|Evidence Statement Number||Author/Group||Factor||Evidence Statement/Conclusion|
|1||USPSTF (9)||hs-CRP||“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.”|
“Few studies directly assessed the effect of CRP on risk reclassification in intermediate-risk persons.”
hs-CRP was associated with risk, and its use resulted in some reclassification in intermediate-risk persons, but it was not clear whether this reclassification led to a net improvement in prediction. Values of receiver operating curve C-statistics (measures of discrimination) are mentioned but not reported; hence, no evidence on discrimination, calibration, net reclassification index, or cost-effectiveness was provided.
Reports some impact on reclassification, probably modest (pp. 488–491).
|2||Helfand et al., 2009 (12)||hs-CRP, CAC, CIMT, ABI||With regard to risk assessment for major CHD, the authors concluded that, “The current evidence does not support the routine use of any of the 9 risk factors for further risk stratification of intermediate-risk persons.” The 9 risk factors examined were: hs-CRP, CAC score as measured by electron-beam computed tomography, lipoprotein (a) level, homocysteine level, leukocyte count, fasting blood glucose, periodontal disease, ABI, and CIMT.|
hs-CRP was associated with CHD and led to some reclassification. The authors cite the JUPITER results to support the conclusion that hs-CRP testing may be useful in intermediate-risk patients to drive statin therapy. The Work Group recognizes that more recent individual study results have been published. Updated systematic reviews addressing discrimination, calibration, reclassification, and cost issues in the context of the newer ASCVD risk assessment model proposed in the present document are needed.
CAC was associated with CHD and with some reclassification, but the size and value of this reclassification are uncertain. The document provides little evidence with regard to discrimination, calibration, and cost-effectiveness. The Work Group also is concerned about radiation and incidental findings. The Work Group recognizes that more recent individual study results have been published. Updated systematic reviews addressing discrimination, calibration, reclassification, cost, and safety issues in the context of the newer ASCVD risk assessment model proposed in the present document are needed.
CIMT was associated with CHD, but the document provides little evidence for reclassification, discrimination, calibration, and cost-effectiveness. The Work Group also has concerns about measurement issues. Standardization of CIMT measurement is a major challenge. The Work Group recognizes that more recent individual study results have been published. Updated systematic reviews addressing discrimination, calibration, reclassification, cost, and measurement (standardization) issues in the context of the newer ASCVD risk assessment model proposed in this document are needed.
ABI was associated with CHD and some reclassification, but the size and value of this reclassification are uncertain. Evidence suggests some improvement in discrimination, but the document provides little evidence with regard to calibration and cost-effectiveness. The Work Group members are uncertain whether more recent individual study results have been published relevant to ABI. Updated systematic reviews addressing discrimination, calibration, reclassification, and cost issues in the context of the newer ASCVD risk assessment model proposed in this document are needed.
|3||Emerging Risk Factors Collaboration (13)||hs-CRP||“CRP concentration has continuous associations with the risk for coronary heart disease, ischaemic stroke, vascular mortality, and death from several cancers and lung disease that are each of broadly similar size. The relevance of CRP to such a range of disorders is unclear. Associations with ischaemic vascular disease depend considerably on conventional risk factors and other markers of inflammation.”|
hs-CRP is associated with risk of CVD. This analysis did not directly assess value in risk prediction. No additional evidence was provided for discrimination, calibration, reclassification, or cost-effectiveness.
|4||Schnell-Inderst et al., 2010 (17)||hs-CRP||For MI and cardiovascular mortality, “Adding hs-CRP to traditional risk factors improves risk prediction, but the clinical relevance and cost-effectiveness of this improvement remain unclear.”|
Absolute differences in C-statistics between models including and not including hs-CRP ranged from 0.00 to 0.027.
Some evidence was provided to support the cost-effectiveness of hs-CRP testing in some modeling scenarios, characterized by intermediate- and higher-risk populations and lower-cost (generic) statins of at least moderate efficacy.
|5||Emerging Risk Factors Collaboration (40)||ApoB||This article provided evidence of rough equivalence of associations of CVD with non–HDL-C and ApoB after multivariable adjustment (including HDL-C). See Figure 1 for CHD and the text for stroke. By inference, this finding means there would be rough equivalence between ApoB and total cholesterol with similar adjustment.|
|6||Sniderman et al., 2011 (42)||ApoB||ApoB was more strongly related to risk of ASCVD than either non–HDL-C or LDL-C in a substitution model that also included HDL-C. No evidence was presented pertinent to an addition model in which ApoB might be added to a model that included total cholesterol, LDL-C, or non–HDL-C. Additional models are the type of model of interest to this question. By inference, these results maymean that ApoB is more strongly related to risk than is total cholesterol. This article did not address directly the value of adding ApoB to a model with traditional risk factors. No information was presented for discrimination, calibration, reclassification, or cost. The relative risks evaluated in the meta-analysis were adjusted for various sets of covariates in the various primary reports, and the adjustments were judged to be incomplete. Furthermore, studies of varying designs and quality were included, leaving the Work Group members concerned about the validity of the evidence.|
|7||Kodama et al., 2009 (41)||Cardiorespiratory fitness||Better cardiorespiratory fitness was associated with lower risk of all-cause mortality and CHD/CVD. According to the sensitivity analyses in Table 2, evidence of association was weaker for CHD/CVD, but still significant, when based on studies with more complete adjustment for other risk factors. The utility of assessing cardiorespiratory fitness in risk prediction was not assessed (discrimination, calibration, reclassification, and cost).|
|8||Ankle Brachial Index Collaboration (11)||ABI||ABI is associated with total CHD risk and leads to significant reclassification, and the pattern of reclassification is different by sex. Among men, the effect is to down-classify high-risk men. Among women, the effect is to up-classify low-risk women. Overall, the FRS, as applied by the investigators, showed relatively poor discrimination in this meta-analysis, with C-statistics of 0.646 (95% CI: 0.643–0.657) in men and 0.605 (0.590–0.619) in women. There was an improvement in C-statistic in both men (0.655 [0.643–0.666]) and women (0.658 [0.644–0.672]) when ABI was added to a model with FRS. The improvement in the C-statistic was greater and significant in women but was not significant in men. No evidence on calibration, net reclassification index, or cost-effectiveness was provided.|
|9||Empana et al., 2011 (10)||Family history of CHD||“In separate models adjusted for age, gender, and study cohort, a family history of CHD, BMI, and waist circumference were all predictors of CHD. When traditional risk factors were controlled for, family history of CHD (p<0.001) and BMI (p=0.03) but not waist circumference (p=0.42) remained associated with CHD. However, the addition of family history of CHD or BMI to the traditional risk factors model did not improve the discrimination of the model (not shown).”|
This article developed a CHD risk prediction algorithm based on 4 French population studies and evaluated, among other factors, the contribution of family history to traditional risk factors. Family history of CHD was defined as the self-report of a MI in first-degree relatives (parents and siblings) in the D.E.S.I.R. and SU.VI.MAX studies, as a history of MI before age 55 years in men and before age 65 years in women in parents, siblings, and grandparents in the PRIME study, and as a death due to MI in first-degree relatives in the Three City study. No evidence on calibration, net reclassification index, or cost-effectiveness was provided.
|10||Moyer et al., 2013 (15)||ABI||This article is an updated review of the utility of assessing ABI for the USPSTF.|
“The USPSTF concludes that the current evidence is insufficient to assess the balance of benefits and harms of screening for PAD and CVD risk assessment with the ABI in adults. (I statement)”
“The USPSTF found no evidence that screening for and treatment of PAD in asymptomatic patients leads to clinically important benefits. It also reviewed the potential benefits of adding the ABI to the FRS and found evidence that this results in some patient risk reclassification; however, how often the reclassification is appropriate or whether it results in improved clinical outcomes is not known.”
The Work Group notes that this review provides some evidence that assessing ABI may improve risk assessment; however, no evidence was found by the USPSTF reviewers pertinent to the question of whether measuring ABI leads to better patient outcomes.
|11.||Peters et al., 2012 (16)||CIMT, CAC||This article is a systematic review of the literature on the contribution to risk assessment of imaging for subclinical atherosclerosis.|
“Published evidence on the added value of atherosclerosis imaging varies across the different markers, with limited evidence for FMD and considerable evidence for CIMT, carotid plaque and CAC. The added predictive value of additional screening may be primarily found in asymptomatic individuals at intermediate cardiovascular risk. Additional research in asymptomatic individuals is needed to quantify the cost-effectiveness and impact of imaging for subclinical atherosclerosis on cardiovascular risk factor management and patient outcomes.”
With regard to CIMT:
“The c-statistic of the prediction models without CIMT increased from 0.00 to 0.03 when CIMT was added. In the Atherosclerosis Risk In Communities (ARIC) study, addition of CIMT to the prediction model resulted in an NRI overall of 7.1% (95% CI 2.2% to 10.6%) and an IDI of 0.007 (95% CI 0.004 to 0.010). The NRI intermediate was 16.7% (95% CI 9.3% to 22.4%). In contrast, 10 year results from the Carotid Atherosclerosis Progression Study showed that addition of CIMT to the prediction model resulted in an IDI of 0.04% and NRI overall of –1.41%. Analysis of 1,574 participants from the Firefighters and Their Endothelium study showed an NRI overall of 11.6% (p=0.044) and an NRI intermediate of 18.0% (p=0.034).”
The Work Group notes that this article provides some evidence to consider assessing CIMT; however, this conclusion was not supported by the article by Den Ruijter et al. described below (18).
With regard to CAC:
“The c-statistic increased from 0.04 to 0.13 when CAC was added to the model. Four recently published studies also reported results on the NRI and/or the IDI. One of these studies comprised a subgroup analysis of an earlier publication in the total population in individuals without indications for statin therapy. Analyses of the MESA study showed that addition of CAC to the conventional prediction model resulted in an NRI overall of 25% (95% CI 16% to 34%) and an NRI intermediate of 55% (95% CI 41% to 69%). The IDI in the MESA study was 0.026. Results were similar in the Rotterdam study. Addition of CAC to the prediction model led to an NRI overall of 14% (p<0.01) which was mainly driven by correctly reclassifying those at intermediate risk according to the traditional prediction model. Results from the Heinz Nixdorf Recall study also showed large NRIs when CAC was added to the Framingham Risk Score. Using different thresholds to define the intermediate risk category (10%–20% or 6%–20%), the NRI overall was 22% and 20%, respectively. The NRI intermediate was 22% for intermediate risk thresholds of 10%–20% and 31% for intermediate risk thresholds of 6%–20%. In addition, the IDI was 0.0152 when the prediction models with and without CAC were compared. The NRI overall was 25.1% and the IDI was 0.0167 in individuals from the Heinz Nixdorf Recall study without indications for statin therapy.” The Work Group notes that this article provides evidence to support the conclusion that assessing CAC is likely to be the most useful approach to improving risk assessment among individuals found to be at intermediate risk after formal risk assessment. Furthermore, we note that the outcomes in the studies reviewed above were CHD, not ASCVD. The Work Group discussed concerns about cost, radiation exposure, and the uncertainty of the contribution of assessing CAC to estimation of 10-year risk of hard ASCVD after formal risk assessment.
|12.||Kashani et al., 2013 (14)||Family history||This article is an integrative literature review on the contribution of assessing family history to risk appraisal.|
“The evidence demonstrates that family history is an independent contributor to risk appraisal and unequivocally supports its incorporation to improve accuracy in global CVD risk estimation.”
The Work Group notes that a variety of endpoints, clinical and subclinical, were included in the reviewed articles. No evidence on discrimination, calibration, net reclassification index, or cost-effectiveness was provided.
|13.||Den Ruijter et al., 2012 (18)||CIMT||This article is an individual-level meta-analysis of “14 population-based cohorts contributing data for 45 828 individuals. During a median follow-up of 11 years, 4007 first-time MIs or strokes occurred.”|
“We first refitted the risk factors of the FRS and then extended the model with common CIMT measurements to estimate the absolute 10-year risks to develop a first-time MI or stroke in both models. The C-statistic of both models was similar (0.757; 95% CI, 0.749–0.764; and 0.759; 95% CI, 0.752–0.766). The net reclassification improvement with the addition of common CIMT was small (0.8%; 95% CI, 0.1%–1.6%). In those at intermediate risk, the net reclassification improvement was 3.6% in all individuals (95% CI, 2.7%–4.6%) and no differences between men and women.”
“The addition of common CIMT measurements to the FRS was associated with small improvement in 10-year risk prediction of first-time MI or stroke, but this improvement is unlikely to be of clinical importance.”
The Work Group judged this article to provide the strongest evidence available on the potential value of CIMT to risk assessment. The Work Group also has concerns about measurement issues. Standardization of CIMT measurement is a major challenge.
ABI indicates ankle-brachial index; ApoB, apolipoprotein B; BMI, body mass index; ASCVD, atherosclerotic cardiovascular disease; CAC, coronary artery calcium; CHD, coronary heart disease; CI, confidence interval; CIMT, carotid intima-media thickness; CRP, C-reactive protein; CVD, cardiovascular disease; FMD, flow-mediated dilation; FRS, Framingham Risk Score; HDL-C, high-density lipoprotein cholesterol; hs-CRP, high-sensitivity C-reactive protein; IDI, integrative discrimination index; JUPITER, Justification for the Use of Statins in Primary Prevention: An Intervention Trial Evaluating Rosuvastatin; LDL-C, low-density lipoprotein cholesterol; MESA, Multi-Ethnic Study of Atherosclerosis; NRI, net reclassification index; PAD, peripheral artery disease; MI, myocardial infarction; and USPSTF, U.S. Preventive Services Task Force.