BMC Medicine | |
Validation of a model to investigate the effects of modifying cardiovascular disease (CVD) risk factors on the burden of CVD: the rotterdam ischemic heart disease and stroke computer simulation (RISC) model | |
MG Myriam Hunink8  Kay-Tee Khaw5  Nicholas J Wareham3  S Matthijs Boekholdt4  Ersen B Colkesen6  Ewout W Steyerberg1  Albert Hofman2  Bart S Ferket7  Bob JH van Kempen7  | |
[1] Department of Public Health, Erasmus MC Rotterdam, dr Molewaterplein 50, Rotterdam, 3015 GE, the Netherlands;Department of Epidemiology, Erasmus MC Rotterdam, dr Molewaterplein 50, Rotterdam, 3015 GE, the Netherlands;Medical Research Council Epidemiology Unit, Hills Road, Cambridge, CB2 0QQ, UK;Department of Cardiology, Amsterdam Medical Center, Meibergdreef 9, Amsterdam, 1150 AZ, the Netherlands;Department of Public Health and Primary Care, University of Cambridge, Robinson Way, Cambridge, CB2 0SR, UK;Department of Cardiology, Antonius Hospital, Koekoekslaan 1, Nieuwegein, 3435 CM, the Netherlands;Department of Radiology, Erasmus MC Rotterdam, dr Molewaterplein 50, Rotterdam, 3015 GE, the Netherlands;Department of Health Policy and Management, Harvard School of Public Health, 677 Huntington Avenue, Boston, MA 02115, USA | |
关键词: Model validation; Simulation modeling; Cardiovascular disease prevention; | |
Others : 857266 DOI : 10.1186/1741-7015-10-158 |
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received in 2012-04-24, accepted in 2012-12-06, 发布年份 2012 | |
【 摘 要 】
Background
We developed a Monte Carlo Markov model designed to investigate the effects of modifying cardiovascular disease (CVD) risk factors on the burden of CVD. Internal, predictive, and external validity of the model have not yet been established.
Methods
The Rotterdam Ischemic Heart Disease and Stroke Computer Simulation (RISC) model was developed using data covering 5 years of follow-up from the Rotterdam Study. To prove 1) internal and 2) predictive validity, the incidences of coronary heart disease (CHD), stroke, CVD death, and non-CVD death simulated by the model over a 13-year period were compared with those recorded for 3,478 participants in the Rotterdam Study with at least 13 years of follow-up. 3) External validity was verified using 10 years of follow-up data from the European Prospective Investigation of Cancer (EPIC)-Norfolk study of 25,492 participants, for whom CVD and non-CVD mortality was compared.
Results
At year 5, the observed incidences (with simulated incidences in brackets) of CHD, stroke, and CVD and non-CVD mortality for the 3,478 Rotterdam Study participants were 5.30% (4.68%), 3.60% (3.23%), 4.70% (4.80%), and 7.50% (7.96%), respectively. At year 13, these percentages were 10.60% (10.91%), 9.90% (9.13%), 14.20% (15.12%), and 24.30% (23.42%). After recalibrating the model for the EPIC-Norfolk population, the 10-year observed (simulated) incidences of CVD and non-CVD mortality were 3.70% (4.95%) and 6.50% (6.29%). All observed incidences fell well within the 95% credibility intervals of the simulated incidences.
Conclusions
We have confirmed the internal, predictive, and external validity of the RISC model. These findings provide a basis for analyzing the effects of modifying cardiovascular disease risk factors on the burden of CVD with the RISC model.
【 授权许可】
2012 van Kempen et al; licensee BioMed Central Ltd.
【 预 览 】
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【 图 表 】
Figure 3.
【 参考文献 】
- [1]Hayward RA, Krumholz HM, Zulman DM, Timbie JW, Vijan S: Optimizing statin treatment for primary prevention of coronary artery disease. Ann Intern Med 2010, 152:69-77.
- [2]Pletcher MJ, Lazar L, Bibbins-Domingo K, Moran A, Rodondi N, Coxson P, Lightwood J, Williams L, Goldman L: Comparing impact and cost-effectiveness of primary prevention strategies for lipid-lowering. Ann Intern Med 2009, 150:243-254.
- [3]Bibbins-Domingo K, Chertow GM, Coxson PG, Moran A, Lightwood JM, Pletcher MJ, Goldman L: Projected effect of dietary salt reductions on future cardiovascular disease. N Engl J Med 2010, 362:590-599.
- [4]Hunink MGP, Siegel J, et al.: Decision making in health and medicine Integrating evidence and values. Cambridge: Cambridge University Press; 2001.
- [5]van Kempen BJH, Ferket BS, Spronk S, Hofman A, Steyerberg E, Hunink M: Do different methods of modeling statin treatment effectiveness influence the optimal decision? Med Decis Making 2012.
- [6]Philips Z, Ginnelly L, Sculpher M, Claxton K, Golder S, Riemsma R, Woolacoot N, Glanville J: Review of guidelines for good practice in decision-analytic modelling in health technology assessment. Health Technol Assess 2004, 8:iii-iv. ix-xi, 1-158
- [7]Weinstein MC, O'Brien B, Hornberger J, Jackson J, Johannesson M, McCabe C, Luce BR, Studies ITFoGRP--M: Principles of good practice for decision analytic modeling in health-care evaluation: report of the ISPOR Task Force on Good Research Practices--modeling studies. Value Health 2003, 6:9-17.
- [8]Goldhaber-Fiebert JD, Stout NK, Goldie SJ: Empirically evaluating decision-analytic models. Value Health 2010, 13:667-674.
- [9]Eddy DM, Schlessinger L: Validation of the archimedes diabetes model. Diabetes Care 2003, 26:3102-3110.
- [10]Palmer AJ, Roze S, Valentine WJ, Minshall ME, Foos V, Lurati FM, Lammert M, Spinas GA: Validation of the CORE Diabetes Model against epidemiological and clinical studies. Curr Med Res Opin 2004, 20(Suppl 1):S27-40.
- [11]Kim LG, Thompson SG: Uncertainty and validation of health economic decision models. Health Econ 2010, 19:43-55.
- [12]Welsing PM, Severens JL, Hartman M, van Gestel AM, van Riel PL, Laan RF: The initial validation of a Markov model for the economic evaluation of (new) treatments for rheumatoid arthritis. Pharmacoeconomics 2006, 24:1011-1020.
- [13]Nijhuis RL, Stijnen T, Peeters A, Witteman JC, Hofman A, Hunink MG: Apparent and internal validity of a Monte Carlo-Markov model for cardiovascular disease in a cohort follow-up study. Med Decis Making 2006, 26:134-144.
- [14]Hofman A, van Duijn CM, Franco OH, Ikram MA, Janssen HL, Klaver CC, Kuipers EJ, Nijsten TE, Stricker BH, Tiemeier H, et al.: The Rotterdam Study: 2012 objectives and design update. Eur J Epidemiol 2011, 26:657-686.
- [15]Hofman A, Grobbee DE, de Jong PT, van den Ouweland FA: Determinants of disease and disability in the elderly: the Rotterdam Elderly Study. Eur J Epidemiol 1991, 7:403-422.
- [16]Groot Koerkamp B, Weinstein MC, Stijnen T, Heijenbrok-Kal MH, Hunink MG: Uncertainty and patient heterogeneity in medical decision models. Med Decis Making 2010, 30:194-205.
- [17]Groot Koerkamp B, Stijnen T, Weinstein MC, Hunink MG: The combined analysis of uncertainty and patient heterogeneity in medical decision models. Med Decis Making 2011, 31:650-661.
- [18]Day N, Oakes S, Luben R, Khaw KT, Bingham S, Welch A, Wareham N: EPIC-Norfolk: study design and characteristics of the cohort. European Prospective Investigation of Cancer. Br J Cancer 1999, 80(Suppl 1):95-103.
- [19]Little R, An H: Robust likelihood-based analysis of multivariate data with missing values. Statistica Sinica 2004, 14:949-968.
- [20]Sinha S, Myint PK, Luben RN, Khaw KT: Accuracy of death certification and hospital record linkage for identification of incident stroke. BMC Med Res Methodol 2008, 8:74. BioMed Central Full Text
- [21]Hollander M, Koudstaal PJ, Bots ML, Grobbee DE, Hofman A, Breteler MM: Incidence, risk, and case fatality of first ever stroke in the elderly population. The Rotterdam Study. J Neurol Neurosurg Psychiatry 2003, 74:317-321.
- [22]D'Agostino RB, Grundy S, Sullivan LM, Wilson P, Group CHDRP: Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA 2001, 286:180-187.
- [23]Unal B, Capewell S, Critchley JA: Coronary heart disease policy models: a systematic review. BMC Public Health 2006, 6:213. BioMed Central Full Text
- [24]Gunning-Schepers L: The health benefits of prevention: a simulation approach. Health Policy 1989, 12:1-255.
- [25]Hamilton VH, Racicot FE, Zowall H, Coupal L, Grover SA: The cost-effectiveness of HMG-CoA reductase inhibitors to prevent coronary heart disease. Estimating the benefits of increasing HDL-C. JAMA 1995, 273:1032-1038.
- [26]Murray CJ, Lopez AD: Alternative projections of mortality and disability by cause 1990-2020: Global Burden of Disease Study. Lancet 1997, 349:1498-1504.
- [27]Weinstein MC, Coxson PG, Williams LW, Pass TM, Stason WB, Goldman L: Forecasting coronary heart disease incidence, mortality, and cost: the Coronary Heart Disease Policy Model. Am J Public Health 1987, 77:1417-1426.
- [28]Grover SA, Abrahamowicz M, Joseph L, Brewer C, Coupal L, Suissa S: The benefits of treating hyperlipidemia to prevent coronary heart disease. Estimating changes in life expectancy and morbidity. JAMA 1992, 267:816-822.
- [29]Naidoo B, Thorogood M, McPherson K, Gunning-Schepers LJ: Modelling the effects of increased physical activity on coronary heart disease in England and Wales. J Epidemiol Community Health 1997, 51:144-150.
- [30]Capewell S, Morrison CE, McMurray JJ: Contribution of modern cardiovascular treatment and risk factor changes to the decline in coronary heart disease mortality in Scotland between 1975 and 1994. Heart 1999, 81:380-386.
- [31]Pencina MJ, D'Agostino RB, Larson MG, Massaro JM, Vasan RS: Predicting the 30-year risk of cardiovascular disease: the framingham heart study. Circulation 2009, 119:3078-3084.
- [32]Ankle Brachial Index C, Fowkes FG, Murray GD, Butcher I, Heald CL, Lee RJ, Chambless LE, Folsom AR, Hirsch AT, Dramaix M, et al.: Ankle brachial index combined with Framingham Risk Score to predict cardiovascular events and mortality: a meta-analysis. JAMA 2008, 300:197-208.
- [33]van Kempen BJ, Ferket BS, Hofman A, Spronk S, Steyerberg E, Hunink MG: Do different methods of modeling statin treatment effectiveness influence the optimal decision? Med Decis Making 2012, 32:507-516.
- [34]Kopec JA, Fines P, Manuel DG, Buckeridge DL, Flanagan WM, Oderkirk J, Abrahamowicz M, Harper S, Sharif B, Okhmatovskaia A, et al.: Validation of population-based disease simulation models: a review of concepts and methods. BMC Public Health 2010, 10:710. BioMed Central Full Text