Prognostic Utility of Aortic Valve Calcium in Risk Stratification for Cardiovascular Disease: Advancements in Low Risk Stratification

Quick Takes

  • Aortic valve calcium (AVC) was associated with increased risk of CVD and CHD mortality along with all-cause mortality (ACM); however, there was a significant interaction between AVC and coronary artery calcium (CAC).
  • AVC >100 was associated with a significantly increased risk of CVD mortality and ACM only when CAC <100.
  • AVC was associated with increased likelihood of death from aortic stenosis (AS) death.
  • Reporting the AVC score as part of CAC scan results can improve mortality risk stratification in asymptomatic individuals, especially among those with low levels of CAC.

Background

Aortic valve calcification (AVC) can be measured on standard coronary artery calcium (CAC) computed tomography (CT) scans. AVC gradually increases over decades and can eventually lead to symptomatic severe aortic stenosis (AS).1-6 The risk factors for the early stages of AVC overlap with those of coronary atherosclerosis; accordingly, AVC is associated with "atherosclerogenesis" including coronary artery disease (CAD).7,8

AVC is associated with an increased risk of cardiovascular disease (CVD) but was not independently associated with CVD, CAD mortality, or all-cause mortality (ACM) after accounting for CAC.9-12 Guidelines recommend selective use of CAC scoring for individuals at moderate risk of atherosclerotic CVD (ASCVD).13,14

This study further evaluated the association between AVC and mortality to examine if AVC holds prognostic significance in certain CAC score subgroups.15

Study Design

Retrospective cohort analysis comprising n=10,007 patients from the CAC Consortium who had a CAC scan performed between 1991-2010 with follow-up until 2014 (median follow-up 8 years).16 The AVC score was done via the Agatston method to measure calcification on the aortic valve leaflets only, excluding the aortic annulus and root.17

Multivariable adjusted Cox regression models were performed to evaluate association between AVC and mortality from CVD, CHD, or ACM. Based on interaction testing, subgroup analysis for CAC <100 or CAC> 100 was performed. A sensitivity analysis was conducted using a propensity-matched case-control analysis to examine the relationship between AVC and mortality due to aortic stenosis.

Results

Individuals with elevated AVC were older, had a higher proportion of men, higher burden of traditional CVD comorbidities, and a higher median CAC score (Table 1). There was a significant positive correlation between AVC and CAC burden (r=0.36, p<0.001).

Table 1

  All
(N=10,007)
Mean±SD or
Number (%)
No AVC (N=8,610)
Mean±SD or
Number (%)
AVC 1-99 (n=876)
Mean±SD or
Number (%)
AVC ≥100 (n=521)
Mean±SD or
Number (%)
p-value
Age 55.8±11.7 53.8±10.7 66.1±10.2 70.4±10.6 <0.001
Women 3603 (36.0) 3158 (36.7) 29 (34.0) 147 (28.2) <0.001
Hypertension 4595 (45.9) 3624 (42.1) 581 (66.3) 391 (75.1) <0.001
Hyperlipidemia 5836 (58.3) 4809 (55.9) 705 (80.5) 429 (82.3) <0.001
Smoker 874 (8.7) 764 (8.9) 75 (8.6) 35 (6.7) 0.235
Diabetes 920 (9.2) 680 (7.9) 125 (14.3) 115 (22.1) <0.001
Family History 3742 (37.4) 3220 (37.4) 326 (37.2) 197 (37.8) 0.975
ASCVD score 9.7±12.4 7.6±9.9 19.5±16.3 27.9±19.2 <0.001
CAC Score
Median (IQR)
2 (0, 114) 0 (0, 59) 164.5 (20-598) 417 (59-1194) <0.001
Table 1. Baseline characteristics of CAC Consortium subgroup by AVC score. Adapted from Han et al. 15

Higher AVC was associated with increased ACM (HR 1.33 [95%CI 1.02-1.74], p=0.03) and CVD (HR 1.72 [95%CI 1.13-2.61], p=0.01), but not CHD (HR 1.65 [95%CI 0.95-2.88], p=0.07) after adjusting for traditional CVD risk factors. However, when CAC was added to the modeling, AVC was no longer significantly associated with mortality.

A significant interaction existed between CAC and AVC (p<0.001), which led them to perform subgroup analyses stratified by CAC score of <100 and ≥100. Among individuals with CAC <100, an AVC >100 was associated with an increased hazard for ACM (HR 1.93 [95%CI 1.14-3.27] p=0.013) and CVD (HR 2.71 [95%CI 1.15-6.34], p=0.022), but not CHD (Table 2). The addition of AVC to CAC improved discrimination characteristics for prediction of ACM and CVD (ACM: 6.5% [95%CI 2.7-10.3%], p=0.001; CVD: 9.9% [95%CI 1.6-18.2%], p=0.027), but not CHD. Among individuals with CAC ≥100, however, AVC was not associated with an increased hazard for mortality outcomes.

Table 2

  All cause death CVD death CHD death
  HR 95% CI p-value HR 95% CI p-value HR 95% CI p-value
Overall Model adjusting for CV Risk Factors and CAC
AVC=0 1 (ref) - - 1 (ref) - - 1 (ref) - -
AVC 1-99 1.05 0.86-1.30 0.624 1.30 0.93-1.81 0.131 1.41 0.91-2.22 0.123
AVC≥100 0.95 0.74-1.23 0.712 1.16 0.77-1.74 0.487 1.40 0.84-2.33 0.196
Overall Model, inclusive of only Low CAC (<100)
AVC=0 1 (ref) - - 1 (ref) - - 1 (ref) - -
AVC 1-99 0.85 0.51-1.41 0.518 0.68 0.24-1.94 0.465 0.54 0.12-2.37 0.411
AVC≥100 1.93 1.14-3.27 0.013 2.71 1.16-6.34 0.022 2.39 0.77-7.47 0.133
Overall Model, inclusive of only High CAC (≥100)
AVC=0 1 (ref) - - 1 (ref) - - 1 (ref) - -
AVC 1-99 0.99 0.74-1.32 0.932 1.32 0.84-2.07 0.231 1.71 0.97-3.02 0.063
AVC≥100 1.08 0.80-1.47 0.604 1.32 0.82-2.12 0.246 1.34 0.72-2.49 0.361
Table 2. Mortality for AVC subgroups, stratified by CAC score inclusion. Adapted from Han et al.15

Discussion

The study by Han et al. builds upon the previously described association between AVC and incident CVD by providing new information on mortality outcomes.15 AVC is significantly associated with increased risk of ACM and CVD, although this association is not significant when adjusting for CAC score. However, in patients with CAC <100, there remains a significant association between AVC score and increased risk of ACM and CVD independent of CAC.

Attenuation of the association between AVC score and mortality outcomes after adjusting for CAC score is due to three important features. First, there is a unified pathological process underpinning calcification in both contexts, namely, subclinical atherosclerosis. Second, CAC is a very strong predictor of CVD outcomes, limiting the possibility of incremental utility of an additional predictive tool.18-22

These two points explain why while AVC has predictive utility, it fails to do so reliably better than the established CAC methodology. Lastly, in the later stages of AVC, atherosclerogenesis is driven by osteogenesis; therefore, AVC is more strongly related to AS than ASCVD.23 It was previously unclear whether AVC measurement provided additional prognostic utility for risk stratification in asymptomatic individuals.

The authors demonstrate that there is a population: individuals with CAC <100. In this group, individuals with AVC >100 have a significantly increased risk of ACM and CVD compared to AVC <100. The inclusion of AVC specifically improves the ability of the predictive model in delineating mortality risk. There is no association with CHD mortality, which is due to the low burden of CHD in the CAC <100 group. The increase in ACM and CVD mortality for CAC <100 but AVC >100 is therefore likely driven by increased risk of severe AS.

There are several reasons why this association was only observed in the CAC <100 subgroup. Mechanistically, calcification may occur earlier in the AV than in coronary arteries due to higher levels of mechanical stress leading to accelerated endothelial damage and fibroblast activation.1,3,5,23 Alternatively, individuals with a CAC <100 and an AVC >100 are likely to be undergoing osteogenic changes predisposing to AS. This is important to identify as there are no options to slow progression of severe AS other than correction with valve replacement. Lastly, individuals with CAC >100 are more likely to receive pharmacological intervention based on their initial scan and statin therapy may alter the progression of subclinical atherosclerosis and AV sclerosis.24-26

The implications of the study are that AVC may be used as a tool to better classify CVD mortality risk in a large group (CAC <100) that may benefit from intervention that would otherwise traditionally not be targeted. Reclassifying risk based on AVC in addition to CAC can identify individuals who should be started on statin therapy, intensification of lifestyle modifications, or receive close follow-up for re-stratification.

It can also help identify patients at increased risk of AS-related mortality that warrant closer monitoring for progression to severe AS. Therefore, routine measurement of AVC should be included as part of standard reporting on CAC scans which would be without significant changes in current cardiac CT workflow.27,28

Conclusions

AVC is associated with increased risk of ACM, CVD, and CHD mortality, but was not an independent predictor after accounting for CAC. However, among patients with CAC <100 there was a significant association of AVC with CVD mortality. Therefore, the measurement of AVC should be considered as a routine part of the reporting for CAC scoring. Further research is needed to determine the generalizability of these results, better understanding of differences in pathophysiology of AVC versus CAC, and whether decisions based on AVC can improve cardiovascular outcomes.

References

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Clinical Topics: Diabetes and Cardiometabolic Disease, Dyslipidemia, Noninvasive Imaging, Valvular Heart Disease, Atherosclerotic Disease (CAD/PAD), Nonstatins, Novel Agents, Statins, Computed Tomography, Nuclear Imaging

Keywords: Dyslipidemias, Hydroxymethylglutaryl-CoA Reductase Inhibitors, Coronary Artery Disease, Aortic Valve, Cardiovascular Diseases, Prognosis, Stress, Mechanical, Sclerosis, Retrospective Studies, Osteogenesis, Follow-Up Studies, Calcinosis, Aortic Valve Stenosis, Atherosclerosis, Risk Factors, Tomography, X-Ray Computed, Risk Assessment, Life Style, Fibroblasts, Tomography, Reference Standards


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