archived

Final Evidence Summary

Coronary Heart Disease: Screening Using Non-Traditional Risk Factors

October 15, 2009

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.

Emerging Risk Factors for Coronary Heart Disease

A Summary of Systematic Reviews Conducted for the U.S. Preventive Services Task Force

Release Date: October 2009

Mark Helfand, MD, MPH; David I. Buckley, MD, MPH; Michele Freeman, MPH; Rongwei Fu, PhD; Kevin Rogers, MD; Craig Fleming, MD; and Linda L. Humphrey, MD, MPH

The information in this report is intended to help clinicians, employers, policymakers, and others make informed decisions about the provision of health care services. This report is intended as a reference and not as a substitute for clinical judgment.

This report may be used, in whole or in part, as the basis for the development of clinical practice guidelines and other quality enhancement tools, or as a basis for reimbursement and coverage policies. AHRQ or U.S. Department of Health and Human Services endorsement of such derivative products may not be stated or implied.

This report was first published in Annals of Internal Medicine, October 2009 (Annals of Internal Medicine 2009;151:496-507.)

Return to Table of Contents

Background: Traditional risk factors do not explain all of the risk for incident coronary heart disease (CHD) events. Various new or emerging risk factors have the potential to improve global risk assessment for CHD.

Purpose: To summarize the results of 9 systematic reviews of novel risk factors to help the U.S. Preventive Services Task Force (USPSTF) evaluate the factors' clinical usefulness.

Data Sources: Results from a MEDLINE search for English-language articles published from 1966 to September 2008, using the Medical Subject Heading terms cohort studies and cardiovascular diseases in combination with terms for each risk factor.

Study Selection: Studies were included if the participants had no baseline cardiovascular disease and the investigators adjusted for at least 6 Framingham risk factors.

Data Extraction: Study quality was evaluated by using USPSTF criteria and overall quality of evidence for each risk factor by using a modified version of the Grading of Recommendations, Assessment, Development, and Evaluation framework. Each factor's potential clinical value was evaluated by using a set of criteria that emphasized the importance of the effect of that factor on the reclassification of intermediate-risk persons.

Data Synthesis: 9 systematic reviews were conducted. C-reactive protein (CRP) was the best candidate for use in screening and the most rigorously studied, but evidence that changes in CRP level lead to primary prevention of CHD events is inconclusive. The other evaluated risk factors were coronary artery calcium score as measured by electron-beam computed tomography, lipoprotein(a) level, homocysteine level, leukocyte count, fasting blood glucose, periodontal disease, ankle-brachial index, and carotid intima-media thickness. The availability and validity of the evidence varied considerably across the risk factors in terms of aggregate quality, consistency of findings, and applicability to intermediate-risk persons in the general population. For most risk factors, no studies assessed their usefulness for reclassifying intermediate-risk persons.

Limitations: Because of lack of access to original data, no firm conclusions could be drawn about differences in risk prediction among racial and ethnic groups. The review did not emphasize within-cohort comparisons of multiple risk factors.

Conclusion: The current evidence does not support the routine use of any of the 9 risk factors for further risk stratification of intermediate-risk persons.

Return to Table of Contents

Clinicians use the Framingham risk score to stratify persons according to their 10-year risk for coronary death or myocardial infarction, also known as major or hard coronary heart disease (CHD) events 1,2. The Framingham risk score predicts major CHD events well in different demographic and ethnic groups 3. Guidelines recommend using the Framingham risk score, or a modified version of it, to identify high-risk persons (persons with a 10-year risk >20%), who benefit from aggressive risk-reduction measures 4,5.

In the United States, 23 million adults with no history of cardiovascular disease are classified as intermediate-risk by the Framingham score, meaning they have a 10-year risk for major CHD events of 10% to 20% 6. New or emerging risk factors, particularly inflammatory markers and markers of atherosclerotic burden, might identify those in this group who are actually at high risk and might benefit from more aggressive risk reduction. More than 100 emerging risk factors have been proposed for their potential to improve global risk assessment 7. However, consensus conferences held in 1998 8 and 2002 4,9 recommended against using these factors in the absence of stronger data to support their ability to independently predict CHD events. These consensus groups also noted that assays for some markers were not sufficiently standardized for clinical use. Among the few tests proven to predict cardiovascular events, none had been demonstrated to re-classify as high-risk a subgroup of persons who were initially classified as intermediate-risk by using the Framingham risk score 9.

Table 1 outlines the criteria a new risk factor must meet to be clinically useful for reclassifying intermediate-risk patients' risk for major CHD events 9-12. Key to these criteria is the concept that the value a new risk factor adds to a risk scoring system (such as the Framingham system) cannot be judged solely by its ability to predict major CHD events independent of other risk factors. Most studies use a hazard ratio (or other risk ratio) to measure how well a new risk factor predicts major CHD events, controlling for the Framingham risk factors. From a clinical viewpoint, calculating a risk ratio is a necessary but far from sufficient step because it does not enable judgment of the effect of using the new test in persons classified as intermediate-risk by the Framingham risk score.

Studies may also measure how well a new prognostic risk factor improves discrimination when incorporated into the Framingham risk score. However, a marker that has a small effect on discrimination may have a large effect on the reclassification of persons from 1 risk group to another 13-18. To estimate the effect of a new risk factor on reclassification, investigators must compare the proportion of persons classified as high-risk by each model, then assess whether the agreement between the predicted and actual event rates in subgroups of persons who have different levels of risk (that is, calibration) has improved. Measuring discrimination is insufficient to judge the clinical effect of the new test without also measuring calibration and reclassification 19.

A better approach is to calculate the Framingham risk score, classify all participants, and then see how well the new risk factor reclassifies those who were assigned to the intermediate-risk group. This sequential approach provides a direct measure of the number or proportion of intermediate-risk persons who could be reclassified by the new test. This type of analysis provides the best information about the clinical effect of using the new test to further stratify intermediate-risk patients.

Using these considerations and the criteria in Table 1 as a guide, we conducted a series of systematic reviews to help the U.S. Preventive Services Task Force (USPSTF) determine which of 9 risk factors should be used to further stratify intermediate-risk persons. Members of the USPSTF determined the risk factors to evaluate: ankle–brachial index (ABI), leukocyte count, fasting blood glucose level, periodontal disease, carotid intima–media thickness (IMT), coronary artery calcium (CAC) score as measured by electron-beam computed tomography, serum homocysteine level, lipoprotein(a) level, and C-reactive protein (CRP) level. The details of several of these reviews are published elsewhere 20-23. We provide a summary overview of the main findings of this series of systematic reviews.

Table 1. Criteria for Evaluating the Clinical Value of a New Risk Factor

To be useful for reclassifying patients currently considered to be at intermediate risk for major CHD events, a new risk factor must meet the following criteria:*

  1. It should be easily and reliably measured. Laboratory, radiographic, or clinical measurement should have accepted population reference values. A relatively high prevalence of abnormal values and a substantial proportion of normal values should be found among intermediate-risk persons.
  2. It should be an independent predictor of major CHD events in intermediate-risk persons who have no history of coronary artery disease and no coronary equivalents, such as cerebrovascular or peripheral vascular disease.
  3. When assessed in intermediate-risk persons, it should reclassify a substantial proportion of them as high-risk.
  4. Reclassified individuals should be managed differently than they would have otherwise been, and new or additional treatment they receive should reduce their risk for CHD events.
  5. If 2 or more risk factors provide similar prognostic information, then convenience, availability, cost, and safety may be important in choosing among them.

CHD = coronary heart disease.
* On the basis of references 9 through 12.

Return to Table of Contents

Analytic Framework

We searched MEDLINE for English-language articles (1966 through September 2008) by using the Medical Subject Heading terms cohort studies and cardiovascular diseases in combination with terms for each of the tests under study. We also searched the reference lists of published reports. We included only studies that recruited participants with no known cardiovascular disease, reported major CHD events, and adjusted for 6 or 7 Framingham risk factors (5 or 6, if participants with diabetes were excluded) in this summary. When we found several reports based on the same cohort, we used the most recent analysis unless an older one used stronger analytic methods. The systematic reviews were originally conducted for literature searches through 2006. Several of those reviews were published or submitted for publication as separate papers. For the current review, we updated the literature searches through September 2008 for ABI, leukocyte count, fasting blood glucose level, carotid IMT, and lipoprotein(a) level. We updated the literature search for electron-beam computed tomography through July 2008.

Critical Appraisal and Quality of Evidence

To assess the quality of each study, we used the USPSTF criteria for cohort studies10 and applied a modified Grading of Recommendations, Assessment, Development, and Evaluation framework to assess the overall quality of evidence for each risk factor24. Specifically, we considered the limitations, consistency, precision, applicability to the target population (intermediate-risk adults with no known cardiovascular disease), dose–response relationship, and likelihood of publication bias for the entire set of studies about the risk factor. These ratings for the overall quality of evidence reflect our confidence in the estimate of the risk factor's usefulness for reclassifying intermediate-risk persons as high-risk. The ratings also reflect appropriate control for confounders and applicability to intermediate-risk persons, among other considerations.

Appropriate Control for Confounding With the Framingham Risk Factors

Most novel risk factors are correlated with Framingham risk factors, so investigators who do not adjust or adjust inappropriately for 1 or more Framingham factors may overestimate the novel factor's predictive ability25,26. Inappropriate adjustment occurs when a variable (for example, a self-reported history of taking medication for cholesterol) is used as a proxy for a better predictor (such as measured total cholesterol or high-density lipoprotein cholesterol levels). We can have confidence in a study's results only when all Framingham risk factors have been correctly measured and adjusted for.

Applicability to Intermediate-Risk Persons

Cohorts that included intermediate-risk persons provide more pertinent information about risk factors. Estimates of the predictive ability of a particular marker vary depending on the pattern and prevalence of other risk factors in the population 19. A few studies used the Framingham risk score to classify participants, which provided direct information about the proportion who were at intermediate risk and the effect of using the new test. In most studies, however, we used average annual event rates and the prevalence of the Framingham risk factors to infer that the study population included intermediate-risk persons.

Other Considerations

We also considered the other criteria listed in Table 1. For some of these criteria (such as test reliability, convenience, cost, or safety), we used information not otherwise included in the literature search.

Role of the Funding Source

This study was funded by the Agency for Healthcare Research and Quality under a contract to support the work of the USPSTF. Agency staff and USPSTF members participated in development of the initial scope of this work and reviewed interim analyses and the final report. A draft version was distributed to content experts for review. Agency approval was required before this manuscript could be submitted for publication, but the authors are solely responsible for the content and the decision to submit it for publication.

Table 2. Risk Factor Characteristics

Risk Factor Description (Reference) Tests, Assays, or Devices, and Availability Agreement Among Methods (Reference) Decision Limits or Categories and Reliability for Use in Risk Assessment (Reference)*
CRP level A serum protein involved in immune and inflammatory responses. Conventional, highly sensitive, and cardiac CRP; turbometric highly sensitive CRP assay is the most widely used; widely available Cardiac CRP assays have a lower detection limit of <1.0 mg/L and an FDA indication for use in cardiac risk stratification 27 Low (<1 mg/L), intermediate (1-3 mg/L), and high (>3 mg/L). Most epidemiologic studies used a single measurement. With any particular assay, use of 2-3 serial measurements for baseline assessment provides reliability similar to that of an LDL cholesterol assay. Interassay agreement has not been evaluated in the setting of cardiac risk assessment.
CAC score Calcium content of the coronary arteries estimated from a radiographic image by using 1 of several scoring systems 28-30. EBT or EBCT, MDCT; available at specialized centers; examination takes 10-15 min Cardiac risk studies used EBCT; MDCT, the newer technology, provides better visualization of the coronary arteries but is used to calculate a CAC score for cardiac risk assessment. None, 1-100, 101-300, and >300. Categories vary among studies, but usually elevated values are compared with zero. No established norms for the general population. Some epidemiologic studies used 2 scans. The reliability of repeated scans has been evaluated in the research setting 31,32 but not in everyday practice.
Lipoprotein(a) level A particle found in serum that contains apolipoprotein B and the glycoprotein apolipoprotein(a). It has structural similarities to LDL and plasminogen. Turbometric, nephelometric, electroimmunodiffusion, ELISA, and immune fluorescence assays; widely available Poor agreement among different methods 33 <300 mg/L and >300 mg/L. Categories vary among studies. No established norms for the general population. Most epidemiologic studies used 1 measurement. Variation among study methods is thought to explain discrepant results among cohort studies.
Homocysteine level An amino acid found in serum, produced in the liver from methionine. ELISA, enzymatic, and other assays; widely available Good agreement among different methods No accepted categories for cardiac risk assessment. Most studies compare quantiles or estimate a risk ratio per 5-μmol/L difference in serum levels. Could be used as a continuous variable in risk assessment. Most epidemiologic studies used 1 measurement.
Leukocyte count The number of leukocytes in a given volume of blood. Automated cell counters; universally available Reliable No accepted categories for cardiac risk assessment. Most studies compare quantiles. Could be used as a continuous variable in risk assessment. Most epidemiologic studies used 1 measurement.
Fasting glucose concentration The quantity of glucose in a given volume of blood. Various assay methods; universally available Reliable No accepted categories for cardiac risk assessment. Most studies compare quantiles. Could be used as a continuous variable in risk assessment. Most epidemiologic studies used 1 measurement.
Periodontal disease Pocket formation, recession of the gingiva, and tooth loss. Physical examination and plain radiography; widely available Interobserver agreement in primary care unknown Descriptors (such as mild, aggressive, or chronic) are used widely in everyday practice, but categories for use in cardiac risk assessment are not well defined. Most epidemiologic studies used 1 examiner.
Ankle-brachial index The ratio of the systolic blood pressure at each ankle to the systolic blood pressure in the right arm. Doppler ultrasonography devices and blood pressure cuffs; universally available Reliable Normal (>90% or >85%) and low (<90% or <85%). Several other cutoff values have been used. A recent meta-analysis used deciles 34. Epidemiologic studies used the lower of 2 measurements.
Carotid IMT Thickness of the intima and media, part of the carotid artery wall. In practice, the combined thickness of the intima and medial layers is measured at ≥1 site (common carotid, carotid bifurcation, and internal carotid arteries). High-resolution B-mode ultrasonography; the equipment is widely available, but estimation of carotid IMT is performed in specialized centers Reliability in large epidemiologic studies is good, but reliability in practice unknown No accepted categories for cardiac risk assessment. Use of age-adjusted and sex- and race-specific values from the major epidemiologic studies is recommended 35, but it is not clear how widely they are used. Epidemiologic studies used various measurements. No established consensus for which measurement approach is best for cardiovascular risk assessment 36.

CAC = coronary artery calcium score; CRP = C-reactive protein; EBCT = electron-beam computed tomography; EBT = electron-beam tomography; ELISA = enzyme-linked immunosorbent assay; FDA = U.S. Food and Drug Administration; IMT = intima-media thickness; LDL = low-density lipoprotein; MDCT = multidetector computed tomography.
* Information reflects the usual practice in epidemiologic studies.

Return to Table of Contents

The Appendix Table (available at www.annals.org) shows how often a particular risk factor was evaluated among the 75 cohorts that have studied at least 1 novel risk factor. Serum tests that can be done on stored samples, such as for CRP, homocysteine, or lipoprotein(a), have been evaluated in the largest, highest-quality, and most diverse population-based studies. The strongest evaluations came from studies in which the cohorts had been followed for 10 years or more and all Framingham risk factors were measured before treatment for hyperlipidemia or hypertension was initiated. Conversely, data about electron-beam computed tomography, carotid IMT, and periodontal disease are relatively sparse. Because radiologic tests (electron-beam computed tomography and carotid IMT) and physical examination (ABI and periodontal examinations) cannot be done retrospectively, few studies of the large, widely studied cohorts used in cardiovascular epidemiology research evaluated these risk factors. Most evaluations of these tests were weaker, in that persons were followed for less time or had incomplete evaluations that did not measure all relevant Framingham risk factors at the time of inception. Many of the cohorts listed in the Appendix Table (available at www.annals.org) had no publications that met the inclusion criteria for our reviews. Many adjusted for too few traditional risk factors or reported composite outcomes that included stroke, angina, or revascularization rather than nonfatal myocardial infarction and coronary deaths. Results for this broader group of studies are re-ported elsewhere 20–23. Table 227–36 includes a description of each test and information about its reliability, availability, reference values, and population norms (criterion 1 in Table 1). Table 337–45 summarizes the information the USPSTF considered in assessing the potential benefit of using each risk factor to predict major CHD events in intermediate-risk persons.

The available evidence varied considerably for each of the risk factors. For periodontal disease, ABI, and carotid IMT, good-quality studies relevant to predicting major CHD events were sparse, which provided insufficient data for estimating pooled risk ratios for major CHD events. For leukocyte count and fasting blood glucose level, good-quality cohort studies did not consistently predict major CHD events. Although we found CRP level, CAC score on electron-beam computed tomography, lipoprotein(a) level, and homocysteine level to be independent predictors of major CHD events when added to Framingham risk factors, the quality of the evidence for these 4 risk factors varied considerably. For most of the 9 risk factors, no studies assessed their usefulness for reclassifying intermediate-risk persons, information critical to a complete assessment of a factor’s potential clinical utility. Although the evidence that CRP level may be used to correctly reclassify intermediate-risk persons is promising, it is insufficient to conclude that changes in CRP level lead to primary prevention of CHD events. The current evidence, therefore, does not support the routine use of any of the 9 risk factors for further risk stratification of intermediate-risk persons.

Table 3. Summary: Strength of Evidence and Magnitude of Effect

Factor Strength of Evidence Magnitude of Effect
  Cohorts, n Limitations Applicability to Intermediate-Risk Persons Other Considerations* Prediction of Cardiovascular Events, Effectiveness of Treatment, and Harms (Reference) Overall Strength of Evidence Adjusted Risk Ratio (95% CI) for Major CHD Events and Comparison Range Reclassified as High-Risk, % (Studies, n) Prevalence of Abnormal Values in Intermediate-Risk or General Population (Reference)
CRP level 10 Some Good Dose–response relationship Weight loss, exercise, smoking cessation, statins, and fibrates reduce serum CRP levels 37–39, but none of these effects have yet been linked to a reduced risk for major CHD events. Good 1.58 (1.37–1.83) for >3.0 vs. <1.0 mg/L; 1.22 (1.11–1.33) for 1.0–3.0 vs. <1.0 mg/L 5 to 153 23% of men and 37% of women in NHANES had CRP levels >3.0 mg/L40
Electron-beam computed tomography 8 Some§ Some uncertainty Sparse or imprecise data and inconsistent results Effects of treatment unclear. Radiation exposure. Fair - 5 to 151 Probably common; 26% of adults in the Rotterdam cohort aged 62–85 y had CAC scores >400.41
Lipoprotein(a) level 6 Some Significant uncertainty None Effect of treatment independent of LDL-c is unclear. Fair 1.45 (1.11–1.89) for ≥300 vs. <300 mg/L - 14% of women and 11.4% of men in the Framingham cohort had lipoprotein(a) levels >300 mg/L.42,43
Homocysteine level 9 Some Significant uncertainty None Treatment with folate decreases serum levels but is ineffective for secondary prevention of major CHD events. The effect of folate on major CHD events for primary prevention is unknown. Fair 1.09 (1.02–1.17) per 5-µmol/L increase - 25.8% of men and women in the Hoom cohort age 50–75 y had homocysteine levels >14 µmol/L.44
Leukocyte count 11 Some Some uncertainty Weak or absent association and inconsistent results No specific treatment available. Fair Inconsistent results (range, 1.01–2.10) - -
Fasting glucose concentration 10 Serious** Significant uncertainty Weak or absent association and inconsistent results Effects of treatment on major CHD events† unclear. Fair - - -
Periodontal disease 1 Some Significant uncertainty Sparse or imprecise data Predictive of CVD events††. Effects of treatment on major CHD events unclear. Fair Insufficient data - Probably common; 23% of U.S. adults had periodontitis and 35% had no teeth.45
Ankle–brachial index 3 Serious** Significant uncertainty Sparse or imprecise data Predictive of some CVD events††. Effects of treatment on major CHD events unclear. Poor - - Men, 3.3%; women, 10%
Carotid intima–media thickness 3 Serious** Significant uncertainty Sparse or imprecise data Predictive of some CVD events††. Effects of treatment independent of LDL-c unclear. Poor - - Poor evidence

CAC = coronary artery calcium; CHD = coronary heart disease; CRP = C-reactive protein; CVD = cardiovascular disease; LDL-c = low-density lipoprotein cholesterol.
NHANES = National Health and Nutrition Examination Survey.
* Negative factors include imprecise or sparse data, high risk for reporting bias, effect of plausible residual confounding, or a weak or absent association. Positive factors include a strong or very strong association, evidence of a dose–response gradient, or all plausible unmeasured confounders that would increase the magnitude of the observed rate ratio.
† From meta-analyses of cohort studies unless otherwise noted.
‡ Nonfatal myocardial infarction and coronary death.
§ Most studies had self-selected patients. Not evaluated in the major population-based cohorts. Use of self-report for Framingham risk factors could inflate estimates of the contribution of CAC score. Results given are for 2 population-based, good-quality cohort studies.
‌ Studies did not establish applicability of results to intermediate-risk persons.
¶ Estimates are from the general population rather than from an intermediate-risk group.
** The major limitations were including patients with known coronary artery disease or symptomatic peripheral vascular disease or not reporting CHD events as an end point.
†† Includes major CHD events, stroke, and death due to cerebrovascular disease, and "soft" cardiac outcomes, such as revascularization or onset of angina.

CRP Level

Of the 9 markers we evaluated, CRP was the best candidate for use in screening. Our findings support the use of CRP level to stratify those with a Framingham risk score of 15% to 20%, but some gaps in the evidence remain. First, although we found more evidence about re-classification for CRP level than for any other novel risk factor, the evidence is still sparse. A CRP level greater than 3.0 mg/L reclassified 5% of intermediate-risk women in the Women’s Health Study19,46 and none in the Cardiovascular Health Study47—an inconsistent and possibly small effect. In the 2 studies of men47,48, high CRP level clearly identified a high-risk subset of persons with a Framingham risk score between 15% and 20%, but we do not know how many—a consistent but imprecise effect.

Second, it is unclear whether performing a CRP test to guide treatment goals is more beneficial than intensifying treatment goals in all intermediate-risk persons. Interventions that reduce CRP (weight loss, exercise, smoking cessation, statins, and fibrates) are already known to reduce the risk for coronary events. A primary prevention trial of rosuvastatin, 20 mg, versus placebo in 17,802 patients with a CRP level greater than 2 mg/L and a low-density lipoprotein cholesterol level less than 3.36 mmol/L (<130 mg/dL) was terminated early because of "overwhelming benefit"49. The investigators did not provide the number of participants who could be classified as low- or intermediate-risk on the basis of their Framingham risk score, so the applicability of this trial to intermediate-risk persons is not clear.

CAC Score on Electron-Beam Computed Tomography

Electron-beam computed tomography can be used to quantify calcification of the coronary arteries into a CAC score28. A newer device, the multidetector computed tomography scanner, provides better visualization of the coronary arteries and is also being evaluated as a screening test, particularly for ruling out coronary disease noninvasively among low-risk persons50,51.

Relatively sparse data from a small number of studies and inconsistent results among these cohorts weakened confidence in our estimates of the risk ratio. We focused on 5 studies that we judged most likely to be accurate because of their valid study designs41,52–55. These studies provided measures of the incremental predictive value of CAC scoring for coronary events. As in a previous systematic review25, we found wide variation in estimates of the risk ratio for higher calcium scores. Studies with notable limitations, including self-referral of participants, unblinded outcome adjudication, and ascertainment of Framingham risk factors by self-report rather than bio-chemical measurement, found higher relative risk estimates. For example, the hazard ratio for a CAC score of 1 to 100 compared with 0 was 1.39 (CI, 0.65 to 2.69) in the best-quality study55, versus 2.25 (CI, 1.63 to 3.02) for men and 2.27 (CI, 1.64 to 2.91) for women53, and 3.98 (CI, 1.72 to 8.79)54, 4.04 (CI, 1.64 to 9.93)41, and 8.91 (CI, 2.21 to 35.87)52 in the other, lower-quality studies. The estimates had substantial heterogeneity (Q = 6.90, I2 = 42.0%, P = 0.140) for scores of 101 to 300 versus 0, but removal of 1 study reduced heterogeneity to 0 (Q = 3.28, I2 = 0.0%, P = 0.51). The study in question was the best-quality one55, which suggests that flaws in the other studies, particularly incorrect or incomplete adjustment for other risk factors, inflated their estimates of the risk ratio. Because of the inconsistent and widely variable risk estimates, the variation in cutoff points used by different studies, and the lack of population-based reference standards, we have not reported a summary risk ratio estimate for electron-beam computed tomography in Table 3.

The effect on reclassification is even less certain. Our review disagrees with one published in 2007 by the American College of Cardiology and American Heart Association guideline committee56, which said that 4 studies provided information about reclassification and estimated that, among intermediate-risk persons, a CAC score in the highest tertile (>400) conferred an annual rate of major CHD events of 2.4%. Their report did not describe how they derived this estimate or how many intermediate-risk patients in the 4 studies had a CAC score greater than 400. In our review of these studies (plus 6 others), we found that only 1 evaluated reclassification in an intermediate-risk group. In that study, participants with CAC scores of 300 or greater had the event rate of a high-risk group (>2% per year), made up 18% of intermediate-risk patients, and potentially could have been reclassified as high-risk55. The main weakness of the study was that the sample was self-selected rather than population-based. More population-based cohort studies relevant to intermediate-risk persons would facilitate the development of definitive guidelines regarding screening with CAC scoring.

Lipoprotein(a) Level

Although lipoprotein(a) is of epidemiologic interest as a potential risk factor, most studies had little relevance to cardiac risk stratification in the clinical setting. Our summary risk ratio estimate supports a relationship between lipoprotein(a) level and CHD events; however, we are uncertain about the applicability of the evidence to intermediate-risk patients. Studies combined low- and high-risk samples and included a broader range of cardiovascular events. Some cohorts undoubtedly included intermediate-risk persons, but no analyses were done to determine how well the risk ratio calculated for the entire sample applied to this subset, and no study directly examined the effect on reclassification of intermediate-risk persons. Other information in Tables 2 and 3 suggest that lipoprotein(a) level is unlikely to be useful for stratifying intermediate-risk persons; commercial assays are poorly standardized, and the prevalence of high serum levels (>1.07 µmol/L) in intermediate-risk persons is uncertain.

Homocysteine Level

Homocysteine is of epidemiologic interest as a potential risk factor, but the applicability of the body of evidence to intermediate-risk patients is uncertain, with most studies having little relevance to cardiac risk stratification in the clinical setting. No studies conducted analyses to determine the relative risk for CHD events specifically in intermediate-risk persons, and many studies included a broader range of cardiovascular events. Although consistent findings from a large number of cohort studies strongly support a relationship between homocysteine level and the risk for cardiovascular events 23]], its value as a risk factor for major coronary events is less certain. In a meta-analysis of the subset of studies that adjusted for 6 or 7 Framingham risk factors and reported major CHD events, each 5-µmol/L increase in homocysteine level confers an approximately 9% increase in the risk for CHD events that is independent of traditional CHD risk factors (RR, 1.09 [CI, 1.02 to 1.17]). (For U.S. adults between 50 and 75 years of age, a 5-µmol/L increase is approximately the mean difference between the 75th and 95th percentile[57]].) Inclusion of studies that did not adjust for all Framingham risk factors or that included other cardiovascular outcomes increased the estimated risk to approximately 20%23. No studies have directly examined the effect of homocysteine level on the reclassification of intermediate-risk persons.

Leukocyte Count

In 14 studies (of 13 cohorts)58-71, the total leukocyte count did not predict major CHD events consistently. In addition, analyses were not limited to intermediate-risk persons, and the quality of adjustment for Framingham risk factors was a serious problem in several studies60–64,67–69. The relationship between leukocyte count and CHD events also varied with the timing of the assessment of end points58,59,66.

Fasting Blood Glucose Level

No study consistently found that elevated fasting blood glucose level could predict CHD events. Only 172 of the 10 cohort studies eligible for our review73–79 found an association—a weak association—between fasting glucose level and CHD events after 4 years of follow-up.

Periodontal Disease

Periodontal disease is common among adults in the United States and is a potential source of chronic inflammation. We investigated whether different manifestations of periodontal disease (periodontitis, tooth loss, gingivitis, and bone loss) are independent risk factors for cardiovascular disease22 or major CHD events. Our review and meta-analyses suggest that periodontal disease is an independent, though relatively weak, risk factor for CHD. Several studies, which were based on either dental examinations or self-report, found periodontal disease to be independently associated with increased risk for CHD45,80,81, whereas other studies found no association82–84. For cardiovascular diseases in general, relative risk estimates for different categories of periodontal disease ranged from 1.24 (CI, 1.01 to 1.51) for periodontitis to 1.34 (CI, 1.10 to 1.63) for persons with 0 to 10 teeth. We found significant statistical heterogeneity across studies that was not explained in subgroup analyses by differences in sex, definition of cardiovascular events, or method of periodontal disease assessment. However, the sensitivity of these subgroup analyses was poor, and we could not rule out differences in measurement of the risk factor or outcomes as causes of heterogeneity. We did not find any direct evidence that periodontal examination would be useful for reclassifying persons classified as intermediate-risk by the Framingham risk score.

ABI

The ABI is an indicator of peripheral arterial disease—atherosclerotic disease that involves the large arteries of the lower extremity. The ABI is determined by measuring systolic blood pressure at the ankle, based on palpation or ultrasonographic measurement of the dorsalis pedis pulse, and dividing this by the systolic blood pressure measured in the arm. An ABI less than 0.9 is the cutoff point commonly used to indicate possible significant compromise of lower-extremity arterial blood flow. In the Framingham cohort, the principal risk factors for CHD events (hyperlipidemia, hypertension, and smoking) were found to be equally good as predictors of incident peripheral artery disease. The Adult Treatment Panel III recommends managing patients with peripheral arterial disease, which is classified as a coronary equivalent, as if they were at high risk according to the Framingham system4,5.

In our original systematic review, we found no evidence that ABI independently predicts the risk for incident CHD events in persons without symptomatic peripheral arterial disease. We reviewed 514 abstracts, evaluated 18 potentially relevant articles in detail, and excluded all of them—most commonly because they did not report results separately for participants with no history of CHD or peripheral artery disease or did not adequately adjust for Framingham risk factors.

The Ankle–Brachial Index Collaboration published an individual-data meta-analysis of 16 of these studies in July 200834. The meta-analysis only included participants with no history of CHD, and investigators calculated a Framingham risk score for each participant. Rates of major CHD events were reported in 11 cohorts of men and 10 cohorts of women. Overall, 7.4% had an ABI of 0.9 or less. When added to the Framingham risk score, an ABI less than 0.9 improved discrimination from 0.646 (CI, 0.643 to 0.657) to 0.655 (CI, 0.643 to 0.666) in men and from 0.605 (CI, 0.590 to 0.619) to 0.658 (CI, 0.644 to 0.672) in women.

The results from the 2008 meta-analysis for reclassification of intermediate-risk persons are imprecise. Of 7392 men with a baseline Framingham risk score of 10% to 19% (mean, 13%), only 3.3% had an ABI less than 0.9, and the 10-year risk among these men was 16%, still within the intermediate-risk range. Among men with a Framingham risk score from 15% to 19% and an ABI less than 0.9, the pooled 10-year risk for major CHD events was 20.2 (CI, 8.0 to 32.3), but the proportion with a posttest Framingham risk score greater than 20% was not reported. The results for women were much more promising; 10% of those classified as intermediate-risk at baseline had an ABI less than 0.9, and these had a 10-year risk of 25%.

The Ankle–Brachial Index Collaboration publication presented no information about how well the Framingham risk score and the ABI predicted major CHD events in the individual studies, making it impossible to judge the consistency or heterogeneity of results or the validity of the pooled results. For the purpose of judging the value of ABI in reclassifying asymptomatic intermediate-risk persons according to their risk for major CHD events, the meta-analysis had important flaws. Most important, the article does not say whether participants with a known history of stroke, transient ischemic attacks, or symptomatic peripheral artery disease were excluded from the analysis. Inclusion of such patients could increase the apparent predictive ability of ABI but reduce its relevance to asymptomatic persons. In addition, we cannot judge the adequacy of Framingham risk factor measurement, which may have been inconsistent among the studies, from the pooled discrimination statistics reported in the article. Of concern, the adjusted 10-year risk for major CHD events among men with a Framingham risk score in the high-risk range (20% to 29%) was 15.3% (CI, 11.5 to 19.1), which suggests underadjustment. For these reasons, this recent publication did not change our original assessment that the evidence is insufficient to assess the value of ABI for cardiac risk assessment in asymptomatic intermediate-risk persons.

Carotid IMT

Carotid IMT, as measured by carotid ultrasonography, has been used widely in the context of randomized trials as a measure of the progression of atherosclerotic disease 85–87]]. Evaluations of carotid IMT as a risk factor have focused primarily on stroke or a broad range of cardiovascular events 88–105]]. Among this broad group of studies, differences in measurement of carotid IMT, extensive over-lap with other risk factors for coronary events, inadequate measurement and adjustment of these risk factors, and different definitions of end points contributed to the wide variation in risk ratios36.

Only 3 studies of carotid IMT estimated an adjusted risk ratio for major coronary events, rather than a broader measure that included stroke or other cardiovascular events, in persons without prevalent cardiovascular disease. In the ARIC (Atherosclerosis Risk in Communities) Study, adding carotid IMT scores to a risk prediction equation based on Framingham risk factors slightly improved the prediction of subsequent CHD among healthy adults, particularly men 93,94. Carotid IMT persisted as an independent risk factor in the other cohorts after full or partial adjustment for Framingham risk factors103,105.

A major roadblock has been the lack of consensus on examination techniques and population-based standards for interpreting quantitative IMT measures. Studies used different methods to measure carotid IMT, which makes comparisons or quantitative synthesis of the results across studies unreliable. Recently, a consensus panel of experts 35]] proposed standards for conducting examinations and reference values for U.S. adults based on 2 large cohort studies 106,107]], one of which (ARIC) has also published data about coronary risk prediction94. Even if these standards are widely adopted, their usefulness in cardiac risk assessment needs to be validated in prospective, population-based cohort studies that use appropriate methods to measure other risk factors and examine the added predictive ability of carotid IMT in persons classified as intermediate-risk by the Framingham risk score.

Summary

To be clinically useful, a novel CHD risk factor must meet the various criteria we discuss. The current evidence does not satisfy all of these criteria for any of the 9 new risk factors that we evaluated. The available evidence varies among the risk factors and is lacking in different ways for different criteria. For some factors, good-quality studies relevant to predicting major CHD events were sparse and data were therefore insufficient, even for estimating pooled risk ratios. For others, an adequate body of studies did not consistently find that the factor in question independently predicted major CHD events, a necessary but not sufficient criterion. A new risk factor should, when added to traditional Framingham risk factors, reclassify a substantial proportion of originally intermediate-risk persons as high-risk. In addition, such reclassification should result in clinical management that is different than it would otherwise have been, and that is effective in reducing the risk for incident CHD. Although several novel risk factors are independent predictors of major CHD events, only the effect of CRP level on risk reclassification has been evaluated by good-quality studies. Although promising evidence indicates that CRP level can be used to correctly reclassify intermediate-risk persons, evidence that changes in CRP level reduce the risk for incident CHD events is insufficient.

Return to Table of Contents

As Lloyd-Jones and colleagues recently pointed out108, "assessments of new prognostic tests should not rely solely on associations measured by relative risks." Our results illustrate the importance of considering multiple criteria to evaluate whether a new risk factor should be incorporated into guidelines for coronary risk assessment in primary care. In addition to the limitations of individual studies, the consistency, precision, and applicability of the body of evidence to the target population are critical components of this evaluation. Future research should also rigorously evaluate the effect of a new risk factor on the reclassification of intermediate-risk persons, as well as the effectiveness of more aggressive risk-reduction measures that are undertaken as a consequence of that reclassification.

Our review has limitations. First, in the absence of access to original data, we could not draw firm conclusions about differences in risk prediction among racial and ethnic groups for most risk factors. Recent studies54,109 have found no major differences in CAC scores among racial groups. Cohort studies, such as the Multi-Ethnic Study of Atherosclerosis110 and the ARIC Study111, recruited diverse groups of participants, but ethnic and racial minority populations were poorly represented in many cohorts. Future studies particularly need to validate proposed additions in different groups, in the manner that has been done for the Framingham risk score3.

In addition, our review did not emphasize within-cohort comparisons among novel risk factors. Several articles112–116 have made head-to-head comparisons of multiple risk factors. Comparison of multiple prognostic factors in the same cohort can add significantly to our confidence in estimates of effect114. The Appendix Table (available at www.annals.org) 117–212, which indirectly compares within-cohort findings, illustrates this principle. For example, separate articles from the ARIC Study found that CRP level and carotid IMT, but not fasting glucose, homocysteine, or leukocyte count, independently predicted cardiac events. If formally analyzed, results like these may deserve more weight than results from cohorts in which all risk factors tested have impressive results. Direct within-cohort comparisons can provide important insights. For example, in the Multi-Ethnic Study of Atherosclerosis, CAC scores were clearly superior to carotid IMT for predicting cardiovascular events95. A recent report from the Cardiovascular Health Study (90) compared carotid IMT with CRP level. Both predicted cardiovascular events, after adjusting for other risk factors, but an elevated CRP level was associated with increased cardiovascular disease risk and all-cause mortality risk only in patients with detectable atherosclerosis. Future systematic reviews should take findings from such comparisons as these into account.

Return to Table of Contents

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.

From the Oregon Evidence-based Practice Center, Veterans Affairs Medical Center, and Oregon Health & Science University, Portland, Oregon; University of Utah Health Sciences Center, Salt Lake City, Utah; and Group Health Olympia Medical Center, Olympia, Washington.

Acknowledgments

The authors thank Agency for Healthcare Research and Quality Medical Officer Janelle Guirguis-Blake, MD, for commenting on draft versions of the Systematic Evidence Synthesis20 and the USPSTF members who served as leads for this project, including Kimberly D. Gregory, MD, MPH; Russell Harris, MD, MPH; George F. Sawaya, MD; and Barbara Yawn, MD, MSc. They also thank Andrew Hamilton, MLS, MS, for conducting the literature searches and Christina Bougatsos, BS, for assistance with the manuscript.

Grant Support: By the Agency for Healthcare Research and Quality (contract no. 290-02-0024, Task Order Number 2).

Potential Financial Conflicts of Interest: None disclosed. Requests for Single Reprints: Mark Helfand, MD, MPH, Oregon Health & Science University, Mailcode BICC, 3181 Southwest Sam Jackson Park Road, Portland, OR 97239.

Current author addresses and author contributions are available at http://www.annals.org.

Return to Table of Contents
  1. Brotman DJ, Walker E, Lauer MS, O'Brien RG. In search of fewer independent risk factors. Arch Intern Med. 2005;165:138-45. [PMID: 15668358]
  2. Grundy SM, Bazzarre T, Cleeman J, D'Agostino RB Sr, Hill M, Houston-Miller N, et al. Prevention Conference V: Beyond secondary prevention: identifying the high-risk patient for primary prevention: medical office assessment: Writing Group I. Circulation. 2000;101:E3-E11. [PMID: 10618316]
  3. 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]
  4. Harris RP, Helfand M, Woolf SH, Lohr KN, Mulrow CD, Teutsch SM, et al; Methods Work Group, Third U.S. Preventive Services Task Force. Current methods of the U.S. Preventive Services Task Force: a review of the process. Am J Prev Med. 2001;20:21-35. [PMID: 11306229]
  5. Fryback DG, Thornbury JR. The efficacy of diagnostic imaging. Med Decis Making. 1991;11:88-94. [PMID: 1907710]
  6. Morrow DA, de Lemos JA. Benchmarks for the assessment of novel cardiovascular biomarkers [Editorial]. Circulation. 2007;115:949-52. [PMID: 17325253]
  7. Pepe MS, Janes H, Longton G, Leisenring W, Newcomb P. Limitations of the odds ratio in gauging the performance of a diagnostic, prognostic, or screening marker. Am J Epidemiol. 2004;159:882-90. [PMID: 15105181]
  8. Moons KG, Harrell FE. Sensitivity and specificity should be de-emphasized in diagnostic accuracy studies. Acad Radiol. 2003;10:670-2. [PMID: 12809422]
  9. Pepe MS, Feng Z, Huang Y, Longton G, Prentice R, Thompson IM, et al. Integrating the predictiveness of a marker with its performance as a classifier. Am J Epidemiol. 2008;167:362-8. [PMID: 17982157]
  10. Janes H, Pepe MS, Gu W. Assessing the value of risk predictions by using risk stratification tables. Ann Intern Med. 2008;149:751-60. [PMID: 19017593]
  11. Pencina MJ, D'Agostino RB Sr, D'Agostino RB Jr, Vasan RS. Evaluating the added predictive ability of a new marker: from area under the ROC curve to reclassification and beyond. Stat Med. 2008;27:157-72; discussion 207-12. [PMID: 17569110]
  12. Cook NR. Statistical evaluation of prognostic versus diagnostic models: beyond the ROC curve. Clin Chem. 2008;54:17-23. [PMID: 18024533]
  13. Cook NR, Buring JE, Ridker PM. The effect of including C-reactive protein in cardiovascular risk prediction models for women. Ann Intern Med. 2006;145:21-9. [PMID: 16818925]
  14. Helfand M, Buckley D, Fleming C, Fu R, Freeman M, Humphrey L, et al. Screening for Intermediate Risk Factors for Coronary Heart Disease: Systematic Evidence Synthesis. Evidence Synthesis No. 73. AHRQ Publication No. 09-05137-EF-1. Rockville, MD: Agency for Healthcare Research and Quality; 2009.
  15. 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.
  16. Humphrey LL, Fu R, Buckley DI, Freeman M, Helfand M. Periodontal disease and coronary heart disease incidence: a systematic review and meta-analysis. J Gen Intern Med. 2008;23:2079-86. [PMID: 18807098]
  17. Humphrey LL, Fu R, Rogers K, Freeman M, Helfand M. Homocysteine level and coronary heart disease incidence: a systematic review and meta-analysis. Mayo Clin Proc. 2008;83:1203-12. [PMID: 18990318]
  18. Guyatt GH, Oxman AD, Kunz R, Vist GE, Falck-Ytter Y, Schünemann HJ; GRADE Working Group. What is "quality of evidence" and why is itü important to clinicians? BMJ. 2008;336:995-8. [PMID: 18456631]
  19. Pletcher MJ, Tice JA, Pignone M, Browner WS. Using the coronary artery calcium score to predict coronary heart disease events: a systematic review and meta-analysis. Arch Intern Med. 2004;164:1285-92. [PMID: 15226161]
  20. Pignone M, Fowler-Brown A, Pletcher M, Tice J. Screening for Asymptomatic Coronary Artery Disease: A Systematic Review for the U.S. Preventive Services Task Force. Systematic Evidence Review Number 22. Rockville, MD:Agency for Healthcare Research and Quality; 2003. Accessed at www.ahrq.gov/downloads/pub/prevent/pdfser/chdser.pdf on 18 August 2009.
  21. Callaghan JV, Gutman SI. Counterpoint: Food and Drug Administration guidance for C-reactive protein assays: matching claims with performance data. Clin Chem. 2006;52:1256-7. [PMID: 16798965]
  22. Agatston AS, Janowitz WR, Hildner FJ, Zusmer NR, Viamonte M Jr, Detrano R. Quantification of coronary artery calcium using ultrafast computed tomography. J Am Coll Cardiol. 1990;15:827-32. [PMID: 2407762]
  23. Carr JJ, Nelson JC, Wong ND, McNitt-Gray M, Arad Y, Jacobs DR Jr, et al. Calcified coronary artery plaque measurement with cardiac CT in population-based studies: standardized protocol of Multi-Ethnic Study of Atherosclerosis (MESA) and Coronary Artery Risk Development in Young Adults (CARDIA) study. Radiology. 2005;234:35-43. [PMID: 15618373]
  24. McCollough CH, Ulzheimer S, Halliburton SS, Shanneik K, White RD, Kalender WA. Coronary artery calcium: a multi-institutional, multimanufacturer international standard for quantification at cardiac CT. Radiology. 2007;243:527-38. [PMID: 17456875]
  25. Sevrukov AB, Bland JM, Kondos GT. Serial electron beam CT measurements of coronary artery calcium: Has your patient's calcium score actually changed? AJR Am J Roentgenol. 2005;185:1546-53. [PMID: 16304011]
  26. Chung H, McClelland RL, Katz R, Carr JJ, Budoff MJ. Repeatability limits for measurement of coronary artery calcified plaque with cardiac CT in the Multi-Ethnic Study of Atherosclerosis. AJR Am J Roentgenol. 2008;190:W87-92. [PMID: 18212206]
  27. Marcovina SM, Albers JJ, Scanu AM, Kennedy H, Giaculli F, Berg K, et al. Use of a reference material proposed by the International Federation of Clinical Chemistry and Laboratory Medicine to evaluate analytical methods for the determination of plasma lipoprotein(a). Clin Chem. 2000;46:1956-67. [PMID: 11106328]
  28. 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 meta-analysis. JAMA. 2008;300:197-208. [PMID: 18612117]
  29. Stein JH, Korcarz CE, Hurst RT, Lonn E, Kendall CB, Mohler ER, et al; American Society of Echocardiography Carotid Intima-Media Thickness Task Force. Use of carotid ultrasound to identify subclinical vascular disease and evaluate cardiovascular disease risk: a consensus statement from the American Society of Echocardiography Carotid Intima-Media Thickness Task Force. Endorsed by the Society for Vascular Medicine. J Am Soc Echocardiogr. 2008;21:93-111; quiz 189-90. [PMID: 18261694]
  30. Bots ML, Baldassarre D, Simon A, de Groot E, O'Leary DH, Riley W, et al. Carotid intima-media thickness and coronary atherosclerosis: weak or strong relations? Eur Heart J. 2007;28:398-406. [PMID: 17277033]
  31. Nicklas BJ, You T, Pahor M. Behavioural treatments for chronic systemic inflammation: effects of dietary weight loss and exercise training. CMAJ. 2005;172:1199-209. [PMID: 15851714]
  32. Nissen SE, Tuzcu EM, Schoenhagen P, Crowe T, Sasiela WJ, Tsai J, et al; Reversal of Atherosclerosis with Aggressive Lipid Lowering (REVERSAL) Investigators. Statin therapy, LDL cholesterol, C-reactive protein, and coronary artery disease. N Engl J Med. 2005;352:29-38. [PMID: 15635110]
  33. Albert MA, Danielson E, Rifai N, Ridker PM; PRINCE Investigators. Effect of statin therapy on C-reactive protein levels: the pravastatin inflammation/ CRP evaluation (PRINCE): a randomized trial and cohort study. JAMA. 2001;286:64-70. [PMID: 11434828]
  34. Miller M, Zhan M, Havas S. High attributable risk of elevated C-reactive protein level to conventional coronary heart disease risk factors: the Third National Health and Nutrition Examination Survey. Arch Intern Med. 2005;165:2063-8. [PMID: 16216995]
  35. 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]
  36. Bostom AG, Cupples LA, Jenner JL, Ordovas JM, Seman LJ, Wilson PW, et al. Elevated plasma lipoprotein(a) and coronary heart disease in men aged 55 years and younger. A prospective study. JAMA. 1996;276:544-8. [PMID: 8709403]
  37. Bostom AG, Gagnon DR, Cupples LA, Wilson PW, Jenner JL, Ordovas JM, et al. A prospective investigation of elevated lipoprotein (a) detected by electrophoresis and cardiovascular disease in women. The Framingham HeartStudy. Circulation. 1994;90:1688-95. [PMID: 7923652]
  38. Hoogeveen EK, Kostense PJ, Jakobs C, Dekker JM, Nijpels G, Heine RJ, et al. Hyperhomocysteinemia increases risk of death, especially in type 2 diabetes : 5-year follow-up of the Hoorn Study. Circulation. 2000;101:1506-11. [PMID: 10747342]
  39. DeStefano F, Anda RF, Kahn HS, Williamson DF, Russell CM. Dental disease and risk of coronary heart disease and mortality. BMJ. 1993;306:688-91. [PMID: 8471920]
  40. Ridker PM, Cook N. Clinical usefulness of very high and very low levels of C-reactive protein across the full range of Framingham Risk Scores. Circulation. 2004;109:1955-9. [PMID: 15051634]
  41. Cushman M, Arnold AM, Psaty BM, Manolio TA, Kuller LH, Burke GL, et al. C-reactive protein and the 10-year incidence of coronary heart disease in older men and women: the cardiovascular health study. Circulation. 2005;112:25-31. [PMID: 15983251]
  42. Koenig W, Löwel H, Baumert J, Meisinger C. C-reactive protein modulates risk prediction based on the Framingham Score: implications for future risk assessment: results from a large cohort study in southern Germany. Circulation. 2004;109:1349-53. [PMID: 15023871]
  43. 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]
  44. Henneman MM, Schuijf JD, van Werkhoven JM, Pundziute G, van der Wall EE, Jukema JW, et al. Multi-slice computed tomography coronary angiography for ruling out suspected coronary artery disease: what is the prevalence of a normal study in a general clinical population? Eur Heart J. 2008;29:2006-13. [PMID: 18573865]
  45. Choi EK, Choi SI, Rivera JJ, Nasir K, Chang SA, Chun EJ, et al. Coronary computed tomography angiography as a screening tool for the detection of occult coronary artery disease in asymptomatic individuals. J Am Coll Cardiol. 2008;52:357-65. [PMID: 18652943]
  46. 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]
  47. Becker A, Leber A, Becker C, Knez A. Predictive value of coronary calcificationsfor future cardiac events in asymptomatic individuals. Am Heart J. 2008;155:154-60. [PMID: 18082507]
  48. Detrano R, Guerci AD, Carr JJ, Bild DE, Burke G, Folsom AR, et al. Coronary calcium as a predictor of coronary events in four racial or ethnic groups. N Engl J Med. 2008;358:1336-45. [PMID: 18367736]
  49. 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]
  50. 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]
  51. Ganji V, Kafai MR. Population reference values for plasma total homocysteine concentrations in US adults after the fortification of cereals with folic acid. Am J Clin Nutr. 2006;84:989-94. [PMID: 17093148]
  52. Folsom AR, Wu KK, Rosamond WD, Sharrett AR, Chambless LE. Prospective study of hemostatic factors and incidence of coronary heart disease: the Atherosclerosis Risk in Communities (ARIC) Study. Circulation. 1997;96:1102-8. [PMID: 9286936]
  53. Gillum RF, Ingram DD, Makuc DM. White blood cell count, coronary heart disease, and death: the NHANES I Epidemiologic Follow-up Study. Am Heart J. 1993;125:855-63. [PMID: 8438715]
  54. Kannel WB, Anderson K, Wilson PW. White blood cell count and cardiovascular disease. Insights from the Framingham Study. JAMA. 1992;267:1253-6. [PMID: 1538564]
  55. Olivares R, Ducimetiére P, Claude JR. Monocyte count: a risk factor for coronary heart disease? Am J Epidemiol. 1993;137:49-53. [PMID: 8434572]
  56. Phillips AN, Neaton JD, Cook DG, Grimm RH, Shaper AG. Leukocyte count and risk of major coronary heart disease events. Am J Epidemiol. 1992;136:59-70. [PMID: 1415132]
  57. Prentice RL, Szatrowski TP, Fujikura T, Kato H, Mason MW, Hamilton HH. Leukocyte counts and coronary heart disease in a Japanese cohort. Am J Epidemiol. 1982;116:496-509. [PMID: 7124717]
  58. Sweetnam PM, Thomas HF, Yarnell JW, Baker IA, Elwood PC. Total and differential leukocyte counts as predictors of ischemic heart disease: the Caerphilly and Speedwell studies. Am J Epidemiol. 1997;145:416-21. [PMID: 9048515]
  59. Weijenberg MP, Feskens EJ, Kromhout D. White blood cell count and the risk of coronary heart disease and all-cause mortality in elderly men. Arterioscler Thromb Vasc Biol. 1996;16:499-503. [PMID: 8624770]
  60. Wheeler JG, Mussolino ME, Gillum RF, Danesh J. Associations between differential leucocyte count and incident coronary heart disease: 1764 incident cases from seven prospective studies of 30,374 individuals. Eur Heart J. 2004;25:1287-92. [PMID: 15288155]
  61. Zalokar JB, Richard JL, Claude JR. Leukocyte count, smoking, and myocardial infarction. N Engl J Med. 1981;304:465-8. [PMID: 7453772]
  62. Mänttäri M, Manninen V, Koskinen P, Huttunen JK, Oksanen E, Tenkanen L, et al. Leukocytes as a coronary risk factor in a dyslipidemic male population. Am Heart J. 1992;123:873-7. [PMID: 1549995]
  63. Margolis KL, Manson JE, Greenland P, Rodabough RJ, Bray PF, Safford M, et al; Women's Health Initiative Research Group. Leukocyte count as a predictor of cardiovascular events and mortality in postmenopausal women: the Women's Health Initiative Observational Study. Arch Intern Med. 2005;165:500-8. [PMID: 15767524]
  64. Rana JS, Boekholdt SM, Ridker PM, Jukema JW, Luben R, Bingham SA, et al. Differential leucocyte count and the risk of future coronary artery disease in healthy men and women: the EPIC-Norfolk Prospective Population Study. J Intern Med. 2007;262:678-89. [PMID: 17908163]
  65. Zakai NA, Katz R, Jenny NS, Psaty BM, Reiner AP, Schwartz SM, et al. Inflammation and hemostasis biomarkers and cardiovascular risk in the elderly: the Cardiovascular Health Study. J Thromb Haemost. 2007;5:1128-35. [PMID: 17388967]
  66. Meigs JB, Nathan DM, D'Agostino RB Sr, Wilson PW; Framingham Offspring Study. Fasting and post-challenge glycemia and cardiovascular disease risk: the Framingham Offspring Study. Diabetes Care. 2002;25:1845-50. [PMID: 12351489]
  67. Antonicelli R, Gesuita R, Boemi M, Paciaroni E; Camerano Study Group. Random fasting hyperglycemia as cardiovascular risk factor in the elderly: a 6-year longitudinal study. Clin Cardiol. 2001;24:341-4. [PMID: 11303705]
  68. Cohen HW, Hailpern SM, Alderman MH. Glucose-cholesterol interaction magnifies coronary heart disease risk for hypertensive patients. Hypertension. 2004;43:983-7. [PMID: 15037563]
  69. Folsom AR, Szklo M, Stevens J, Liao F, Smith R, Eckfeldt JH. A prospective study of coronary heart disease in relation to fasting insulin, glucose, and diabetes. The Atherosclerosis Risk in Communities (ARIC) Study. Diabetes Care. 1997;20:935-42. [PMID: 9167103]
  70. Ohlson LO, Svärdsudd K, Welin L, Eriksson H, Wilhelmsen L, Tibblin G, et al. Fasting blood glucose and risk of coronary heart disease, stroke, and all-cause mortality: a 17-year follow-up study of men born in 1913. Diabet Med. 1986;3:33-7. [PMID: 2951132]
  71. Pyörälä K, Savolainen E, Kaukola S, Haapakoski J. Plasma insulin as coronary heart disease risk factor: relationship to other risk factors and predictive value during 9 1/2-year follow-up of the Helsinki Policemen Study population. Acta Med Scand Suppl. 1985;701:38-52. [PMID: 3907294]
  72. 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]
  73. Yarnell JW, Pickering JE, Elwood PC, Baker IA, Bainton D, Dawkins C, et al. Does non-diabetic hyperglycemia predict future IHD? Evidence from the Caerphilly and Speedwell studies. J Clin Epidemiol. 1994;47:383-8. [PMID: 7730863]
  74. Ajwani S, Mattila KJ, Tilvis RS, Ainamo A. Periodontal disease and mortality in an aged population. Spec Care Dentist. 2003;23:125-30. [PMID: 14765890]
  75. Beck J, Garcia R, Heiss G, Vokonas PS, Offenbacher S. Periodontal disease and cardiovascular disease. J Periodontol. 1996;67:1123-37. [PMID: 8910831]
  76. Howell TH, Ridker PM, Ajani UA, Hennekens CH, Christen WG. Periodontal disease and risk of subsequent cardiovascular disease in U.S. male physicians. J Am Coll Cardiol. 2001;37:445-50. [PMID: 11216961]
  77. Morrison HI, Ellison LF, Taylor GW. Periodontal disease and risk of fatal coronary heart and cerebrovascular diseases. J Cardiovasc Risk. 1999;6:7-11. [PMID: 10197286]
  78. Tuominen R, Reunanen A, Paunio M, Paunio I, Aromaa A. Oral health indicators poorly predict coronary heart disease deaths. J Dent Res. 2003;82:713-8. [PMID: 12939356]
  79. Yu CM, Zhang Q, Lam L, Lin H, Kong SL, Chan W, et al. Comparison of intensive and low-dose atorvastatin therapy in the reduction of carotid intimal-medial thickness in patients with coronary heart disease. Heart. 2007;93:933-9. [PMID: 17344325]
  80. Crouse JR 3rd, Raichlen JS, Riley WA, Evans GW, Palmer MK, O'Leary DH, et al; METEOR Study Group. Effect of rosuvastatin on progression of carotid intima-media thickness in low-risk individuals with subclinical atherosclerosis: the METEOR Trial. JAMA. 2007;297:1344-53. [PMID: 17384434]
  81. Hodis HN, Mack WJ, LaBree L, Selzer RH, Liu CR, Liu CH, et al. The role of carotid arterial intima-media thickness in predicting clinical coronary events. Ann Intern Med. 1998;128:262-9. [PMID: 9471928]
  82. Belcaro G, Nicolaides AN, Laurora G, Cesarone MR, De Sanctis M, Incandela L, et al. Ultrasound morphology classification of the arterial wall and cardiovascular events in a 6-year follow-up study. Arterioscler Thromb Vasc Biol. 1996;16:851-6. [PMID: 8673559]
  83. Bots ML, Hoes AW, Koudstaal PJ, Hofman A, Grobbee DE. Common carotid intima-media thickness and risk of stroke and myocardial infarction: the Rotterdam Study. Circulation. 1997;96:1432-7. [PMID: 9315528]
  84. Cao JJ, Arnold AM, Manolio TA, Polak JF, Psaty BM, Hirsch CH, et al. Association of carotid artery intima-media thickness, plaques, and C-reactive protein with future cardiovascular disease and all-cause mortality: the Cardiovascular Health Study. Circulation. 2007;116:32-8. [PMID: 17576871]
  85. Cao JJ, Thach C, Manolio TA, Psaty BM, Kuller LH, Chaves PH, et al. C-reactive protein, carotid intima-media thickness, and incidence of ischemic stroke in the elderly: the Cardiovascular Health Study. Circulation. 2003;108:166-70. [PMID: 12821545]
  86. Chambless LE, Folsom AR, Clegg LX, Sharrett AR, Shahar E, Nieto FJ, et al. Carotid wall thickness is predictive of incident clinical stroke: the Atherosclerosis Risk in Communities (ARIC) study. Am J Epidemiol. 2000;151:478-87. [PMID: 10707916]
  87. 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]
  88. 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]
  89. Folsom AR, Kronmal RA, Detrano RC, O'Leary DH, Bild DE, Bluemke DA, et al. Coronary artery calcification compared with carotid intima-media thickness in the prediction of cardiovascular disease incidence: the Multi-Ethnic Study of Atherosclerosis (MESA). Arch Intern Med. 2008;168:1333-9. [PMID: 18574091]
  90. Johnsen SH, Mathiesen EB, Joakimsen O, Stensland E, Wilsgaard T, Løchen ML, et al. Carotid atherosclerosis is a stronger predictor of myocardial infarction in women than in men: a 6-year follow-up study of 6226 persons: the Tromsø Study. Stroke. 2007;38:2873-80. [PMID: 17901390]
  91. Kitamura A, Iso H, Imano H, Ohira T, Okada T, Sato S, et al. Carotid intima-media thickness and plaque characteristics as a risk factor for stroke in Japanese elderly men. Stroke. 2004;35:2788-94. [PMID: 15528460]
  92. Lorenz MW, von Kegler S, Steinmetz H, Markus HS, Sitzer M. Carotid intima-media thickening indicates a higher vascular risk across a wide age range: prospective data from the Carotid Atherosclerosis Progression Study (CAPS). Stroke. 2006;37:87-92. [PMID: 16339465]
  93. Murakami S, Otsuka K, Hotta N, Yamanaka G, Kubo Y, Matsuoka O, et al. Common carotid intima-media thickness is predictive of all-cause and cardiovascular mortality in elderly community-dwelling people: Longitudinal Investigation for the Longevity and Aging in Hokkaido County (LILAC) study. Biomed Pharmacother. 2005;59 Suppl 1:S49-53. [PMID: 16275507]
  94. 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]
  95. Prabhakaran S, Rundek T, Ramas R, Elkind MS, Paik MC, Boden-Albala B, et al. Carotid plaque surface irregularity predicts ischemic stroke: the northern Manhattan study. Stroke. 2006;37:2696-701. [PMID: 17008627]
  96. Prabhakaran S, Singh R, Zhou X, Ramas R, Sacco RL, Rundek T. Presence of calcified carotid plaque predicts vascular events: the Northern Manhattan Study. Atherosclerosis. 2007;195:e197-201. [PMID: 17482197]
  97. Rosvall M, Janzon L, Berglund G, Engström G, Hedblad B. Incident coronary events and case fatality in relation to common carotid intima-media thickness. J Intern Med. 2005;257:430-7. [PMID: 15836659]
  98. Salonen JT, Salonen R. Ultrasonographically assessed carotid morphology and the risk of coronary heart disease. Arterioscler Thromb. 1991;11:1245-9. [PMID: 1911709]
  99. 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]
  100. Tzou WS, Douglas PS, Srinivasan SR, Bond MG, Tang R, Li S, et al. Distribution and predictors of carotid intima-media thickness in young adults. Prev Cardiol. 2007;10:181-9. [PMID: 17917514]
  101. Howard G, Sharrett AR, Heiss G, Evans GW, Chambless LE, Riley WA, et al. Carotid artery intimal-medial thickness distribution in general populations as evaluated by B-mode ultrasound. ARIC Investigators. Stroke. 1993;24:1297-304. [PMID: 8362421]
  102. Lloyd-Jones DM, Liu K, Tian L, Greenland P. Narrative review: Assessment of C-reactive protein in risk prediction for cardiovascular disease. Ann Intern Med. 2006;145:35-42. [PMID: 16818927]
  103. Kronmal RA, McClelland RL, Detrano R, Shea S, Lima JA, Cushman M, et al. Risk factors for the progression of coronary artery calcification in asymptomatic subjects: results from the Multi-Ethnic Study of Atherosclerosis (MESA). Circulation. 2007;115:2722-30. [PMID: 17502571]
  104. Bild DE, Bluemke DA, Burke GL, Detrano R, Diez Roux AV, Folsom AR, et al. Multi-ethnic study of atherosclerosis: objectives and design. Am J Epidemiol. 2002;156:871-81. [PMID: 12397006]
  105. Schreiner PJ. Lipoprotein(a) as a risk factor for preclinical atherosclerotic disease in a biracial cohort: the Atherosclerosis Risk in Communities (ARIC) Study.Chem Phys Lipids. 1994;67-68:405-10. [PMID: 8187241]
  106. Woodward M, Rumley A, Welsh P, MacMahon S, Lowe G. A comparison of the associations between seven hemostatic or inflammatory variables and coronary heart disease. J Thromb Haemost. 2007;5:1795-800. [PMID: 17723116]
  107. Witherell HL, Smith KL, Friedman GD, Ley C, Thom DH, Orentreich N, et al. C-reactive protein, Helicobacter pylori, Chlamydia pneumoniae, cytomegalovirus and risk for myocardial infarction. Ann Epidemiol. 2003;13:170-7. [PMID: 12604160]
  108. Wang TJ, Gona P, Larson MG, Tofler GH, Levy D, Newton-Cheh C, et al. Multiple biomarkers for the prediction of first major cardiovascular events and death. N Engl J Med. 2006;355:2631-9. [PMID: 17182988]
  109. Tzoulaki I, Murray GD, Lee AJ, Rumley A, Lowe GD, Fowkes FG. Relative value of inflammatory, hemostatic, and rheological factors for incident myocardial infarction and stroke: the Edinburgh Artery Study. Circulation. 2007;115:2119-27. [PMID: 17404162]
  110. Mora S, Rifai N, Buring JE, Ridker PM. Additive value of immunoassay-measured fibrinogen and high-sensitivity C-reactive protein levels for predicting incident cardiovascular events. Circulation. 2006;114:381-7. [PMID: 16864722]
  111. Weatherley BD, Nelson JJ, Heiss G, Chambless LE, Sharrett AR, Nieto FJ, et al. The association of the ankle-brachial index with incident coronary heart disease: the Atherosclerosis Risk In Communities (ARIC) study, 1987-2001. BMC Cardiovasc Disord. 2007;7:3. [PMID: 17227586]
  112. Ballantyne CM, Hoogeveen RC, Bang H, Coresh J, Folsom AR, Heiss G, et al. Lipoprotein-associated phospholipase A2, high-sensitivity C-reactive protein, and risk for incident coronary heart disease in middle-aged men and women in the Atherosclerosis Risk in Communities (ARIC) study. Circulation. 2004;109:837-42. [PMID: 14757686]
  113. Folsom AR, Aleksic N, Catellier D, Juneja HS, Wu KK. C-reactive protein and incident coronary heart disease in the Atherosclerosis Risk In Communities (ARIC) study. Am Heart J. 2002;144:233-8. [PMID: 12177639]
  114. Folsom AR, Chambless LE, Ballantyne CM, Coresh J, Heiss G, Wu KK, et al. 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. 2006;166:1368-73. [PMID: 16832001]
  115. Folsom AR, Nieto FJ, McGovern PG, Tsai MY, Malinow MR, Eckfeldt JH, et al. Prospective study of coronary heart disease incidence in relation to fasting total homocysteine, related genetic polymorphisms, and B vitamins: the Atherosclerosis Risk in Communities (ARIC) study. Circulation. 1998;98:204-10. [PMID: 9697819]
  116. Sharrett AR, Ballantyne CM, Coady SA, Heiss G, Sorlie PD, et al; Atherosclerosis Risk in Communities Study Group. Coronary heart disease prediction from lipoprotein cholesterol levels, triglycerides, lipoprotein(a), apolipoproteins A-I and B, and HDL density subfractions: The Atherosclerosis Risk in Communities (ARIC) Study. Circulation. 2001;104:1108-13. [PMID: 11535564]
  117. Kornitzer M, Dramaix M, Sobolski J, Degre S, De Backer G. Ankle/arm pressure index in asymptomatic middle-aged males: an independent predictor of ten-year coronary heart disease mortality. Angiology. 1995;46:211-9. [PMID: 7879961]
  118. Danesh J, Whincup P, Walker M, Lennon L, Thomson A, Appleby P, et al. Low grade inflammation and coronary heart disease: prospective study and updated meta-analyses. BMJ. 2000;321:199-204. [PMID: 10903648]
  119. Wald NJ, Watt HC, Law MR, Weir DG, McPartlin J, Scott JM. Homocysteine and ischemic heart disease: results of a prospective study with implications regarding prevention. Arch Intern Med. 1998;158:862-7. [PMID: 9570171]
  120. Lawlor DA, Smith GD, Rumley A, Lowe GD, Ebrahim S. Associations of fibrinogen and C-reactive protein with prevalent and incident coronary heart disease are attenuated by adjustment for confounding factors. British Women's Heart and Health Study. Thromb Haemost. 2005;93:955-63. [PMID: 15886815]
  121. Kronenberg F, Kronenberg MF, Kiechl S, Trenkwalder E, Santer P, Oberhollenzer F, et al. Role of lipoprotein(a) and apolipoprotein(a) phenotype in atherogenesis: prospective results from the Bruneck study. Circulation. 1999;100:1154-60. [PMID: 10484534]
  122. Lowe GD, Sweetnam PM, Yarnell JW, Rumley A, Rumley C, Bainton D, et al. C-reactive protein, fibrin D-dimer, and risk of ischemic heart disease: the Caerphilly and Speedwell studies. Arterioscler Thromb Vasc Biol. 2004;24:1957-62. [PMID: 15308549]
  123. Lowe GD, Yarnell JW, Rumley A, Bainton D, Sweetnam PM. C-reactive protein, fibrin D-dimer, and incident ischemic heart disease in the Speedwell study: are inflammation and fibrin turnover linked in pathogenesis? Arterioscler Thromb Vasc Biol. 2001;21:603-10. [PMID: 11304479]
  124. Fallon UB, Ben-Shlomo Y, Elwood P, Ubbink JB, Smith GD. Homocysteine and coronary heart disease in the Caerphilly cohort: a 10 year follow up. Heart. 2001;85:153-8. [PMID: 11156664]
  125. Yarnell JW, Patterson CC, Sweetnam PM, Lowe GD. Haemostatic/inflammatory markers predict 10-year risk of IHD at least as well as lipids: the Caerphilly collaborative studies. Eur Heart J. 2004;25:1049-56. [PMID: 15191776]
  126. 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]
  127. Newman AB, Shemanski L, Manolio TA, Cushman M, Mittelmark M, Polak JF, et al. Ankle-arm index as a predictor of cardiovascular disease and mortality in the Cardiovascular Health Study. The Cardiovascular Health Study Group. Arterioscler Thromb Vasc Biol. 1999;19:538-45. [PMID: 10073955]
  128. 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]
  129. 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]
  130. Leng GC, Fowkes FG, Lee AJ, Dunbar J, Housley E, Ruckley CV. Use of ankle brachial pressure index to predict cardiovascular events and death: a cohort study. BMJ. 1996;313:1440-4. [PMID: 8973232]
  131. Price JF, Lee AJ, Rumley A, Lowe GD, Fowkes FG. Lipoprotein (a) and development of intermittent claudication and major cardiovascular events in men and women: the Edinburgh Artery Study. Atherosclerosis. 2001;157:241-9. [PMID: 11427227]
  132. Boekholdt SM, Hack CE, Sandhu MS, Luben R, Bingham SA, Wareham NJ, et al. C-reactive protein levels and coronary artery disease incidence and mortality in apparently healthy men and women: the EPIC-Norfolk prospective population study 1993-2003. Atherosclerosis. 2006;187:415-22. [PMID: 16257408]
  133. Pischon T, Möhlig M, Hoffmann K, Spranger J, Weikert C, Willich SN, et al. Comparison of relative and attributable risk of myocardial infarction and stroke according to C-reactive protein and low-density lipoprotein cholesterol levels. Eur J Epidemiol. 2007;22:429-38. [PMID: 17557140]
  134. Tuomisto K, Jousilahti P, Sundvall J, Pajunen P, Salomaa V. C-reactive protein, interleukin-6 and tumor necrosis factor a as predictors of incident coronary and cardiovascular events and total mortality. A population-based, prospective study. Thromb Haemost. 2006;95:511-8. [PMID: 16525580]
  135. Salomaa V, Rasi V, Kulathinal S, Vahtera E, Jauhiainen M, Ehnholm C, et al. Hemostatic factors as predictors of coronary events and total mortality: the FINRISK '92 Hemostasis Study. Arterioscler Thromb Vasc Biol. 2002;22:353-8. [PMID: 11834541]
  136. Murabito JM, Evans JC, Nieto K, Larson MG, Levy D, Wilson PW. Prevalence and clinical correlates of peripheral arterial disease in the Framingham Offspring Study. Am Heart J. 2002;143:961-5. [PMID: 12075249]
  137. Wilson PW, Nam BH, Pencina M, D'Agostino RB Sr, Benjamin EJ, O'Donnell CJ. C-reactive protein and risk of cardiovascular disease in men and women from the Framingham Heart Study. Arch Intern Med. 2005;165:2473-8. [PMID: 16314543]
  138. Bostom AG, Silbershatz H, Rosenberg IH, Selhub J, D'Agostino RB, Wolf PA, et al. Nonfasting plasma total homocysteine levels and all-cause and cardiovascular disease mortality in elderly Framingham men and women. Arch Intern Med. 1999;159:1077-80. [PMID: 10335684]
  139. Zylberstein DE, Bengtsson C, Björkelund C, Landaas S, Sundh V, Thelle D, et al. Serum homocysteine in relation to mortality and morbidity from coronary heart disease: a 24-year follow-up of the population study of women in Gothenburg. Circulation. 2004;109:601-6. [PMID: 14769681]
  140. Rosengren A, Wilhelmsen L, Eriksson E, Risberg B, Wedel H. Lipoprotein (a) and coronary heart disease: a prospective case-control study in a general population sample of middle aged men. BMJ. 1990;301:1248-51. [PMID: 2148699]
  141. Cremer P, Nagel D, Mann H, Labrot B, Müller-Berninger R, Elster H, et al. Ten-year follow-up results from the Goettingen Risk, Incidence and Prevalence Study (GRIPS). I. Risk factors for myocardial infarction in a cohort of 5790 men. Atherosclerosis. 1997;129:221-30. [PMID: 9105565]
  142. Fowler B, Jamrozik K, Norman P, Allen Y. Prevalence of peripheral arterial disease: persistence of excess risk in former smokers. Aust NZ J Public Health. 2002;26:219-24. [PMID: 12141616]
  143. Pai JK, Pischon T, Ma J, Manson JE, Hankinson SE, Joshipura K, et al. Inflammatory markers and the risk of coronary heart disease in men and women. N Engl J Med. 2004;351:2599-610. [PMID: 15602020]
  144. Pischon T, Girman CJ, Sacks FM, Rifai N, Stampfer MJ, Rimm EB. Non-high-density lipoprotein cholesterol and apolipoprotein B in the prediction of coronary heart disease in men. Circulation. 2005;112:3375-83. [PMID: 16316964]
  145. Hung HC, Joshipura KJ, Colditz G, Manson JE, Rimm EB, Speizer FE, et al. The association between tooth loss and coronary heart disease in men and women. J Public Health Dent. 2004;64:209-15. [PMID: 15562943]
  146. Jauhiainen M, Koskinen P, Ehnholm C, Frick MH, Mänttäri M, Manninen V, et al. Lipoprotein (a) and coronary heart disease risk: a nested case-control study of the Helsinki Heart Study participants. Atherosclerosis. 1991;89:59-67. [PMID: 1837713]
  147. Abbott RD, Petrovitch H, Rodriguez BL, Yano K, Schatz IJ, Popper JS, et al. Ankle/brachial blood pressure in men > 70 years of age and the risk of coronary heart disease. Am J Cardiol. 2000;86:280-4. [PMID: 10922433]
  148. Jager A, Kostense PJ, Ruhé HG, Heine RJ, Nijpels G, Dekker JM, et al. Microalbuminuria and peripheral arterial disease are independent predictors of cardiovascular and all-cause mortality, especially among hypertensive subjects: five-year follow-up of the Hoorn Study. Arterioscler Thromb Vasc Biol. 1999;19:617-24. [PMID: 10073965]
  149. Nurk E, Tell GS, Vollset SE, Nygård O, Refsum H, Ueland PM. Plasma total homocysteine and hospitalizations for cardiovascular disease: the Hordaland Homocysteine Study. Arch Intern Med. 2002;162:1374-81. [PMID: 12076236]
  150. Vollset SE, Refsum H, Tverdal A, Nygård O, Nordrehaug JE, Tell GS, et al. Plasma total homocysteine and cardiovascular and noncardiovascular mortality: the Hordaland Homocysteine Study. Am J Clin Nutr. 2001;74:130-6. [PMID: 11451728]
  151. McDermott MM, Guralnik JM, Albay M, Bandinelli S, Miniati B, Ferrucci L. Impairments of muscles and nerves associated with peripheral arterial disease and their relationship with lower extremity functioning: the InCHIANTI Study. J Am Geriatr Soc. 2004;52:405-10. [PMID: 14962156]
  152. Voutilainen S, Virtanen JK, Rissanen TH, Alfthan G, Laukkanen J, Nyyssönen K, et al. Serum folate and homocysteine and the incidence of acute coronary events: the Kuopio Ischaemic Heart Disease Risk Factor Study. Am J Clin Nutr. 2004;80:317-23. [PMID: 15277151]
  153. Hooi JD, Kester AD, Stoffers HE, Rinkens PE, Knottnerus JA, van Ree JW. Asymptomatic peripheral arterial occlusive disease predicted cardiovascular morbidity and mortality in a 7-year follow-up study. J Clin Epidemiol. 2004;57:294-300. [PMID: 15066690]
  154. Schaefer EJ, Lamon-Fava S, Jenner JL, McNamara JR, Ordovas JM, Davis CE, et al. Lipoprotein(a) levels and risk of coronary heart disease in men. The lipid Research Clinics Coronary Primary Prevention Trial. JAMA. 1994;271:999-1003. [PMID: 8139085]
  155. Lind P, Hedblad B, Hultberg B, Stavenow L, Janzon L, Lindgärde F. Risk of myocardial infarction in relation to plasma levels of homocysteine and inflammation-sensitive proteins: a long-term nested case-control study. Angiology. 2003;54:401-10. [PMID: 12934759]
  156. Ogren M, Hedblad B, Isacsson SO, Janzon L, Jungquist G, Lindell SE. Non-invasively detected carotid stenosis and ischaemic heart disease in men with leg arteriosclerosis. Lancet. 1993;342:1138-41. [PMID: 7901475]
  157. Knekt P, Alfthan G, Aromaa A, Heliövaara M, Marniemi J, Rissanen H, et al. Homocysteine and major coronary events: a prospective population study amongst women. J Intern Med. 2001;249:461-5. [PMID: 11350570]
  158. Knekt P, Reunanen A, Alfthan G, Heliövaara M, Rissanen H, Marniemi J, et al. Hyperhomocystinemia: a risk factor or a consequence of coronary heart disease? Arch Intern Med. 2001;161:1589-94. [PMID: 11434790]
  159. Koenig W, Khuseyinova N, Baumert J, Thorand B, Loewel H, Chambless L, et al. Increased concentrations of C-reactive protein and IL-6 but not IL-18 are independently associated with incident coronary events in middle-aged men and women: results from the MONICA/KORA Augsburg case-cohort study, 1984-2002. Arterioscler Thromb Vasc Biol. 2006;26:2745-51. [PMID: 17008587]
  160. Koenig W, Khuseyinova N, Löwel H, Trischler G, Meisinger C. Lipoprotein-associated phospholipase A2 adds to risk prediction of incident coronary events by C-reactive protein in apparently healthy middle-aged men from the general population: results from the 14-year follow-up of a large cohort from southern Germany. Circulation. 2004;110:1903-8. [PMID: 15451783]
  161. Dahlén GH, Weinehall L, Stenlund H, Jansson JH, Hallmans G, Huhtasaari F, et al. Lipoprotein(a) and cholesterol levels act synergistically and apolipoprotein A-I is protective for the incidence of primary acute myocardial infarction in middle-aged males. An incident case-control study from Sweden. J Intern Med. 1998;244:425-30. [PMID: 9845859]
  162. Thøgersen AM, Söderberg S, Jansson JH, Dahlén G, Boman K, NilssonTK, et al. Interactions between fibrinolysis, lipoproteins and leptin related to a first myocardial infarction. Eur J Cardiovasc Prev Rehabil. 2004;11:33-40. [PMID: 15167204]
  163. Gram J, Bladbjerg EM, Møller L, Sjøl A, Jespersen J. Tissue-type plasminogen activator and C-reactive protein in acute coronary heart disease. A nested case-control study. J Intern Med. 2000;247:205-12. [PMID: 10692083]
  164. de Bree A, Verschuren WM, Blom HJ, Nadeau M, Trijbels FJ, Kromhout D. Coronary heart disease mortality, plasma homocysteine, and B-vitamins: a prospective study. Atherosclerosis. 2003;166:369-77. [PMID: 12535751]
  165. Evans RW, Shaten BJ, Hempel JD, Cutler JA, Kuller LH. Homocyst(e)ine and risk of cardiovascular disease in the Multiple Risk Factor Intervention Trial. Arterioscler Thromb Vasc Biol. 1997;17:1947-53. [PMID: 9351358]
  166. Evans RW, Shpilberg O, Shaten BJ, Ali S, Kamboh MI, Kuller LH. Prospective association of lipoprotein(a) concentrations and apo(a) size with coronary heart disease among men in the Multiple Risk Factor Intervention Trial. J Clin Epidemiol. 2001;54:51-7. [PMID: 11165468]
  167. Raggi P, Cooil B, Callister TQ. Use of electron beam tomography data to develop models for prediction of hard coronary events. Am Heart J. 2001;141:375-82. [PMID: 11231434]
  168. Hujoel PP, Drangsholt M, Spiekerman C, DeRouen TA. Periodontal disease and coronary heart disease risk. JAMA. 2000;284:1406-10. [PMID: 10989403]
  169. Hujoel PP, Drangsholt M, Spiekerman C, Derouen TA. Examining the link between coronary heart disease and the elimination of chronic dental infections. J Am Dent Assoc. 2001;132:883-9. [PMID: 11480641]
  170. Alfthan G, Pekkanen J, Jauhiainen M, Pitkäniemi J, Karvonen M, Tuomilehto J, et al. Relation of serum homocysteine and lipoprotein(a) concentrations to atherosclerotic disease in a prospective Finnish population based study. Atherosclerosis. 1994;106:9-19. [PMID: 8018111]
  171. Sacco RL, Anand K, Lee HS, Boden-Albala B, Stabler S, Allen R, et al. Homocysteine and the risk of ischemic stroke in a triethnic cohort: the NOrthern MAnhattan Study. Stroke. 2004;35:2263-9. [PMID: 15345803]
  172. Shai I, Stampfer MJ, Ma J, Manson JE, Hankinson SE, Cannuscio C, et al. Homocysteine as a risk factor for coronary heart diseases and its association with inflammatory biomarkers, lipids and dietary factors. Atherosclerosis. 2004;177:375-81. [PMID: 15530913]
  173. Nguyen TT, Ellefson RD, Hodge DO, Bailey KR, Kottke TE, Abu-Lebdeh HS. Predictive value of electrophoretically detected lipoprotein(a) for coronary heart disease and cerebrovascular disease in a community-based cohort of 9936 men and women. Circulation. 1997;96:1390-7. [PMID: 9315522]
  174. Ridker PM, Cushman M, Stampfer MJ, Tracy RP, Hennekens CH. Inflammation, aspirin, and the risk of cardiovascular disease in apparently healthy men. N Engl J Med. 1997;336:973-9. [PMID: 9077376]
  175. Ridker PM, Hennekens CH, Stampfer MJ. A prospective study of lipoprotein(a) and the risk of myocardial infarction. JAMA. 1993;270:2195-9. [PMID: 8411602]
  176. Stampfer MJ, Malinow MR, Willett WC, Newcomer LM, Upson B, Ullmann D, et al. A prospective study of plasma homocyst(e)ine and risk of myocardial infarction in US physicians. JAMA. 1992;268:877-81. [PMID: 1640615]
  177. von Eckardstein A, Schulte H, Cullen P, Assmann G. Lipoprotein(a) further increases the risk of coronary events in men with high global cardiovascular risk. J Am Coll Cardiol. 2001;37:434-9. [PMID: 11216959]
  178. Luc G, Bard JM, Arveiler D, Ferrieres J, Evans A, Amouyel P, et al; PRIME Study Group. Lipoprotein (a) as a predictor of coronary heart disease: the PRIME Study. Atherosclerosis. 2002;163:377-84. [PMID: 12052486]
  179. Luc G, Bard JM, Juhan-Vague I, Ferrieres J, Evans A, Amouyel P, et al; PRIME Study Group. C-reactive protein, interleukin-6, and fibrinogen as predictors of coronary heart disease: the PRIME Study. Arterioscler Thromb Vasc Biol. 2003;23:1255-61. [PMID: 12775578]
  180. Pirro M, Bergeron J, Dagenais GR, Bernard PM, Cantin B, Després JP, et al. Age and duration of follow-up as modulators of the risk for ischemic heart disease associated with high plasma C-reactive protein levels in men. Arch Intern Med. 2001;161:2474-80. [PMID: 11700160]
  181. St-Pierre AC, Cantin B, Bergeron J, Pirro M, Dagenais GR, Després JP, et al. Inflammatory markers and long-term risk of ischemic heart disease in men. A 13-year follow-up of the Quebec Cardiovascular Study. Atherosclerosis. 2005;182:315-21. [PMID: 16159604]
  182. Cantin B, Gagnon F, Moorjani S, Després JP, Lamarche B, Lupien PJ, et al. Is lipoprotein(a) an independent risk factor for ischemic heart disease in men? The Quebec Cardiovascular Study. J Am Coll Cardiol. 1998;31:519-25. [PMID: 9502629]
  183. Danesh J, Wheeler JG, Hirschfield GM, Eda S, Eiriksdottir G, Rumley A, et al. C-reactive protein and other circulating markers of inflammation in the prediction of coronary heart disease. N Engl J Med. 2004;350:1387-97. [PMID: 15070788]
  184. Bots ML, Launer LJ, Lindemans J, Hoes AW, Hofman A, Witteman JC, et al. Homocysteine and short-term risk of myocardial infarction and stroke in the elderly: the Rotterdam Study. Arch Intern Med. 1999;159:38-44. [PMID: 9892328]
  185. van der Meer IM, de Maat MP, Kiliaan AJ, van der Kuip DA, Hofman A, Witteman JC. The value of C-reactive protein in cardiovascular risk prediction: the Rotterdam Study. Arch Intern Med. 2003;163:1323-8. [PMID: 12796068]
  186. Criqui MH, Langer RD, Fronek A, Feigelson HS, Klauber MR, McCann TJ, et al. Mortality over a period of 10 years in patients with peripheral arterial disease. N Engl J Med. 1992;326:381-6. [PMID: 1729621]
  187. Hiatt WR, Hoag S, Hamman RF. Effect of diagnostic criteria on the prevalence of peripheral arterial disease. The San Luis Valley Diabetes Study. Circulation. 1995;91:1472-9. [PMID: 7867189]
  188. Seed M, Ayres KL, Humphries SE, Miller GJ. Lipoprotein (a) as a predictor of myocardial infarction in middle-aged men. Am J Med. 2001;110:22-7. [PMID: 11152861]
  189. Park R, Detrano R, Xiang M, Fu P, Ibrahim Y, LaBree L, et al. Combined use of computed tomography coronary calcium scores and C-reactive protein levels in predicting cardiovascular events in nondiabetic individuals. Circulation. 2002;106:2073-7. [PMID: 12379576]
  190. 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]
  191. Arad Y, Goodman KJ, Roth M, Newstein D, Guerci AD. Coronary calcification, coronary disease risk factors, C-reactive protein, and atherosclerotic cardiovascular disease events: the St. Francis Heart Study. J Am Coll Cardiol. 2005;46:158-65. [PMID: 15992651]
  192. Arad Y, Spadaro LA, Goodman K, Newstein D, Guerci AD. Prediction of coronary events with electron beam computed tomography. J Am Coll Cardiol. 2000;36:1253-60. [PMID: 11028480]
  193. Wild SH, Fortmann SP, Marcovina SM. A prospective case-control study of lipoprotein(a) levels and apo(a) size and risk of coronary heart disease in Stanford Five-City Project participants. Arterioscler Thromb Vasc Biol. 1997;17:239-45. [PMID: 9081676]
  194. Resnick HE, Lindsay RS, McDermott MM, Devereux RB, Jones KL, Fabsitz RR, et al. Relationship of high and low ankle brachial index to all-cause and cardiovascular disease mortality: the Strong Heart Study. Circulation. 2004;109:733-9. [PMID: 14970108]
  195. Arnesen E, Refsum H, Bønaa KH, Ueland PM, Førde OH, Nordrehaug JE. Serum total homocysteine and coronary heart disease. Int J Epidemiol. 1995;24:704-9. [PMID: 8550266]
  196. McDermott MM, Fried L, Simonsick E, Ling S, Guralnik JM. Asymptomatic peripheral arterial disease is independently associated with impaired lower extremity functioning: the women's health and aging study. Circulation. 2000;101:1007-12. [PMID: 10704168]
  197. Pradhan AD, Manson JE, Rossouw JE, Siscovick DS, Mouton CP, Rifai N, et al. Inflammatory biomarkers, hormone replacement therapy, and incident coronary heart disease: prospective analysis from the Women's Health Initiative observational study. JAMA. 2002;288:980-7. [PMID: 12190368]
  198. Blake GJ, Rifai N, Buring JE, Ridker PM. Blood pressure, C-reactive protein, and risk of future cardiovascular events. Circulation. 2003;108:2993-9. [PMID: 14638538]
  199. Everett BM, Kurth T, Buring JE, Ridker PM. The relative strength of C-reactive protein and lipid levels as determinants of ischemic stroke compared with coronary heart disease in women. J Am Coll Cardiol. 2006;48:2235-42. [PMID: 17161253]
  200. Ridker PM, Rifai N, Cook NR, Bradwin G, Buring JE. Non-HDL cholesterol, apolipoproteins A-I and B100, standard lipid measures, lipid ratios, and CRP as risk factors for cardiovascular disease in women. JAMA. 2005;294:326-33. [PMID: 16030277]
  201. Ridker PM, Rifai N, Rose L, Buring JE, Cook NR. Comparison of C-reactive protein and low-density lipoprotein cholesterol levels in the prediction of first cardiovascular events. N Engl J Med. 2002;347:1557-65. [PMID: 12432042]
  202. Ridker PM, Hennekens CH, Buring JE, Rifai N. C-reactive protein and other markers of inflammation in the prediction of cardiovascular disease in women. N Engl J Med. 2000;342:836-43. [PMID: 10733371]
  203. Ridker PM, Buring JE, Shih J, Matias M, Hennekens CH. Prospective study of C-reactive protein and the risk of future cardiovascular events among apparently healthy women. Circulation. 1998;98:731-3. [PMID: 9727541]
  204. Suk Danik J, Rifai N, Buring JE, Ridker PM. Lipoprotein(a), measured with an assay independent of apolipoprotein(a) isoform size, and risk of future cardiovascular events among initially healthy women. JAMA. 2006;296:1363-70. [PMID: 16985228]
  205. Rifai N, Buring JE, Lee IM, Manson JE, Ridker PM. Is C-reactive protein specific for vascular disease in women? Ann Intern Med. 2002;136:529-33. [PMID: 11926788]
  206. Stehouwer CD, Weijenberg MP, van den Berg M, Jakobs C, Feskens EJ, Kromhout D. Serum homocysteine and risk of coronary heart disease and cerebrovascular disease in elderly men: a 10-year follow-up. Arterioscler Thromb Vasc Biol. 1998;18:1895-901. [PMID: 9848881]
  207. Wilson PW, D'Agostino RB, Levy D, Belanger AM, Silbershatz H, Kannel WB. Prediction of coronary heart disease using risk factor categories. Circulation. 1998;97:1837-47. [PMID: 9603539]
  208. McGill HC Jr, McMahan CA, Malcom GT, Oalmann MC, Strong JP. Effects of serum lipoproteins and smoking on atherosclerosis in young men and women. The PDAY Research Group. Pathobiological Determinants of Atherosclerosis in Youth. Arterioscler Thromb Vasc Biol. 1997;17:95-106. [PMID: 9012643]
  209. D'Agostino RB Sr, Grundy S, Sullivan LM, Wilson P; CHD Risk Prediction Group. Validation of the Framingham coronary heart disease prediction scores: results of a multiple ethnic groups investigation. JAMA. 2001;286:180-7. [PMID: 11448281]
  210. National Cholesterol Education Program (NCEP) Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III). 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) final report. Circulation. 2002;106:3143-421. [PMID: 12485966]
  211. Grundy SM, Cleeman JI, Merz CN, Brewer HB Jr, Clark LT, Hunninghake DB, et al; National Heart, Lung, and Blood Institute. Implications of recent clinical trials for the National Cholesterol Education Program Adult Treatment Panel III guidelines. Circulation. 2004;110:227-39. [PMID: 15249516]
  212. Ford ES, Giles WH, Mokdad AH. The distribution of 10-Year risk for coronary heart disease among US adults: findings from the National Health and Nutrition Examination Survey III. J Am Coll Cardiol. 2004;43:1791-6. [PMID: 15145101]
Return to Table of Contents