You Are Here:
Date: October 2009
Summary of Recommendation
Select for a Clinical Summary of this recommendation.
This Recommendation Statement was first published in Annals of Internal Medicine in October 2009 (Annals of Internal Medicine 2009;151:474-82.). Select for copyright and source information.
|Task Force Grade Definitions
Coronary heart disease is the most common cause of mortality in adults in the United States. Treatment to prevent CHD events by modifying risk factors is currently based on the Framingham risk model, which sorts individuals into low-, intermediate-, or high-risk groups. If the risk model could be improved, treatment might be better targeted, thereby maximizing screening benefits and minimizing harms. The most likely opportunity to improve the model is use of additional risk factors to reclassify those in the intermediate-risk group to either high- or low-risk.
There is insufficient evidence to determine the percentage of persons with an intermediate CHD risk who would be reclassified by screening with nontraditional risk factors other than hs-CRP and ABI.
About 11% of men with an intermediate CHD risk would be reclassified into the high-risk category by hs-CRP screening, and about 12% of men would be reclassified into the low-risk category. National estimates of the number of women who would be reclassified by hs-CRP screening are not reliable because of small study samples. The available meta-analysis of individual data on ABI does not yield a clear picture on the proportion of intermediate-risk men who would be reclassified but does suggest that approximately 10% of women would be reclassified from intermediate to high risk for CHD.
Benefits of Detection and Early Intervention
The evidence is insufficient to determine the magnitude of any reduction in CHD events and CHD-related deaths obtained by using nontraditional risk factors in CHD screening. This constitutes a critical gap in the evidence for benefit from screening.
Harms of Detection and Early Treatment
Little evidence is available to determine the harms of using nontraditional risk factors in CHD screening. Harms include lifelong use of medications without proof of benefit but with expense and potential side effects. Statins are the class of medication most commonly used; these medications have been demonstrated to be safe but are associated with the rare but serious side effect of rhabdomyolysis.1 Psychological and other harms may result from being put into a higher risk category for CHD events.
The USPSTF concludes that the evidence is insufficient to determine the balance between benefits and harms of using nontraditional risk factors in screening for CHD risk.
Although using hs-CRP and ABI to screen men and women with intermediate Framingham CHD risk would reclassify some into the low-risk group and others into the high-risk group, the evidence is insufficient to determine the ultimate effect on the occurrence of CHD events and CHD-related deaths.
Patient Population Under Consideration
The USPSTF intends this recommendation for asymptomatic men and women with no history of CHD, diabetes, or any CHD risk equivalent.
Suggestions for Practice Regarding the I Statement
Clinicians should use the Framingham model to assess CHD risk and to guide risk-based therapy until further evidence is obtained. (See the Other Considerations section for a discussion of risk calculators.)
Because adding nontraditional risk factors to CHD assessment requires additional patient and clinical staff time and effort, routinely screening with nontraditional risk factors could result in lost opportunities for provision of other important health services of proven benefit.
Assessment of Risk
This recommendation is to be used for those who fall into a 10% to 20% (intermediate) 10-year risk category after being screened for CHD risk by using traditional CHD risk factors. Using a risk assessment tool is a key step in managing CHD risk in patients. One validated method of assessing CHD risk is the Framingham model. Persons with low (<10%) Framingham risk scores do not benefit from aggressive risk factor modification, whereas those with high (>20%) Framingham risk scores do benefit. Examples of persons who fall into the intermediate-risk category include a 60-year-old male smoker with untreated hypertension or a 60-year-old female with untreated hypertension and hyperlipidemia. The current recommendation used the Adult Treatment Panel III (ATP III) Framingham risk calculator (available at http://hp2010.nhlbihin.net/atpiii/calculator.asp?usertype.prof) and does not include diabetic populations.
About 31% of asymptomatic U.S. men and 7% of asymptomatic U.S. women age 40 to 79 years without diabetes will fall into the intermediate-risk category. No evidence or consensus is available regarding how to treat and counsel these persons.
Other USPSTF recommendations1-5 provide guidance for preventing CHD events.
Because of limitations in the evidence of effectiveness, little information is available on the cost-effectiveness of using nontraditional risk factors in CHD screening. When the evidence for effectiveness is clearer, evaluating cost-effectiveness will be a research priority.
Research Needs and Gaps
For hs-CRP, ABI, and EBCT, high priority should be given to determining the benefits and harms of aggressive treatment of persons reclassified from intermediate to high risk on the basis of additional information obtained from these tests.
For hs-CRP and ABI, future priority should be given to studies that assess the health effect of reclassifying those at high and intermediate risk for CHD events into lower-risk categories on the basis of this assessment. Similar studies for EBCT would be useful.
The predictive value and prevalence of periodontal disease, carotid IMT, and lipoprotein(a) should be examined in conjunction with traditional Framingham risk factors for predicting CHD events and death.
Various risk models for CHD are available. Some consider diabetes as a CHD equivalent and others use it as a risk factor for CHD. The predictive value and prevalence of nontraditional risk factors for predicting CHD events and death should be examined specifically in diabetic populations.
Several risk calculators are available that use data from the Framingham studies; 2 of the most commonly used are the ATP III and the traditional Framingham risk calculator (available at www.intmed.mcw.edu/clincalc/heartrisk.html). Evidence for this recommendation relied on the risk estimation from the ATP III calculator.
Burden of Disease
In the United States, CHD is the leading cause of death, accounting for 27% of all deaths in 2004.6 The decision to adopt preventive interventions as well as the intensity of these interventions are guided by a person's 10-year risk for myocardial infarction (MI) or death from CHD. Several risk calculators are available for this purpose, including the ATP III and traditional Framingham calculators.7,8 The ATP III of the National Cholesterol Education Program algorithm categorizes adults without CHD, diabetes, or noncardiac vascular disease into 3 risk categories, low (<10% risk over 10 years), intermediate (10% to 20% risk over 10 years), and high (>20% risk over 10 years), on the basis of age, sex, systolic blood pressure, serum total cholesterol level, high-density lipoprotein cholesterol level, and cigarette smoking. The traditional Framingham risk calculator uses these risk factors plus diastolic blood pressure and diabetes. Neither risk calculator takes hs-CRP, ABI, leukocyte count, fasting blood glucose, periodontal disease, carotid intimal thickness, EBCT, homocysteine, or lipoprotein(a) into account.
In the United States, approximately 31% of asymptomatic men and 7% of asymptomatic women fall into the intermediate-risk category. It would be useful if those in the intermediate category could be recategorized into the low-risk category to be reassured or into the high-risk category to be prescribed more aggressive medical management (such as treatment to lower low-density lipoprotein level or blood pressure or chemoprophylactic aspirin administration) or possibly invasive interventions (such as coronary catheterization or bypass) if such management were judged beneficial for reclassified persons.
Scope of Review
For this review, the USPSTF addressed the health benefits, including reduction in CHD events, CHD mortality, and overall mortality, of applying nontraditional risk factors to those identified as intermediate-risk by the Framingham CHD risk algorithm. The nontraditional risk factors addressed in this recommendation include ABI, leukocyte count, fasting glucose level, periodontal disease, carotid IMT, EBCT, homocysteine level, lipoprotein(a) level, and hs-CRP level. In addition to direct evidence for benefit, the USPSTF evaluated indirect evidence for the independent predictive value of these risk factors for MI and death from cardiovascular disease (CVD), the prevalence of such risk factors in intermediate- and low-risk persons, the frequency with which those in the low- and intermediate-risk groups would be restratified into high-risk groups, the benefit of aggressive medical management or other treatments of groups identified as high-risk by using these risk factors, and the harms and burdens of risk restratification resulting from use of these risk factors.9
Effectiveness, in Terms of Health Outcomes, of Using Nontraditional Risk Factors
The USPSTF found no evidence that risk stratification with any of these risk factors, either independently or in addition to Framingham risk scoring, reduces MI or CVD mortality compared with risk stratification and treatment on the basis of Framingham scoring alone. Therefore, the USPSTF examined the evidence for the independent and additive predictive value of each nontraditional risk factor in assessing 10-year risk for MI and CHD mortality. For those risk factors for which evidence for independent or additive predictive value is available, the USPSTF evaluated the evidence for the effect such factors may have on recategorizing intermediate-risk persons into low- or high-risk groups.
Independent Predictive Value of Each Risk Factor
A recent well-conducted meta-analysis of 16 population-based cohort studies concluded that lower ABI is associated with an increased risk for CVD events and mortality, independent of Framingham risk score.10 However, because of particular aspects of the meta-analysis, this evidence cannot provide an unbiased determination of how many asymptomatic men without known vascular disease would be reclassified from the intermediate classification obtained by using Framingham factors alone to a higher cardiac risk stratum. This analysis did provide an unbiased estimate that approximately 10% of women would be reclassified from intermediate to high CHD risk.
Three good- and 3 fair-quality cohort studies and 1 meta-analysis examined the value of leukocyte count in predicting CHD risk, independent of Framingham risk factors, in participants without known coronary disease.9 The results of these studies are conflicting: 4 of the studies found an independent predictive value for leukocyte count, whereas the others did not. The USPSTF concluded that there is at least fair evidence of no association between leukocyte count and the risk for coronary events.
Impaired Fasting Glucose
Fair-quality evidence indicates that impaired fasting serum glucose (defined as levels of 5.55 and 6.94 mmol/L [100 and 125 mg/dL]) is a weak predictor of CHD, independent of Framingham risk factors, in persons without diabetes. Two good- and 5 fair-quality studies had conflicting results. One good-quality study showed a weak association between fasting glucose level and CHD after 4 years of follow-up (hazard ratio, 1.09 [95% CI, 1.02 to 1.16] per 0.72-mmol/L [13-mg/dL] increase in fasting glucose level), after adjusting for Framingham risk score without diabetes,11 and the other good-quality study found no association after 8 years of follow-up (adjusted hazard ratio, 1.05 [CI, 0.94 to 1.17]).12 The remaining fair-quality cohort studies compared patients with elevated fasting glucose level with those with normal fasting glucose level and found no significant increased risk for CHD.13
Fair-quality evidence indicates that periodontal disease can predict CHD risk independent of Framingham risk factors. A meta-analysis performed by Humphrey and colleagues14 examined the results from 3 good and 4 fair-quality cohort studies in North America and Finland, which included from 175 to more than 100 000 men and women and had follow-up that ranged from 5 to 21 years; pooled data from 6 of these studies showed a risk ratio of 1.24 (CI, 1.01 to 1.51) for any CHD or CVD event. Of note, these studies did not consistently define periodontal disease or CHD outcomes.
Periodontal bone loss was an important risk factor for subsequent CHD, with 2 studies showing statistically significant relative risks that ranged from 1.36 to 1.90. A meta-analysis of 4 cohort studies showed that tooth loss, a component of periodontal disease, predicts CVD events independent of Framingham risk factors. Investigators observed a 41% increased risk for CHD or CVD events among those with 0 to 10 teeth at baseline, compared with those who had 25 to 32 teeth (combined risk estimate, 1.41 [CI, 1.22 to 1.63]).14 No information was available about prevalence or applicability in populations at intermediate risk for CHD events.
Fair-quality evidence indicates, on the basis of 1 fair- and 2 good-quality population-based longitudinal studies in the United States and the Netherlands, that carotid IMT predicts CHD independent of Framingham risk factors in asymptomatic persons (1300 to 16 000 men and women who showed a relative risk of 1.19 to 3.80).15-17 Adding carotid IMT scores to a risk prediction equation based on traditional risk factors modestly improved the prediction of subsequent CHD among healthy adults, particularly for men.18 However, the studies that show an association of carotid IMT with CHD outcome have all been done in research settings, and the ability to conduct carotid IMT with precision in nonresearch settings has not been established. No information is available about the prevalence or applicability of carotid IMT to populations at intermediate risk for CHD events.
CAC Score on EBCT
Poor- to fair-quality evidence indicates that higher CAC scores on EBCT predict CHD events independent of Framingham risk factors, on the basis of a systematic review of 8 cohort studies. Three good-quality population cohort studies and 5 fair-quality studies reported that the highest CAC score groups had significantly greater relative risk estimates than the lowest score groups.19-26 Although 3 of the studies met the technical requirements for a good-quality rating, none of them make a convincing case that CAC adds information about intermediate-risk persons. One of the 3 included only low-risk persons. Another study, from the Rotterdam Coronary Calcification Study, used self-selected participants who were classified into 2 categories (10-year Framingham risk of >20% or <20%), and results for the intermediate-risk group (10% to 20%) were therefore not reported separately. Several features of the third study, from the South Bay Heart Watch, limit its applicability to an intermediate risk group. The predictive value of a high CAC score was inconsistent; for example, participants with a Framingham risk score of 11% to 15% and participants with a risk score of 16% to 20% had the same baseline risk (7%). The CAC score also seemed to be imprecise; among participants who had a high CAC score, those with a pretest Framingham risk score of 10% to 15% had a higher posttest risk (19%) than those with a pretest score of 16% to 20%. Finally, participants were potentially self-selected.
The 5 studies rated as fair quality were primarily limited by their use of proxy measures to control for Framingham risk factors or their recruitment of self-selected participants.
In summary, although the 8 included studies consistently reported statistically significant relative risks for coronary events with increasing CAC scores, no study uniformly met all 3 of the following conditions: addressed an intermediate-risk cohort, was population-based or free of selection bias, and appropriately measured or controlled for traditional risk factors.13
Fair-quality evidence indicates that elevated homocysteine levels predict CHD events after adjustment for some Framingham risk factors; however, no studies calculated a Framingham risk score, assessed predictive value beyond Framingham risk scoring, or assessed whether homocysteine levels contribute to reclassification from intermediate to another risk category.27 Results from 21 studies in 20 cohorts were conflicting; 16 found a positive association and 5 found no association or a negative association. When all good- or fair-quality studies in participants without previous coronary disease were pooled, each 5-µmol/L increase in homocysteine level was associated with an 18% increase in the risk for coronary events (1.21 [CI, 1.10 to 1.32]).27 However, none of the studies addressed the prevalence and applicability of homocysteine level in intermediate-risk participants.
Fair-quality evidence indicates that lipoprotein(a) level predicts CHD events after adjustment for some Framingham risk factors, but no studies calculated a Framingham risk score, assessed predictive value beyond Framingham risk scoring, or assessed whether lipoprotein(a) contributes to reclassification from intermediate to another risk category. In a systematic review and meta-analysis of 4 good- and 11 fair-quality studies, 12 of the 15 found a positive association.13 A meta-analysis of the 15 fair- and good quality studies that excluded baseline CHD and CVD showed an increased relative risk of 1.59 (CI, 1.29 to 1.97) when comparing lipoprotein(a) levels of 300 mg/L or greater with levels less than 300 mg/L.13 The pooled estimate was similar among men and women, and the association between lipoprotein(a) level and CHD was greater in studies with follow-up times of more than 10 years. No studies attempted to evaluate the prevalence and applicability of lipoprotein(a) level in intermediate-risk participants.
Ten good-quality studies, 13 fair-quality studies, and 2 meta-analyses provide fair-to-good evidence that an elevated hs-CRP level predicts a higher risk for CHD events independent of Framingham risk factors.28 For studies that adjusted for all Framingham risk variables (including diabetes), the summary estimate of relative risk for incident CHD was 1.58 (CI, 1.37 to 1.83) for an hs-CRP level greater than 3.0 mg/L, compared with a level of less than 1.0 mg/L. No trials directly addressed application of hs-CRP in the intermediate-risk population.
Effectiveness of Treatment in Groups Identified as High-Risk by Nontraditional Risk Factors
The USPSTF found no evidence that using ABI in addition to Framingham-based risk assessment to guide risk factor treatment reduces CVD events more than using Framingham risk assessment alone to guide treatment.
The USPSTF found no evidence that treating persons with a high homocysteine level improves outcomes. In several well-conducted trials,29,30 homocysteine therapy did not prevent CHD events in persons with known heart disease. Trials are currently under way to evaluate the strategy of treating elevated homocysteine levels for primary prevention of CHD.31,32
The USPSTF found no evidence regarding the efficacy of preventive dental care or treatment for periodontal disease in reducing CHD events.
Lipid-lowering therapy has been shown to be associated with slowing of carotid IMT.
CAC Score on EBCT
Statins have not been shown to decrease mortality in patients screened and found to have elevated CAC scores, and evidence conflicts about whether statins produce the intermediate outcome of reduction in CAC scores.33,34
JUPITER (Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin)35 did not address the issue of whether using hs-CRP in addition to Framingham risk assessment would reduce CVD events beyond the use of Framingham risk assessment alone, and no other treatment studies answer this question. However, there are observational studies or small controlled trials showing that weight loss, exercise training, or both have been associated with reductions in hs-CRP level.36 Intervention trials in those with MI have shown that statins decrease hs-CRP level (as well as low-density lipoprotein cholesterol level), and that this reduction is independently associated with slower atherosclerotic progression.37
Potential Harms of Risk Assessment
The USPSTF found no studies that addressed the harms of assessing nontraditional risk factors and using this information for risk assessment. Electron-beam computed tomography uses the equivalent radiation of 10 chest x-rays. Potential adverse effects of using these risk factors include false-positive test results and labeling, resulting in unnecessary invasive diagnostic procedures (such as coronary angiography), and side effects of aggressive risk factor management (such as the adverse effects of antihypertensive and lipid-lowering drugs). In particular, the potential harm associated with the long-term decrease of low-density lipoprotein cholesterol to very low levels is cause for concern.
Estimate of Magnitude of Net Benefit
C-reactive protein is the only risk marker for which magnitude of benefit could be estimated by modeling based on sufficient information about predictive value and prevalence among persons at intermediate risk. Buckley and colleagues include analyses in their review28 that model the additive benefit of hs-CRP to traditional Framingham risk factors in those at intermediate risk. The model predicts that 11% of men in the intermediate group would be reclassified as high-risk; if those reclassified men are provided intensive risk-reduction therapy, it could avert 47.8 CHD events over 10 years per 1000 among men age 40 to 79 years. The net benefit of hs-CRP testing was felt to be of uncertain magnitude because of the lack of information on harms of testing and the unknown effect of intensive therapy on those who are defined as high-risk by virtue of hs-CRP testing.
Recommendations of Others
The American Heart Association encourages Framingham risk assessment in asymptomatic persons, advises against CAC assessment by EBCT in asymptomatic persons at low and high risk (those at <10% and >20% 10-year risk, respectively), and states that "it may be reasonable to consider use of CAC measurement in such patients based on available evidence that demonstrates incremental risk prediction information in this selected (intermediate-risk) patient group. This conclusion is based on the possibility that such patients might be reclassified to a higher-risk status based on high CAC score, and that subsequent patient management may be modified."38
A joint statement by the American Heart Association and the Centers for Disease Control and Prevention recommends against the use of hs-CRP as a risk marker in the general population and against the use of other inflammatory markers or acute-phase reactants for CHD risk prediction (Class III, Level of Evidence C). The recommendation states that "measurement of hs-CRP is an independent marker of risk and, in those judged at intermediate risk by global risk assessment (10 to 20% risk of CHD per 10 years), at the discretion of the physician, may help direct further evaluation and therapy in the primary prevention of CVD. The benefits of such therapy based on this strategy remain uncertain. (Class IIa, Level of Evidence B)."39
The ATP III states that homocysteine level, hs-CRP level, carotid IMT, and CAC score on EBCT may be useful in certain circumstances but does not recommend incorporating any emerging risk factors into risk assessment for all persons receiving primary prevention risk assessment.40
1. U.S. Preventive Services Task Force. Screening for lipid disorders in adults: U.S. Preventive Services Task Force recommendation statement. Rockville, MD: Agency for Healthcare Research and Quality; 2008. Accessed at www.ahrq.gov/uspstf08/lipid/lipidrs.htm on 15 July 2009.
6. Miniño AM, Heron MP, Murphy SL, Kochanek KD. Deaths: Final Data for 2004. National Vital Statistics Reports; vol 55 no 19. Hyattsville, MD: National Center for Health Statistics; 2007. Accessed at www.cdc.gov/nchs/data/nvsr/nvsr55/nvsr55_19.pdf on 15 July 2009.
7. National Heart Lung and Blood Institute, National Cholesterol Education Program; Third Report of the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Risk Assessment Tool for Estimating 10-Year Risk of Developing Hard CHD (Myocardial Infarction and Coronary Death). Bethesda, MD: National Institutes of Health; 2002. Accessed at http://hp2010.nhlbihin.net/atpiii/calculator.asp?usertype.prof on 15 July 2009.
8. Medical College of Wisconsin. Coronary Heart Disease Risk Calculator. Milwaukee, WI: Medical College of Wisconsin; 2009. Accessed at www.mcw.edu/calculators/CoronaryHeartDiseaseRisk.htm on 15 July 2009.
9. Helfand M, Buckley DI, Freeman M, Fu R, Rogers K, Fleming C, et al. Emerging risk factors for coronary heart disease: A summary of systematic reviews conducted for the U.S. Preventive Services Task Force. Ann Intern Med 2009;151:496-507.
10. Fowkes FG, Murray GD, Butcher I, Heald CL, Lee RJ, Chambless LE, et al; Ankle Brachial Index Collaboration. Ankle brachial index combined with Framingham Risk Score to predict cardiovascular events and mortality: a metaanalysis. JAMA 2008;300:197-208. [PMID: 18612117]
11. Meigs JB, Nathan DM, D'Agostino RB Sr, Wilson PW; Framingham Offspring Study. Fasting and postchallenge glycemia and cardiovascular disease risk: the Framingham Offspring Study. Diabetes Care 2002;25:1845-50. [PMID: 12351489]
12. Qiao Q, Pyörälä K, Pyörälä M, Nissinen A, Lindström J, Tilvis R, et al. Two-hour glucose is a better risk predictor for incident coronary heart disease and cardiovascular mortality than fasting glucose. Eur Heart J 2002;23:1267-75. [PMID: 12175663]
13. Helfand M, Buckley D, Fleming C, Fu R, Freeman M, Humphrey L, Rogers K, Walker M. Screening for Intermediate Risk Factors for Coronary Heart Disease: Systematic Evidence Synthesis. Evidence synthesis No. 73. AHRQ Publication No. 10-05141-EF-1. Rockville, MD: Agency for Healthcare Research and Quality; 2009.
14. Humphrey LL, Fu R, Buckley DI, Freeman M, Helfand M. Periodontal disease and coronary heart disease incidence: a systematic review and metaanalysis. J Gen Intern Med 2008;23:2079-86. [PMID: 18807098]
15. Chambless LE, Heiss G, Folsom AR, Rosamond W, Szklo M, Sharrett AR, et al. Association of coronary heart disease incidence with carotid arterial wall thickness and major risk factors: the Atherosclerosis Risk in Communities (ARIC) Study, 1987-1993. Am J Epidemiol 1997;146:483-94. [PMID: 9290509]
16. O'Leary DH, Polak JF, Kronmal RA, Manolio TA, Burke GL, Wolfson SK Jr. Carotid-artery intima and media thickness as a risk factor for myocardial infarction and stroke in older adults. Cardiovascular Health Study Collaborative Research Group. N Engl J Med 1999;340:14-22. [PMID: 9878640]
17. van der Meer IM, Bots ML, Hofman A, del Sol AI, van der Kuip DA, Witteman JC. Predictive value of noninvasive measures of atherosclerosis for incident myocardial infarction: the Rotterdam Study. Circulation 2004;109:1089-94. [PMID: 14993130]
18. Chambless LE, Folsom AR, Sharrett AR, Sorlie P, Couper D, Szklo M, et al. Coronary heart disease risk prediction in the Atherosclerosis Risk in Communities (ARIC) study. J Clin Epidemiol 2003;56:880-90. [PMID: 14505774]
20. Greenland P, LaBree L, Azen SP, Doherty TM, Detrano RC. Coronary artery calcium score combined with Framingham score for risk prediction in asymptomatic individuals. JAMA 2004;291:210-5. [PMID: 14722147]
21. Kondos GT, Hoff JA, Sevrukov A, Daviglus ML, Garside DB, Devries SS, et al. Electron-beam tomography coronary artery calcium and cardiac events: a 37-month follow-up of 5635 initially asymptomatic low- to intermediate-risk adults. Circulation 2003;107:2571-6. [PMID: 12743005]
22. LaMonte MJ, FitzGerald SJ, Church TS, Barlow CE, Radford NB, Levine BD, et al. Coronary artery calcium score and coronary heart disease events in a large cohort of asymptomatic men and women. Am J Epidemiol 2005;162:421-9. [PMID: 16076829]
24. Taylor AJ, Bindeman J, Feuerstein I, Cao F, Brazaitis M, O'Malley PG. Coronary calcium independently predicts incident premature coronary heart disease over measured cardiovascular risk factors: mean three-year outcomes in the Prospective Army Coronary Calcium (PACC) project. J Am Coll Cardiol 2005;46:807-14. [PMID: 16139129]
25. Vliegenthart R, Oudkerk M, Hofman A, Oei HH, van Dijck W, van Rooij FJ, et al. Coronary calcification improves cardiovascular risk prediction in the elderly. Circulation 2005;112:572-7. [PMID: 16009800]
26. Wong ND, Hsu JC, Detrano RC, Diamond G, Eisenberg H, Gardin JM. Coronary artery calcium evaluation by electron beam computed tomography and its relation to new cardiovascular events. Am J Cardiol 2000;86:495-8. [PMID: 11009264]
28. Buckley DI, Fu R, Freeman M, Rogers K, Helfand M. C-reactive protein as a risk factor for coronary heart disease: a systematic review and meta-analyses for the U.S. Preventive Services Task Force. Ann Intern Med 2009;151:483-95.
29. Bønaa KH, Njølstad I, Ueland PM, Schirmer H, Tverdal A, Steigen T, et al; NORVIT Trial Investigators. Homocysteine lowering and cardiovascular events after acute myocardial infarction. N Engl J Med 2006;354:1578-88. [PMID: 16531614]
30. Lonn E, Yusuf S, Arnold MJ, Sheridan P, Pogue J, Micks M, et al; Heart Outcomes Prevention Evaluation (HOPE) 2 Investigators. Homocysteine lowering with folic acid and B vitamins in vascular disease. N Engl J Med 2006;354:1567-77. [PMID: 16531613]
31. MacMahon M, Kirkpatrick C, Cummings CE, Clayton A, Robinson PJ, Tomiak RH, et al. A pilot study with simvastatin and folic acid/vitamin B12 in preparation for the Study of the Effectiveness of Additional Reductions in Cholesterol and Homocysteine (SEARCH). Nutr Metab Cardiovasc Dis 2000;10:195-203. [PMID: 11079257]
32. Bassuk SS, Albert CM, Cook NR, Zaharris E, MacFadyen JG, Danielson E, et al. The Women's Antioxidant Cardiovascular Study: design and baseline characteristics of participants. J Womens Health (Larchmt) 2004;13:99-117. [PMID: 15006283]
33. Arad Y, Spadaro LA, Roth M, Newstein D, Guerci AD. Treatment of asymptomatic adults with elevated coronary calcium scores with atorvastatin, vitamin C, and vitamin E: the St. Francis Heart Study randomized clinical trial. J Am Coll Cardiol 2005;46:166-72. [PMID: 15992652]
34. Achenbach S, Ropers D, Pohle K, Leber A, Thilo C, Knez A, et al. Influence of lipid-lowering therapy on the progression of coronary artery calcification: a prospective evaluation. Circulation 2002;106:1077-82. [PMID: 12196332]
35. Ridker PM, Danielson E, Fonseca FA, Genest J, Gotto AM Jr, Kastelein JJ, et al; JUPITER Study Group. Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein. N Engl J Med 2008;359:2195-207. [PMID: 18997196]
36. Ridker PM, Group JS; JUPITER Study Group. Rosuvastatin in the primary prevention of cardiovascular disease among patients with low levels of low-density lipoprotein cholesterol and elevated high-sensitivity C-reactive protein: rationale and design of the JUPITER trial. Circulation 2003;108:2292-7. [PMID: 14609996]
37. Ridker PM, Cannon CP, Morrow D, Rifai N, Rose LM, McCabe CH, et al; Pravastatin or Atorvastatin Evaluation and Infection Therapy-Thrombolysis in Myocardial Infarction 22 (PROVE IT-TIMI 22) Investigators. C-reactive protein levels and outcomes after statin therapy. N Engl J Med 2005;352:20-8. [PMID: 15635109]
38. Greenland P, Bonow RO, Brundage BH, Budoff MJ, Eisenberg MJ, Grundy SM, et al; American College of Cardiology Foundation Clinical Expert Consensus Task Force (ACCF/AHA Writing Committee to Update the 2000 Expert Consensus Document on Electron Beam Computed Tomography). ACCF/AHA 2007 clinical expert consensus document on coronary artery calcium scoring by computed tomography in global cardiovascular risk assessment and in evaluation of patients with chest pain: a report of the American College of Cardiology Foundation Clinical Expert Consensus Task Force (ACCF/AHA Writing Committee to Update the 2000 Expert Consensus Document on Electron Beam Computed Tomography). Circulation 2007;115:402-26. [PMID: 17220398]
39. Pearson TA, Mensah GA, Alexander RW, Anderson JL, Cannon RO 3rd, Criqui M, et al; Centers for Disease Control and Prevention. Markers of inflammation and cardiovascular disease: application to clinical and public health practice: A statement for healthcare professionals from the Centers for Disease Control and Prevention and the American Heart Association. Circulation 2003;107:499-511. [PMID: 12551878]
40. National Heart Lung and Blood Institute, National Cholesterol Education Project. Third Report of the Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). Bethesda, MD: National Institutes of Health; 2002.
Members of the U.S. Preventive Services Task Force
Members of the U.S. Preventive Services Task Force* Ned Calonge, MD, MPH, Chair (Colorado Department of Public Health and Environment, Denver, Colorado); Diana B. Petitti, MD, MPH, Vice Chair (Arizona State University, Phoenix, Arizona); Thomas G. DeWitt, MD (Children's Hospital Medical Center, Cincinnati, Ohio); Kimberly D. Gregory, MD, MPH (Cedars-Sinai Medical Center, Los Angeles, California); Russell Harris, MD, MPH (University of North Carolina School of Medicine, Chapel Hill, North Carolina); George Isham, MD, MS (HealthPartners, Minneapolis, Minnesota); Michael L. LeFevre, MD, MSPH (University of Missouri School of Medicine, Columbia, Missouri); Carol Loveland-Cherry, PhD, RN (University of Michigan School of Nursing, Ann Arbor, Michigan); Lucy N. Marion, PhD, RN (Medical College of Georgia, Augusta, Georgia); Virginia A. Moyer, MD, MPH (Baylor College of Medicine, Houston, Texas); Judith K. Ockene, PhD (University of Massachusetts Medical School, Worcester, Massachusetts); George F. Sawaya, MD (University of California, San Francisco, San Francisco, California); Albert L. Siu, MD, MSPH (Mount Sinai Medical Center, New York, New York); Steven M. Teutsch, MD, MPH (Merck & Company, West Point, Pennsylvania); and Barbara P. Yawn, MD, MSc (Olmsted Medical Center, Rochester, Minnesota).
*Members of the Task Force at the time this recommendation was finalized. For a list of current Task Force members, go to http://www.uspreventiveservicestaskforce.org/about.htm.
Disclaimer: Recommendations made by the USPSTF are independent of the U.S. government. They should not be construed as an official position of the Agency for Healthcare Research and Quality or the U.S. Department of Health and Human Services.
Copyright and Source Information
This document is in the public domain within the United States.
Requests for linking or to incorporate content in electronic resources should be sent via the USPSTF contact form.
AHRQ Publication No. 10-05141-EF-2
Current as of October 2009
U.S. Preventive Services Task Force. Using Nontraditional Risk Factors in Coronary Heart Disease Risk Assessment: Recommendation Statement. AHRQ Publication No. 10-05141-EF-2, October 2009. http://www.uspreventiveservicestaskforce.org/uspstf09/riskcoronaryhd/coronaryhdrs.htm