Abstract
Aims
The purpose of this study was to compare coronary computed tomography angiography (CCTA) and guideline-recommended clinical risk assessment for the value in statin allocation in outpatients with suspected coronary artery disease (CAD).
Methods
For the 7860 eligible outpatients with suspected CAD who underwent CCTA, we evaluate hard atherosclerotic cardiovascular disease (ASCVD) and major adverse cardiac and cerebrovascular event (MACCE) stratified by guideline-recommended clinical risk assessment, and CCTA. For intermediate risk patients, we also compared the predictive value of CCTA and CAC.
Results
Over a median follow-up period of 3.6 years, a total of 83 (1.1 %) hard ASCVD and 170 (2.2 %) MACCE occurred. The event rate increased with both the intensity of statin recommendation (e.g., hard ASCVD: 1.5 per 1000 person-years [PY] for statin not recommended, 4.1 per 1000 PY for moderate-intensity statin, and 8.9 per 1000 PY for high-intensity statin) and the severity of coronary stenosis (e.g., hard ASCVD: 0.7 per 1000 PY for no plaque, 5.1 per 1000 PY for non-obstructive CAD, and 11.2 per 1000 PY for obstructive CAD). When stratified by CCTA, higher intensity statin recommendation was not a statistically significant independent risk factor, both for hard ASCVD and MACCE. For the predictive value of hard ASCVD in intermediate risk patients, there was no statistically significant difference between CCTA and CAC (the area under the receiver operating characteristic curve: 0.692 versus 0.702; P = 0.78).
Conclusions
CCTA played a more important role in statin allocation compared to guideline-recommended clinical risk assessment in outpatients who underwent CCTA.
Keywords: Atherosclerosis, Coronary artery disease, Coronary computed tomography angiography, Risk stratification, Clinical risk score, Prognosis
1. Introduction
Currently, multiple guidelines recommended using clinical risk score systems as the basis for statin allocation in primary prevention [[1], [2], [3]]. In 2019, the American College of Cardiology (ACC)/ American Heart Association (AHA) guideline on the primary prevention of cardiovascular disease recommended that clinicians should routinely evaluate traditional cardiovascular risk factors and determine the 10-year risk of atherosclerotic cardiovascular disease (ASCVD) by using the pooled cohort equations (PCE) for adults aged 40 to 75 years [1]. The PCE consists of a series of clinical risk factors and demographic characteristics, including sex, age, race, blood pressure, serum lipid, diabetes, smoking, and treatment for hypertension. The current risk score systems are accessible but less than satisfactory, especially for addressing lipid-specific risk in primary prevention [4].
Coronary computed tomography angiography (CCTA) is highly effective in non-invasively detecting coronary atherosclerotic plaque and assessing the degree of coronary artery luminal stenosis. The role of CCTA has been recognized and endorsed by guidelines and an expert consensus as the first-line initial test for the diagnosis of coronary artery disease (CAD) [[5], [6], [7]]. However, the value of CCTA in guiding statin treatment decision-making in primary prevention remains unknown.
This study specifically aimed to compare the prognostic value of CCTA assessment with guideline-recommended clinical risk assessment for statin allocation in outpatients with suspected CAD. These findings are important in exploring the potential value of CCTA in CAD prevention, and may improve the efficiency and cost-effectiveness of statin allocation in primary prevention.
2. Methods
2.1. Study participants
The data analyzed in this study were from the CREATION (Coronary Atherosclerosis Disease Early Identification and Risk Stratification by Noninvasive Imaging; NCT03518437) registry, which was a prospective Chinese cohort of outpatients undergoing CCTA. The current study included consecutive outpatients aged 40–79 years old who underwent CCTA between June 3, 2015 and January 22, 2020 for suspected CAD in Fuwai Hospital of Beijing. All of these outpatients were referred for CCTA by cardiologists due to the relevant symptoms, such as chest pain, or having one or more risk factors, such as obesity, smoking, hypertension, hypercholesterolemia, diabetes mellitus, and the family history of CAD to rule out the obstructive CAD. Exclusion criteria were: statin use, low-density lipoprotein cholesterol (LDL-C) <1.8 mmol/L (70 mg/dL), revascularization within 90 days after CCTA, and missing data for clinical risk assessment such as risk factors included in the PCE. All patients provided written informed consent, and ethics committee approval for this study was obtained from the review board of Fuwai Hospital (No.2017–926).
2.2. Demographic characteristics and risk factors
The demographic characteristics and cardiovascular risk factors of all participants were collected at baseline. Demographic characteristics included age, sex, and race. Plasma biomarkers were evaluated, including total cholesterol, high-density lipoprotein cholesterol, LDL-C, and triglycerides. Hypertension was defined as systolic blood pressure ≥140 mmHg, diastolic blood pressure ≥90 mmHg, or use of antihypertensives. Diabetes mellitus was defined as a condition with a fasting glucose level of ≥126 mg/dl, a non-fasting glucose level of ≥200 mg/dl, or insulin/ oral hypoglycemic therapy. Smoking was considered with at least one cigarette used per day on average for at least a year. The body mass index (BMI) was determined as BMI =weight/ height2 (kg/m2). Aspirin use prior to CCTA was defined as aspirin prescription occurring >90 days before CCTA scan.
2.3. Clinical risk score and statin treatment eligibility
Using the collected clinical information, the 10-year ASCVD risk of each participant was determined by PCE based on a method introduced by the 2018 guideline on the management of blood cholesterol [8]. And according to ACC/AHA guidelines [1,8], outpatients were classified into the following groups for statin treatment recommendation.
1. Statin not recommended: LDL-C value between 1.8 and 4.9 mmol/L (70 mg/dL-190 mg/dL), no diabetes, and 10-year ASCVD risk <5 %.
2. Moderate-intensity statin: a. LDL-C value between 1.8 and 4.9 mmol/L (70 mg/dL-190 mg/dL), and 10-year ASCVD risk between 5 % and 20 %; b. diabetes mellitus patients.
3. High-intensity statin: a. LDL-C value between 1.8 and 4.9 mmol/L (70 mg/dL-190 mg/dL), and 10-year ASCVD risk ≥20 %; b. LDL-C ≥ 4.9 mmol/L (190 mg/dL).
2.4. CT acquisition and image analysis
CCTA was performed with CT scanners consisting of at least 64 detector rows. CCTA image acquisition followed the Society of Cardiovascular Computed Tomography guidelines [9]. The patients underwent non-contrast CT to determine coronary artery calcium (CAC) according to a method described by Agatston et al. [10]. CCTA images were collected and sent to a central processing and analysis platform. Scanned images, e.g., axial images, multiplanar reconstructions, and maximum intensity projections, as appropriate, were retrospectively analyzed with the workstation (ADW4.6; GE Healthcare, Milwaukee, WI, USA) by at least 2 expert radiologists. The coronary artery tree was partitioned into 16 segments based on the modified American Heart Association classification [11], and each coronary segment with a diameter of >1.5 mm was assessed for coronary luminal stenosis. All images were read, and the data were recorded following CAD-RADS [12]. Any disagreement between the two experts’ consensus was resolved by consulting another senior radiologist’s opinion.
In the classification of the severity of coronary atherosclerosis, no plaque was considered with no visible plaque (including calcified, non-calcified, and mixed plaque) and no suspected stenosis on the CCTA longitudinal images, non-obstructive CAD was defined as having plaque but with <50 % luminal stenosis at its most severe site of narrowing, obstructive CAD was defined as at least one coronary luminal stenosis of ≥50 %. According to the application of ACC/AHA guideline on the primary prevention of cardiovascular disease [1], CAC burden was categorized as CAC scores of 0, 1–99, and ≥100.
2.5. Clinical outcomes
Patients were followed up by telephone or outpatient interviews and hospital records. We defined hard ASCVD as a composite endpoint of all-cause death, acute myocardial infarction (MI), and stroke. Major adverse cardiac and cerebrovascular event (MACCE) included hard ASCVD and coronary revascularization (percutaneous coronary intervention [PCI] and coronary artery bypass grafting [CABG]) occurring >90 days after CCTA until the end of follow-up). Confirmation of all-cause death was based on hospital records and telephone interviews of patients’ families. Acute MI diagnosis was defined based on the elevated cardiac enzyme levels, with or without symptoms of myocardial ischemia, typical alterations on the electrocardiogram or imaging [13]. Stroke was defined by the rapid onset of a documented focal neurological impairment lasting 24 h or until death, or the evidence of a clinically relevant lesion on brain images.
As this study focused on primary prevention, late coronary revascularization was included in MACCE. Revascularization procedures within 90 days after CCTA were considered to be probably triggered by the scan and were excluded. An adjudication outcome panel of 2 physicians reviewed all patient data forms and verified via hospital records review the occurrence of MACCE. The adjudication panel was blinded to the CCTA findings. Any disagreement was resolved by consensus, involving an additional senior cardiologist.
2.6. Statistical analysis
The baseline characteristics of study participants were categorized according to the recommendation of statin therapy. Data were presented as frequency and proportion for categorical variables, and as mean ± standard deviation or median with interquartile range for continuous variables. The Chi-square tests, one-way ANOVA, and the Kruskal-Wallis H tests were used for the comparison of variables among groups, as appropriate. The prevalence rates of no plaque, non-obstructive CAD, and obstructive CAD were calculated and stratified by statin treatment recommendation (statin not recommended, moderate-intensity statin, and high-intensity statin).
Kaplan-Meier estimates of cumulative event-free survival were used to describe the occurrence of hard ASCVD and MACCE over time for overall and different CCTA findings groups, and log-rank tests were used for comparison. Event rates per 1000 person-years with 95 % confidence intervals (CIs) were determined across different statin recommendation classes, CAC groups, and CCTA findings groups. Data were stratified by CCTA findings to further assess the performance of guideline-recommended clinical risk assessment. Meanwhile, Cox proportional regression modeling analyzing the time to first event was employed to compute multivariable-adjusted hazard ratios (HRs) for each stratified group. The proportional hazard assumption was met for all models. Models were adjusted for age, sex, smoking, systolic pressure, fasting plasma glucose, LDL-C, CAC score, and aspirin use prior to CCTA.
Furthermore, we compared the value of CCTA and CAC for intermediate risk patients (those recommended for moderate-intensity statin). First, data were stratified by CAC groups to assess the event rate and HR value of CCTA findings. Second, receiver operating characteristic (ROC) curves based on logistic regression models were used to estimate the predictive value of CCTA and CAC by calculating the area under the curve (AUC). Significance between differences of AUC was performed by DeLong et al. method. The categorized net reclassification index (NRI) of CCTA was calculated with reference to the CAC among intermediate risk patients. All statistical analyses were performed using R software (version 4.2.1) and considered two-sided P-values of <0.05 as statistically significant.
3. Results
Baseline characteristics and the distribution of study participants with distinct statin recommendation classes are presented in Table 1. Overall, the final study participants consisted of 7860 eligible outpatients. The median age was 57.0 years (51.0–63.0) and 47.7 % were male. After a median follow-up of 3.6 years (2.3–4.2; maximum follow-up, 6.2 years), 83 participants (1.1 %) experienced hard ASCVD, and 170 participants (2.2 %) experienced a first MACCE. Specific events were: all-cause death (n = 32), acute MI (n = 8), stroke (n = 43), PCI (n = 91), and CABG (n = 14).
Table 1.
Baseline characteristics of study participants.
| Statin Not Recommended (3437) | Moderate-intensity Statin (3940) | High-intensity Statin (483) | p Value | |
|---|---|---|---|---|
| Age, yrs | 53.0 (47.0–57.0) | 60.0 (54.0–65.0) | 67.0 (59.0–73.0) | <0.001 |
| Male | 874 (25) | 2595 (66) | 281 (58) | <0.001 |
| Diabetes | 0 (0) | 910 (23) | 31 (6) | <0.001 |
| Hypertension | 1093 (32) | 2100 (53) | 319 (66) | <0.001 |
| Smoking | 269 (8) | 1789 (45) | 202 (42) | <0.001 |
| BMI, kg/m2 | 24.9 (22.9–27.1) | 25.3 (23.4–27.3) | 24.9 (23.4–26.8) | <0.001 |
| Total cholesterol, mmol/L | 4.9 (4.4–5.5) | 4.9 (4.4–5.5) | 6.0 (4.8–7.2) | <0.001 |
| HDL-C, mmol/L | 1.4 (1.2–1.6) | 1.2 (1.0–1.4) | 1.3 (1.1–1.5) | <0.001 |
| LDL-C, mmol/L | 3.1 (2.6–3.6) | 3.1 (2.6–3.6) | 4.1 (3.1–5.2) | <0.001 |
| Triglycerides, mmol/L | 1.4 (1.0–1.9) | 1.6 (1.1–2.2) | 1.7 (1.2–2.2) | <0.001 |
| Aspirin use before CCTA | 572 (17) | 1077 (27) | 129 (27) | <0.001 |
| Agatston calcium score | <0.001 | |||
| CAC=0 | 2804 (82) | 2079 (53) | 204 (42) | |
| CAC=1–99 | 463 (14) | 1008 (26) | 115 (24) | |
| CAC≥100 | 170 (5) | 853 (22) | 164 (34) | |
| CCTA | <0.001 | |||
| No plaque | 2537 (74) | 1623 (41) | 147 (30) | |
| Non-obstructive CAD | 767 (22) | 1813 (46) | 239 (50) | |
| Obstructive CAD | 133 (4) | 504 (13) | 97 (20) |
Values are median (interquartile range) for continuous variables, and n ( %) for categorical variables.
BMI, body mass index; HDL-C, high-density lipoprotein cholesterol; LDL-C, low-density lipoprotein cholesterol; CAC, coronary artery calcium; CCTA, coronary computed tomography angiography; CAD, coronary artery disease.
3.1. Statin recommendation classifications according to guidelines
According to ACC/AHA guidelines [1,8], the patients were stratified into different statin recommendation classes (Fig. 1). Of the 7860 eligible outpatients without statin therapy, 208 (2.6 %) patients had LDL-C ≥ 4.9mmol/L and were classified as high-intensity statin recommendation; 910 (11.6 %) patients had diabetes mellitus and were classified as moderate-intensity statin recommendation. The remaining 6742 patients were eligible for the determination of 10-year ASCVD risk by using the PCE: 3437 (43.7 %) patients had a 10-year ASCVD risk of <5 % and were classified in statin not recommended;1000 (12.7 %) participants had a 10-year ASCVD risk of 5 %−7.5 % and 2030 (25.8 %) patients had a 10-year ASCVD risk of 7.5 %−20 %, who were all classified as moderate-intensity statin recommendation; 275 (3.5 %) patients had a 10-year ASCVD risk of ≥20 % and were classified as high-intensity statin recommendation. As a result, overall, according to ACC/AHA guidelines, 3437 (43.7 %) patients were statin not recommended, 3940 (50.1 %) patients were recommended moderate-intensity statin, and 483 (6.1 %) patients were recommended high-intensity statin in this study.
Fig. 1.
Flow diagram and statin recommendation classifications among baseline study participants
Overall, 43.7 % of the participants were not recommended for statin, 50.1 % were recommended for moderate-intensity statin, and 6.1 % were recommended for high-intensity statin.
CCTA, coronary computed tomography angiography; CAD, coronary artery disease; LDL-C, low-density lipoprotein cholesterol; ASCVD, atherosclerotic cardiovascular disease.
3.2. Distribution of coronary atherosclerosis across statin recommendation classifications
The distribution of CCTA-based coronary atherosclerosis across statin recommendation classifications is shown in Fig. 2 and Graphical Abstract. Overall, from statin not recommended, to moderate-intensity statin, to high-intensity statin, the proportion of no plaque progressively decreased, while the proportions of non-obstructive and obstructive CAD increased stepwise. In the high-intensity statin group and moderate-intensity statin group, 30.4 % and 41.2 % patients had no plaque, respectively. In the statin not recommended group, 26.2 % patients had non-obstructive or obstructive CAD.
Fig. 2.
Distribution of coronary atherosclerosis across statin recommendation classifications
Among the participants with statin recommendation (moderate and high-intensity statin), 40 % (1770/4423) had no plaque, while among those not recommended for statin, 26.2 % (900/3437) had plaque (non-obstructive CAD or obstructive CAD).
CAD, coronary artery disease.
3.3. Events according to statin recommendation classifications, CAC burden and CCTA
Overall, both the risk of hard ASCVD and MACCE increased progressively with higher statin recommendation level, CAC burden and CCTA (Table 2 and Graphical Abstract). For statin recommendation classifications, the hard ASCVD event rate per 1000 person-years ranged from 1.5 (95 %CI: 0.9 to 2.4) in the statin not recommended group to 8.9 (95 %CI: 5.2–15.3) in the recommended high-intensity statin group, and the MACCE rate per 1000 person-years ranged from 2.4 (95 %CI: 1.7 to 3.5) in the statin not recommended group to 16.4 (95 %CI: 11.0–24.4) in the recommended high-intensity statin group. As for CAC burden, the hard ASCVD event rate per 1000 person-years ranged from 1.0 (95 %CI: 0.6–1.6) in the CAC=0 group to 11.7 (95 %CI: 8.7–15.6) in the CAC≥100 group, and the MACCE rate per 1000 person-years ranged from 2.1 (95 %CI: 1.5–2.9) in the CAC=0 group to 24.4 (95 %CI: 19.9–29.8) in the CAC≥100 group. Similarly, for CCTA findings, the hard ASCVD event rate per 1000 person-years increased from 0.7 (95 %CI: 0.4–1.3) in the no plaque group to 11.2 (95 %CI: 7.6–16.4) in the obstructive CAD group, and the MACCE rate per 1000 person-years ranged from 0.8 (95 %CI: 0.5–1.5) in the no plaque group to 31.9 (95 %CI: 25.5–39.9) in the obstructive CAD group.
Table 2.
Events based on statin recommendation classifications, CAC burden and CCTA.
|
Hard ASCVD |
MACCE |
||||||
|---|---|---|---|---|---|---|---|
| Total | Events ( %) | Event Rate per 1000 Person-Yrs | HR (95 % CI) | Events ( %) | Event Rate per 1000 Person-Yrs | HR (95 % CI) | |
| Statin recommendation | |||||||
| Statin not recommended | 3437 | 17 (0.5 %) | 1.5 (0.9–2.4) | 1 (reference) | 28 (0.8 %) | 2.4 (1.7–3.5) | 1 (reference) |
| Moderate-intensity statin | 3940 | 53 (1.3 %) | 4.1 (3.1–5.4) | 1.4 (0.7–2.7) | 118 (3.0 %) | 9.2 (7.7–11.0) | 2.3 (1.4–3.7) |
| High-intensity statin | 483 | 13 (2.7 %) | 8.9 (5.2–15.3) | 1.9 (0.7–5.0) | 24 (5.0 %) | 16.4 (11.0–24.4) | 3.3 (1.7–6.5) |
| CAC | |||||||
| CAC=0 | 5087 | 17 (0.3 %) | 1.0 (0.6–1.6) | 1 (reference) | 35 (0.7 %) | 2.1 (1.5–2.9) | 1 (reference) |
| CAC=1–99 | 1586 | 22 (1.4 %) | 4.3 (2.8–6.5) | 3.5 (1.9–6.8) | 43 (2.7 %) | 8.3 (6.2–11.2) | 3.6 (2.3–5.6) |
| CAC≥100 | 1187 | 44 (3.7 %) | 11.7 (8.7–15.6) | 8.2 (4.5–15.0) | 92 (7.8 %) | 24.4 (19.9–29.8) | 9.3 (6.1–14.2) |
| CCTA | |||||||
| No plaque | 4307 | 10 (0.2 %) | 0.7 (0.4–1.3) | 1 (reference) | 12 (0.3 %) | 0.8 (0.5–1.5) | 1 (reference) |
| Non-obstructive CAD | 2819 | 47 (1.7 %) | 5.1 (3.8–6.8) | 5.4 (2.7–10.9) | 84 (3.0 %) | 9.1 (7.4–11.3) | 9.0 (4.9–16.7) |
| Obstructive CAD | 734 | 26 (3.5 %) | 11.2 (7.6–16.4) | 11.5 (5.4–24.7) | 74(10.1 %) | 31.9 (25.5–39.9) | 30.0 (16.0–56.1) |
Adjusted for age and sex.
ASCVD, atherosclerotic cardiovascular disease; MACCE, major adverse cardiac and cerebrovascular event; HR, hazard ratio; CI, confidence interval; CCTA, coronary computed tomography angiography; CAD, coronary artery disease.
3.4. Events across different statin recommendation classifications stratified by CCTA
Kaplan-Meier estimates of event-free survival for hard ASCVD and MACCE across different statin recommendation classifications stratified by CCTA are shown in Fig. 3. Overall, there were significant differences (p < 0.001) in the risk of events (both hard ASCVD and MACCE) across patients with distinct statin recommendation classes. However, stratified by CCTA, no significant differences were found (p > 0.05) in the risk of events across patients with distinct statin recommendation classes in the no plaque and non-obstructive CAD groups. Only in patients with obstructive CAD did significant differences in the risk of events remain across different statin recommendation classes (p < 0.05).
Fig. 3.
Kaplan-Meier survival curves across statin recommendation classifications in overall and stratified by CCTA
(A) Survival from hard ASCVD with different statin recommendation classifications in overall and stratified by CCTA. (B) Survival from MACCE with different statin recommendation classifications in overall and stratified by CCTA. Hard ASCVD included all-cause death, acute myocardial infarction, and stroke. MACCE included all-cause death, acute myocardial infarction, late revascularization, and stroke.
ASCVD, atherosclerotic cardiovascular disease; MACCE, major adverse cardiac and cerebrovascular event; CCTA, coronary computed tomography angiography; CAD, coronary artery disease.
The frequencies of observed hard ASCVD and MACCE, the corresponding event rates per 1000 person-years, and the multivariable adjusted HRs associated with different statin recommendation classifications in study participants across distinct CCTA groups are detailed in Table 3. Cox regression modeling analysis adjusted for baseline characteristics and CAC score showed that higher intensity statin recommendation (from statin not recommended, to moderate-intensity statin recommended, or to high-intensity statin recommended) was not a statistically significant independent risk factor as stratified by CCTA, both for hard ASCVD and MACCE. Specifically, for example, in patients with non-obstructive CAD, those recommended a moderate or high-intensity statin were not statistically associated with a higher risk of events compared with those not recommended a statin. Similar results were demonstrated in analyses using the SCORE2 & SCORE2-OP classifications recommended by the European guidelines [3] (Supplementary material, Table S1).
Table 3.
Events in statin recommendation classifications stratified by CCTA.
|
Hard ASCVD |
MACCE |
||||||
|---|---|---|---|---|---|---|---|
| Total | Events ( %) | Event Rate per 1000 Person-Yrs | HR (95 % CI) | Events ( %) | Event Rate per 1000 Person-Yrs | HR (95 % CI) | |
| No plaque | |||||||
| Statin not recommended | 2537 | 5 (0.2 %) | 0.6 (0.2–1.4) | 1 (reference) | 6 (0.2 %) | 0.7 (0.3–1.6) | 1 (reference) |
| Moderate-intensity statin | 1623 | 5 (0.3 %) | 0.9 (0.4–2.2) | 2.1 (0.3–13.2) | 6 (0.4 %) | 1.1 (0.5–2.5) | 2.7 (0.5–14.3) |
| High-intensity statin | 147 | 0 (0.0 %) | 0 | – | 0 (0.0 %) | 0 | – |
| Non-obstructive CAD | |||||||
| Statin not recommended | 767 | 9 (1.2 %) | 3.5 (1.8–6.6) | 1 (reference) | 15 (2.0 %) | 5.8 (3.5–9.5) | 1 (reference) |
| Moderate-intensity statin | 1813 | 32 (1.8 %) | 5.4 (3.9–7.7) | 1.0 (0.4–2.6) | 60 (3.3 %) | 10.2 (7.9–13.1) | 1.4 (0.7–2.9) |
| High-intensity statin | 239 | 6 (2.5 %) | 8.1 (3.6–17.9) | 1.4 (0.3–6.1) | 9 (3.8 %) | 12.1 (6.3–23.1) | 1.9 (0.7–5.4) |
| Obstructive CAD | |||||||
| Statin not recommended | 133 | 3 (2.3 %) | 6.5 (2.1–20.2) | 1 (reference) | 7 (5.3 %) | 15.3 (7.3–31.8) | 1 (reference) |
| Moderate-intensity statin | 504 | 16 (3.2 %) | 10.0 (6.1–16.3) | 1.5 (0.3–7.0) | 52 (10.3 %) | 32.5 (24.9–42.4) | 1.9 (0.8–4.8) |
| High-intensity statin | 97 | 7 (7.2 %) | 26.9 (13.0–56.0) | 3.6 (0.5–27.0) | 15 (15.5 %) | 57.7 (35.3–94.4) | 3.4 (1.0–11.4) |
Adjusted for age, sex, smoking, systolic pressure, fasting plasma glucose, low-density lipoprotein cholesterol, coronary artery calcium score, and aspirin use before CCTA.
CCTA, coronary computed tomography angiography; ASCVD, atherosclerotic cardiovascular disease; MACCE, major adverse cardiac and cerebrovascular event; CI, confidence interval; HR, hazard ratio; CAD, coronary artery disease.
3.5. Events across different CCTA groups stratified by CAC burden in intermediate risk patients
For patients at intermediate risk, the ACC/AHA guidelines [1,8] recommended adding CAC to the risk discussion for statin therapy decision making. As depicted in Table 4, for MACCE, non-obstructive CAD and obstructive CAD were risk factors for patients without CAC, and obstructive CAD was risk factor for patients with CAC>0 (using non-obstructive CAD as the reference). However, as for hard ASCVD, non-obstructive CAD for patients without CAC and obstructive CAD for patients with CAC>0 were no longer statistically significant risk factors. Consistent results are reflected in the ROC in Fig. 4, there was no significant difference between the AUC of CCTA and CAC (0.692 versus 0.702; P = 0.78) in intermediate risk patients for hard ASCVD. And for MACCE, the AUC of CCTA and CAC were 0.757 and 0.705, respectively (P < 0.05). With the CAC as references, the NRI of CCTA was −0.089 (95 % CI: −0.342–0.191) for hard ASCVD and 0.053 (95 % CI: −0.068–0.311) for MACCE among intermediate risk patients.
Table 4.
Events in different CCTA groups stratified by CAC burden in intermediate risk patients.
|
Hard ASCVD |
MACCE |
||||||
|---|---|---|---|---|---|---|---|
| Total | Events (%) | Event Rate per 1000 Person-Yrs | HR (95 % CI) | Events (%) | Event Rate per 1000 Person-Yrs | HR (95 % CI) | |
| CAC=0 | |||||||
| No plaque | 1623 | 5 (0.3 %) | 0.9 (0.4–2.2) | 1 (reference) | 6 (0.4 %) | 1.1 (0.5–2.5) | 1 (reference) |
| Non-obstructive CAD | 347 | 3 (0.9 %) | 2.5 (0.8–7.8) | 2.9 (0.7–12.4) | 9 (2.6 %) | 7.6 (3.9–14.5) | 6.7 (2.4–19.0) |
| Obstructive CAD | 109 | 3 (2.8 %) | 8.3 (2.7–25.5) | 9.9 (2.3–42.4) | 10 (9.2 %) | 27.6 (15.0–50.8) | 24.5 (8.8–68.2) |
| CAC=1–99 | |||||||
| Non-obstructive CAD | 879 | 11 (1.3 %) | 3.9 (2.2–7.1) | 1 (reference) | 18 (2.0 %) | 6.4 (4.1–10.2) | 1 (reference) |
| Obstructive CAD | 129 | 3 (2.3 %) | 7.3 (2.4–22.6) | 1.8 (0.5–6.7) | 12 (9.3 %) | 29.3 (16.8–51.2) | 4.3 (2.0–9.0) |
| CAC≥100 | |||||||
| Non-obstructive CAD | 587 | 18 (3.1 %) | 9.5 (6.0–15.1) | 1 (reference) | 33 (5.6 %) | 17.5 (12.5–24.5) | 1 (reference) |
| Obstructive CAD | 266 | 10 (3.8 %) | 12.1 (6.5–22.3) | 1.3 (0.6–2.8) | 30 (11.3 %) | 36.2 (25.5–51.4) | 2.0 (1.2–3.2) |
Adjusted for age and sex.
ASCVD, atherosclerotic cardiovascular disease; MACCE, major adverse cardiac and cerebrovascular event; CI, confidence interval; HR, hazard ratio; CAC, coronary artery calcium; CCTA, coronary computed tomography angiography; CAD, coronary artery disease.
Fig. 4.
ROC curves of CAC and CCTA for intermediate risk patients
ROC curves show the event predictive value of CAC and CCTA for intermediate risk patients. (A) AUC of CAC and CCTA for hard ASCVD are 0.702 (95 %CI: 0.64–0.77) and 0.692 (95 %CI: 0.64–0.75), respectively (P = 0.78). (B) AUC of CAC and CCTA for MACCE are 0.705 (95 %CI: 0.66–0.75) and 0.757 (95 %CI: 0.72–0.79), respectively (P < 0.05).
ROC, receiver operating characteristic; AUC, area under the curve; CAC, coronary artery calcium; CCTA, coronary computed tomography angiography; ASCVD, atherosclerotic cardiovascular disease; MACCE, major adverse cardiac and cerebrovascular event; CI, confidence interval.
4. Discussion
Based on a large contemporary cohort of consecutive outpatients who underwent CCTA for suspected CAD, the present study provides an important new perspective on the use of CCTA assessment to guide statin allocation in patients who underwent CCTA, which is likely to be more accurate than current clinical risk assessment. As shown above, CCTA identified outpatients at lower risk and higher risk, respectively, than those indicated by ACC/AHA guideline-recommended clinical risk assessment. When stratified by CCTA, a higher intensity statin recommendation did not represent a statistically significant independent risk factor. Therefore, compared with guideline-recommended clinical risk assessment, CCTA played a more important role in statin allocation in primary prevention.
In current guidelines and clinical practice of primary prevention, clinical risk assessment, including the evaluation of risk factors and the estimation of 10-year ASCVD risk, is primarily recommended for statin prescription [1,8,14]. However, clinical risk assessment based on risk score has limitations. Different risk algorithms used in North America and Europe differed substantially in risk estimation [4], leading to inconsistency in statin recommendations. In 2023, an AHA scientific advisory group developed the Predicting Risk of cardiovascular disease EVENTs (PREVENT) equations [15], which included the risk factor of estimated glomerular filtration rate and extended the age range for younger people. Similar to the results of the study investigating CCTA to statin allocation, the PREVENT equations could reduce the number of people eligible for statin [16]. While researchers added new clinical risk factors to prediction tools to improve the models, risk scores were based on known clinical risk factors and could not cover unknown risk factors or genetic susceptibility [17]. With advances in non-invasive imaging, besides clinical risk scores, risk stratification, event prediction, and statin allocation have become possible with imaging tools to indirectly or directly visualize atherosclerotic lesions. To date, few studies have examined the impact of CCTA on statin allocation in primary prevention. Multiple studies have focused on using CAC as a risk enhancer to perform risk stratification and statin treatment decision-making [[18], [19], [20], [21]]. A report of the Multi-Ethnic Study of Atherosclerosis revealed the absence of CAC as a strong protective factor, compared to CAC presence, which reclassified candidates as non-eligible for statin therapy [18]. However, CAC did not reflect the non-calcified components of coronary atherosclerotic lesions, which are considered high risk plaques [22]. The issue of the residual risk of clinical risk scores and CAC may be addressed by applying CCTA findings. Specifically, the important role of statin is to suppress plaque progression [23] and coronary inflammation [24]. Meanwhile, CCTA is well known for its ability to detect coronary atherosclerotic plaques and to assess coronary luminal stenosis, directly showing the status of the target lesions in statin therapy. Several studies have demonstrated the value of CCTA in monitoring plaque suppression and transformation under statin therapy [[25], [26], [27]]. Therefore, the “good match” of CCTA and statin primary prevention may be a possible explanation for the current findings.
The present study results suggest that CCTA assessment has a better predictive value than traditional clinical risk assessment in patients who underwent CCTA. Although univariate analysis showed significant differences in diverse statin recommendation classes in patients with obstructive CAD, multivariable-adjusted HRs showed opposite results both for hard ASCVD and MACCE. Overall, this study shows a consistent pattern, with CCTA assessment of coronary atherosclerosis playing a more important role in risk stratification and statin allocation than clinical risk assessment in patients underwent CCTA. In addition, we present the distribution of CCTA-based coronary atherosclerosis across statin recommendation classifications. Of concern, a large proportion of patients without plaque, whose risk of adverse cardiovascular events was very low, were classified as recommended for statin use. This study validates the strong negative predictive value of CCTA, which can reclassify low-risk patients among individuals recommended for statin therapy. Whether there is a long-term benefit of statin use in people without current coronary artery plaque remains to be investigated.
Furthermore, we assessed whether CCTA-based coronary atherosclerosis assessment is still valuable compared to CAC burden in the intermediate risk patients, for whom CAC is recommended in current guidelines as an adjunct to risk discussion. Results showed that CCTA was still effective for MACCE after stratification by CAC. However, as for hard ASCVD, only obstructive CAD on CCTA was a statistically significant risk factor in patients with CAC=0. Overall, the predictive value of CCTA and CAC for hard ASCVD was similar. The reason for the higher ability of CCTA to predict MACCE than hard ASCVD may be that the assessment of coronary luminal stenosis by CCTA leads to some PCI and CABG use in clinical practice. CAC burden assessment remains effective for hard events in intermediate risk patients, and is cost-effective and efficient.
The results suggest an important role for coronary atherosclerosis detected by CCTA in statin allocation for primary prevention. Imaging can be used not only to diagnose diseases, but also to re-stratify the risk and guide interventions. CCTA provides a more direct and uniform indication of ASCVD risk and whether statin therapy is recommended, which may reveal the patients’ overall congenital and acquired risk through plaque phenotypes. This study provides a basis for further assessing the role of CCTA in risk stratification and preventive interventions.
5. Limitations
First, this was an observational study. Although we adjusted Cox analyses for baseline characteristics (including age, sex, smoking, systolic pressure, fasting plasma glucose, low-density lipoprotein cholesterol, and aspirin use before CCTA) and CAC score, potential uncontrolled confounders could not be ruled out. And to control for the effect of statin use before CCTA exam on study results and to ensure comparability across different statin recommendation classifications, we excluded patients who were on statin therapy at baseline. Secondly, although the registry cohort was multicenter, this study only analyzed follow-up data from single center, and the limited follow-up time and number of events in this study may affect the power of subgroup analyses. Thirdly, we did not analyze other coronary atherosclerosis information from CCTA, e.g., plaque characteristics, plaque burden, pericoronary adipose tissue, and fractional flow reserve-CT. Finally, we defined obstructive CAD in this study as coronary luminal stenosis of ≥50 %, which may yield different results if other definitions are used. However, obstructive CAD, defined as coronary luminal stenosis of ≥50 %, showed good predictive ability in this study. In addition, this study did not include information on the effect of therapy changes after CCTA, which may have contributed to the lower event rates and influenced the conclusions obtained. Further large randomized controlled studies are required to validate the current conclusions.
6. Conclusions
CCTA played a more important role in statin allocation compared to guideline-recommended clinical risk assessment in outpatients who underwent CCTA. CCTA provided better risk stratification value than traditional clinical risk assessment. In intermediate risk patients, CCTA did not show a higher predictive value than CAC for hard events. Our findings support the value of CCTA and CAC in primary prevention statin allocation, especially in patients who have undergone CCTA and CAC.
Central Illustration
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CCTA, coronary computed tomography angiography; CAD, coronary artery disease; CAC, coronary artery calcium; ASCVD, atherosclerotic cardiovascular disease; MACCE, major adverse cardiac and cerebrovascular event; HR, hazard ratio; CI, confidence interval.
Data availability
The data underlying this article will be shared on reasonable request to the corresponding author.
CRediT authorship contribution statement
Jianan Zheng: Writing – original draft, Visualization, Methodology, Formal analysis, Data curation, Conceptualization. Zhihui Hou: Supervision, Resources, Project administration, Investigation, Data curation. Yang Gao: Supervision, Methodology. Weihua Yin: Supervision, Methodology, Investigation. Yanan Ma: Supervision, Methodology. Yunqiang An: Methodology, Formal analysis, Data curation. Yang Wang: Supervision, Methodology. Lei Song: Writing – review & editing, Supervision. Bin Lu: Writing – review & editing, Supervision, Resources, Project administration, Methodology, Investigation, Funding acquisition.
Declaration of competing interest
The authors declare the following financial interests/personal relationships which may be considered as potential competing interests:
Bin Lu reports financial support was provided by Ministry of Science and Technology of the People’s Republic of China. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.
Funding
This study was supported by the CAMS Innovation Fund for Medical Sciences (CIFMS) (2021-I2M-1-008) and the Ministry of Science and Technology of China through the national key research and development project (2016YFC1300400).
Footnotes
Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.ajpc.2025.100995.
Appendix. Supplementary materials
References
- 1.Arnett D.K., Blumenthal R.S., Albert M.A., et al. 2019 ACC/AHA Guideline on the primary prevention of cardiovascular disease: a report of the American college of cardiology/American heart association task force on clinical practice guidelines[J] Circulation. 2019;140(11):e596–e646. doi: 10.1161/cir.0000000000000678. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 2.Mach F., Baigent C., Catapano A.L., et al. 2019 ESC/EAS Guidelines for the management of dyslipidaemias: lipid modification to reduce cardiovascular risk[J] Eur Heart J. 2020;41(1):111–188. doi: 10.1093/eurheartj/ehz455. [DOI] [PubMed] [Google Scholar]
- 3.Visseren F.L.J., Mach F., Smulders Y.M., et al. 2021 ESC guidelines on cardiovascular disease prevention in clinical practice[J] Eur Heart J. 2021;42(34):3227–3337. doi: 10.1093/eurheartj/ehab484. [DOI] [PubMed] [Google Scholar]
- 4.Mancini G.B.J., Ryomoto A., Yeoh E., et al. Recommendations for statin management in primary prevention: disparities among international risk scores[J] Eur Heart J. 2023 doi: 10.1093/eurheartj/ehad539. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 5.Knuuti J., Wijns W., Saraste A., et al. 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes[J] Eur Heart J. 2019 doi: 10.1093/eurheartj/ehz425. [DOI] [PubMed] [Google Scholar]
- 6.Gulati M., Levy P.D., Mukherjee D., et al. 2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the evaluation and diagnosis of chest pain: a report of the American college of cardiology/American heart association joint committee on clinical practice guidelines[J] J Cardiovasc Comput Tomogr. 2022;16(1):54–122. doi: 10.1016/j.jcct.2021.11.009. [DOI] [PubMed] [Google Scholar]
- 7.Narula J., Chandrashekhar Y., Ahmadi A., et al. SCCT 2021 expert consensus document on coronary computed tomographic angiography: a report of the society of cardiovascular computed tomography[J] J Cardiovasc Comput Tomogr. 2021;15(3):192–217. doi: 10.1016/j.jcct.2020.11.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Grundy S.M., Stone N.J., Bailey A.L., et al. 2018 AHA/ACC/AACVPR/AAPA/ABC/ACPM/ADA/AGS/APhA/ASPC/NLA/PCNA guideline on the management of blood cholesterol: a report of the American college of cardiology/American heart association task force on clinical practice guidelines[J] Circulation. 2019;139(25):e1082–e1143. doi: 10.1161/cir.0000000000000625. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 9.Abbara S., Blanke P., Maroules C.D., et al. SCCT guidelines for the performance and acquisition of coronary computed tomographic angiography: a report of the society of cardiovascular computed tomography guidelines committee: endorsed by the North American society for cardiovascular imaging (NASCI)[J] J Cardiovasc Comput Tomogr. 2016;10(6):435–449. doi: 10.1016/j.jcct.2016.10.002. [DOI] [PubMed] [Google Scholar]
- 10.Agatston A.S., Janowitz W.R., Hildner F.J., et al. Quantification of coronary artery calcium using ultrafast computed tomography[J] J Am Coll Cardiol. 1990;15(4):827–832. doi: 10.1016/0735-1097(90)90282-t. [DOI] [PubMed] [Google Scholar]
- 11.Austen W.G., Edwards J.E., Frye R.L., et al. A reporting system on patients evaluated for coronary artery disease. Report of the Ad Hoc committee for grading of coronary artery disease, council on cardiovascular surgery, American heart association[J] Circulation. 1975;51(4 Suppl):5–40. doi: 10.1161/01.cir.51.4.5. [DOI] [PubMed] [Google Scholar]
- 12.Cury R.C., Abbara S., Achenbach S., et al. CAD-RADS(TM) coronary artery Disease - reporting and Data System. An expert consensus document of the Society of Cardiovascular Computed Tomography (SCCT), the American College of Radiology (ACR) and the North American Society for Cardiovascular Imaging (NASCI). Endorsed by the American College of Cardiology[J] J Cardiovasc Comput Tomogr. 2016;10(4):269–281. doi: 10.1016/j.jcct.2016.04.005. [DOI] [PubMed] [Google Scholar]
- 13.Thygesen K., Alpert J.S., Jaffe A.S., et al. Fourth universal definition of myocardial infarction (2018)[J] Eur Heart J. 2019;40(3):237–269. doi: 10.1093/eurheartj/ehy462. [DOI] [PubMed] [Google Scholar]
- 14.Mangione C.M., Barry M.J., Nicholson W.K., et al. Statin use for the primary prevention of cardiovascular disease in adults: US preventive services task force recommendation statement[J] JAMA. 2022;328(8):746–753. doi: 10.1001/jama.2022.13044. [DOI] [PubMed] [Google Scholar]
- 15.Khan S.S., Matsushita K., Sang Y., et al. Development and validation of the American Heart Association's PREVENT equations[J] Circulation. 2024;149(6):430–449. doi: 10.1161/circulationaha.123.067626. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Diao J.A., Shi I., Murthy V.L., et al. Projected changes in statin and antihypertensive therapy eligibility with the AHA PREVENT cardiovascular risk equations[J] JAMA. 2024;332(12):989–1000. doi: 10.1001/jama.2024.12537. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Natarajan P., Young R., Stitziel N.O., et al. Polygenic risk score identifies subgroup with higher burden of atherosclerosis and greater relative benefit from Statin therapy in the primary prevention setting[J] Circulation. 2017;135(22):2091–2101. doi: 10.1161/circulationaha.116.024436. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Nasir K., Bittencourt M.S., Blaha M.J., et al. Implications of coronary artery calcium testing among statin candidates according to American college of cardiology/American heart association cholesterol management guidelines: MESA (Multi-Ethnic Study of Atherosclerosis)[J] J Am Coll Cardiol. 2015;66(15):1657–1668. doi: 10.1016/j.jacc.2015.07.066. [DOI] [PubMed] [Google Scholar]
- 19.Muhlestein J.B., Knowlton K.U., Le V.T., et al. Coronary artery calcium versus pooled cohort equations score for primary prevention guidance: randomized feasibility trial[J] JACC Cardiovasc Imaging. 2022;15(5):843–855. doi: 10.1016/j.jcmg.2021.11.006. [DOI] [PubMed] [Google Scholar]
- 20.Blaha M.J., Whelton S.P., Al Rifai M., et al. Comparing risk scores in the prediction of coronary and cardiovascular deaths: coronary artery calcium Consortium[J] JACC Cardiovasc Imaging. 2021;14(2):411–421. doi: 10.1016/j.jcmg.2019.12.010. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 21.Yeboah J., Young R., McClelland R.L., et al. Utility of nontraditional risk markers in atherosclerotic cardiovascular disease risk assessment[J] J Am Coll Cardiol. 2016;67(2):139–147. doi: 10.1016/j.jacc.2015.10.058. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 22.Williams M.C., Kwiecinski J., Doris M., et al. Low-attenuation noncalcified plaque on coronary computed tomography angiography predicts myocardial infarction: results from the Multicenter SCOT-HEART trial (Scottish Computed Tomography of the HEART)[J] Circulation. 2020 doi: 10.1161/circulationaha.119.044720. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Brown G., Albers J.J., Fisher L.D., et al. Regression of coronary artery disease as a result of intensive lipid-lowering therapy in men with high levels of apolipoprotein B[J] N Engl J Med. 1990;323(19):1289–1298. doi: 10.1056/nejm199011083231901. [DOI] [PubMed] [Google Scholar]
- 24.Tawakol A., Fayad Z.A., Mogg R., et al. Intensification of statin therapy results in a rapid reduction in atherosclerotic inflammation: results of a multicenter fluorodeoxyglucose-positron emission tomography/computed tomography feasibility study[J] J Am Coll Cardiol. 2013;62(10):909–917. doi: 10.1016/j.jacc.2013.04.066. [DOI] [PubMed] [Google Scholar]
- 25.Lee S.E., Chang H.J., Sung J.M., et al. Effects of statins on coronary atherosclerotic plaques: the PARADIGM study[J] JACC Cardiovasc Imaging. 2018;11(10):1475–1484. doi: 10.1016/j.jcmg.2018.04.015. [DOI] [PubMed] [Google Scholar]
- 26.van Rosendael A.R., van den Hoogen I.J., Gianni U., et al. Association of Statin treatment with progression of coronary atherosclerotic plaque composition[J] JAMA Cardiol. 2021 doi: 10.1001/jamacardio.2021.3055. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Shin S., Park H.B., Chang H.J., et al. Impact of intensive LDL cholesterol lowering on coronary artery atherosclerosis progression: a serial CT angiography study[J] JACC Cardiovasc Imaging. 2017;10(4):437–446. doi: 10.1016/j.jcmg.2016.04.013. [DOI] [PubMed] [Google Scholar]
Associated Data
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Supplementary Materials
Data Availability Statement
The data underlying this article will be shared on reasonable request to the corresponding author.