Validation of the Atherosclerotic Cardiovascular Disease Pooled Cohort Risk Equations
Open accessAbstract
IMPORTANCE: The American College of Cardiology/American Heart Association (ACC/AHA) Pooled Cohort risk equations were developed to estimate atherosclerotic cardiovascular disease (CVD) risk and guide statin initiation. OBJECTIVE: To assess calibration and discrimination of the Pooled Cohort risk equations in a contemporary US population. DESIGN, SETTING, AND PARTICIPANTS: Adults aged 45 to 79 years enrolled in the Reasons for Geographic and Racial Differences in Stroke (REGARDS) study between January 2003 and October 2007 and followed up through December 2010. We studied participants for whom atherosclerotic CVD risk may trigger a discussion of statin initiation (those without clinical atherosclerotic CVD or diabetes, low-density lipoprotein cholesterol level between 70 and 189 mg/dL, and not taking statins; n = 10,997). MAIN OUTCOMES AND MEASURES: Predicted risk and observed adjudicated atherosclerotic CVD incidence (nonfatal myocardial infarction, coronary heart disease [CHD] death, nonfatal or fatal stroke) at 5 years because REGARDS participants have not been followed up for 10 years. Additional analyses, limited to Medicare beneficiaries (n = 3333), added atherosclerotic CVD events identified in Medicare claims data. RESULTS: There were 338 adjudicated events (192 CHD events, 146 strokes). The observed and predicted 5-year atherosclerotic CVD incidence per 1000 person-years for participants with a 10-year predicted atherosclerotic CVD risk of less than 5% was 1.9 (95% CI, 1.3-2.7) and 1.9, respectively, risk of 5% to less than 7.5% was 4.8 (95% CI, 3.4-6.7) and 4.8, risk of 7.5% to less than 10% was 6.1 (95% CI, 4.4-8.6) and 6.9, and risk of 10% or greater was 12.0 (95% CI, 10.6-13.6) and 15.1 (Hosmer-Lemeshow χ2 = 19.9, P = .01). The C index was 0.72 (95% CI, 0.70-0.75). There were 234 atherosclerotic CVD events (120 CHD events, 114 strokes) among Medicare-linked participants and the observed and predicted 5-year atherosclerotic CVD incidence per 1000 person-years for participants with a predicted risk of less than 7.5% was 5.3 (95% CI, 2.8-10.1) and 4.0, respectively, risk of 7.5% to less than 10% was 7.9 (95% CI, 4.6-13.5) and 6.4, and risk of 10% or greater was 17.4 (95% CI, 15.3-19.8) and 16.4 (Hosmer-Lemeshow χ2 = 5.4, P = .71). The C index was 0.67 (95% CI, 0.64-0.71). CONCLUSIONS AND RELEVANCE: In this cohort of US adults for whom statin initiation is considered based on the ACC/AHA Pooled Cohort risk equations, observed and predicted 5-year atherosclerotic CVD risks were similar, indicating that these risk equations were well calibrated in the population for which they were designed to be used, and demonstrated moderate to good discrimination.
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
Overall risk prediction of the ACC/AHA ASCVD risk calculator does not differ between people with and without diabetes, despite calibration variability in some subgroups.
“Although some variability in calibration exists in various subgroups, including by sex, race, and diabetes, the overall risk prediction does not differ in those with or without diabetes (13 -16), validating the use of risk calculators in people with diabetes.”
From 10. Cardiovascular Disease and Risk Management: <i>Standards of Care in Diabetes—2023</i> (2023) · cites this paper as [15]
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Cites
(1990) · Choice Reviews Online · doi:10.5860/choice.27-3338 · Cited by 35,305 · see citing works
Friedewald, W. T., Levy, R. I., & Fredrickson, D. S. (1972) · Clinical Chemistry · doi:10.1093/clinchem/18.6.499 · Cited by 32,423 · see citing works
Hosmer, D. W., & Lemeshow, S. (2000) · doi:10.1002/0471722146 · Cited by 20,302 · see citing works
2013 ACCF/AHA Guideline for the Management of Heart Failure
Yancy, C. W., Jessup, M., Bozkurt, B., Butler, J., Casey, D. E., Drazner, M. H., Fonarow, G. C., Geraci, S. A., Horwich, T., Januzzi, J. L., et al. (2013) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2013.05.019 · Cited by 12,536 · see citing works
2013 ACC/AHA Guideline on the Assessment of Cardiovascular Risk
Goff, D. C., Lloyd-Jones, D. M., Bennett, G., Coady, S., D’Agostino, R. B., Gibbons, R., Greenland, P., Lackland, D. T., Levy, D., O’Donnell, C. J., et al. (2014) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2013.11.005 · Cited by 4,945 · see citing works
Self-citationUniversal Definition of Myocardial Infarction
Thygesen, K. A., Alpert, J. S., White, H. D., TASK FORCE MEMBERS: Chairpersons: Kristian Thygesen (Denmark), J. S. A. (., Biomarker Group: Allan S. Jaffe, C. (., ECG Group: Bernard Chaitman, C.-O. (., Imaging Group: Richard Underwood, C. (., Intervention Group: Jean-Pierre Bassand, C.-O. (., Mendis, S., Implementation Group: Lars C. Wallentin Coordinator (Sweden), F. F.-A. (., et al. (2007) · Circulation · doi:10.1161/circulationaha.107.187397 · Cited by 4,422 · see citing works
A REVIEW OF GOODNESS OF FIT STATISTICS FOR USE IN THE DEVELOPMENT OF LOGISTIC REGRESSION MODELS1
LEMESHOW, S., & HOSMER, D. W. (1982) · American Journal of Epidemiology · doi:10.1093/oxfordjournals.aje.a113284 · Cited by 1,947 · see citing works
Pencina, M. J., & D’Agostino, R. B. (2004) · Statistics in Medicine · doi:10.1002/sim.1802 · Cited by 1,446 · see citing works
The Reasons for Geographic and Racial Differences in Stroke Study: Objectives and Design
Howard, V. J., Cushman, M., Pulley, L., Gomez, C. R., Go, R. C. P., Prineas, R. J., Graham, A., Moy, C. S., & Howard, G. (2005) · Neuroepidemiology · doi:10.1159/000086678 · Cited by 1,175 · see citing works
Self-citationKokotailo, R., & Hill, M. D. (2005) · Stroke · doi:10.1161/01.str.0000174293.17959.a1 · Cited by 710 · see citing works
Validating Administrative Data in Stroke Research
Tirschwell, D., & Longstreth, W. T. (2002) · Stroke · doi:10.1161/01.str.0000032240.28636.bd · Cited by 664 · see citing works
Kiyota, Y., Schneeweiß, S., Glynn, R. J., Cannuscio, C. C., Avorn, J., & Solomon, D. H. (2004) · American Heart Journal · doi:10.1016/j.ahj.2004.02.013 · Cited by 533 · see citing works
Disparities in stroke incidence contributing to disparities in stroke mortality
Howard, V. J., Kleindorfer, D., Judd, S. E., McClure, L. A., Safford, M. M., Rhodes, J. D., Cushman, M., Moy, C. S., Soliman, E. Z., D, B. M. K. M., et al. (2011) · Annals of Neurology · doi:10.1002/ana.22385 · Cited by 488 · see citing works
Self-citationStatins: new American guidelines for prevention of cardiovascular disease
Ridker, P. M., & Cook, N. R. (2013) · The Lancet · doi:10.1016/s0140-6736(13)62388-0 · Cited by 477 · see citing works
Rosamond, W. D., Chambless, L. E., HEISS, G. M., Mosley, T. H., Coresh, J., Whitsel, E. A., Wagenknecht, L. E., Ni, H., & Folsom, A. R. (2012) · Circulation · doi:10.1161/circulationaha.111.047480 · Cited by 348 · see citing works
Verifying the Stroke-Free Phenotype by Structured Telephone Interview
Meschia, J. F., Brott, T. G., Chukwudelunzu, F. E., Hardy, J., Brown, R. D., Meissner, I., Hall, L. J., Atkinson, E. J., & O’Brien, P. C. (2000) · Stroke · doi:10.1161/01.str.31.5.1076 · Cited by 146 · see citing works
Use of Medicare Data to Identify Coronary Heart Disease Outcomes in the Women’s Health Initiative
Hlatky, M. A., Ray, R. M., Burwen, D. R., Margolis, K. L., Johnson, K., Kucharska‐Newton, A., Manson, J. E., Robinson, J. G., Safford, M. M., Allison, M., et al. (2014) · Circulation Cardiovascular Quality and Outcomes · doi:10.1161/circoutcomes.113.000373 · Cited by 84 · see citing works
Self-citationMuntner, P., Levitan, E. B., Brown, T. M., Sharma, P., Zhao, H., Bittner, V., Glasser, S. P., Kilgore, M. L., Yun, H., Woolley, J. M., et al. (2013) · The American Journal of Cardiology · doi:10.1016/j.amjcard.2013.04.041 · Cited by 62 · see citing works
Self-citationFonseca, C., Oliveira, A. G., Mota, T., et al. (2004) · European Journal of Heart Failure · doi:10.1016/j.ejheart.2004.08.003 · Cited by 46 · see citing works
Harrell, F., Jr. (1996) · doi:10.1002/(sici)1097-0258(19960229)15:4
Flagged first, then by citations
Research works printed but not linked: 7
- [2]Stone NJ Robinson J Lichtenstein AH 2013 ACC/AHA Guideline on the Treatment of Blood Cholesterol to Reduce Atherosclerotic Cardiovascular Risk in Adults: A Report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines. Circulation 12 11 2013 doi: 10.1161/1101.cir.0000437738.0000463853.0000437737a · DOI
- [4]Kleindorfer DO Khoury J Moomaw CJ Stroke incidence is decreasing in whites but not in blacks: a population-based estimate of temporal trends in stroke incidence from the Greater Cincinnati/Northern Kentucky Stroke Study. Stroke 7 2010 41 7 1326 1331 20489177 PMC2904073
- [6]Safford MM Brown TM Muntner P Asociation of race and sex with risk of incident acute coronary heart disease events in the REasons for Geographic and Racial Differences in Stroke (REGARDS) study. JAMA 2012 308 17 1768 1774 23117777 PMC3772637
- [12]Soliman EZ Howard G Cushman M Prolongation of QTc and risk of stroke: The REGARDS (REasons for Geographic and Racial Differences in Stroke) study. J Am Coll Cardiol 17 4 2012 59 16 1460 1467 22497826 PMC3345207
- [14]Luepker RV Apple FS Christenson RH Case definitions for acute coronary heart disease in epidemiology and clinical research studies: a statement from the AHA Council on Epidemiology and Prevention; AHA Statistics Committee; World Heart Federation Council on Epidemiology and Prevention; the European Society of Cardiology Working Group on Epidemiology and Prevention; Centers for Disease Control and Prevention; and the National Heart, Lung, and Blood Institute. Circulation 18 11 2003 108 20 2543 2549 14610011
- [16]Prineas RJ Crow RS Zhang ZM Minnesota Code Manual of Electrocardiographic Findings 2010 Springer-Verlag London, England 2nd edition ed.
- [28]D'Agostino RB Sr. Grundy S Sullivan LM Wilson P Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA 2001 286 2 180 187 7/11/2001 11448281
Cited by
Sorted by citations
Grundy, S. M., Stone, N. J., Bailey, A. L., Beam, C., Birtcher, K. K., Blumenthal, R. S., Braun, L. T., de Ferranti, S., Faiella-Tommasino, J., Forman, D. E., et al. (2019) · Circulation · doi:10.1161/cir.0000000000000625 · Cited by 6,185 · see citing works
Self-citationArnett, D. K., Blumenthal, R. S., Albert, M. A., Buroker, A. B., Goldberger, Z. D., Hahn, E. J., Himmelfarb, C. D., Khera, A., Lloyd-Jones, D., McEvoy, J. W., et al. (2019) · Circulation · doi:10.1161/cir.0000000000000678 · Cited by 4,536 · see citing works
Self-citationRajkomar, A., Dean, J., & Kohane, I. (2019) · New England Journal of Medicine · doi:10.1056/nejmra1814259 · Cited by 4,579 · see citing works
Grundy, S. M., Stone, N. J., Bailey, A. L., Beam, C., Birtcher, K. K., Blumenthal, R. S., Braun, L. T., de Ferranti, S., Faiella-Tommasino, J., Forman, D. E., et al. (2019) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.11.003 · Cited by 2,691 · see citing works
Self-citation2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease
Arnett, D. K., Blumenthal, R. S., Albert, M. A., Buroker, A. B., Goldberger, Z. D., Hahn, E. J., Himmelfarb, C. D., Khera, A., Lloyd-Jones, D., McEvoy, J. W., et al. (2019) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2019.03.010 · Cited by 1,896 · see citing works
Self-citationEnsuring fairness in machine learning to advance health equity.
Rajkomar, A., Hardt, M., Howell, M. D., Corrado, G., & Chin, M. H. (2018) · Annals of Internal Medicine · doi:10.7326/m18-1990 · Cited by 1,341 · see citing works
Carnethon, M. R., Pu, J., Howard, G., Albert, M. A., Anderson, C. A. M., Bertoni, A. G., Mujahid, M. S., Palaniappan, L., Taylor, H. A., Willis, M., et al. (2017) · Circulation · doi:10.1161/cir.0000000000000534 · Cited by 1,147 · see citing works
Self-citationBias in medical AI: Implications for clinical decision-making
Cross, J. L., Choma, M. A., & Onofrey, J. A. (2024) · PLOS Digital Health · doi:10.1371/journal.pdig.0000651 · Cited by 607 · see citing works
Lloyd-Jones, D. M., Braun, L. T., Ndumele, C. E., Smith, S. C., Sperling, L. S., Virani, S. S., & Blumenthal, R. S. (2019) · Circulation · doi:10.1161/cir.0000000000000638 · Cited by 554 · see citing works
Self-citation10. Cardiovascular Disease and Risk Management: <i>Standards of Medical Care in Diabetes—2020</i>
American Diabetes Association (2020) · Diabetes Care · doi:10.2337/dc20-s010 · Cited by 487 · see citing works
10. Cardiovascular Disease and Risk Management: <i>Standards of Care in Diabetes—2023</i>
ElSayed, N. A., Aleppo, G., Aroda, V. R., Bannuru, R. R., Brown, F. M., Bruemmer, D., Collins, B. S., Das, S. R., Hilliard, M. E., Isaacs, D., et al. (2023) · Diabetes Care · doi:10.2337/dc23-s010 · Cited by 465 · see citing works
10. Cardiovascular Disease and Risk Management: <i>Standards of Medical Care in Diabetes—2019</i>
American Diabetes Association (2019) · Diabetes Care · doi:10.2337/dc19-s010 · Cited by 471 · see citing works
Lloyd-Jones, D. M., Braun, L. T., Ndumele, C. E., Smith, S. C., Sperling, L. S., Virani, S. S., & Blumenthal, R. S. (2019) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.11.005 · Cited by 302 · see citing works
Self-citationVistisen, D., Andersen, G. S., Hansen, C. S., Hulman, A., Henriksen, J. E., Bech-Nielsen, H., & Jørgensen, M. E. (2016) · Circulation · doi:10.1161/circulationaha.115.018844 · Cited by 229 · see citing works
Damen, J. A., Pajouheshnia, R., Heus, P., Moons, K. G. M., Reitsma, J. B., Scholten, R. J. P. M., Hooft, L., & Debray, T. P. A. (2019) · BMC Medicine · doi:10.1186/s12916-019-1340-7 · Cited by 250 · see citing works
Machine Learning Outperforms ACC/AHA CVD Risk Calculator in MESA
Kakadiaris, I. A., Vrigkas, M., Yen, A. A., Kuznetsova, T., Budoff, M., & Naghavi, M. (2018) · Journal of the American Heart Association · doi:10.1161/jaha.118.009476 · Cited by 227 · see citing works
Sackner-Bernstein, J., Kanter, D., & Kaul, S. (2015) · PLOS ONE · doi:10.1371/journal.pone.0139817 · Cited by 220 · see citing works
Ward, A., Sarraju, A., Chung, S., Li, J., Harrington, R., Heidenreich, P., Palaniappan, L., Scheinker, D., & Rodriguez, F. (2020) · npj Digital Medicine · doi:10.1038/s41746-020-00331-1 · Cited by 112 · see citing works
The epic sepsis model falls short-the importance of external validation
Habib, A. R., Lin, A. L., & Grant, R. W. (2021) · JAMA Internal Medicine · doi:10.1001/jamainternmed.2021.3333 · Cited by 101 · see citing works
Predicting inpatient medication orders from electronic health record data
Rough, K., Dai, A. M., Zhang, K., Xue, Y., Vardoulakis, L. M., Cui, C., Butte, A. J., Howell, M. D., & Rajkomar, A. (2020) · Clinical Pharmacology & Therapeutics · doi:10.1002/cpt.1826 · Cited by 28 · see citing works
Cardiovascular risk reduction following metabolic and bariatric surgery.
Albaugh, V. L., Kindel, T. L., Nissen, S. E., & Aminian, A. (2021) · Surgical Clinics of North America · doi:10.1016/j.suc.2020.12.012 · Cited by 21 · see citing works
- Authors
- Muntner, P., Colantonio, L. D., Cushman, M., Goff, D. C., Howard, G., Howard, V. J., Kissela, B., Levitan, E. B., Lloyd-Jones, D. M., & Safford, M. M.
- Affiliations
- University of Alabama at Birmingham (US)
- University of Vermont (US)
- Colorado School of Public Health (US)
- Department of Neurology and Rehabilitation Medicine, University of Cincinnati, Cincinnati, Ohio
- Department of Preventive Medicine, Northwestern University Feinberg School of Medicine, Chicago, Illinois
- ORCID
- Venue
- JAMA
- Publisher
- American Medical Association (AMA)
- Published
- 2014-04-09
- Volume
- 311
- Issue
- 14
- Pages
- 1406
- ISSN
- 0002-9955 (ISSN-L)
- 0098-7484
- PMC
- PMC4189930
- OpenAlex
- W2096849439
- Cited by
- 603
- References
- 21
- Citations by year
- 2026: 25 · 2025: 38 · 2024: 49 · 2023: 40 · 2022: 53 · 2021: 60 · 2020: 59 · 2019: 48 · 2018: 31 · 2017: 47 · 2016: 61 · 2015: 59 · 2014: 30 · 2013: 1
- FWCI
- 65.16
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- JAMA (publishedVersion)
- PubMed (publishedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- Funders
- National Institutes of Health (UL1TR001425)
- National Heart, Lung, and Blood Institute (R01HL080477, K24HL111154)
- National Institute of Diabetes and Digestive and Kidney Diseases (P30DK079626)
- National Institute of Neurological Disorders and Stroke (U01NS041588, R01NS041588)
- National Center for Advancing Translational Sciences
- National Institute on Minority Health and Health Disparities (P20MD006899)
- Topics
- Health Sciences › Medicine › Surgery › Lipoproteins and Cardiovascular Health
- Health Sciences › Medicine › Public Health, Environmental and Occupational Health › Health Promotion and Cardiovascular Prevention
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- atherosclerotic cardiovascular disease, Pooled Cohort Equations, risk prediction model validation, calibration, discrimination (statistics), statin initiation, coronary artery disease, stroke, myocardial infarction, REGARDS study, Medicare beneficiaries, low LDL cholesterol, cardiovascular risk assessment, coronary heart disease mortality, stroke mortality
- MeSH terms
- Aged, Cardiovascular Diseases, Female, Humans, Hyperlipidemias, Interviews as Topic, Male, Middle Aged, Risk, United States, Cohort Studies, Incidence, Risk Assessment, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Atherosclerosis, Mathematical Concepts
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review