Skip Navigation
American College of Physicians Logo
  • Subscribe
  • Submit a Manuscript
  • Sign In
    Sign in below to access your subscription for full content
    INDIVIDUAL SIGN IN
    Sign In|Set Up Account
    You will be directed to acponline.org to register and create your Annals account
    INSTITUTIONAL SIGN IN
    Open Athens|Shibboleth|Log In
    Annals of Internal Medicine
    SUBSCRIBE
    Subscribe to Annals of Internal Medicine.
    You will be directed to acponline.org to complete your purchase.
Annals of Internal Medicine Logo Menu
  • Latest
  • Issues
  • Channels
  • CME/MOC
  • In the Clinic
  • Journal Club
  • Web Exclusives
  • Author Info
Advanced Search
  • ‹ PREV ARTICLE
  • This Issue
  • NEXT ARTICLE ›
Clinical Guidelines |6 October 2009

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 Free

David I. Buckley, MD, MPH; Rongwei Fu, PhD; Michele Freeman, MPH; Kevin Rogers, MD; Mark Helfand, MD, MPH

David I. Buckley, MD, MPH

Rongwei Fu, PhD

Michele Freeman, MPH

Kevin Rogers, MD

Mark Helfand, MD, MPH

Article, Author, and Disclosure Information
Author, Article, and Disclosure Information
Acknowledgment: The authors thank Agency for Healthcare Research and Quality Medical Officer Janelle Guirguis-Blake, MD, for commenting on draft versions of the Systematic Evidence Synthesis (22) 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.
Grant Support: By the Agency for Healthcare Research and Quality (contract no. 290-02-0024, Task Order Number 2).
Potential Conflicts of Interest: None disclosed.
Requests for Single Reprints: David I. Buckley, MD, MPH, Oregon Health & Science University, Mailcode FM, 3181 Southwest Sam Jackson Park Road, Portland, OR 97239.
Current Author Addresses: Drs. Buckley, Fu, and Helfand: Oregon Health & Science University, Mailcode FM, 3181 Southwest Sam Jackson Park Road, Portland, OR 97239.
Ms. Freeman: Portland Veterans Affairs Medical Center, 3710 U.S. Veterans Hospital Road, Mailcode RD 71, Portland, OR 97239.
Dr. Rogers: 2150 South Main 511, Salt Lake City, UT 84115.
Author Contributions: Conception and design: D.I. Buckley, K. Rogers, M. Helfand.
Analysis and interpretation of the data: D.I. Buckley, R. Fu, M. Freeman, K. Rogers, M. Helfand.
Drafting of the article: D.I. Buckley, R. Fu, M. Helfand.
Critical revision of the article for important intellectual content: D.I. Buckley, R. Fu, M. Freeman, K. Rogers, M. Helfand.
Final approval of the article: D.I. Buckley, R. Fu, K. Rogers, M. Helfand.
Statistical expertise: R. Fu, M. Helfand.
Obtaining of funding: M. Helfand.
Administrative, technical, or logistic support: M. Freeman, M. Helfand.
Collection and assembly of data: D.I. Buckley, R. Fu, K. Rogers, M. Helfand.
  • From the Oregon Evidence-based Practice Center, Oregon Health & Science University, and Veterans Affairs Medical Center, Portland, Oregon, and University of Utah Health Sciences Center, Salt Lake City, Utah.
×
  • ‹ PREV ARTICLE
  • This Issue
  • NEXT ARTICLE ›
Jump To
  • Full Article
  • FULL ARTICLE
    • Abstract
    • Methods
    • Results
    • Discussion
      1. References
  • Figures
  • Tables
  • Supplements
  • Audio/Video
  • Summary for Patients
  • Clinical Slide Sets
  • CME / MOC
  • Comments
  • Twitter Link
  • Facebook Link
  • Email Link
More
  • LinkedIn Link
  • CiteULike Link

Abstract

Background:

C-reactive protein (CRP) may help to refine global risk assessment for coronary heart disease (CHD), particularly among persons who are at intermediate risk on the basis of traditional risk factors alone.

Purpose:

To assist the U.S. Preventive Services Task Force (USPSTF) in determining whether CRP should be incorporated into guidelines for CHD risk assessment.

Data Sources:

MEDLINE search of English-language articles (1966 to November 2007), supplemented by reference lists of reviews, pertinent studies, editorials, and Web sites and by expert suggestions.

Study Selection:

Prospective cohort, case–cohort, and nested case–control studies relevant to the independent predictive ability of CRP when used in intermediate-risk persons.

Data Extraction:

Included studies were reviewed according to predefined criteria, and the quality of each study was rated.

Data Synthesis:

The validity of the body of evidence and the net benefit or harm of using CRP for CHD risk assessment were evaluated. The combined magnitude of effect was determined by meta-analysis. The body of evidence is of good quality, consistency, and applicability. For good studies that adjusted for all Framingham risk variables, the summary estimate of relative risk for incident CHD was 1.58 (95% CI, 1.37 to 1.83) for CRP levels greater than 3.0 mg/L compared with levels less than 1.0 mg/L. Analyses from 4 large cohorts were consistent in finding evidence that including CRP improves risk stratification among initially intermediate-risk persons. C-reactive protein has desirable test characteristics, and good data exist on the prevalence of elevated CRP levels in intermediate-risk persons. Limited evidence links changes in CRP level to primary prevention of CHD events.

Limitations:

Study methods for measuring Framingham risk variables and other covariates varied. Ethnic and racial minority populations were poorly represented in most studies, limiting generalizability. Few studies directly assessed the effect of CRP on risk reclassification in intermediate-risk persons.

Conclusion:

Strong evidence indicates that CRP is associated with CHD events. Moderate, consistent evidence suggests that adding CRP to risk prediction models among initially intermediate-risk persons improves risk stratification. However, sufficient evidence that reducing CRP levels prevents CHD events is lacking.

In the United States, cardiovascular disease accounts for nearly 40% of all deaths each year (1). The factors that make up the Framingham risk score (age, sex, blood pressure, serum total cholesterol or low-density lipoprotein cholesterol level, high-density lipoprotein cholesterol level, cigarette smoking, and diabetes) account for most of the excess risk for incident coronary heart disease (CHD) (2, 3). However, these factors do not explain all of the excess risk (4, 5), and approximately 40% of CHD deaths occur in persons with cholesterol levels that are lower than the population average (6). Several lines of evidence (7, 8) have implicated chronic inflammation in CHD, and inflammatory markers have received much attention as new or emerging risk factors that could account for some of the unexplained variability in CHD risk.
C-reactive protein (CRP) is a sensitive, nonspecific systemic marker of inflammation (9). Although it is unknown whether CRP is involved in CHD pathogenesis (10, 11), elevated serum CRP levels are associated with traditional cardiovascular risk factors and obesity (12, 13). In 2002, an expert panel recommended against routine use of CRP in risk assessment for primary prevention of CHD but supported CRP measurement in persons with a 10-year CHD risk of 10% to 20%. It noted that the benefits of this strategy “remain uncertain” and recommended further research into the implications of using CRP in risk categorization for therapeutic risk reduction in patients (14).
The potential clinical benefit of new risk factors for refining global risk assessment is thought to be greatest for persons who are classified as intermediate-risk when stratified by using conventional risk factors (15). In the Framingham risk scoring system, intermediate-risk persons are those with a 10% to 20% risk for coronary death or nonfatal myocardial infarction (“hard CHD events”) over 10 years. Further stratification by using new markers might reclassify some intermediate-risk persons as low-risk (10-year risk <10%) and others as high-risk (10-year risk  >20%). This would permit more aggressive risk reduction therapy in persons reclassified as high-risk and may consequently reduce incident CHD events (16).
Several previous meta-analyses (17–19) have assessed the possible independent predictive ability of CRP level for incident CHD risk. In 1998, a meta-analysis of 5 long-term, population-based prospective cohort studies and 2 cohorts of patients with preexisting CHD (17) calculated a risk ratio for coronary events of 1.7 (95% CI, 1.4 to 2.1) for CRP levels in the top tertile versus the bottom tertile. An update of this meta-analysis in 2000 (18) included 7 additional studies. The combined risk ratio for the 11 population-based prospective cohort studies of persons without preexisting CHD was 2.0 (CI, 1.6 to 2.5). Another update in 2004 (19) included 11 new studies as well as the 11 previous cohorts. The combined odds ratio for all 22 studies was 1.58 (CI, 1.48 to 1.69).
These 3 meta-analyses, however, lacked a systematic assessment of the characteristics and quality of study design and execution. In particular, they did not systematically assess the degree of adjustment for standard measures of CHD risk (such as the Framingham risk score). Although the first 2 meta-analyses reported the degree of adjustment for potential confounders in each of the included studies, they did not specify how many or which standard coronary risk factors were adjusted for. Furthermore, these meta-analyses did not use the degree of adjustment as a basis for quality rating or inclusion. The most recent meta-analysis (19) did not rate quality or degree of adjustment for potential confounders. In addition, because the investigators used broad inclusion criteria, the studies in these meta-analyses do not necessarily represent the intermediate-risk population.
We conducted a systematic review and meta-analyses of epidemiologic studies to help the U.S. Preventive Services Task Force (USPSTF) determine whether CRP level should be incorporated into guidelines for coronary and cardiovascular risk assessment in primary care. Our review addresses the question of whether elevated CRP levels are independently predictive of incident CHD events, specifically among intermediate-risk persons. Our approach incorporated elements previously used by the USPSTF (20) and several domains of the approach developed by the Grading of Recommendations, Assessment, Development, and Evaluation workgroup (21).

Methods

Data Sources and Searches

We searched MEDLINE for original epidemiologic studies published between 1966 and November 2007. Our search strategy included the terms cardiovascular diseases, C-reactive protein, inflammation, and biological markers and was limited to articles published in English. We obtained additional articles from recent systematic reviews; reference lists of pertinent studies, reviews, editorials, and Web sites; and consultations with experts.

Study Selection

We included studies that published original data relevant to measuring the increased risk for incident CHD associated with elevated CRP level. We only considered prospective cohort studies (including those based on a cohort within a randomized trial), case–cohort studies, and nested case–control studies. We only included studies that had a follow-up of 2 years or more, reported the outcomes of coronary death and nonfatal myocardial infarction, and adjusted for a minimum of 5 of the 7 risk factors used in the Framingham risk score. We excluded studies in which no participants were likely to be classified as intermediate-risk by using the Framingham risk score and those conducted exclusively in patients with previously diagnosed coronary disease, coronary disease equivalents (such as diabetes), or medical conditions that may cause premature CHD. We included studies in which some patients had cardiovascular disease at baseline only if the studies adjusted for prevalent disease in their analysis. The full systematic evidence report (22) provides a more detailed description of our study methods.

Data Extraction and Quality Assessment

One investigator reviewed the relevant articles and recorded overlap with the studies included in previous meta-analyses. For our meta-analyses, when multiple articles were published from a single cohort, we included the findings from the analysis with the highest applicability to the study question and the highest validity, on the basis of our quality ratings. In general, we selected cohort studies over nested case–control studies, good-quality studies over fair-quality studies, studies that adjusted for more Framingham risk variables, studies with longer follow-up, and studies that most closely addressed our principal question.
We used standardized forms to abstract data on study design, population, size, CRP measurement, Framingham risk factor measurement, length of follow-up, outcomes, and data analysis. For each study, we recorded how many Framingham risk factors and other confounding factors were included in the model; whether the investigators reported model fit measures, discrimination measures, or model calibration statistics separately for models with and without CRP; and whether the study assessed the degree to which persons were reclassified on the basis of CRP level, overall or in the intermediate-risk group.
Two investigators used the USPSTF criteria (20) to independently assess the quality of each study as good, fair, or poor. These criteria are specific to the study design (cohort or nested case–control) and include such items as appropriate assembly or ascertainment of the cohort or the case patients and control participants, reliability and equal application of measurements, response or follow-up rate, and appropriate adjustment for confounding. Because we sought to evaluate the predictive ability of CRP independent of the Framingham risk factors, we required that a study adjust for all 7 of the Framingham variables to receive a quality rating of “good,” even if the study otherwise had high internal validity. We resolved disagreements regarding quality by discussion, further review, and adjudication by a third reviewer (if necessary).

Data Synthesis and Analysis

The ideal approach to assessing the clinical effect of expanding the Framingham risk score has been debated extensively. Most previous research on the effect of a new risk factor has focused on the c-statistic, a measure of discrimination. The c-statistic, however, may be a poor indicator of the effect of using CRP level to further stratify persons classified as intermediate-risk by the Framingham risk score. For this reason, recent literature (23–26) has emphasized that studies should examine how well assessing CRP level improves risk prediction and further risk stratification among persons initially classified as intermediate-risk.
Most studies provided an overall estimate of the risk associated with high CRP levels, after adjustment for other risk factors, but did not provide specific evidence about the intermediate-risk group. For these studies, we conducted 2 meta-analyses to obtain pooled adjusted risk ratios for the association of hard CHD events and CRP level. The first included all studies that were fair-quality or better, adjusted for at least 5 Framingham risk factors, included at least some participants who were likely to be at intermediate risk, and estimated the risk for CHD associated with CRP level after adjusting for confounders. Because including studies that had methodological flaws or assessed fewer Framingham risk factors could have led to overestimation of the pooled risk ratio, we conducted a second meta-analysis that was restricted to good-quality studies, all of which adjusted for all Framingham risk factors.
Because different studies reported ratios for different cutoff levels (including tertiles, quartiles, or quintiles), or as an increase in risk for a given unit of increase in CRP level, we standardized the risk ratio of CRP level for our meta-analyses to provide clinically relevant and easily interpretable results. We used currently recommended cutoff points (14) for low (<1.0 mg/L), average (1.0 to 3.0 mg/L), and high (>3.0 mg/L), with less than 1.0 mg/L as a reference. When studies used other cutoff points to categorize CRP level, we calculated risk ratios at cutoff points of 1.0 and 3.0 mg/L by assuming a log-normal distribution of CRP level (17, 27) and a log-linear association of CHD risk over the midrange of log-CRP levels (17, 28). We estimated distribution parameters of CRP level from published information from each study. We estimated CIs by using reported SEs for the coefficient of CRP level when studies analyzed CRP level as a continuous variable and by applying the same assumption of a log-linear relationship when studies categorized CRP level by using other cutoff points. We combined the risk ratio estimates by using a random-effects model to incorporate variation among studies into the combined estimate (29). We assessed statistical heterogeneity among the studies by using standard chi-square tests and estimated the magnitude of heterogeneity by using the I2 statistic (30). We used random-effect meta-regression to examine possible sources of heterogeneity and investigate whether the risk ratio estimates were associated with various study-level characteristics (30). We tested whether the distribution of the effect sizes was symmetric with respect to the precision measure by using funnel plots and the Egger linear regression method (31). We used Stata, version 10.0 (StataCorp, College Station, Texas), to perform the analyses.
Although our meta-analyses addressed whether CRP adds information to the Framingham risk score, they could not assess how well risk ratios derived from the entire population apply to intermediate-risk participants, or how those participants would be reclassified if CRP were used. To examine reclassification, we identified and critically appraised the studies that either compared predictive models that used all Framingham risk factors, with and without CRP levels, or measured the incidence of CHD events among intermediate-risk participants classified by CRP levels.

Role of the Funding Source

The Agency for Healthcare Research and Quality suggested the topic and provided copyright release for this manuscript but did not participate in the literature search, data analysis, or interpretation of the results.

Results

Study Characteristics

Of 1292 abstracts of potentially relevant studies, 37 published studies (8, 18, 19, 23, 28, 32–63) conducted in 24 cohorts met our inclusion criteria (Appendix Figure). (Appendix Tables 1 and 2, have more information on these studies.) From these, we identified 23 principal articles that represented the most pertinent publication for meta-analysis from each of the 24 cohorts (18, 19, 28, 33, 35, 37, 42–46, 48, 50–52, 54–56, 59–63) (Table). All but 1 study (37) explicitly excluded patients with baseline CHD or cardiovascular disease, and this study adjusted for prevalent CHD. All studies measured CRP level by using a high-sensitivity CRP assay.
Appendix Figure.
Literature search and selection.

FRS = Framingham risk score.

Image: 9FF4

Table.

Study Characteristics and Adjusted Estimates of CHD Risk Associated With CRP

Image: 9TT1
Table.
Thirteen of the 24 cohorts in our review were also included in the 2004 meta-analysis (19). Five of these 13 cohorts were represented by the same article in both our meta-analysis and the previous meta-analysis (18, 19, 46, 48, 54). For the other 8, we used more recent articles (33, 37, 42, 51, 52, 56, 59, 60). We included 1 additional cohort study published in 2002 (28) and studies from 10 new cohorts published after the timeframe of the previous meta-analysis (35, 43–45, 50, 55, 61–63). We excluded studies from 8 cohorts that the previous meta-analysis had included. Most of these were studies in which the participants were or were likely to be at increased risk for CHD (64–69). We excluded 2 studies from our review because they studied mortality only (70, 71). We rated 10 studies in 11 of the 24 cohorts as good-quality (33, 42, 44–46, 52, 55, 56, 60, 61) and 13 studies in 14 cohorts as fair-quality (18, 19, 28, 35, 37, 43, 48, 50, 51, 54, 59, 62, 63). Baseline CRP level was positively associated with incident CHD events in 23 of the 24 cohorts, with adjusted relative risks that ranged from 0.98 to 2.61.

Meta-analysis of Fair-Quality or Better Studies

Our meta-analysis of the 22 studies (in 23 cohorts) that explicitly excluded baseline CHD yielded a risk ratio of 1.60 (CI, 1.43 to 1.78) for high versus low CRP levels (Figure 1) and 1.26 (CI, 1.17 to 1.35) for average versus low CRP levels (Figure 2). Including the study that did not explicitly exclude baseline CHD (37) did not appreciably change the combined risk ratio estimates. We found statistically significant heterogeneity of effects among studies at a P value less than 0.100, both for the comparison of high versus low CRP levels (I2 = 31.9%; P = 0.072) and average versus low CRP levels (I2 = 44.0%; P = 0.015). However, the standardized estimates of effect were consistently positive, with a range of 0.98 to 2.75 for high CRP levels and 0.99 to 1.88 for average CRP levels. Furthermore, the positive relationship persisted in analyses of all subgroups at both high and average levels of CRP (Figure 3). In subgroup meta-regression analyses, we found no statistically significant differences among categories for any study-level characteristic, including number of Framingham variables and other covariates adjusted, outcome measures (major CHD events vs. major CHD plus other CHD events or cardiovascular events), study design, sex, quality rating, and length of follow-up. We conducted a sensitivity analysis to compare the 17 studies that required standardization of risk ratios with the 6 studies that used recommended cutoffs. The combined risk ratio estimates were similar between the 2 groups of studies. We detected no statistically significant asymmetry when we examined funnel plots or used the Egger linear regression method and no evidence of a tendency for smaller studies to show a larger degree of association.
Figure 1.
Risk ratio for coronary heart disease associated with C-reactive protein level >3.0 versus <1.0 mg/L.

* Number of participants included in the analysis.

Image: 9FF1
Figure 2.
Risk ratio for coronary heart disease associated with C-reactive protein level 1.0 to 3.0 versus <1.0 mg/L.
Image: 9FF2
Figure 3.
Analyses of all subgroups at high (>3.0 mg/L) and average (1.0 to 3.0 mg/L) CRP levels.

CHD = coronary heart disease; CRP = C-reactive protein; CVD = cardiovascular disease.

* Number of cohorts included in the analysis.

† Framingham risk factors are based on reference 2.

Image: 9FF3

Meta-analysis of Good-Quality Studies

We also performed a meta-analysis limited to the 10 good-quality studies from 11 cohorts, all of which adjusted for all Framingham risk factors or calculated a Framingham risk score (33, 42, 44–46, 52, 55, 56, 60, 61). The relative risk was 1.58 (CI, 1.37 to 1.83) for high versus low CRP levels (Figure 1) and 1.22 (CI, 1.11 to 1.33) for average versus low CRP levels (Figure 2). We found no statistically significant heterogeneity of effects among studies in this analysis. We excluded 4 fair-quality studies that used all Framingham risk factors (43, 50, 59, 62). We conducted a sensitivity analysis and found similar results with and without these 4 studies. The relative risk was 1.53 (CI, 1.36 to 1.73) for high versus low CRP levels and 1.20 (CI, 1.12 to 1.29) for average versus low CRP levels.

Reclassification of Persons at Intermediate Risk

From a clinical perspective, the most meaningful measure of CRP's value as a marker is its effect on rates of reclassification from intermediate-risk to other risk categories. Recent articles (24–26, 72) have proposed methods of assessing clinical risk reclassification when the goal of analysis is risk prediction. They note that measures of risk reclassification are probably better than the c-statistic for assessing the value of adding a new marker to a prediction model.
Five studies (23, 33, 40, 43, 56) included an analysis that compared predictive models that used all Framingham risk factors, with and without CRP level, specifically among participants whose 10-year Framingham risk score categorized them as intermediate-risk. Three of the 5 (23, 33, 43) measured the c-statistic or the area under the receiver-operating characteristic curve. Only 1 study (23) used statistical analyses to compare the calibration of prediction models with and without CRP level. Using data from the Women's Health Study, Cook and colleagues (23) demonstrated that although measures of discrimination did not substantially differ between models with and without CRP level, a model that included CRP level had better fit, as measured by the Hosmer–Lemeshow calibration statistic. In that analysis, 14% of participants originally classified as intermediate-risk (10% to 20%) were reclassified as low-risk (<10%) and 5% were reclassified as high-risk (>20%). The actual 10-year risk was 19.9% for those reclassified as high-risk and 11.5% for those who remained intermediate-risk.
The other 4 studies used less rigorous analyses to assess the effect of CRP level on risk classification and did not measure calibration, with mixed results. Three studies (33, 40, 56) found that assessing CRP improved risk stratification specifically among intermediate-risk participants. In the Monitoring of Trends and Determinants in Cardiovascular Disease study (33), assessing CRP level in addition to the Framingham risk factors resulted in improved risk classification among participants with an initial 10-year risk of 11% to 19%. Among participants with a CRP level greater than 3.0 mg/L, some with an initial 10-year risk of 15% to 19% were reclassified as high-risk, whereas no participants with an initial 10-year risk of 11% to 14% were reclassified as high-risk. In an analysis of data from the Women's Health Study (40), CRP level was clearly predictive of incident cardiovascular disease among participants with 10-year Framingham risk scores between 10% and 20%. The risk for cardiovascular events was twice as high for those with CRP levels between 1.0 and 3.0 mg/L or between 3.0 and 10.0 mg/L than for those with levels less than 1.0 mg/L, although CIs were not reported. Similarly, in an analysis from the Cardiovascular Health Study, CRP level added to risk prediction among men at intermediate risk (56). Among men with a 10-year Framingham risk score between 10% and 20%, the observed 10-year incidence of CHD was 32% for those with CRP levels greater than 3.0 mg/L, compared with between 15% and 16% for those with CRP levels between 1.0 and 3.0 mg/L or less than 1.0 mg/L (56). In that cohort, however, CRP level did not add to risk prediction among intermediate-risk women. The negative study (43), an analysis from the Framingham cohort, estimated the 10-year risk for incident cardiovascular disease by tertile of CRP level among participants previously stratified as having a 10-year Framingham risk score between 10% and 20%. Tertile cut-points were 0.81 mg/L and 3.78 mg/L. The estimated 10-year risk did not significantly differ among the 3 CRP tertiles, and all 3 subgroups based on CRP level had an estimated 10-year risk in the intermediate range.

Discussion

The body of evidence that CRP level is independently associated with incident CHD is strong, with a risk ratio of 1.58 (CI, 1.37 to 1.83). Our search and systematic selection identified 23 studies of appropriate design from 24 cohorts. The aggregate quality of these studies is good to fair, and the body of evidence has no important inconsistency. We found no indication that the data from included studies were imprecise or sparse and no indication of high risk for reporting bias. We also noted some evidence of a dose–response gradient. These criteria support the conclusion of a strong body of evidence.
Previous meta-analyses (17–19) have found an association between CRP level and incident CHD. These meta-analyses were limited by their lack of a systematic basis for judging the validity of the evidence they used, and applicability to the target population and question of interest may be limited. Our systematic review and meta-analyses included more recent and updated studies, excluded studies of predominantly high-risk or low-risk populations, systematically rated the quality of all studies, and qualitatively appraised findings that are directly applicable to intermediate-risk patients.
The clinical implications of the association of CRP level with CHD events are less clear, because the pooled risk ratio does not necessarily measure the usefulness of CRP level in reclassifying intermediate-risk persons. The underlying studies did not directly assess whether the risk ratio for the overall sample applied to the intermediate-risk subgroup (for example, by looking for an interaction between the Framingham risk score and CRP levels). The strength of evidence from studies that attempted to measure the effect of using CRP level to improve risk classification among persons initially classified as intermediate-risk is moderate. Among intermediate-risk persons, subgroups with high CRP levels generally had a higher risk for coronary events than did those with average or low CRP levels.
In addition to multivariate regression analyses in prospective studies, many investigators (72–75) have advocated the use of other statistical methods to assess the incremental value of adding CRP level to global risk assessment. Several studies in our review (23, 33, 40, 42, 43, 50, 56, 58) compared predictive models that used all Framingham risk factors with and without a CRP level. Most of these used the change in the c-statistic or the area under the receiver-operating characteristic curve to compare the performance after adding CRP level. However, a marker can have a small effect on the c-statistic, a measure of discrimination, but be strongly related to risk as assessed in a multiple logistic or Cox regression model, or vice versa (76–78). Recent articles (24–26, 72) have discussed the limitations of the c-statistic and proposed methods of assessing clinical risk reclassification when risk prediction is the goal of analysis.
Relatively few studies have evaluated the effect of adding CRP level to reclassify initially intermediate-risk persons. Four studies in our review (33, 40, 43, 56) assessed differences in CHD risk among subgroups of intermediate-risk participants who were stratified by CRP level. Three of the 4 studies (33, 40, 56) found that those with higher CRP levels were at higher risk for CHD. However, their results are imprecise and their estimates are group averages, so they do not show how many persons would be reclassified as high-risk. A fifth study (23) calculated the risk reclassification when CRP level was added to a predictive model that included all Framingham risk score variables and found that the model with CRP level had better calibration to observed risk. In the negative study (43), researchers of the Framingham cohort concluded that CRP level does not seem to be beneficial for CHD risk assessment, particularly because adding CRP level to the risk model did not improve c-statistic results. Recently, these researchers reported a good-quality analysis of Framingham data (79) in which they calculated the risk reclassification of individual study participants when CRP level was added to traditional risk factors; including CRP level improved risk assessment by appropriately reclassifying a statistically significant percentage of incident CHD cases and noncases into higher or lower risk categories.
Although the types of analyses differed, 4 large, good-quality cohort studies are consistent in finding that assessing CRP level improves CHD risk stratification (23, 33, 40, 56, 79). These consistent findings provide moderately strong evidence that adding CRP level to risk models in intermediate-risk patients improves the identification of those at higher risk for incident CHD. However, additional research is needed to assess the effect of CRP level on risk reclassification of initially intermediate-risk persons and to statistically evaluate the calibration of prediction models to observed risk (26).
Establishing the independent predictive ability of a new risk factor is necessary but not sufficient for assessing its potential usefulness in screening for CHD risk. Other criteria must be considered, such as the prevalence of the factor in the target population, the reliability and cost of the test, potential harms of testing, and the effect that treatment for the risk factor has on modifying risk (80). C-reactive protein level favorably satisfies most of these criteria. National survey data suggest a prevalence of high CRP level of at least 20% to 25% among intermediate-risk persons (13, 81). Inexpensive, precise, high-sensitivity CRP serum assays are available (82, 83). Although considerable within-patient variation among CRP measurements has been reported (84), the reliability of 2 or 3 serial measurements is similar to that of a total cholesterol assay (84, 85). Weight loss, exercise, and smoking cessation can reduce serum CRP levels (86, 87), and lowering CRP levels with statin therapy in patients with acute coronary syndrome can lower their risk for recurrent myocardial infarction or coronary death (88). The viability of CRP as a new factor in global risk assessment for incident CHD is limited by sparse evidence that directly links therapeutic changes in CRP level to primary prevention of CHD events.
Results were recently published for JUPITER (Justification for the Use of Statins in Prevention: an Intervention Trial Evaluating Rosuvastatin), a good-quality randomized, controlled trial of rosuvastatin for primary prevention of cardiovascular events in 17 802 men and women with elevated (>2 mg/L) CRP levels, low-density lipoprotein cholesterol levels less than 3.4 mmol/L (<130 mg/dL) (median, 2.8 mmol/L [108 mg/dL]), and no other indication (such as diabetes) for statin therapy (89). Of 8901 participants who received 20 mg of rosuvastatin daily, 83 experienced first cardiovascular events (myocardial infarction, stroke, or death from cardiovascular causes) during the study period (median, 1.9 years), compared with 157 of 8901 participants in the placebo group, for a hazard ratio of 0.53 (CI, 0.40 to 0.69). By 1 year of follow-up, the median low-density lipoprotein cholesterol level was unchanged in participants receiving placebo and 1.4 mmol/L (55 mg/dL) in participants assigned to receive rosuvastatin. Rosuvastatin was also associated with an increased risk for physician-reported diabetes (3.0% vs. 2.4%).
Current guidelines recommend aggressive therapy only for high-risk patients, such as those with a Framingham risk score greater than 20%, diabetes, or known cardiovascular disease. Because approximately half of the patients in JUPITER had a Framingham risk score greater than 10%, these results provide evidence that 1 form of intensive risk reduction—aggressive lipid-lowering therapy—produces benefit for a population that includes intermediate-risk persons.
The implications of JUPITER for screening are less clear. JUPITER did not evaluate whether intermediate-risk patients who are reclassified as high-risk by using CRP level would benefit from treatment compared with intermediate-risk patients who are not reclassified. For example, the risk reduction from rosuvastatin therapy may have been as great in intermediate-risk participants who had CRP levels closer to the population average. The study also did not directly test whether lowering CRP levels reduced cardiac risk. Finally, JUPITER did not report rates of coronary events separately for low-risk and intermediate-risk persons. To fully understand the balance of benefits and harms associated with any particular form of intensive risk reduction intended for patients classified according to CRP levels, we also need to know the numbers needed to treat and the harms for different risk category subgroups. The length of follow-up was inadequate to fully evaluate the potential harms of aggressive statin therapy (90). When the trial was terminated, only 1076 (1 in 18) participants had 4 years of follow-up, and 2705 had 3 years of follow-up.
Other issues may influence guideline recommendations and merit discussion. Cross-sectional studies have found correlations between CRP level and traditional CHD risk factors (91), but the implications for the use of CRP in global risk assessment are not clear. The findings have been interpreted to mean that CRP level may represent a different aspect of risk, with complex interrelationships among CRP level, traditional risk factors, and CHD (91, 92). Others conclude that elevated CRP level is largely attributable to traditional risk factors, and CRP level “may have limited clinical utility as a screening tool” (13). In fact, the causal relationships between CRP level and traditional CHD risk factors are not clear (93). Correlation of CRP level with traditional risk factors does not preclude its potential association with CHD. The findings of many studies, including our meta-analyses, suggest that the degree of correlation between CRP level and traditional risk factors is not so great that CRP loses its independent effect. Although this statistical independence does not establish causality (94), it does support the potential use of CRP level as an adjunct in global risk assessment, particularly for targeted groups—such as intermediate-risk persons.
Our review has limitations. Studies used varying definitions, cutoffs, and methods of measurement for the Framingham risk factors and other cofactors. We accounted for these differences in our quality assessments and standardized our meta-analyses to recommended cut-off values. Because all studies were prospective, the likelihood of differential bias in measurement or reporting within studies is low. However, the net effect of the Framingham variables may vary from that of a calculated Framingham risk score for studies that did not measure each variable as defined for the Framingham risk score. In addition, although we distinguished those studies that completely adjusted for Framingham factors in our quality assessments and subgroup analyses, the inclusion of a nonuniform assortment of additional potential confounders might influence a study's relative risk estimate, with the net effect expected to be a reduction in the magnitude. Minority populations were poorly represented in most studies in our review. Ethnic and racial differences in biomarker levels (95, 96) and applicability of the Framingham risk score (97, 98) may limit the generalizability of our results.
In summary, our systematic review and meta-analyses indicate that CRP level is independently associated with incident CHD. The clinical implication of this finding is less clear, because the pooled risk ratio does not necessarily measure the usefulness of CRP level in reclassifying intermediate-risk persons. Although current evidence on the risk reclassification that would result from adding CRP level to a global risk score is promising, the strength of evidence from the 4 cohorts that attempted to measure the effect of using CRP among intermediate-risk persons is moderate. The viability of CRP as an adjunct to traditional factors is also uncertain because evidence linking changes in CRP level to primary prevention of CHD events is insufficient.

References

  1. Ferdinand
    KC
    Coronary artery disease in minority racial and ethnic groups in the United States.
    Am J Cardiol
    2006
    97
    12A
    19A
    PubMed
    CrossRef
  2. 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
    PubMed
  3. 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
    PubMed
  4. Greenland
    P
    Knoll
    MD
    Stamler
    J
    Neaton
    JD
    Dyer
    AR
    Garside
    DB
    et al.  
    Major risk factors as antecedents of fatal and nonfatal coronary heart disease events.
    JAMA
    2003
    290
    891
    7
    PubMed
  5. Khot
    UN
    Khot
    MB
    Bajzer
    CT
    Sapp
    SK
    Ohman
    EM
    Brener
    SJ
    et al.  
    Prevalence of conventional risk factors in patients with coronary heart disease.
    JAMA
    2003
    290
    898
    904
    PubMed
  6. Smith
    SC
    Jr
    .
    Current and future directions of cardiovascular risk prediction.
    Am J Cardiol
    2006
    97
    28A
    32A
    PubMed
  7. Ross
    R
    Atherosclerosis—an inflammatory disease.
    N Engl J Med
    1999
    340
    115
    26
    PubMed
  8. 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
    PubMed
  9. Pepys
    MB
    Hirschfield
    GM
    C-reactive protein: a critical update.
    J Clin Invest
    2003
    111
    1805
    12
    PubMed
  10. Scirica BM, Morrow DA. Is C-reactive protein an innocent bystander or proatherogenic culprit? The verdict is still out. Circulation. 2006;113:2128-34; discussion 2151. [PMID: 16651484]
  11. Hingorani
    AD
    Shah
    T
    Casas
    JP
    Linking observational and genetic approaches to determine the role of C-reactive protein in heart disease risk [Editorial].
    Eur Heart J
    2006
    27
    1261
    3
    PubMed
  12. Lemieux
    I
    Pascot
    A
    Prud'homme
    D
    Alméras
    N
    Bogaty
    P
    Nadeau
    A
    et al.  
    Elevated C-reactive protein: another component of the atherothrombotic profile of abdominal obesity.
    Arterioscler Thromb Vasc Biol
    2001
    21
    961
    7
    PubMed
  13. 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
    PubMed
  14. 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
    PubMed
  15. Pasternak
    RC
    Abrams
    J
    Greenland
    P
    Smaha
    LA
    Wilson
    PW
    Houston-Miller
    N
    34th Bethesda Conference: Task force 1—Identification of coronary heart disease risk: is there a detection gap?
    J Am Coll Cardiol
    2003
    41
    1863
    74
    PubMed
  16. 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
    3
    E11
    PubMed
  17. Danesh
    J
    Collins
    R
    Appleby
    P
    Peto
    R
    Association of fibrinogen, C-reactive protein, albumin, or leukocyte count with coronary heart disease: meta-analyses of prospective studies.
    JAMA
    1998
    279
    1477
    82
    PubMed
  18. 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
    PubMed
  19. 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
    PubMed
  20. Harris
    RP
    Helfand
    M
    Woolf
    SH
    Lohr
    KN
    Mulrow
    CD
    Teutsch
    SM
    et al.  
    Methods Work Group
    Third US Preventive Services Task Force
    Current methods of the US Preventive Services Task Force: a review of the process.
    Am J Prev Med
    2001
    20
    21
    35
    PubMed
  21. Guyatt
    GH
    Oxman
    AD
    Vist
    GE
    Kunz
    R
    Falck-Ytter
    Y
    Alonso-Coello
    P
    et al.  
    GRADE Working Group
    GRADE: an emerging consensus on rating quality of evidence and strength of recommendations.
    BMJ
    2008
    336
    924
    6
    PubMed
  22. 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
  23. 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
    PubMed
  24. Janes
    H
    Pepe
    MS
    Gu
    W
    Assessing the value of risk predictions by using risk stratification tables.
    Ann Intern Med
    2008
    149
    751
    60
    PubMed
  25. 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]
  26. Cook
    NR
    Statistical evaluation of prognostic versus diagnostic models: beyond the ROC curve.
    Clin Chem
    2008
    54
    17
    23
    PubMed
  27. Koenig
    W
    Sund
    M
    Fröhlich
    M
    Fischer
    HG
    Löwel
    H
    Döring
    A
    et al.  
    C-Reactive protein, a sensitive marker of inflammation, predicts future risk of coronary heart disease in initially healthy middle-aged men: results from the MONICA (Monitoring Trends and Determinants in Cardiovascular Disease) Augsburg Cohort Study, 1984 to 1992.
    Circulation
    1999
    99
    237
    42
    PubMed
  28. 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
    PubMed
  29. DerSimonian
    R
    Laird
    N
    Meta-analysis in clinical trials.
    Control Clin Trials
    1986
    7
    177
    88
    PubMed
  30. Higgins
    JP
    Thompson
    SG
    Quantifying heterogeneity in a meta-analysis.
    Stat Med
    2002
    21
    1539
    58
    PubMed
  31. Egger
    M
    Davey Smith
    G
    Schneider
    M
    Minder
    C
    Bias in meta-analysis detected by a simple, graphical test.
    BMJ
    1997
    315
    629
    34
    PubMed
  32. Blake
    GJ
    Rifai
    N
    Buring
    JE
    Ridker
    PM
    Blood pressure, C-reactive protein, and risk of future cardiovascular events.
    Circulation
    2003
    108
    2993
    9
    PubMed
  33. 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
    PubMed
  34. 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
    PubMed
  35. 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
    PubMed
  36. 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
    PubMed
  37. 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
    PubMed
  38. 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
    PubMed
  39. 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
    PubMed
  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
    PubMed
  41. 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
    PubMed
  42. 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
    PubMed
  43. 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
    PubMed
  44. 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
    PubMed
  45. 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
    PubMed
  46. 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
    PubMed
  47. 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
    PubMed
  48. 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
    PubMed
  49. 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
    PubMed
  50. 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
    PubMed
  51. 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
    PubMed
  52. 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
    PubMed
  53. 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
    PubMed
  54. 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
    PubMed
  55. 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
    PubMed
  56. 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
    PubMed
  57. 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
    PubMed
  58. 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
    PubMed
  59. 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
    PubMed
  60. 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
    PubMed
  61. 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
    PubMed
  62. Tuomisto
    K
    Jousilahti
    P
    Sundvall
    J
    Pajunen
    P
    Salomaa
    V
    C-reactive protein, interleukin-6 and tumor necrosis factor alpha as predictors of incident coronary and cardiovascular events and total mortality. A population-based, prospective study.
    Thromb Haemost
    2006
    95
    511
    8
    PubMed
  63. 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
    PubMed
  64. Kuller
    LH
    Tracy
    RP
    Shaten
    J
    Meilahn
    EN
    Relation of C-reactive protein and coronary heart disease in the MRFIT nested case-control study. Multiple Risk Factor Intervention Trial.
    Am J Epidemiol
    1996
    144
    537
    47
    PubMed
  65. Agewall
    S
    Wikstrand
    J
    Fagerberg
    B
    Prothrombin fragment 1 + 2 is a risk factor for myocardial infarction in treated hypertensive men.
    J Hypertens
    1998
    16
    537
    41
    PubMed
  66. Roivainen
    M
    Viik-Kajander
    M
    Palosuo
    T
    Toivanen
    P
    Leinonen
    M
    Saikku
    P
    et al.  
    Infections, inflammation, and the risk of coronary heart disease.
    Circulation
    2000
    101
    252
    7
    PubMed
  67. Strandberg
    TE
    Tilvis
    RS
    C-reactive protein, cardiovascular risk factors, and mortality in a prospective study in the elderly.
    Arterioscler Thromb Vasc Biol
    2000
    20
    1057
    60
    PubMed
  68. Packard
    CJ
    O'Reilly
    DS
    Caslake
    MJ
    McMahon
    AD
    Ford
    I
    Cooney
    J
    et al.  
    Lipoprotein-associated phospholipase A2 as an independent predictor of coronary heart disease. West of Scotland Coronary Prevention Study Group.
    N Engl J Med
    2000
    343
    1148
    55
    PubMed
  69. Ridker
    PM
    High-sensitivity C-reactive protein: potential adjunct for global risk assessment in the primary prevention of cardiovascular disease.
    Circulation
    2001
    103
    1813
    8
    PubMed
  70. Harris
    TB
    Ferrucci
    L
    Tracy
    RP
    Corti
    MC
    Wacholder
    S
    Ettinger
    WH
    Jr
    et al.  
    Associations of elevated interleukin-6 and C-reactive protein levels with mortality in the elderly.
    Am J Med
    1999
    106
    506
    12
    PubMed
  71. Jager
    A
    van Hinsbergh
    VW
    Kostense
    PJ
    Emeis
    JJ
    Yudkin
    JS
    Nijpels
    G
    et al.  
    von Willebrand factor, C-reactive protein, and 5-year mortality in diabetic and nondiabetic subjects: the Hoorn Study.
    Arterioscler Thromb Vasc Biol
    1999
    19
    3071
    8
    PubMed
  72. Cook
    NR
    Use and misuse of the receiver operating characteristic curve in risk prediction.
    Circulation
    2007
    115
    928
    35
    PubMed
  73. Greenland
    P
    O'Malley
    PG
    When is a new prediction marker useful? A consideration of lipoprotein-associated phospholipase A2 and C-reactive protein for stroke risk [Editorial].
    Arch Intern Med
    2005
    165
    2454
    6
    PubMed
  74. 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
    PubMed
  75. Koenig
    W
    Cardiovascular biomarkers: added value with an integrated approach? [Editorial].
    Circulation
    2007
    116
    3
    5
    PubMed
  76. 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
    PubMed
  77. Moons
    KG
    Harrell
    FE
    Sensitivity and specificity should be de-emphasized in diagnostic accuracy studies.
    Acad Radiol
    2003
    10
    670
    2
    PubMed
  78. 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
    PubMed
  79. Wilson
    PWF
    Pencina
    MJ
    Jacques
    P
    Selhub
    J
    D'Agostino
    RB
    O'Donnell
    CJ
    C-reactive protein and reclassification of cardiovascular risk in the Framingham Heart Study.
    Circ Cardiovasc Qual Outcomes
    2008
    1
    92
    97
  80. 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
    PubMed
  81. Ajani
    UA
    Ford
    ES
    Mokdad
    AH
    Prevalence of high C-reactive protein in persons with serum lipid concentrations within recommended values.
    Clin Chem
    2004
    50
    1618
    22
    PubMed
  82. Hutchinson
    WL
    Koenig
    W
    Fröhlich
    M
    Sund
    M
    Lowe
    GD
    Pepys
    MB
    Immunoradiometric assay of circulating C-reactive protein: age-related values in the adult general population.
    Clin Chem
    2000
    46
    934
    8
    PubMed
  83. Wilkins
    J
    Gallimore
    JR
    Moore
    EG
    Pepys
    MB
    Rapid automated high sensitivity enzyme immunoassay of C-reactive protein.
    Clin Chem
    1998
    44
    1358
    61
    PubMed
  84. Koenig
    W
    Sund
    M
    Fröhlich
    M
    Löwel
    H
    Hutchinson
    WL
    Pepys
    MB
    Refinement of the association of serum C-reactive protein concentration and coronary heart disease risk by correction for within-subject variation over time: the MONICA Augsburg studies, 1984 and 1987.
    Am J Epidemiol
    2003
    158
    357
    64
    PubMed
  85. Ockene
    IS
    Matthews
    CE
    Rifai
    N
    Ridker
    PM
    Reed
    G
    Stanek
    E
    Variability and classification accuracy of serial high-sensitivity C-reactive protein measurements in healthy adults.
    Clin Chem
    2001
    47
    444
    50
    PubMed
  86. 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
    PubMed
  87. 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
    PubMed
  88. Ridker
    PM
    Cannon
    CP
    Morrow
    D
    Rifai
    N
    Rose
    LM
    McCabe
    CH
    et al.  
    Pravastatin or Atorvastatin Evaluation and Infection Therapy-Thrombolysis in Myocardial Infarction 22 (PROVE IT-TIMI 22) Investigators
    C-reactive protein levels and outcomes after statin therapy.
    N Engl J Med
    2005
    352
    20
    8
    PubMed
  89. 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
    PubMed
  90. Hlatky
    MA
    Expanding the orbit of primary prevention—moving beyond JUPITER [Editorial].
    N Engl J Med
    2008
    359
    2280
    2
    PubMed
  91. Albert
    MA
    Glynn
    RJ
    Ridker
    PM
    Plasma concentration of C-reactive protein and the calculated Framingham Coronary Heart Disease Risk Score.
    Circulation
    2003
    108
    161
    5
    PubMed
  92. Bermudez
    EA
    Rifai
    N
    Buring
    J
    Manson
    JE
    Ridker
    PM
    Interrelationships among circulating interleukin-6, C-reactive protein, and traditional cardiovascular risk factors in women.
    Arterioscler Thromb Vasc Biol
    2002
    22
    1668
    73
    PubMed
  93. Engström G. The role of inflammation for heart disease risk cannot be determined by correlations between C-reactive protein and risk factors [Letter]. Arch Intern Med. 2006;166:1040; author reply 1040-1. [PMID: 16682580]
  94. Brotman
    DJ
    Walker
    E
    Lauer
    MS
    O'Brien
    RG
    In search of fewer independent risk factors.
    Arch Intern Med
    2005
    165
    138
    45
    PubMed
  95. Howard
    BV
    Le
    Belcher
    JD
    Flack
    JM
    Jacobs
    DR
    Jr
    Lewis
    CE
    et al.  
    Concentrations of Lp(a) in black and white young adults: relations to risk factors for cardiovascular disease.
    Ann Epidemiol
    1994
    4
    341
    50
    PubMed
  96. Wang
    W
    Hu
    D
    Lee
    ET
    Fabsitz
    RR
    Welty
    TK
    Robbins
    DC
    et al.  
    Lipoprotein(a) in American Indians is low and not independently associated with cardiovascular disease. The Strong Heart Study.
    Ann Epidemiol
    2002
    12
    107
    14
    PubMed
  97. 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
    PubMed
  98. Liu
    J
    Hong
    Y
    D'Agostino
    RB
    Sr
    Wu
    Z
    Wang
    W
    Sun
    J
    et al.  
    Predictive value for the Chinese population of the Framingham CHD risk assessment tool compared with the Chinese Multi-Provincial Cohort Study.
    JAMA
    2004
    291
    2591
    9
    PubMed
Appendix Figure.
Literature search and selection.

FRS = Framingham risk score.

Image: 9FF4
Figure 1.
Risk ratio for coronary heart disease associated with C-reactive protein level >3.0 versus <1.0 mg/L.

* Number of participants included in the analysis.

Image: 9FF1
Figure 2.
Risk ratio for coronary heart disease associated with C-reactive protein level 1.0 to 3.0 versus <1.0 mg/L.
Image: 9FF2
Figure 3.
Analyses of all subgroups at high (>3.0 mg/L) and average (1.0 to 3.0 mg/L) CRP levels.

CHD = coronary heart disease; CRP = C-reactive protein; CVD = cardiovascular disease.

* Number of cohorts included in the analysis.

† Framingham risk factors are based on reference 2.

Image: 9FF3

Table.

Study Characteristics and Adjusted Estimates of CHD Risk Associated With CRP

Image: 9TT1
Table.
PDF Supplemental Content
Nested Case-Control and Case-Cohort Studies
PDF Supplemental Content
Recommendation Summary

Clinical Slide Sets

Terms of Use

The In the Clinic® slide sets are owned and copyrighted by the American College of Physicians (ACP). All text, graphics, trademarks, and other intellectual property incorporated into the slide sets remain the sole and exclusive property of the ACP. The slide sets may be used only by the person who downloads or purchases them and only for the purpose of presenting them during not-for-profit educational activities. Users may incorporate the entire slide set or selected individual slides into their own teaching presentations but may not alter the content of the slides in any way or remove the ACP copyright notice. Users may make print copies for use as hand-outs for the audience the user is personally addressing but may not otherwise reproduce or distribute the slides by any means or media, including but not limited to sending them as e-mail attachments, posting them on Internet or Intranet sites, publishing them in meeting proceedings, or making them available for sale or distribution in any unauthorized form, without the express written permission of the ACP. Unauthorized use of the In the Clinic slide sets will constitute copyright infringement.


Using Nontraditional Risk Factors to Estimate Risk for Coronary Heart Disease

This feature is available only to Registered Users

Subscribe/Learn More
Submit a Comment

2 Comments

Nancy R. Cook

Brigham and Women's Hospital, Harvard Medical School, Boston, MA

October 17, 2009

Biomarker evaluation "“ the case for CRP

In their review Buckley et al (1) state that the utility of measuring CRP is uncertain and conclude that routine screening of CRP cannot be recommended. The reasoning behind this conclusion, however, appears flawed. First, since the literature review in 2007, additional papers have been published, particularly ones featuring risk reclassification including the Reynolds Risk Score for men (2) and the analysis of high- sensitivity CRP in the Framingham cohort (3). The latter work should replace the cited negative study from Framingham which did not use the high-sensitivity assay.

Second, the authors cite a lack of evidence that change in CRP directly links to prevention. Whether CRP is causal or not does not limit its use as a predictive marker. The same criterion has not been applied to other risk factors such as high-density lipoprotein (HDL) cholesterol, which has been well-accepted as a risk marker for decades. There is a notable lack of randomized trial data showing that raising HDL directly leads to the prevention of cardiovascular events (4).

Third, while the focus on risk reclassification is appreciated, this is not the most meaningful measure of a marker's value as stated. JUPITER presents stronger evidence, showing that those above and below a Framingham risk of 10% but with high CRP both experienced the same sizeable reduction in risk. Given these results, whether these individuals would be reclassified into a higher risk group seems moot for clinical utility and only relevant for cost-effectiveness analyses.

The authors should take note of a recent statement from the AHA regarding the evaluation of novel markers (5). This proposes phases, including case-control studies, prospective evaluation, and incremental value, all of which the USPSTF agrees are fulfilled by CRP. Additional phases are clinical utility, evaluating whether a novel marker changes predicted risk enough to change therapy. Risk reclassification suggests that this is true for CRP, comparable to well-accepted markers. A stronger criterion is whether use of the marker improves clinical outcomes, especially in randomized trials. JUPITER used CRP to identify individuals who would not otherwise be treated, and found a substantial reduction in cardiovascular events. A final question is whether the additional costs of testing and treatment are justified. The low cost of the test and the dramatic results of treatment should make this simple test worthwhile in avoiding cardiovascular events and perhaps saving lives.

References

1. 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.

2. Ridker PM, Paynter NP, Rifai N, Gaziano JM, Cook NR. C-reactive protein and parental history improve global cardiovascular risk prediction: the Reynolds Risk Score for men. Circulation. 2008;118:2243- 51.

3. Wilson PWF, Pencina M, Jacques P, Selhub J, D'Agostino Sr R, O'Donnell CJ. C-reactive protein and reclassification of cardiovascular risk in the Framingham Heart Study. Circ Cardiovasc Qual Outcomes. 2008;1:92-97.

4. Pfeffer MA, Sacks FM. Leapfrogging data: No shortcuts for safety or efficacy information. Circulation. 2008;118:2491-4.

5. Hlatky MA, Greenland P, Arnett DK, et al. Criteria for evaluation of novel markers of cardiovascular risk: a scientific statement from the American Heart Association. Circulation. 2009;119:2408-16.

Conflict of Interest:

None declared

David I. Buckley

Oregon Evidence-based Practice Center; Oregon Health & Science University

January 11, 2010

The Authors Respond

Dr. Cook asserts that, in our systematic review and assessment of the body of evidence (1), we conclude that "routine screening of CRP cannot be recommended." This is incorrect. We made no recommendations about routine screening. Rather, we presented our findings to the US Preventive Services Task Force (USPSTF), which is solely responsible for USPSTF recommendations.

We found that CRP is associated with CHD events and adding CRP level to a global risk score among initially intermediate-risk persons reclassifies some patients. However, we found that the benefit of reclassifying patients in this manner is uncertain (1).

We agree that direct causality is not an essential criterion. We also agree that a marker's ability to improve clinical outcomes is better evidence of usefulness than its ability to improve risk classification; but we disagree about whether or not CRP meets this criterion. Reclassification means that CRP identifies some patients for more intensive treatment, and not others. Is it really a better way of selecting patients for more intensive treatment than alternatives? For example, would randomly selected intermediate-risk patients benefit as much from intensive statin therapy? A trial that compares CRP testing to no CRP testing, or one that compares treatment in patients with high CRP levels to patients with intermediate or low CRP, could answer this question.

JUPITER, a trial of high-dose statin treatment, did neither (2). It found that high-dose statin treatment improved CVD outcomes in subjects with an elevated CRP, but did not test the hypothesis that use of CRP improves outcomes compared with the alternative of intensifying therapy without a CRP test. JUPITER did not determine whether reclassification based on CRP might identify intermediate risk patients who are most likely to benefit from high dose statin therapy in addition to therapeutic lifestyle changes. For example, JUPITER excluded intermediate risk patients with LDL levels above 130 mg/dL, a group that might also be considered for intensifying therapy.

Cook suggests that we take note of the AHA statement regarding the evaluation of novel markers (3). While it uses different terminology, the AHA statement is consistent with the criteria we proposed to the USPSTF, in 2005, to assess CRP and other markers (4). In AHA terms, our review found that CRP meets the criteria at several evaluation phases, including "prospective validation, and incremental value." We also found it likely that CRP meets the next criterion, "corresponding to reclassification in our system." The AHA then calls for randomized trials of whether use of the marker improves clinical outcomes. As discussed above, CRP has not met this criterion. Finally, the AHA considers cost-effectiveness, which we did not evaluate in our review.

References

1. 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.

2. Hlatky MA. Expanding the orbit of primary prevention--moving beyond JUPITER. New England Journal of Medicine. 2008;359(21):2280-2.

3. Hlatky MA, Greenland P, Arnett DK, et al. Criteria for evaluation of novel markers of cardiovascular risk: a scientific statement from the American Heart Association. Circulation. 2009;119:2408-16.

4. Helfand M, Buckley DI, Freeman M, Fu R, Rogers K, Fleming C, Humphrey LL. Emerging risk factors for coronary heart disease: a summary of systematic reviews conducted for the U.S. Preventive Services Task Force. Ann Intern Med. 2009;151:496-507.

Conflict of Interest:

None declared

PDF
Not Available
Citations
Citation

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;151:483–495. doi: 10.7326/0003-4819-151-7-200910060-00009

Download citation file:

  • RIS (Zotero)
  • EndNote
  • BibTex
  • Medlars
  • ProCite
  • RefWorks
  • Reference Manager

© 2018

×
Permissions

Published: Ann Intern Med. 2009;151(7):483-495.

DOI: 10.7326/0003-4819-151-7-200910060-00009

275 Citations

See Also

Using Nontraditional Risk Factors in Coronary Heart Disease Risk Assessment: U.S. Preventive Services Task Force Recommendation Statement
Emerging Risk Factors for Coronary Heart Disease: A Summary of Systematic Reviews Conducted for the U.S. Preventive Services Task Force
Using Nontraditional Risk Factors to Estimate Risk for Coronary Heart Disease
The Case for C-Reactive Protein as a Risk Marker for Coronary Heart Disease
The Case for C-Reactive Protein as a Risk Marker for Coronary Heart Disease
View MoreView Less

Related Articles

Using Nontraditional Risk Factors in Coronary Heart Disease Risk Assessment: U.S. Preventive Services Task Force Recommendation Statement
Annals of Internal Medicine; 151 (7): 474-482
Emerging Risk Factors for Coronary Heart Disease: A Summary of Systematic Reviews Conducted for the U.S. Preventive Services Task Force
Annals of Internal Medicine; 151 (7): 496-507
Framework for Evaluating Novel Risk Markers
Annals of Internal Medicine; 156 (6): 468-469
Narrative Review: Assessment of C-Reactive Protein in Risk Prediction for Cardiovascular Disease
Annals of Internal Medicine; 145 (1): 35-42
View MoreView Less

Journal Club

Review: In primary care, CRP testing, shared decision making, and procalcitonin reduce antibiotic prescribing for ARI
Annals of Internal Medicine; 168 (2): JC11
Review: In benign paroxysmal positional vertigo, the Epley maneuver increases symptom resolution
Annals of Internal Medicine; 162 (6): JC10
Applying evidence: What’s the next action?
Annals of Internal Medicine; 150 (2): JC1-2
Modified Framingham Risk Score predicted 10-y CAD better than the original score in patients with lupus
Annals of Internal Medicine; 164 (12): JC71
View MoreView Less

Related Topics

Guidelines

Guidelines.

PubMed Articles

Effects of psychological interventions on systemic levels of inflammatory biomarkers in humans: A systematic review and meta-analysis.
Brain Behav Immun 2018.
NFE2L2, PPARGC1a, and pesticides and Parkinson's disease risk and progression.
Mech Ageing Dev 2018.
View More

Results provided by: PubMed

CME/MOC Activity Requires Users to be Registered and Logged In.
Sign in below to access your subscription for full content
INDIVIDUAL SIGN IN
Sign In|Set Up Account
You will be directed to acponline.org to register and create your Annals account
Annals of Internal Medicine
CREATE YOUR FREE ACCOUNT
Create Your Free Account|Why?
To receive access to the full text of freely available articles, alerts, and more. You will be directed to acponline.org to complete your registration.
×
The Comments Feature Requires Users to be Registered and Logged In.
Sign in below to access your subscription for full content
INDIVIDUAL SIGN IN
Sign In|Set Up Account
You will be directed to acponline.org to register and create your Annals account
Annals of Internal Medicine
CREATE YOUR FREE ACCOUNT
Create Your Free Account|Why?
To receive access to the full text of freely available articles, alerts, and more. You will be directed to acponline.org to complete your registration.
×
link to top

Content

  • Home
  • Latest
  • Issues
  • Channels
  • CME/MOC
  • In the Clinic
  • Journal Club
  • Web Exclusives

Information For

  • Author Info
  • Reviewers
  • Press
  • Readers
  • Institutions / Libraries / Agencies
  • Advertisers

Services

  • Subscribe
  • Renew
  • Alerts
  • Current Issue RSS
  • Online First RSS
  • In the Clinic RSS
  • Reprints & Permissions
  • Contact Us
  • Help
  • About Annals
  • About Mobile
  • Patient Information
  • Teaching Tools
  • Annals in the News
  • Share Your Feedback

Awards

  • Personae Photography Prize
  • Junior Investigator Awards
  • Poetry Prize

Other Resources

  • ACP Online
  • Career Connection
  • ACP Advocate Blog
  • ACP Journal Wise

Follow Annals On

  • Twitter Link
  • Facebook Link
acp link acp
silverchair link silverchair

Copyright © 2018 American College of Physicians. All Rights Reserved.

Print ISSN: 0003-4819 | Online ISSN: 1539-3704

Privacy Policy

|

Conditions of Use

×

You need a subscription to this content to use this feature.

×
PDF Downloads Require Access to the Full Article.
Sign in below to access your subscription for full content
INDIVIDUAL SIGN IN
Sign In|Set Up Account
You will be directed to acponline.org to register and create your Annals account
INSTITUTIONAL SIGN IN
Open Athens|Shibboleth|Log In
Annals of Internal Medicine
PURCHASE OPTIONS
Buy This Article|Subscribe
You will be redirected to acponline.org to sign-in to Annals to complete your purchase.
CREATE YOUR FREE ACCOUNT
Create Your Free Account|Why?
To receive access to the full text of freely available articles, alerts, and more. You will be directed to acponline.org to complete your registration.
×
Access to this Free Content Requires Users to be Registered and Logged In. Please Choose One of the Following Options
Sign in below to access your subscription for full content
INDIVIDUAL SIGN IN
Sign In|Set Up Account
You will be directed to acponline.org to register and create your Annals account
Annals of Internal Medicine
CREATE YOUR FREE ACCOUNT
Create Your Free Account|Why?
To receive access to the full text of freely available articles, alerts, and more. You will be directed to acponline.org to complete your registration.
×