Cardiovascular Disease Risk Assessment: Insights from Framingham

Global Heart - Tập 8 - Trang 11-23
Ralph B. D'Agostino1,2,3, Michael J. Pencina1,2,3, Joseph M. Massaro1,2,3, Sean Coady4
1Mathematics and Statistics Department, Boston University, Boston, MA, USA
2Framingham Study, Framingham, MA, USA
3Biostatistics Department, Boston University, Boston, MA, USA
4National Heart, Lung, and Blood Institute, Rockville, MD, USA

Tài liệu tham khảo

Dawber, 1980 D'Agostino, 1989, Epidemiological background and design: the Framingham study Dawber, 1951, Epidemiological approaches to heart disease: the Framingham study, Am J Public Health Nations Health, 41, 279, 10.2105/AJPH.41.3.279 Dawber, 1963, An approach to longitudinal studies in a community: the Framingham study, Ann N Y Acad Sci, 107, 539, 10.1111/j.1749-6632.1963.tb13299.x Dawber TR, Moore FE. Longitudinal study of heart disease in Framingham, Massachusetts: an interim report. In: Research in Public Health: Papers Presented at the 1951 Annual Conference of the Milbank Memorial Fund. 1952:241–247. Kannel, 1979, An investigation of coronary heart disease in families: the Framingham Offspring Study, Am J Epidemiol, 110, 281, 10.1093/oxfordjournals.aje.a112813 Splansky, 2007, The Third Generation Cohort of the National Heart, Lung, and Blood Institute's Framingham Heart Study: design, recruitment, and initial examination, Am J Epidemiol, 165, 1328, 10.1093/aje/kwm021 Kannel, 1961, Factors of risk in the development of coronary heart disease—six year follow up experience. The Framingham Study, Ann Intern Med, 55, 33, 10.7326/0003-4819-55-1-33 Kannel, 2006, Multivariate evaluation of candidates for cardiovascular disease, 3 Truett, 1967, A multivariate analysis of the risk of coronary heart disease in Framingham, J Chronic Dis, 20, 511, 10.1016/0021-9681(67)90082-3 Cornfield, 1961, Quantal response curves for experimentally uncontrolled variables, Bull Int Stat Inst, 28 Walker, 1967, Estimation of the probability of an event as a function of several independent variables, Biometrika, 54, 167, 10.1093/biomet/54.1-2.167 1973 Kannel, 1976, A general cardiovascular risk profile: the Framingham study, Am J Cardiol, 38, 46, 10.1016/0002-9149(76)90061-8 Gordon, 1982, Multiple risk functions for predicting coronary heart disease: the concepts, accuracy, and application, Am Heart J, 103, 1031, 10.1016/0002-8703(82)90567-1 D'Agostino, 1990, Relation of pooled logistic regression to time dependent Cox regression analysis: the Framingham Heart Study, Stat Med, 9, 1501, 10.1002/sim.4780091214 Anderson, 1991, An updated coronary risk profile: a statement for health professionals, Circulation, 83, 356, 10.1161/01.CIR.83.1.356 Wilson, 1998, Prediction of coronary heart disease using risk factor categories, Circulation, 97, 1837, 10.1161/01.CIR.97.18.1837 1994, National Cholesterol Education Program: Second Report of the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adults Treatment Panel II), Circulation, 89, 1333, 10.1161/01.CIR.89.3.1333 1993, The fifth report of the Joint National Committee on Detection, Evaluation, and Treatment of High Blood Pressure (JNC V), Arch Intern Med, 153, 154, 10.1001/archinte.1993.00410020010002 D'Agostino, 2001, Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic group investigation, JAMA, 286, 180, 10.1001/jama.286.2.180 Wolf, 1991, Probability of stroke: a risk profile from the Framingham study, Stroke, 22, 312, 10.1161/01.STR.22.3.312 D'Agostino, 1994, Stoke risk profile: adjustment for antihypertensive medication. The Framingham study, Stroke, 25, 40, 10.1161/01.STR.25.1.40 D'Agostino, 2000, Primary and subsequent coronary risk appraisal: new results from the Framingham study, Am Heart J, 139, 272, 10.1016/S0002-8703(00)90236-9 Murabito, 1997, Intermittent claudication: a risk profile from the Framingham study, Circulation, 96, 44, 10.1161/01.CIR.96.1.44 Kannel, 1999, Profile for estimating risk of heart failure, Arch Intern Med, 159, 1197, 10.1001/archinte.159.11.1197 Wang, 2003, A risk score for predicting stroke or death in individuals with new-onset atrial fibrillation in the community: the Framingham Heart Study, JAMA, 290, 1049, 10.1001/jama.290.8.1049 Schnabel, 2009, Development of a risk score for atrial fibrillation (Framingham Heart Study): a community-based cohort, Lancet, 373, 739, 10.1016/S0140-6736(09)60443-8 2001, 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, 285, 2486, 10.1001/jama.285.19.2486 Grundy, 1999, Primary prevention of coronary heart disease: integrating risk assessment with intervention, Circulation, 100, 988, 10.1161/01.CIR.100.9.988 Sullivan, 2004, Presentation of multivariate data for clinical use: the Framingham Study risk score functions, Stat Med, 23, 1631, 10.1002/sim.1742 D'Agostino, 2008, General cardiovascular risk profile for use in primary care: the Framingham Heart Study, Circulation, 117, 743, 10.1161/CIRCULATIONAHA.107.699579 Abbott, 1987, National Technical Information Service. The probability of developing certain cardiovascular diseases in eight years specified values of some characteristics Vine, 1994, Ischaemic heart disease and cholesterol: absolute risk more informative than relative risk, BMJ, 308, 1040 Jackson, 2000, Guidelines on preventing cardiovascular disease in clinical practice, BMJ, 320, 656, 10.1136/bmj.320.7236.659 Jackson, 2000, Updated New Zealand cardiovascular disease risk-benefit prediction guidelines, BMJ, 320, 709, 10.1136/bmj.320.7236.709 Harrell, 1996, Multivariable prognostic models: issues in developing models, evaluating assumptions and adequacy, and measuring and reducing errors, Stat Med, 15, 361, 10.1002/(SICI)1097-0258(19960229)15:4<361::AID-SIM168>3.0.CO;2-4 D'Agostino, 2003, Evaluation of the performance of survival analysis models: discrimination and calibration measures, Vol. 23, 1 Pencina, 2004, Overall C as a measure of discrimination in survival analysis: model specific population value and confidence interval estimation, Stat Med, 23, 2109, 10.1002/sim.1802 Pencina, 2012, Quantifying discrimination of Framingham risk functions with different survival C statistics, Stat Med, 31, 1543, 10.1002/sim.4508 Hosmer, 2000 Steyerberg, 2001, Internal validation of predictive models: efficiency of some procedures for logistic regression analysis, J Clin Epidemiol, 54, 774, 10.1016/S0895-4356(01)00341-9 Kannel, 2004, Concepts and usefulness of cardiovascular risk profiles, Am Heart J, 148, 16, 10.1016/j.ahj.2003.10.022 1978, Pooling Project Research Group. Relationship of blood pressure, serum cholesterol, smoking habit, relative weight, and ECG abnormalities to the incidence of major coronary events: final report of the pooling project, J Chronic Dis, 31, 201, 10.1016/0021-9681(78)90073-5 Brand, 1976, Multivariate prediction of coronary heart disease in Western Collaboration Group Study compared to findings of the Framingham study, Circulation, 53, 348, 10.1161/01.CIR.53.2.348 Leaverton, 1987, Representativeness of the Framingham risk model for coronary heart disease mortality: a comparison with a national cohort study, J Chronic Dis, 40, 775, 10.1016/0021-9681(87)90129-9 McGee, 1976, The results of the Framingham Study applied to four other US-based studies of cardiovascular disease Grundy, 2001, Cardiovascular risk assessment based on US cohort studies: findings from a National Heart, Lung, and Blood Institute workshop, Circulation, 104, 491, 10.1161/01.CIR.104.4.491 Empana, 2003, Are the Framingham and PROCAM coronary heart disease risk functions applicable to different Europeans populations? The PRIME study, Eur Heart J, 24, 1903, 10.1016/j.ehj.2003.09.002 Scheltens, 2008, Estimation of cardiovascular risk: a comparison between Framingham and the SCORE model in people under 60 years of age, Eur J Cardiovasc Prev Rehabil, 15, 562, 10.1097/HJR.0b013e3283063a65 Aktas, 2004, Global risk scores and exercise testing for predicting all-cause mortality in preventive medicine program, JAMA, 292, 1462, 10.1001/jama.292.12.1462 Barzi, 2007, Cardiovascular risk prediction tools for populations in Asia, J Epidemiol Community Health, 61, 115, 10.1136/jech.2005.044842 Hippisley-Cox, 2008, Performance of the QRISK cardiovascular risk prediction algorithm in an independent UK sample of patients from general practice: a validation study, Heart, 94, 34, 10.1136/hrt.2007.134890 Simmons, 2008, Evaluation of the Framingham risk score in the European Prospective Investigation of Cancer-Norfolk cohort: does adding glycated hemoglobin improve the prediction of coronary heart disease events?, Arch Intern Med, 168, 1209, 10.1001/archinte.168.11.1209 Brindle, 2005, The accuracy of the Framingham risk-score in different socioeconomic groups: a prospective study, Br J Gen Pract, 55, 838 May, 2006, Cardiovascular disease risk assessment in older women: can we improve on Framingham? British Women's Heart and Health prospective cohort study, Heart, 92, 1396, 10.1136/hrt.2005.085381 Ferrario, 2005, Prediction of coronary events in a low incidence population. Assessing accuracy of the CUORE Cohort Study prediction equation, Int J Epidemiol, 34, 413, 10.1093/ije/dyh405 Marrugat, 2003, An adaptation of the Framingham coronary heart disease risk function to European Mediterranean areas, J Epidemiol Community Health, 57, 634, 10.1136/jech.57.8.634 Liu, 2004, Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese Multi-Provincial Cohort Study, JAMA, 291, 2591, 10.1001/jama.291.21.2591 Kaplan, 1958, Nonparametric estimation from incomplete observations, J Am Stat Assoc, 53, 457, 10.1080/01621459.1958.10501452 D'Agostino, 1997, Measures for evaluating model performance, 253 Brindle, 2006, Primary prevention of cardiovascular disease: a web-based risk score for seven British black and minority ethnic groups, Heart, 92, 1595, 10.1136/hrt.2006.092346 Whittemore, 2010, Evaluating health risk models, Stat Med, 29, 2438, 10.1002/sim.3991 Risk Score Profiles Framingham Heart Study. Available at: http://www.framinghamheartstudy.org/risk/index.html. Accessed November 30, 2011. Koenig, 1998, Haemostatic risk factors for cardiovascular disease, Eur Heart J, 19, C39 Ridker, 1997, Inflammation, aspirin, and the risk of cardiovascular disease in apparently healthy men, N Engl J Med, 336, 973, 10.1056/NEJM199704033361401 Welch, 1998, Homocysteine and atherothrombosis, N Engl J Med, 338, 1042, 10.1056/NEJM199804093381507 Ridker, 2002, Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in prediction of first cardiovascular events, N Engl J Med, 347, 1557, 10.1056/NEJMoa021993 Rutter, 2004, C-reactive protein, the metabolic syndrome, and prediction of cardiovascular events in the Framingham Offspring Study, Circulation, 110, 380, 10.1161/01.CIR.0000136581.59584.0E Wilson, 2005, C-reactive protein and risk of cardiovascular disease in men and women from the Framingham Heart Study, Arch Intern Med, 165, 2473, 10.1001/archinte.165.21.2473 Detrano, 2008, Coronary calcium as a predictor of coronary events in four racial or ethnic groups, N Engl J Med, 358, 1336, 10.1056/NEJMoa072100 Lloyd-Jones, 2004, Parental cardiovascular disease as a risk factor for cardiovascular disease in middle-aged adults: a prospective study of parents and offspring, JAMA, 291, 2204, 10.1001/jama.291.18.2204 Folsom, 2006, An assessment of incremental coronary risk prediction using C-reactive protein and other novel risk markers: the Atherosclerosis Risk in Communities Study, Arch Intern Med, 166, 1368, 10.1001/archinte.166.13.1368 Wang, 2006, Multiple biomarkers for the prediction of first major cardiovascular events and death, N Engl J Med, 355, 2631, 10.1056/NEJMoa055373 Polak, 2011, Carotid-wall intima-media thickness and cardiovascular events, N Engl J Med, 365, 213, 10.1056/NEJMoa1012592 Thanassoulis, 2012, A genetic risk score is associated with incident cardiovascular disease and coronary artery calcium: the Framingham Heart Study, Circ Cardiovasc Genet, 5, 113, 10.1161/CIRCGENETICS.111.961342 Demler, 2011, Equivalence of improvement in area under ROC curve and linear discriminant analysis coefficient under the assumption of normality, Stat Med, 30, 1410, 10.1002/sim.4196 Demler, 2012, Misuse of DeLong test to compare AUCs for nested models, Stat Med, 31, 2577, 10.1002/sim.5328 Pencina, 2008, Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond, Stat Med, 27, 157, 10.1002/sim.2929 Pencina, 2008, Comments on integrated discrimination and net reclassification improvements—practical advice, Stat Med, 27, 207, 10.1002/sim.3106 Pencina, 2011, Extensions of net reclassification improvement calculations to measure usefulness of new biomarkers, Stat Med, 30, 11, 10.1002/sim.4085 Pencina, 2012, Novel metrics for evaluating improvement in discrimination: net reclassification and integrated discrimination improvement for normal variables and nested models, Stat Med, 31, 101, 10.1002/sim.4348 Pencina, 2012, Interpreting incremental value of markers added to risk prediction models, Am J Epidemiol, 176, 473, 10.1093/aje/kws207 Seshadri, 1997, Lifetime risk of dementia and Alzheimer's disease: the impact of mortality on risk estimates in the Framingham study, Neurology, 49, 1498, 10.1212/WNL.49.6.1498 Beiser, 2002, Computing estimates of incidence, including lifetime risk: Alzheimer's disease in the Framingham Study. The practical Incidence Estimators (PIE) macro, Stat Med, 19, 1495, 10.1002/(SICI)1097-0258(20000615/30)19:11/12<1495::AID-SIM441>3.0.CO;2-E Lloyd-Jones, 1999, Lifetime risk of developing coronary heart disease, Lancet, 353, 89, 10.1016/S0140-6736(98)10279-9 Lloyd-Jones, 2002, Lifetime risk for developing congestive heart failure: the Framingham Heart Study, Circulation, 106, 3068, 10.1161/01.CIR.0000039105.49749.6F Lloyd-Jones, 2004, Lifetime risk for development of atrial fibrillation: the Framingham Heart Study, Circulation, 110, 1042, 10.1161/01.CIR.0000140263.20897.42 Lloyd-Jones, 2003, Lifetime risk for coronary heart disease by cholesterol levels at selected age, Arch Intern Med, 163, 1966, 10.1001/archinte.163.16.1966 Pencina, 2009, Predicting the 30-year risk of cardiovascular disease: the Framingham Heart Study, Circulation, 119, 3078, 10.1161/CIRCULATIONAHA.108.816694 Lloyd-Jones, 2010, Cardiovascular risk prediction: basic concepts, current status, and future directions, Circulation, 121, 1768, 10.1161/CIRCULATIONAHA.109.849166 Conroy, 2003, Estimation of ten-year risk of fatal cardiovascular disease in Europe: the SCORE project, Eur Heart J, 24, 987, 10.1016/S0195-668X(03)00114-3 Assmann, 2002, Simple scoring scheme for calculating the risk of acute coronary events based on the 10-year follow-up of the Prospective Cardiovascular Münster (PROCAM) study, Circulation, 105, 310, 10.1161/hc0302.102575 Hippisley-Cox, 2007, Derivation and validation of QRISK, a new cardiovascular disease risk score for the United Kingdom: prospective open cohort study, BMJ, 335, 136, 10.1136/bmj.39261.471806.55 Ridker, 2007, Development and validation of improved algorithms for the assessment of global cardiovascular risk in women: the Reynolds Risk Score, JAMA, 297, 611, 10.1001/jama.297.6.611 Ridker, 2008, C-reactive protein and parental history improve global cardiovascular risk prediction: the Reynolds Risk Score for men, Circulation, 118, 2243, 10.1161/CIRCULATIONAHA.108.814251 Cooney, 2010, Cardiovascular risk-estimation system in primary prevention: do they differ? Do they make a difference? Can we see the future?, Circulation, 122, 300, 10.1161/CIRCULATIONAHA.109.852756 1989, The ARIC Investigators. The Atherosclerosis Risk in Communities (ARIC) Study: design and objective, Am J Epidemiol, 129, 687, 10.1093/oxfordjournals.aje.a115184 Fried, 1991, The Cardiovascular Health Study: design and rationale, Ann Epidemiol, 1, 263, 10.1016/1047-2797(91)90005-W Friedman, 1988, CARDIA: study design, recruitment, and some characteristics of the examined subjects, J Clin Epidemiol, 41, 1105, 10.1016/0895-4356(88)90080-7 Graham, 2008 Greenland, 2008, Stat Med, 27, 199, 10.1002/sim.2995 Steyerberg, 2010, Assessing the performance of prediction models: a framework for traditional and novel measures, Epidemiology, 21, 128, 10.1097/EDE.0b013e3181c30fb2 Khalili, 2012, Clinical usefulness of the Framingham cardiovascular risk profile beyond its statistical performance: the Tehran Lipid and Glucose Study, Am J Epidemiol, 176, 177, 10.1093/aje/kws204 D’Agostino, 2012, Invited commentary: clinical usefulness of the Framingham cardiovascular risk profile beyond its statistical performance, Am J Epidemiol, 176, 187, 10.1093/aje/kws203