Abstract
Importance
Observations
Conclusions and Relevance
Disclosure
Keywords
Scope of the Problem
American College of Cardiology. ASCVD Risk Estimator Plus. Available at: https://tools.acc.org/ascvd-risk-estimator-plus/#!/calculate/estimate/. Accessed October 27, 2022.
- •A Population-Based Approach Misses the Majority of Individuals Who Will Develop Coronary Artery Disease. While risk factors are associated with coronary artery disease in large populations, they possess significantly less diagnostic and prognostic precision when applied to individual patients. As an example, in the Get with the Guidelines database of 136,905 individuals hospitalized for coronary artery disease, >50% had low-density lipoprotein <100 mg/dL, the level considered ideal at the time of publication.5These findings are consistent with the Framingham Heart Study, wherein >80% overlap of cholesterol levels was observed for patients with and without coronary artery disease in a 26-year follow-up.6
- •Risk Factor-Guided Approaches Perform Differently in Different Populations. Atherosclerotic cardiovascular disease risk estimation is known to perform better in certain populations than others. In the Women's Health Initiative of a multiethnic population of 19,995 women, observed risks of atherosclerotic cardiovascular disease events were significantly lower than that estimated by risk calculators.7Similar disparities for risk factor scoring are observed for younger patients and those of different races and ethnicities.8
- •Risk Factor Presence Does Not Ensure Presence of Coronary Artery Disease, Even in High-Risk Individuals. While diabetes is widely considered a “coronary artery disease equivalent,”9population-based cohorts of diabetic individuals undergoing coronary computed tomography angiography have revealed that one-third have no or minimal coronary artery disease, a finding associated with low rates of major adverse cardiovascular events.10Population-based definitions do not ideally classify individuals with diabetes who may actually be at low clinical risk.
- •Risk Factor Control Fails the Majority of Individuals Who Retain High Residual Risk. Risk factor control does not reliably pinpoint individuals who are successfully treated for risk factors but who retain significant residual risk for major adverse cardiovascular events. As an example, Libby11has espoused the concept of the “forgotten majority” to the 62%-75% of individuals with dyslipidemia who are treated with statin therapy but still go on to experience major adverse cardiovascular events.
- •Atherosclerotic Cardiovascular Disease Risk Scoring Does Not Account for Other Well-Known Factors That Predispose an Individual to Major Adverse Cardiovascular Events. Hundreds of conditions have been identified that predispose an individual to major adverse cardiovascular events, and are unaccounted for in atherosclerotic cardiovascular disease scoring.4These include: cardiometabolic disorders such as non-alcoholic steatohepatitis; renal disorders such as chronic kidney disease; pulmonary disorders such as chronic obstructive pulmonary disease and exposure to air pollution; and many others.
- •Atherosclerotic Cardiovascular Disease Risk Scoring Does Not Account for As-Yet Unknown Factors That Predispose an Individual to Major Adverse Cardiovascular Events. It remains likely that there is an array of contributors to atherosclerotic cardiovascular disease risk that have not yet been identified.12Further, beyond risk factor presence, it is likely that its severity, duration, and treatment efficacy contribute to major adverse cardiovascular events risk, and are not accounted for by atherosclerotic cardiovascular disease risk scoring. Precision prevention to reduce atherosclerotic cardiovascular disease risk will ideally integrate the totality of clinical, psychosocial, environmental, and genetic determinants into actionable metrics that can improve personalized evaluation and treatment and can be tracked over time.
Coronary Computed Tomography Angiography
National Institute for Health and Care Excellence (NICE). NICE Guidance for Stable Chest Pain Patients (CG95 & MTG32) to Appropriately Diagnose Patients with Suspected Coronary Artery Disease. Available at: https://www.nice.org.uk/sharedlearning/nice-guidance-for-stable-chest-pain-patients-cg95-mtg32-to-appropriately-diagnose-patients-with-suspected-coronary-artery. Accessed October 27, 2022.
Coronary CTA for Atherosclerosis Burden and Type

Coronary CTA for Atherosclerosis Progression
Intervention | Study Design | Follow-Up Serial CCTA | CCTA Atherosclerosis | Results |
---|---|---|---|---|
Statins | • Multicenter observational cohort | • ≥2 y | • Annualized plaque volume △ • Annualized plaque volume △ by composition | • Statins associated with lower rate of plaque progression • Statins associated with higher rate of calcified plaque formation, lower rate of non-calcified plaque formation |
Icosapent ethyl | • RCT | • 18 mo | • LD-NCP volume | • Icosapent ethyl reduced LD-NCP volume compared with placebo |
Evolocumab | • Single center, retrospective | • 6 mo | • Stability and size of plaques at 6 months | • Evolocumab increased CT density of plaques • Evolocumab decreased % stenosis |
Colchicine | • Single center, prospective | • 12.6 mo | • LD-NCP volume | • Colchicine reduced LD-NCP |
DASH diet + physical activity | • RCT | • 15.4 mo | • △ in percent atheroma volume and plaque composition | • Diet + activity slowed the progression of atherosclerosis • Diet + activity reduced non-calcified plaque |
Rationale and Aim of the Atherosclerosis Treatment Algorithms
- 1.Advanced imaging for disease visualization;
- 2.Staging by presence (tumor), extent (lymph nodes), and severity (metastasis);
- 3.Classification of type of cancer;
- 4.Personalization of treatment to an individual's actual disease characteristics, and;
- 5.Repeat advanced imaging to assess therapeutic response.
Defining Severity of Coronary Atherosclerosis by Coronary CTA
- Stuijfzand WJ
- van Rosendael AR
- Lin FY
- et al.
- Stuijfzand WJ
- van Rosendael AR
- Lin FY
- et al.
Stage of Atherosclerosis | Angiographic Stenosis Severity | Total Plaque Volume (mm3) | Percent Atheroma Volume (%) |
---|---|---|---|
None | No stenosis | 0 | 0% |
Stage 1 | 1%-49% stenosis 1-vessel CAD >50% stenosis | >0 to 250 | >0%-5.0% |
Stage 2 | 2-vessel CAD >50% stenosis | >250 to 750 | >5%-15.0% |
Stage 3 | 3-vessel CAD >50% stenosis | >750 | >15.0% |

- Stuijfzand WJ
- van Rosendael AR
- Lin FY
- et al.
- •Stage 0 = 0 mm3 (0% percent atheroma volume);
- •Stage 1 = >0-250 mm3 (>0-5.0% percent atheroma volume);
- •Stage 2 = >250-750 mm3 (>5%-15% percent atheroma volume);
- •Stage 3 = >750 mm3 (>15% percent atheroma volume).
Treating Atherosclerosis Burden and Progression
- •Lipid-lowering agents: (1) PCSK9 inhibitors, (2) Icosapent ethyl, (3) Bempedoic acid, (4) Inclisiran49,53,54,55,56
- •Antithrombotic agents: (5) Rivaroxaban57
- •Anti-inflammatory agents: (6) Colchicine58
- •Novel anti-atherosclerotic diabetic agents: (7) Glucagon-like peptide (GLP)-1 receptor agonists, and (8) Sodium-glucose transport protein 2 (SGLT2) inhibitors59,60,61,62,63,64,65,66,67,68
Atherosclerosis Treatment Algorithms
Stage | Treatment | Serial CCTA |
---|---|---|
Stage 0 | • GDMT/Shared decision for de-escalation of therapy | 4 years |
Stage 1 | • Statin: (rosuvastatin 10-20 mg QD/atorvastatin 20-40 mg QD) • Ezetimibe 10 mg QD | 3 years |
Stage 2 | • High-intensity statin (rosuvastatin 40 mg QD/atorvastatin 80 mg QD) • Ezetimibe 10 mg QD • Aspirin 81-100 mg QD • Rivaroxaban 2.5 mg BID If diabetic, GLP-1 receptor agonist | 2 years |
Stage 3 | • High-intensity statin (rosuvastatin 40 mg QD/atorvastatin 80 mg QD) • Ezetimibe 10 mg QD • ASA 81-100 mg QD • Rivaroxaban 2.5 mg BID • Other lipid-lowering medications: PCSK-9 inhibitors, icosapent ethyl, inclisiran, bempedoic acid • Colchicine 0.6 mg QD • Cardiac rehabilitation or other supervised exercise program (if covered) If diabetic: GLP-1 receptor agonist and SGLT2 inhibitor | 1 year |
Medication | Eligibility Criteria | Study Size | Duration | Primary Endpoint | Results | Relative Risk Reduction | Ref |
---|---|---|---|---|---|---|---|
Lipid-lowering medications | |||||||
Bempedoic acid | ASCVD (clinically significant CHD by imaging), heterozygous FH or both; LDL ≥70 mg/dL | 2230 | 52 wk | LDL lowering | 16.5% lower LDL | N/A | 45 |
Evolocumab | 40-85 y, clinical ASCVD; ≥70 mg/dL LDL or non-HDL 100 mg/dL; on ≥20 mg atorvastatin | 27,564 | 2.2 y | CV death, MI, stroke, UA, TVR | 9.8% vs 11.3%, HR 0.85 | 15% | 46
Age- and sex-related differences in all-cause mortality risk based on coronary computed tomography angiography findings results from the International Multicenter CONFIRM (Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter Registry) of 23,854 patients without known coronary artery disease. J Am Coll Cardiol. 2011; 58: 849-860 |
Alirocumab | >40, h/o ACS 1-2 mo prior to randomization, LDL ≥70 mg/dL, non-HDL ≥100 mg/dL, or apolipoprotein B ≥80 mg, on statin | 18,924 | 2.8 y | CHD death, MI, stroke, UA | 9.5% vs 11.1% | 15% | 47 |
Isocapent ethyl | >45 y w/ established CVD or >50 y w/ DM + 1 RF, TG≥135 mg/dl and LDL 41-100 mg/dl | 8179 | 4.9 y | CV death, MI, stroke, revasc, UA | 17.2% vs 22.0% | 25% | 48 |
Inclisiran | Adults w/ h/o ASCVD (CHD, CVD, or PAD) or ASCVD-risk equivalent (T2DM, familial hypercholesterolemia) and 10-y FRS risk w/ target LDL <100 mg/dL; LDL ≥70 mg/dL or ≥100 mg/dL for ASCVD-risk equivalent | 3178 | 510 d | % change LDL at 510 d; and time-adjusted % change LDL 90-540 d | ∼50% lower LDL and time-adjusted LDL | N/A | 50 |
Antithrombotic medications | |||||||
Rivaroxaban | >65 w/ CAD or <65 w/ atherosclerosis in ≥2 vascular beds or ≥2 RFs | 27,395 | 1.9 y | CV death, stroke, MI | 17.2% vs 22.0% | 25% | 51 |
Anti-inflammatory medications | |||||||
Colchicine | Age >35 and ≤82 y; proven CAD by CCTA or CACS >400 or h/o CABG >10 y prior, or angiographic evidence of graft failure or PCI after CABG | 5522 | 28.6 mo | CV death, MI, ischemic stroke or ischemia-driven revascularization | 6.8% vs 9.6% | 31% | 52 |
SGLT2 inhibitors | |||||||
Empagliflozin | Type 2 diabetes w/ BMI <40 and eGFR >30 w/ CVD (≥2 vessels w/ 50% stenosis or 1 vessel 50% stenosis and ischemia) | 7020 | 3.1 y | CV death, MI, stroke | 10.5% vs 12.1% | 14% | 58 |
Dapagliflozin | >40 y/o, type 2 diabetes; HgbA1C >6.5%; CrCl >60; multiple risk factors for ASCVD | 17,160 | 4.2 y | CV death, MI, stroke, heart failure | 8.8% vs 9.4% | None | 59 |
Canagliflozin | Type 2 diabetes + ASCVD (>30 y) or ≥2 risk factors (>50 y), eGFR >30 | 10,142 | 2.4 y | CV death, MI, stroke | 26.9 vs 31.5 participants / 1000 pt-years | 14% | 60 |
GLP-1 receptor agonists | |||||||
Semaglutide | T2DM + HgbA1C >7%; >50 w/ ASCVD or >60 w/ 1 CV RF | 2735 | 2 y | CV death, MI, stroke | 6.6% vs 8.9% | 26% | 53 |
Exenatide | Type 2 diabetes w/ h/o ASCVD events (70%) or not (30%) | 14,752 | 3.2 y | CV death, MI, stroke | 11.4% vs 12.2% | None | 55 ,56 |
Liraglutide | Type 2 diabetes, HgbA1C >7.0%; >50 years w/ ASCVD; >60 years w/ >1 CV RF | 9340 | 3.8 y | CV death, MI, stroke | 13.0% vs 14.9% | 13% | 54 |
Dulaglutide | Type 2 diabetes; >50 w/ prior CV event or CV risk factors | 9901 | 5.4 y | CV death, MI, stroke | 12.0%vs 13.4% | 12% | 57 |
Lixisenatide | Type 2 diabetes w/ prior MI or UA hospitalization | 6068 | 25 mo | CV death, MI, stroke, UA | 13.4% vs 13.2% | N/A | 62 |






- •Atherosclerosis Treatment Algorithms emphasize patient-based, rather than lesion-based, measures of atherosclerosis burden and progression. We advocate the concept of assessing the “vulnerable patient” over that of the “vulnerable plaque.” In part, this may be due to the dynamism of atherosclerosis and morphologic changes over time that contribute to the likelihood of any given plaque to become culprit in future acute coronary syndrome.70,71The authors' current thinking is that morphologic quantitative assessment of plaques alone is inadequate to precisely pinpoint lesions at risk of becoming culprit, and that significant contributors to major adverse cardiovascular events risk beyond atherosclerosis itself—such as inflammation and thrombosis—will improve predictive precision.
- •Atherosclerosis Treatment Algorithms highlight total atherosclerosis burden rather than focusing on a specific plaque composition. The preponderance of prognostic data has emphasized overall atherosclerotic burden for risk stratification.27,28,29,31,42As future studies are performed examining the differential prognostic utility of atherosclerotic plaques by compositional phenotype, the Atherosclerosis Treatment Algorithms may be updated accordingly to account for not only atherosclerosis stage, but also classification of phenotypic disease type.
- •Atherosclerosis Treatment Algorithms do not incorporate advanced atherosclerosis markers of risk by coronary CTA (eg, high-risk plaques). Several high-risk features have been observed by coronary CTA to be predictive of future major adverse cardiovascular events, including low-density non-calcified plaque, positive remodeling, and others.32We elected not to include these Atherosclerosis Treatment Algorithms for reasons of simplicity, and to offer a single integrated metric (percent atheroma volume) that represents a patient's total atherosclerotic burden.47
- •Atherosclerosis Treatment Algorithms propose longitudinal coronary CTA-based evaluation commensurate to the burden of disease. Given that baseline plaque burden is the strongest predictor of plaque progression, we reasoned that those with higher atherosclerotic burden should undergo re-evaluation after therapeutic initiation at a shorter inter-scan interval than individuals with lesser amounts of disease. A 4-3-2-1-year inter-scan interval for repeat coronary CTA was considered reasonable for patients with Stage 0, 1, 2, and 3 atherosclerosis, respectively.
Future Outlook
- •Atherosclerotic Plaque Composition. Given the continuum of prognosis that has been observed across the continuum of Hounsfield unit gray scale (ie, lower-density = greater risk, higher density = lower risk), incorporating continuous measures of plaque compositions may improve understanding of patient- and plaque-level risk.31
- •Additional Atherosclerosis Features. In addition to measures of high-risk plaque—such as low-density non-calcified plaque and positive remodeling—several other atherosclerosis and vascular morphology features have been demonstrated to impart prognostic importance.32These include plaque location, diffuseness, geometry, vessel and lumen volume; and may accentuate evaluation of those undergoing coronary CTA .
Economic Implications of a Personalized Approach to Coronary Artery Disease Diagnosis
- Caparrotta TM
- Blackbourn LAK
- McGurnaghan SJ
- et al.
- Min JK
- Dunning A
- Lin FY
- et al.
Conclusion
Supplementary Data
References
- Framingham Heart Study: JACC Focus Seminar, 1/8.J Am Coll Cardiol. 2021; 77: 2680-2692
- 2019 ACC/AHA Guideline on the Primary Prevention of Cardiovascular Disease: Executive Summary: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines.J Am Coll Cardiol. 2019; 74: 1376-1414
American College of Cardiology. ASCVD Risk Estimator Plus. Available at: https://tools.acc.org/ascvd-risk-estimator-plus/#!/calculate/estimate/. Accessed October 27, 2022.
- Heart Disease and Stroke Statistics–2021 Update: a report from the American Heart Association.Circulation. 2021; 143: e254-e743
- Lipid levels in patients hospitalized with coronary artery disease: an analysis of 136,905 hospitalizations in Get With The Guidelines.Am Heart J. 2009; 157 (111-117 e2)
- Lipids, risk factors and ischaemic heart disease.Atherosclerosis. 1996; 124: S1-S9
- Evaluation of the pooled cohort risk equations for cardiovascular risk prediction in a multiethnic cohort from the Women's Health Initiative.JAMA Intern Med. 2018; 178: 1231-1240
- Preventing myocardial infarction in the young adult in the first place: how do the National Cholesterol Education Panel III guidelines perform?.J Am Coll Cardiol. 2003; 41: 1475-1479
- Mortality from coronary heart disease in subjects with type 2 diabetes and in nondiabetic subjects with and without prior myocardial infarction.N Engl J Med. 1998; 339: 229-234
- Effect of screening for coronary artery disease using CT angiography on mortality and cardiac events in high-risk patients with diabetes: the FACTOR-64 randomized clinical trial.JAMA. 2014; 312: 2234-2243
- The forgotten majority: unfinished business in cardiovascular risk reduction.J Am Coll Cardiol. 2005; 46: 1225-1228
- Panomics: new databases for advancing cardiology.Front Cardiovasc Med. 2021; 8587768
- Finding the gatekeeper to the cardiac catheterization laboratory: coronary CT angiography or stress testing?.J Am Coll Cardiol. 2015; 65: 2747-2756
- The sub-millisievert era in CTCA: the technical basis of the new radiation dose approach.Radiol Med. 2020; 125: 1024-1039
- Coronary CT angiography and 5-year risk of myocardial infarction.N Engl J Med. 2018; 379: 924-933
- Anatomical versus functional testing for coronary artery disease.N Engl J Med. 2015; 373: 91
- Coronary CTA in the evaluation of stable chest pain: clear benefits, but not for all.J Am Coll Cardiol. 2017; 69: 1771-1773
- 2019 ESC Guidelines for the diagnosis and management of chronic coronary syndromes.Eur Heart J. 2020; 41: 407-477
National Institute for Health and Care Excellence (NICE). NICE Guidance for Stable Chest Pain Patients (CG95 & MTG32) to Appropriately Diagnose Patients with Suspected Coronary Artery Disease. Available at: https://www.nice.org.uk/sharedlearning/nice-guidance-for-stable-chest-pain-patients-cg95-mtg32-to-appropriately-diagnose-patients-with-suspected-coronary-artery. Accessed October 27, 2022.
Saleh M, Ambrose JA. Understanding myocardial infarction. F1000Res. 2018;7:F1000 Faculty Rev-1378. Ecollection 2018. doi:10.12688/f1000research.15096.1.
- Coronary computed tomographyangiography versus intravascular ultrasound for estimation of coronary stenosis and atherosclerotic plaque burden: a meta-analysis.J Cardiovasc Comput Tomogr. 2013; 7: 256-266
- Automatic quantification and characterization of coronary atherosclerosis with computed tomography coronary angiography: cross-correlation with intravascular ultrasound virtual histology.Int J Cardiovasc Imaging. 2013; 29: 1177-1190
- Plaque type and composition as evaluated non-invasively by MSCT angiography and invasively by VH IVUS in relation to the degree of stenosis.Heart. 2009; 95: 1990-1996
- Optimized prognostic score for coronary computed tomographic angiography: results from the CONFIRM registry (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter Registry).J Am Coll Cardiol. 2013; 62: 468-476
- The multidimensionality of coronary artery disease: combining, conflating, and changing.JACC Asia. 2021; 1: 49-52
- Prognostic implications of comprehensive whole vessel plaque quantification using coronary computed tomography angiography.JACC Asia. 2021; 1: 37-48
- Coronary atherosclerotic precursors of acute coronary syndromes.J Am Coll Cardiol. 2018; 71: 2511-2522
- Use of high-risk coronary atherosclerotic plaque detection for risk stratification of patients with stable chest pain: a secondary analysis of the PROMISE randomized clinical trial.JAMA Cardiol. 2018; 3: 144-152
- 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).Circulation. 2020; 141: 1452-1462
- Risk stratification with the use of coronary computed tomographic angiography in patients with nonobstructive coronary artery disease.JACC Cardiovasc Imaging. 2021; 14: 2186-2195
- Association of high-density calcified 1K plaque with risk of acute coronary syndrome.JAMA Cardiol. 2020; 5: 282-290
- Coronary computed tomography angiography from clinical uses to emerging technologies: JACC state-of-the-art review.J Am Coll Cardiol. 2020; 76: 1226-1243
- Stress myocardial perfusion imaging vs coronary computed tomographic angiography for diagnosis of invasive vessel-specific coronary physiology: predictive modeling results from the computed tomographic evaluation of atherosclerotic determinants of myocardial ischemia (CREDENCE) trial.JAMA Cardiol. 2020; 5: 1338-1348
- Plaque characterization by coronary computed tomography angiography and the likelihood of acute coronary events in mid-term follow-up.J Am Coll Cardiol. 2015; 66: 337-346
- Effects of statins on coronary atherosclerotic plaques: the PARADIGM study.JACC Cardiovasc Imaging. 2018; 11: 1475-1484
- Progression of whole-heart atherosclerosis by coronary CT and major adverse cardiovascular events.J Cardiovasc Comput Tomogr. 2021; 15: 322-330
- Effect of icosapent ethyl on progression of coronary atherosclerosis in patients with elevated triglycerides on statin therapy: final results of the EVAPORATE trial.Eur Heart J. 2020; 41: 3925-3932
- Effect of icosapent ethyl on progression of coronary atherosclerosis in patients with elevated triglycerides on statin therapy: a prospective, placebo-controlled randomized trial (EVAPORATE): interim results.Cardiovasc Res. 2021; 117: 1070-1077
- Effect of evolocumab on vulnerable coronary plaques: a serial coronary computed tomography angiography study.J Clin Med. 2020; 9: 3338
- High-risk coronary plaque regression after intensive lifestyle intervention in nonobstructive coronary disease: a randomized study.JACC Cardiovasc Imaging. 2021; 14: 1192-1202
- Colchicine therapy and plaque stabilization in patients with acute coronary syndrome: a CT coronary angiography study.JACC Cardiovasc Imaging. 2018; 11: 305-316
- Coronary calcium score and cardiovascular risk.J Am Coll Cardiol. 2018; 72: 434-447
- Breast-cancer screening–viewpoint of the IARC Working Group.N Engl J Med. 2015; 373: 1479
- The IARC perspective on colorectal cancer screening.N Engl J Med. 2018; 378: 1734-1740
- Reduced lung-cancer mortality with low-dose computed tomographic screening.N Engl J Med. 2011; 365: 395-409
- Age- and sex-related differences in all-cause mortality risk based on coronary computed tomography angiography findings results from the International Multicenter CONFIRM (Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter Registry) of 23,854 patients without known coronary artery disease.J Am Coll Cardiol. 2011; 58: 849-860
- Percent atheroma volume: optimal variable to report whole-heart atherosclerotic plaque burden with coronary CTA, the PARADIGM study.J Cardiovasc Comput Tomogr. 2020; 14: 400-406
- The EVAPORATE trial provides important mechanistic data on plaque characteristics that have relevance to the REDUCE-IT results and clinical use of icosapent ethyl.Eur Heart J. 2021; 42: 3025-3026
- Cardiovascular risk reduction with icosapent ethyl for hypertriglyceridemia.N Engl J Med. 2019; 380: 11-22
- A randomized controlled trial of eicosapentaenoic acid in patients with coronary heart disease on statins.J Cardiol. 2017; 70: 537-544
- “Cholesterol-Years” for ASCVD risk prediction and treatment.J Am Coll Cardiol. 2020; 76: 1517-1520
- Targeting cardiovascular inflammation: next steps in clinical translation.Eur Heart J. 2021; 42: 113-131
- Evolocumab in patients with cardiovascular disease.N Engl J Med. 2017; 377: 787-788
- Alirocumab and cardiovascular outcomes after acute coronary syndrome.N Engl J Med. 2018; 379: 2097-2107
- Safety and efficacy of bempedoic acid to reduce LDL cholesterol.N Engl J Med. 2019; 380: 1022-1032
- Two phase 3 trials of inclisiran in patients with elevated LDL cholesterol.N Engl J Med. 2020; 382: 1507-1519
- Rivaroxaban in stable cardiovascular disease.N Engl J Med. 2018; 378: 397-398
- Colchicine in patients with chronic coronary disease.N Engl J Med. 2020; 383: 1838-1847
- Semaglutide and cardiovascular outcomes in patients with type 2 diabetes.N Engl J Med. 2016; 375: 1834-1844
- Liraglutide and cardiovascular outcomes in type 2 diabetes.N Engl J Med. 2016; 375: 311-322
- Once-weekly exenatide and cardiovascular outcomes in type 2 diabetes.N Engl J Med. 2017; 377: 2502
- Effects of once-weekly exenatide on cardiovascular outcomes in type 2 diabetes.N Engl J Med. 2017; 377: 1228-1239
- Dulaglutide and cardiovascular outcomes in type 2 diabetes (REWIND): a double-blind, randomised placebo-controlled trial.Lancet. 2019; 394: 121-130
- Empagliflozin, cardiovascular outcomes, and mortality in type 2 diabetes.N Engl J Med. 2015; 373: 2117-2128
- Dapagliflozin and cardiovascular outcomes in type 2 diabetes.N Engl J Med. 2019; 380: 347-357
- Canagliflozin and cardiovascular and renal events in type 2 diabetes.N Engl J Med. 2017; 377: 644-657
- Sotagliflozin in patients with diabetes and recent worsening heart failure.N Engl J Med. 2021; 384: 117-128
- Lixisenatide in patients with type 2 diabetes and acute coronary syndrome.N Engl J Med. 2015; 373: 2247-2257
- Metabolic surgery: weight loss, diabetes, and beyond.J Am Coll Cardiol. 2018; 71: 670-687
- From subclinical atherosclerosis to plaque progression and acute coronary events: JACC state-of-the-art review.J Am Coll Cardiol. 2019; 74: 1608-1617
- Coronary artery calcification and its progression: what does it really mean?.JACC Cardiovasc Imaging. 2018; 11: 127-142
- Eligibility, clinical outcomes, and budget impact of PCSK9 inhibitor adoption: the CANHEART PCSK9 study.J Am Heart Assoc. 2018; 7e010007
- National trends in statin use and ein the US adult population from 2002 to 2013: insights from the Medical Expenditure Panel Survey.JAMA Cardiol. 2017; 2: 56-65
- LDL cholesterol response to statins and future risk of cardiovascular disease.Heart. 2019; 105: 1290-1291
- Prescribing paradigm shift? Applying the 2019 European Society of Cardiology-led guidelines on diabetes, prediabetes, and cardiovascular disease to assess eligibility for sodium-glucose cotransporter 2 inhibitors or glucagon-like peptide 1 receptor agonists as first-line monotherapy (or add-on to metformin monotherapy) in type 2 diabetes in Scotland.Diabetes Care. 2020; 43: 2034-2041
- What does it cost physician practices to interact with health insurance plans?.Health Aff (Millwood). 2009; 28: w533-w543
Min JK, Chang HJ, Andreini D, et al. Coronary CTA plaque volume severity stages according to invasive coronary angiography and FFR. J Cardiovasc Comput Tomogr. 2022;16(5):415–422.
Article info
Publication history
Footnotes
Funding: None.
Conflicts of Interest: DLB discloses the following relationships—Advisory Board: Cardax, CellProthera, Cereno Scientific, Elsevier Practice Update Cardiology, Janssen, Level Ex, Medscape Cardiology, MyoKardia, Novo Nordisk, PhaseBio, PLx Pharma, Regado Biosciences; Boston VA Research Institute: Bristol Myers Squibb, Board of Directors, Society of Cardiovascular Patient Care, TobeSoft; Chair: American Heart Association Quality Oversight Committee; Data Monitoring Committees: Baim Institute for Clinical Research (formerly Harvard Clinical Research Institute, for the PORTICO trial, funded by St. Jude Medical, now Abbott), Cleveland Clinic (including for the ExCEED trial, funded by Edwards), Contego Medical (Chair, PERFORMANCE 2), Duke Clinical Research Institute, Mayo Clinic, Mount Sinai School of Medicine (for the ENVISAGE trial, funded by Daiichi Sankyo), Population Health Research Institute; Honoraria: American College of Cardiology (Senior Associate Editor, Clinical Trials and News, ACC.org; Vice-Chair, ACC Accreditation Committee), Baim Institute for Clinical Research (formerly Harvard Clinical Research Institute; RE-DUAL PCI clinical trial steering committee funded by Boehringer Ingelheim; AEGIS-II executive committee funded by CSL Behring), Belvoir Publications (Editor in Chief, Harvard Heart Letter), Canadian Medical and Surgical Knowledge Translation Research Group (clinical trial steering committees), Duke Clinical Research Institute (clinical trial steering committees, including for the PRONOUNCE trial, funded by Ferring Pharmaceuticals), HMP Global (Editor in Chief, Journal of Invasive Cardiology), Journal of the American College of Cardiology (Guest Editor; Associate Editor), K2P (Co-Chair, interdisciplinary curriculum), Level Ex, Medtelligence/ReachMD (CME steering committees), MJH Life Sciences, Population Health Research Institute (for the COMPASS operations committee, publications committee, steering committee, and USA national co-leader, funded by Bayer), Slack Publications (Chief Medical Editor, Cardiology Today's Intervention), Society of Cardiovascular Patient Care (Secretary/Treasurer), WebMD (CME steering committees); Other: Clinical Cardiology (Deputy Editor), NCDR-ACTION Registry Steering Committee (Chair), VA CART Research and Publications Committee (Chair); Abbott, Afimmune, Amarin, Amgen, AstraZeneca, Bayer, Boehringer Ingelheim, Bristol-Myers Squibb, Cardax, CellProthera, Cereno Scientific, Chiesi: Cleerly, Research Funding, CSL Behring, Eisai, Ethicon, Ferring Pharmaceuticals, Forest Laboratories, Fractyl, Garmin, HLS Therapeutics, Idorsia, Ironwood, Ischemix, Janssen, Lexicon, Lilly, Medtronic, MyoKardia, Novartis, Novo Nordisk, Owkin, Pfizer, PhaseBio, PLx Pharma, Regeneron, Roche, Sanofi, Synaptic, The Medicines Company, 89Bio; Royalties: Elsevier (Editor, Cardiovascular Intervention: A Companion to Braunwald's Heart Disease); Site Co-Investigator: Abbott, Biotronik, Boston Scientific, CSI, St. Jude Medical (now Abbott), Svelte; Trustee: American College of Cardiology; Unfunded Research: FlowCo, Merck, Takeda.
JKM discloses the following relationships: Cleerly (employment and equity interest); Arineta (advisory board); National Institutes of Health (grant funding).
AMF discloses the following relationships: Non-promotional speaking for Boehringer-Ingelheim, Consulting for Medtronic.
MA discloses: She receives honoraria for speaking and royalties from books. She conducts research with Flourish, Inc and through this, she is the primary investigator for a study with IQVIA.
JPE discloses: Employed by Cleerly; Equity Holding in Cleerly.
Authorship: All authors contributed through data collection, collation, manuscript writing, manuscript editing, and figure creation.