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Journal of Peking University (Health Sciences) ›› 2021, Vol. 53 ›› Issue (3): 460-466. doi: 10.19723/j.issn.1671-167X.2021.03.004

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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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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

CLC Number: 

  • R181.32

Figure 1

Markov model diagram for screening of cardiovascular diseases CVD, cardiovascular diseases; P1, probability from CVD-free status to alive with CVD status; P2, probability from CVD-free status to CVD death status; P3, probability from alive to non-CVD death status; P4, probability to stay alive without CVD; P5, probability from alive with CVD status to CVD death status; P6, probability to stay alive with CVD."

Table 1

Parameters related to effect sizes and the data sources in Markov model"

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]

Table 2

Baseline characteristics of study population by gender"

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

Table 3

Comparisons of effectiveness by different cardiovascular screening strategies"

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)

Figure 2

One-way sensitivity analyses on quality adjusted life years (QALYs) by different incidence rates Strategy 0, non-screening; Strategy 1, screening strategy based on cardiovascular risk charts by numbers of risk factors in adults aged 40-74 years; Strategy 2, screening strategy based on the prediction for atherosclerotic cardiovascular disease risk in China (China-PAR) models in adults aged 40-74 years; Strategy 3, screening strategy based on China-PAR models in adults aged 50-74 years."

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