Email Alert | RSS

Journal of Peking University (Health Sciences) ›› 2022, Vol. 54 ›› Issue (3): 443-449. doi: 10.19723/j.issn.1671-167X.2022.03.008

Previous Articles     Next Articles

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

Chao GONG1,Qiu-ping LIU1,Jia-min WANG1,Xiao-fei LIU1,Ming-lu ZHANG1,Han YANG1,Peng SHEN2,Hong-bo LIN2,Xun TANG1,*(),Pei GAO1,3,*()   

  1. 1. Department of Epidemiology and Biostatistics, Peking University School of Public Health, Beijing 100191, China
    2. Yinzhou District Center for Disease Control and Prevention, Ningbo 315101, Zhejiang, China
    3. Center of Real-World Evidence Evaluation, Peking University Clinical Research Institute, Beijing 100191, China
  • Received:2022-02-07 Online:2022-06-18 Published:2022-06-14
  • Contact: Xun TANG,Pei GAO E-mail:tangxun@bjmu.edu.cn;peigao@bjmu.edu.cn
  • Supported by:
    National Natural Sciences Foundation of China(81973132);National Key Research and Development Program of China(2020YFC2003503)

RICH HTML

 18   

PDF (PC)

147

Abstract:

Objective: To evaluate the effectiveness of statin treatment strategies based on risk assessment for the primary prevention of cardiovascular diseases by the Western guidelines in a community-based Chinese population from economically developed areas using data from the Chinese electronic health records research in Yinzhou (CHERRY) study. Methods: A Markov model was used to evaluate the effectiveness of the following statin treatment strategies, including: (1) usual care without cardiovascular risk assessment(Strategy 0); (2) using the World Health Organization (WHO) non-laboratory-based risk charts with statin treatment for high-risk group (risk ≥ 20%) (Strategy 1); (3) using the WHO laboratory-based risk charts with statin treatment for high-risk group (risk ≥ 20%) (Strategy 2); and (4) using the Prediction for Atherosclerotic cardiovascular disease Risk in China (China-PAR) model with statin treatment for high-risk group (risk ≥ 10%, Strategy 3). According to the guidelines, adults in the medium-risk group received lifestyle intervention, and adults in the high-risk group received life-style intervention and statin treatment under these strategies. The Markov model simulated different strategies for ten years (cycles) using parameters from the CHERRY study, published data, meta-analyses and systematic reviews for Chinese. The number of cardiovascular events or deaths, as well as the number need to treat (NNT) with statin per cardiovascular event or death prevented, were calculated to compare the effectiveness of different strategies. One-way sensitivity analysis on the uncertainty of incidence rate of cardiovascular diseases, and probabilistic sensitivity analysis on the uncertainty of hazard ratios of interventions were conducted. Results: Totally 225 811 Chinese adults aged 40-79 years without cardiovascular diseases at baseline were enrolled. In contrast to the usual care without risk assessment-based statin treatment strategy, Strategy 1 using the WHO non-laboratory-based risk charts could prevent 3 482 [95% uncertainty interval (UI): 2 110-4 661] cardiovascular events, Strategy 2 using the WHO laboratory-based risk charts could prevent 3 685 (95%UI: 2 255-4 912) events, and Strategy 3 using the China-PAR model could prevent 3 895 (95%UI: 2 396-5 181) events. NNTs with statin per cardiovascular event prevented were 22 (95%UI: 14-54), 21 (95%UI: 14-52), and 27 (95%UI: 17-67), respectively. Strategy 3 could prevent more cardiovascular events, while Strategies 1 and 2 required fewer numbers need to treat with statin per cardiovascular event prevented. The results were consistent in the sensitivity analyses. Conclusion: The statin treatment strategies based on risk assessment for the primary prevention of cardiovascular diseases recommended by the Western guidelines could achieve substantive health benefits in adults from developed areas of China. Using the China-PAR model for cardiovascular risk assessment could prevent more cardiovascular diseases while using the WHO risk charts seems more efficient.

Key words: Cardiovascular diseases, Primary prevention, Statin, Markov model

CLC Number: 

  • R181.2

Figure 1

Markov model diagram for statin treatment strategy based on cardiovascular risk assessment 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 CVD-free status 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 from alive with CVD status to non-CVD death status; P7, probability to stay alive with CVD."

Table 1

Parameters and data sources in the Markov model"

Items Incidence of cardiovascular diseases Mortality of cardiovascular diseases Data sources
40-49 years 50-59 years 60-69 years 70-79 years 40-49 years 50-59 years 60-69 years 70-79 years
Probability (1/100 000)
  Strategy 0, n Estimated from the current study
    Non-stratified 179 468 1 186 3 039 13 30 99 677
  Strategy 1, n Estimated from the current study
    Low risk 178 442 827 0 13 28 45 0
    Medium risk 361 667 1 305 2 448 40 49 117 458
    High risk 0 1 142 1 892 3 352 0 265 203 793
  Strategy 2, n Estimated from the current study
    Low risk 173 410 744 0 12 24 49 0
    Medium risk 687 791 1 296 2 367 67 65 107 421
    High risk 0 1 036 2 131 3 397 0 149 234 814
  Strategy 3, n Estimated from the current study
    Low risk 167 378 812 2 042 12 24 60 103
    Medium risk 449 701 1 209 2 659 40 43 96 578
    High risk 375 1 067 1 743 3 334 34 105 172 763
HR of intervention effects, ${\bar x}$±s
  Weight control 0.93±0.05 0.93±0.16 Meta-analysis[9]
  Smoking cessation 0.85±0.02 0.72±0.13 Meta-analysis[10] and cohort study[11]
  Salt reduction 0.81±0.08 0.66±0.14 Meta-analysis[12]
  Statin treatment 0.76±0.07 0.76±0.07 Clinical trial[13]

Table 2

Baseline characteristics of study population"

Characteristics Men (n=105 550) Women (n=120 261) P value
Age/years, ${\bar x}$±s 55.50 ± 9.90 54.48 ± 9.54 < 0.001
Urban, n (%) 32 394 (30.69) 39 332 (32.71) < 0.001
Smoker, n (%) 40 148 (38.04) 1 619 (1.35) < 0.001
Family history of ASCVD, n (%) 789 (0.75) 688 (0.57) < 0.001
Diabetes mellitus, n (%) 9 166 (8.68) 10 408 (8.65) 0.804
SBP/mmHg, ${\bar x}$±s 131.82 ± 15.17 130.60 ± 16.03 < 0.001
DBP/mmHg, ${\bar x}$±s 82.85 ± 9.56 81.32 ± 9.61 < 0.001
BMI/(kg/m2), ${\bar x}$±s 23.35 ± 2.68 23.23 ± 2.91 < 0.001
Waist circumference/cm, ${\bar x}$±s 83.45 ± 7.37 79.38 ± 7.73 < 0.001
Total cholesterol/(mmol/L), ${\bar x}$±s 4.80 ± 0.96 5.02 ± 0.97 < 0.001
HDL-C/(mmol/L), ${\bar x}$±s 1.25 ± 0.34 1.34 ± 0.32 < 0.001
LDL-C/(mmol/L), ${\bar x}$±s 2.77 ± 0.81 2.89 ± 0.83 < 0.001

Table 3

Comparisons of effectiveness by different strategies with statin treatment"

Strategy 1 vs. Strategy 0 Strategy 2 vs. Strategy 0 Strategy 3 vs. Strategy 0 Strategy 2 vs. Strategy 1 Strategy 3 vs. Strategy 1 Strategy 3 vs. Strategy 2
Total numbers for assessment 225 811 225 811 225 811
Total numbers for lifestyle intervention 66 781 69 433 80 418
Total numbers for statin treatment 15 806 17 815 24 568
QALYs gained 7 570 (4 843, 9 507) 7 881 (5 120, 9 853) 7 939 (5 118, 9 966) 311 (246, 365) 369 (245, 473) 57 (-12, 114)
Cardiovascular events could be prevented 3 482 (2 110, 4 661) 3 685 (2 255, 4 912) 3 895 (2 396, 5 181) 203 (143, 254) 413 (279, 525) 211 (137, 271)
Cardiovascular deaths could be prevented 1 019 (516, 1 328) 1 044 (538, 1 356) 1 040 (523, 1 357) 25 (19, 29) 21 (8, 29) -4 (-15, 3)
All deaths could be prevented 1 230 (748, 1 554) 1 286 (800, 1 615) 1 278 (782, 1 614) 55 (45, 63) 47 (31, 61) -8 (-18, 0)
NNT with statin per cardiovas- cular event prevented 22 (14, 54) 21 (14, 52) 27 (17, 67) 0 (-2, 0) 5 (3, 14) 5 (3, 16)
NNT with statin per cardiovas- cular death prevented 66 (46, 128) 69 (48, 131) 104 (72, 205) 3 (2, 3) 38 (26, 77) 35 (24, 74)
NNT with statin per all death prevented 51 (37, 85) 52 (38, 83) 78 (56, 131) 0 (-1, 1) 26 (19, 47) 26 (18, 48)

Figure 2

One-way sensitivity analyses on cardiovascular events by different incidence rates of cardiovascular diseases Strategy 0, usual care without cardiovascular risk assessment; Strategy 1, statin treatment strategy based on cardiovascular risk assessment using the WHO non-laboratory-based model; Strategy 2, statin treatment strategy based on cardiovascular risk assessment using the WHO laboratory-based model; Strategy 3, statin treatment strategy based on cardiovascular risk assessment using the China-PAR model. WHO, World Health Organization; China-PAR, prediction for atherosclerotic cardiovascular disease risk in China."

1 Mortensen MB , Nordestgaard BG . Statin use in primary prevention of atherosclerotic cardiovascular disease according to 5 major guidelines for sensitivity, specificity, and number needed to treat[J]. JAMA Cardiol, 2019, 4 (11): 1131- 1138.
doi: 10.1001/jamacardio.2019.3665
2 Arnett DK , Blumenthal RS , Albert MA , et al. 2019 ACC/AHA guideline on the primary prevention of cardiovascular disease: a report of the American College of Cardiology/American Heart Association task force on clinical practice guidelines[J]. Circulation, 2019, 140 (11): e596- e646.
3 Pearson GJ , Thanassoulis G , Anderson TJ , et al. 2021 Canadian Cardiovascular Society guidelines for the management of dyslipidemia for the prevention of cardiovascular disease in adults[J]. Can J Cardiol, 2021, 37 (8): 1129- 1150.
doi: 10.1016/j.cjca.2021.03.016
4 Kaptoge S , Pennells L , de Bacquer D , et al. World Health Organization cardiovascular disease risk charts: revised models to estimate risk in 21 global regions[J]. Lancet Glob Health, 2019, 7 (10): e1332- e1345.
doi: 10.1016/S2214-109X(19)30318-3
5 World Health Organization . HEARTS technical package for cardiovascular disease management in primary health care: risk-based CVD management[M]. Geneva: World Health Organization, 2020: 19
6 中国心血管病风险评估和管理指南编写联合委员会. 中国心血管病风险评估和管理指南[J]. 中华预防医学杂志, 2019, (1): 13- 35.
doi: 10.3760/cma.j.issn.0253-9624.2019.01.004
7 Lin H , Tang X , Shen P , et al. Using big data to improve cardiovascular care and outcomes in China: a protocol for the Chinese electronic health records research in Yinzhou (CHERRY) study[J]. BMJ Open, 2018, 8 (2): e019698.
doi: 10.1136/bmjopen-2017-019698
8 刘秋萍, 陈汐瑾, 王佳敏, 等. 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[J]. 北京大学学报(医学版), 2021, 53 (3): 460- 466.
9 Ma C , Avenell A , Bolland M , et al. Effects of weight loss interventions for adults who are obese on mortality, cardiovascular disease, and cancer: systematic review and meta-analysis[J]. BMJ, 2017, 359, j4849.
10 Tan CE , Glantz SA . Association between smoke-free legislation and hospitalizations for cardiac, cerebrovascular, and respiratory diseases[J]. Circulation, 2012, 126 (18): 2177- 2183.
doi: 10.1161/CIRCULATIONAHA.112.121301
11 Lim SH , Tai BC , Yuan JM , et al. Smoking cessation and mortality among middle-aged and elderly Chinese in Singapore: the Singapore Chinese health study[J]. Tob Control, 2013, 22 (4): 235- 240.
doi: 10.1136/tobaccocontrol-2011-050106
12 Adler AJ , Taylor F , Martin N , et al. Reduced dietary salt for the prevention of cardiovascular disease[J]. Cochrane Database Syst Rev, 2014, (12): CD009217.
13 Yusuf S , Bosch J , Dagenais G , et al. Cholesterol lowering in intermediate-risk persons without cardiovascular disease[J]. N Engl J Med, 2016, 374 (21): 2021- 2031.
doi: 10.1056/NEJMoa1600176
14 Collins R , Reith C , Emberson J , et al. Interpretation of the evidence for the efficacy and safety of statin therapy[J]. Lancet, 2016, 388 (10059): 2532- 2561.
doi: 10.1016/S0140-6736(16)31357-5
15 Pennells L , Kaptoge S , Wood A , et al. Equalization of four car-diovascular risk algorithms after systematic recalibration: individual-participant meta-analysis of 86 prospective studies[J]. Eur Heart J, 2019, 40 (7): 621- 631.
doi: 10.1093/eurheartj/ehy653
16 Pandya A , Weinstein MC , Salomon JA , et al. Who needs laboratories and who needs statins? Comparative and cost-effectiveness analyses of non-laboratory-based, laboratory-based, and staged primary cardiovascular disease screening guidelines[J]. Circ Cardiovasc Qual Outcomes, 2014, 7 (1): 25- 32.
doi: 10.1161/CIRCOUTCOMES.113.000397
17 Zhou M , Wang H , Zeng X , et al. Mortality, morbidity, and risk factors in China and its provinces, 1990—2017: a systematic analysis for the Global Burden of Disease Study 2017[J]. Lancet, 2019, 394 (10204): 1145- 1158.
doi: 10.1016/S0140-6736(19)30427-1
18 Cai T , Abel L , Langford O , et al. Associations between statins and adverse events in primary prevention of cardiovascular disease: systematic review with pairwise, network, and dose-response meta-analyses[J]. BMJ, 2021, 374, n1537.
[1] WANG Jia-min, LIU Qiu-ping, ZHANG Ming-lu, GONG Chao, LIU Shu-dan, CHEN Wei-ye, SHEN Peng, LIN Hong-bo, GAO Pei, TANG Xun. Effectiveness of different screening strategies for type 2 diabete on preventing cardiovascular diseases in a community-based Chinese population using a decision-analytic Markov model [J]. Journal of Peking University (Health Sciences), 2022, 54(3): 450-457.
[2] GUO Zi-ning, LIANG Zhi-sheng, ZHOU Yi, ZHANG Na, HUANG Jie. Genetic study of cardiovascular disease subtypes defined by International Classification of Diseases [J]. Journal of Peking University (Health Sciences), 2021, 53(3): 453-459.
[3] LIU Qiu-ping,CHEN Xi-jin,WANG Jia-min,LIU Xiao-fei,SI Ya-qin,LIANG Jing-yuan,SHEN Peng,LIN Hong-bo,TANG Xun,GAO Pei. Effectiveness of different screening strategies for cardiovascular diseases prevention in a community-based Chinese population: A decision-analytic Markov model [J]. Journal of Peking University (Health Sciences), 2021, 53(3): 460-466.
[4] Jia-li CHEN,Yue-bo JIN,Yi-fan WANG,Xiao-ying ZHANG,Jing LI,Hai-hong YAO,Jing HE,Chun LI. Clinical characteristics and risk factors of cardiovascular disease in patients with elderly-onset rheumatoid arthritis: A large cross-sectional clinical study [J]. Journal of Peking University (Health Sciences), 2020, 52(6): 1040-1047.
[5] YANG Chao, WANG Jin-wei, YANG Yao-zheng, BAI Kun-hao, GAO Bi-xia, ZHAO Ming-hui, ZHANG Lu-xia, WU Shou-ling， WANG Fang. Impact of anemia and chronic kidney disease on the risk of cardiovascular disease and all-cause mortality among diabetic patients [J]. Journal of Peking University(Health Sciences), 2018, 50(3): 495-500.
[6] SI Ya-qin, TANG Xun, ZHANG Du-dan, HE Liu, CAO Yang, WANG Jin-wei, LI Na, LIU Jian-jiang, GAO Pei, HU Yong-hua. Effectiveness of different screening strategies for primary prevention of cardiovascular diseases in a rural northern Chinese population [J]. Journal of Peking University(Health Sciences), 2018, 50(3): 443-449.
[7] TANG Xun1, ZHANG Du-dan, HE Liu, CAO Yang, WANG Jin-wei, LI Na, HUANG Shao-ping, DOU Hui-dong, GAO Pei， HU Yong-hua. Application of the China-PAR risk prediction model for atherosclerotic cardiovascular disease in a rural northern Chinese population [J]. Journal of Peking University(Health Sciences), 2017, 49(3): 439-445.
[8] JIA Li-jing, YI Liang, YANG Zhi-xu, WANG Shu-peng, LI Gang, ZHU Xi. Preventive effects of ulinastatin on acute respiratory distress syndrome [J]. Journal of Peking University(Health Sciences), 2016, 48(4): 672-679.
[9] GAO Ying, ZHU Cheng-gang, WU Na-qiong, GUO Yuan-lin, LIU Geng, DONG Qian, LI Jian-jun. Study on the reliability of CardioChek PA for measuring lipid profile [J]. Journal of Peking University(Health Sciences), 2016, 48(3): 523-528.
[10] ZHANG Jing， REN Jing-yi， CHEN Hong， HAN Guan-ping. Statins decreases expression of five inflammation-associated microRNAs in the plasma of patients with unstable angina [J]. Journal of Peking University(Health Sciences), 2015, 47(5): 761-768.
[11] 欧Meng-恩 , ZHANG Xiao, LIU Yun-Song, GE Yan-Jun, ZHOU Yong-Sheng. Ectopic osteogenesis of stromal cell-derived factor 1 combined with simvastatin loaded collagen scaffold in vivo [J]. Journal of Peking University(Health Sciences), 2015, 47(1): 47-51.
[12] XU Lu, WANG Chao, SHEN Wen-Wen, QI Rong. Effects of simvastatin nano-liposomes on osteogenic differentiation of bone marrow stromal cells [J]. Journal of Peking University(Health Sciences), 2014, 46(6): 883-888.
[13] GUAN Jing-Lin, JIANG Wen- , WANG Huai-Yu, ZENG Hui, ZHANG Su-Min, WANG Guang, MAO Jie-Ming. Multiple effect of simvastatin on vascular endothelium of hypercholesterolemia patients [J]. Journal of Peking University(Health Sciences), 2014, 46(5): 703-706.
[14] XIA Jing-Gang, QU Yang, Hu-Shao-Dong, XU Ji, YIN Chun-Lin, XU Dong. Cardioprotective effect and mechanism of intensive lipid modulation on patients with coronary artery disease undergoing noncardiac surgery [J]. Journal of Peking University(Health Sciences), 2014, 46(4): 601-605.
[15] YU Yang, SHENG Qin-Hui, ZHANG Bao-Wei, DING Wen-Hui. Left atrial size predicts adverse cardiac events in patients with non-obstruction hypertrophic cardiomyopathy [J]. Journal of Peking University(Health Sciences), 2014, 46(2): 207-210.
Viewed
Full text


Abstract

Cited
  Shared   
  Discussed   
[1] . [J]. Journal of Peking University(Health Sciences), 2009, 41(4): 456 -458 .
[2] . [J]. Journal of Peking University(Health Sciences), 2009, 41(2): 158 -161 .
[3] . [J]. Journal of Peking University(Health Sciences), 2009, 41(2): 188 -191 .
[4] . [J]. Journal of Peking University(Health Sciences), 2009, 41(3): 376 -379 .
[5] . [J]. Journal of Peking University(Health Sciences), 2009, 41(4): 459 -462 .
[6] . [J]. Journal of Peking University(Health Sciences), 2009, 41(5): 599 -601 .
[7] . [J]. Journal of Peking University(Health Sciences), 2009, 41(5): 516 -520 .
[8] . [J]. Journal of Peking University(Health Sciences), 2007, 39(3): 304 -309 .
[9] . [J]. Journal of Peking University(Health Sciences), 2007, 39(3): 315 -318 .
[10] . [J]. Journal of Peking University(Health Sciences), 2007, 39(3): 319 -322 .
Copyright © Journal of Peking University (Health Sciences), All Rights Reserved.
Powered by Beijing Magtech Co. Ltd