prevented and number needed to be screened (NNS) were calculated to compare the effectiveness between the different strategies. One-way sensitivity analysis on uncertainty of cardiovascular disease incidence rate and probabilistic sensitivity analysis on uncertainty of distributions for the hazard ratios were conducted. Results: Compared with non-screening strategy, QALYs gained were 1 433 [95% uncertainty interval (UI): 969-1 831], 1 401 (95%UI: 936-1 807), and 716 (95%UI: 265-1 111) for the Strategies 1,2, and 3; and the NNS per QALY in the above strategies were 141 (95%UI: 110-209), 144 (95%UI: 112-216), and 198 (95%UI: 127-529), respectively. The Strategies 1 and 2 based on different guidelines showed similar effectiveness, while more benefits were found for screening using China-PAR models in adults aged 40-74 years than those aged 50-74 years. The results were consistent in the sensitivity analyses. Conclusion: Screening for cardiovascular diseases in Chinese adults aged above 40 years seems effective in coastal developed areas of China, and the different screening strategies based on risk charts by the 2020 Chinese guideline on the primary prevention of cardiovascular diseases or China-PAR models by the 2019 Guideline on the assessment and management of cardiovascular risk in China may have similar effectiveness.

Key words: Cardiovascular diseases, Screening, Markov model

中图分类号: 

  • R181.32

图1

基于马尔可夫模型的心血管病筛查的状态转换结构图"

表1

马尔可夫模型中的效应值参数及来源"

Items Cardiovascular diseases incidence Cause-specific mortality on cardiovascular diseases
HR SD Data source HR SD Data source
Strategy 1
Low risk 0.64 0.01 Estimated from the current study 1
Medium risk 1.41 0.03 Estimated from the current study 1
High risk 1.89 0.04 Estimated from the current study 1.17 0.02 Cohort study[10]
Strategy 2
Low risk 0.48 0.01 Estimated from the current study 1
Medium risk 1.71 0.04 Estimated from the current study 1
High risk 3.30 0.08 Estimated from the current study 1.17 0.02 Cohort study[10]
Strategy 3
Low risk 0.66 0.02 Estimated from the current study 1
Medium risk 1.68 0.03 Estimated from the current study 1
High risk 3.33 0.07 Estimated from the current study 1.17 0.02 Cohort study[10]
Lifestyle intervention
Weight control 0.93 0.05 Meta-analysis[11] 0.93 0.16 Meta-analysis[11]
Smoke cession 0.85 0.02 Meta-analysis[12] 0.72 0.13 Cohort study[13]
Salt reduction 0.81 0.08 Meta-analysis[14] 0.66 0.14 Meta-analysis[14]
Statin and antihypertensive 0.70 0.17 Clinical trial[15] 0.82 0.13 Clinical trial[15]
Cardiovascular diseases history 1.37 0.03 Cohort study[16] 3.12 0.10 IPD-meta[17]

表2

研究人群的基线特征"

Characteristics Men(n=93 127) Women(n=109 052) P value
Age/years, $\bar{x} \pm s$ 55.8 ± 8.6 54.8 ± 8.4 <0.001
Urban, n (%) 24 821 (26.6) 31 572 (28.9) <0.001
Smoker, n (%) 41 570 (44.6) 2 219 (2.0) <0.001
Family history of ASCVD, n (%) 858 (0.9) 739 (0.7) <0.001
Diabetes mellitus, n (%) 8 486 (9.1) 11 042 (10.1) <0.001
CKD stage 3/4, n (%) 278 (0.3) 346 (0.3) 0.448
Hypertension, n (%) 28 819 (30.9) 36 153 (33.2) <0.001
Anti-hypertensive treatment, n (%) 3 779 (5.2) 5 680 (4.0) <0.001
SBP/mmHg, $\bar{x} \pm s$ 131.3 ± 16.1 130.9 ± 16.8 <0.001
DBP/mmHg, $\bar{x} \pm s$ 81.9 ± 9.6 80.9 ± 9.6 <0.001
BMI/(kg/m2), $\bar{x} \pm s$ 23.4 ± 2.7 23.4 ± 3.0 0.005
Waist circumference/cm, $\bar{x} \pm s$ 83.7 ± 8.1 80.0 ± 8.3 <0.001
Total cholesterol/(mmol/L), $\bar{x} \pm s$ 4.8 ± 1.0 5.1 ± 1.0 <0.001
HDL-C/(mmol/L), $\bar{x} \pm s$ 1.3 ± 0.4 1.4 ± 0.3 <0.001
LDL-C/(mmol/L), $\bar{x} \pm s$ 2.8 ± 0.8 3.0 ± 0.8 <0.001

表3

不同心血管病筛查策略之间的效果比较"

Measures Strategy 1
vs.
Non-screening		 Strategy 2
vs.
Non-screening		 Strategy 3
vs.
Non-screening		 Strategy 2
vs.
Strategy 1		 Strategy 2
vs.
Strategy 3
Total numbers for screening 202 179 202 179 141 729
Total numbers for lifestyle intervention 74 221 68 013 65 786
Total numbers for medication treatment 35 572 17 881 17 650
QALYs gained 1 433
(969, 1 831)		 1 401
(936, 1 807)		 716
(265, 1 111)		 -32
(-143, 76)		 685
(601, 771)
Life years gained 746
(395, 998)		 695
(379, 927)		 548
(242, 771)		 -51
(-89, 4)		 148
(130, 167)
CVD events could be prevented 1 310
(782, 1 773)		 1 344
(776, 1 853)		 321
(-238, 820)		 34
(-126, 182)		 1 023
(892, 1 150)
CVD deaths could be prevented 150
(80, 201)		 140
(76, 186)		 109
(49, 155)		 -10
(-18, 1)		 30
(27, 34)
All deaths could be prevented 150
(79, 199)		 140
(76, 185)		 109
(48, 153)		 -10
(-18, 1)		 30
(27, 34)
NNS per QALY 141
(110, 209)		 144
(112, 216)		 198
(127, 529)		 3
(-9, 19)		 -54
(-313, -15)
NNS per CVD event prevented 154
(114, 259)		 150
(109, 261)		 441
(-3 655, 4 167)		 -4
(-26, 23)		 -291
(-3 980, 3 870)
NNS per CVD death prevented 1 351
(1 008, 2 521)		 1 449
(1 084, 2 630)		 1 298
(916, 2 864)		 98
(-14, 225)		 151
(-284, 186)

图2

不同发病率对质量调整生命年影响的单因素敏感性分析"

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