BMC Cardiovascular Disorders | |
Identification of effective screening strategies for cardiovascular disease prevention in a developing country: using cardiovascular risk-estimation and risk-reduction tools for policy recommendations | |
Michiel L Bots1  Kee Chee Cheong3  Adam Bujang2  Tee Guat Hiong4  Gurpreet Kaur4  Jamaiyah Haniff2  Sharmini Selvarajah5  | |
[1] Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, The Netherlands;Clinical Research Centre, Ministry of Health Malaysia, Kuala Lumpur, Malaysia;Institute for Medical Research, Ministry of Health Malaysia, Kuala Lumpur, Malaysia;Institute for Public Health, Ministry of Health Malaysia, Kuala Lumpur, Malaysia;Julius Centre University of Malaya, Kuala Lumpur, Malaysia | |
关键词: Screening; Policy; Cardiovascular disease; Cardiovascular risk; | |
Others : 857848 DOI : 10.1186/1471-2261-13-10 |
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received in 2012-05-03, accepted in 2013-02-19, 发布年份 2013 | |
【 摘 要 】
Background
Recent increases in cardiovascular risk-factor prevalences have led to new national policy recommendations of universal screening for primary prevention of cardiovascular disease in Malaysia. This study assessed whether the current national policy recommendation of universal screening was optimal, by comparing the effectiveness and impact of various cardiovascular screening strategies.
Methods
Data from a national population based survey of 24 270 participants aged 30 to 74 was used. Five screening strategies were modelled for the overall population and by gender; universal and targeted screening (four age cut-off points). Screening strategies were assessed based on the ability to detect high cardiovascular risk populations (effectiveness), incremental effectiveness, impact on cardiovascular event prevention and cost of screening.
Results
26.7% (95% confidence limits 25.7, 27.7) were at high cardiovascular risk, men 34.7% (33.6, 35.8) and women 18.9% (17.8, 20). Universal screening identified all those at high-risk and resulted in one high-risk individual detected for every 3.7 people screened, with an estimated cost of USD60. However, universal screening resulted in screening an additional 7169 persons, with an incremental cost of USD115,033 for detection of one additional high-risk individual in comparison to targeted screening of those aged ≥35 years. The cost, incremental cost and impact of detection of high-risk individuals were more for women than men for all screening strategies. The impact of screening women aged ≥45 years was similar to universal screening in men.
Conclusions
Targeted gender- and age-specific screening strategies would ensure more optimal utilisation of scarce resources compared to the current policy recommendations of universal screening.
【 授权许可】
2013 Selvarajah et al; licensee BioMed Central Ltd.
【 预 览 】
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【 参考文献 】
- [1]Institute for Public Health, Ministry of Health Malaysia: The Third National Health and Morbidity Survey (NHMS III) 2006. Kuala Lumpur: Institute for Public Health, Ministry of Health Malaysia; 2008.
- [2]Selvarajah S, Haniff J, Kaur G, Guat Hiong T, Chee Cheong K, Lim CM: Clustering of cardiovascular risk factors in a middle-income country: a call for urgency. Eur J Prev Cardiolog 2012.
- [3]Law MR, Wald NJ: Risk factor thresholds: their existence under scrutiny. BMJ 2002, 324:1570-1576.
- [4]Powles J, Shroufi A, Mathers C, Zatonski W, Vecchia CL, Ezzati M: National cardiovascular prevention should be based on absolute disease risks, not levels of risk factors. Eur J Public Health 2010, 20:103-106.
- [5]Non Communicable Disease Section, Disease Control Division: National Strategic Plan for Non Communicable Disease. Putrajaya: Ministry of Health Malaysia; 2010.
- [6]D’Agostino RB, Vasan RS, Pencina MJ, Wolf PA, Cobain M, Massaro JM, Kannel WB: General cardiovascular risk profile for use in Primary Care. Circulation 2008, 117:743-53.
- [7]Cheng NF, Han PZ, Gansky SA: Methods and software for estimating health disparities: The case of children’s oral health. Am J Epidemiol 2008, 168:906-14.
- [8]Chamnan P, Simmons RK, Khaw K-T, Wareham NJ, Griffin SJ: Estimating the population impact of screening strategies for identifying and treating people at high risk of cardiovascular disease: modelling study. BMJ 2010, 340:c1693.
- [9]Law MR, Morris JK, Wald NJ: Use of blood pressure lowering drugs in the prevention of cardiovascular disease: meta-analysis of 147 randomised trials in the context of expectations from prospective epidemiological studies. BMJ 2009, 338:b1665.
- [10]Corvol J-C, Bouzamondo A, Sirol M, Hulot J-S, Sanchez P, Lechat P: Differential effects of lipid-lowering therapies on stroke prevention: A meta-analysis of randomized trials. Arch Intern Med 2003, 163:669-76.
- [11]Kelly TN, Bazzano LA, Fonseca VA, Thethi TK, Reynolds K, He J: Systematic Review: Glucose control and cardiovascular disease in Type 2 Diabetes. Ann Intern Med 2009, 151:394-403.
- [12]Critchley JA, Capewell S: Mortality risk reduction associated with smoking cessation in patients with Coronary Heart Disease. JAMA 2003, 290:86-97.
- [13]Diabetes Registry Malaysia: Preliminary Report of An Audit of Diabetes Control and Management (DRM-ADCM) July-December 2008. Edited by Bebakar WMW, Ismail M. Kuala Lumpur: Diabetes Registry Malaysia; 2009.
- [14]Malaysian Medical Association: Schedule of Fees: Guidelines for Medical Practitioners in Malaysia. 5th edition. Kuala Lumpur: Malaysian Medical Association; 2008.
- [15]Lawson KD, Fenwick EAL, Pell ACH, Pell JP: Comparison of mass and targeted screening strategies for cardiovascular risk: simulation of the effectiveness, cost-effectiveness and coverage using a cross-sectional survey of 3921 people. Heart 2010, 96:208-12.
- [16]Empana J, Tafflet M, Escolano S, Vergnaux AC, Bineau S, Ruidavets JB, Montaye M, Haas B, Czernichow S, Balkau B, Ducimetiere P: Predicting CHD risk in France: a pooled analysis of the D.E.S.I.R., Three City, PRIME, and SU.VI.MAX studies. Eur J Cardiovasc Prev Rehabil 2011, 18:175-85.
- [17]Zomer E, Owen A, Magliano DJ, Liew D, Reid C: Validation of two Framingham cardiovascular risk prediction algorithms in an Australian population: the ‘old’ versus the ‘new’ Framingham equation. Eur J Cardiovasc Prev Rehabil 2011, 18:115-20.
- [18]Bozorgmanesh M, Hadaegh F, Azizi F: Predictive accuracy of the ‘Framingham’s general CVD algorithm’ in a Middle Eastern population: Tehran Lipid and Glucose Study. Int J Clin Pract 2011, 65:264-73.
- [19]D’Agostino RB, Grundy S, Sullivan LM, Wilson P, CHD Risk Prediction Group: Validation of the Framingham coronary heart disease prediction scores. JAMA 2001, 286:180-7.
- [20]Liu J, Hong Y, D’Agostino RB, Wu Z, Wang W, Sun J, Wilson PWF, Kannel WB, Zhao D: Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese multi-provincial cohort study. JAMA 2004, 291:2591-9.
- [21]Yusuf S, Hawken S, Ôunpuu S, Dans T, Avezum A, Lanas F, McQueen M, Budai A, Pais P, Varigos J, Lisheng L, INTERHEART Study Investigators: Effect of potentially modifiable risk factors associated with myocardial infarction in 52 countries (the INTERHEART study): case–control study. Lancet 2004, 364:937-52.
- [22]Alkerwi A, Sauvageot N, Couffignal S, Albert A, Lair ML, Guillaume M: Comparison of participants and non-participants to the ORISCAV-LUX population-based study on cardiovascular risk factors in Luxembourg. BMC Med Res Methodol 2010, 10:80. BioMed Central Full Text
- [23]Chin CY, Pengal S: Cardiovascular disease risk in a semirural community in Malaysia. Asia Pac J Public Health 2009, 21:410-420.
- [24]Ikeda A, Iso H, Toyoshima H, Fujino Y, Mizoue T, Yoshimura T, Inaba Y, Tamakoshi A: The relationships between interest for and participation in health screening and risk of mortality: the Japan Collaborative Cohort Study. Prev Med 2005, 41(3–4):767-771.
- [25]International Diabetes Federation (IDF): Worldwide definition of the Metabolic Syndrome. Brussels: IDF; 2006.
- [26]Chobanian AV, Bakris GL, Black HR, Cushman WC, Green LA, Izzo JL Jr, Jones DW, Materson BJ, Oparil S, Wright JT Jr, Roccella EJ, National Heart, Lung and Blood Institute Joint National Committee on Prevention, Detection, Evaluation and Treatment of High Blood Pressure; National High Blood Pressure Education Program Coordinating Committee: Seventh report of the joint national committee on prevention, detection, evaluation, and treatment of high blood pressure. Hypertension 2003, 42:1206-52.
- [27]Expert Panel on Detection, Evaluation and Treatment of High Blood Cholesterol in Adults: Executive Summary of the Third Report of the National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). JAMA 2001, 285:2486-97.
- [28]World Health Organization: Definition, diagnosis and classification of Diabetes Mellitus and its Complications. Report of a WHO Consultation 1999. Geneva: World Health Organization; 1999.