==== Front JAMA Netw Open JAMA Netw Open JAMA Netw Open JAMA Network Open 2574-3805 American Medical Association 33315111 10.1001/jamanetworkopen.2020.28312 zoi200904 Research Original Investigation Online Only Health Policy Cost-effectiveness Analysis of Anatomic vs Functional Index Testing in Patients With Low-Risk Stable Chest Pain Cost-effectiveness of Anatomic vs Functional Index Testing in Patients With Low-Risk Stable Chest PainCost-effectiveness of Anatomic vs Functional Index Testing in Patients With Low-Risk Stable Chest PainKarády Júlia MD12 Mayrhofer Thomas PhD13 Ivanov Alexander BS1 Foldyna Borek MD1 Lu Michael T. MDMPH1 Ferencik Maros MDPhDMCR14 Pursnani Amit MD5 Salerno Michael MDPhDMS6 Udelson James E. MD7 Mark Daniel B. MDMPH89 Douglas Pamela S. MD89 Hoffmann Udo MDMPH1 1 Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, Boston 2 MTA-SE Cardiovascular Imaging Research Group, Heart and Vascular Center, Semmelweis University, Budapest, Hungary 3 School of Business Studies, Stralsund University of Applied Sciences, Stralsund, Germany 4 Knight Cardiovascular Institute, Oregon Health and Science University, Portland 5 Cardiology Division, Evanston Hospital, Evanston, Illinois 6 Departments of Medicine and Radiology, University of Virginia Health System, Charlottesville 7 Division of Cardiology, Tufts Medical Center, Boston, Massachusetts 8 Duke Clinical Research Institute, Duke University School of Medicine, Durham, North Carolina 9 Division of Cardiology, Department of Medicine, Duke University School of Medicine, Durham, North Carolina Article Information Accepted for Publication: October 8, 2020. Published: December 14, 2020. doi:10.1001/jamanetworkopen.2020.28312 Open Access: This is an open access article distributed under the terms of the CC-BY License. © 2020 Karády J et al. JAMA Network Open. Corresponding Author: Udo Hoffmann, MD, MPH, Cardiovascular Imaging Research Center, Massachusetts General Hospital, Harvard Medical School, 165 Cambridge St, Ste 400, Boston, MA 02114 (uhoffmann@mgh.harvard.edu).Author Contributions: Drs Mayrhofer and Hoffmann had full access to all of the data in the study and take responsibility for the integrity of the data and the accuracy of the data analysis. Drs Karády and Mayrhofer contributed equally to this manuscript. Concept and design: Mayrhofer, Ferencik, Pursnani, Udelson, Hoffmann. Acquisition, analysis, or interpretation of data: Karády, Mayrhofer, Ivanov, Foldyna, Lu, Ferencik, Pursnani, Salerno, Mark, Douglas, Hoffmann. Drafting of the manuscript: Karády, Mayrhofer, Foldyna, Hoffmann. Critical revision of the manuscript for important intellectual content: All authors. Statistical analysis: Mayrhofer, Foldyna. Obtained funding: Mark, Douglas, Hoffmann. Administrative, technical, or material support: Mayrhofer, Ivanov, Foldyna, Lu, Ferencik, Douglas, Hoffmann. Supervision: Udelson, Hoffmann. Conflict of Interest Disclosures: Dr Karády reported receiving the Fulbright Visiting Researcher Grant and grants from Rosztoczy Foundation outside the submitted work. Dr Mayrhofer reported receiving grants from HeartFlow Inc and grants from the National Heart, Lung, and Blood Institute during the conduct of the study. Dr Foldyna reported receiving grants from the National Heart, Lung, and Blood Institute outside the submitted work. Dr Lu reported receiving grants from the American Heart Association Precision Medicine Institute, the Harvard University Center for AIDS Research, and the Nvidia Corporation Academic Program outside the submitted work. Dr Ferencik reported receiving grants from the American Heart Association during the conduct of the study and receiving grants from the National Institutes of Health and the American Heart Association as well as receiving consulting fees from Biograph outside the submitted work. Dr Pursnani reported receiving grants from the National Heart, Lung, and Blood Institute outside the submitted work. Dr Salerno reported receiving grants from the National Institutes of Health and nonfinancial support in the form of support code from Siemens Healthineers and use of a clinical trial site from Heart Flow outside the submitted work. Dr Udelson reported receiving grants from Heartflow during the conduct of the study as well as receiving grants from Lantheus Medical Imaging, Abbott Laboratories, and the National Heart, Lung, and Blood Institute and participating in clinical trial committee work for Pfizer/GlaxoSmithKline and HeartFlow outside the submitted work. Dr Mark reported receiving grants from the National Institutes of Health during the conduct of the study and receiving grants from Merck, HeartFlow, Eli Lilly and Co, Bristol-Myers Squibb, Gilead Sciences, AGA Medical, Oxygen Biotherapeutics, and AstraZeneca outside the submitted work; and receiving personal fees from Medtronic, CardioDx, and St Jude Medical outside the submitted work. Dr Douglas reported receiving grants from HeartFlow during the conduct of the study. Dr Hoffmann reported receiving grants from Heartflow during the conduct of the study as well as receiving personal fees from Duke University, Abbott, and Recor Medical and receiving grants from KOWA, Medimmune, AstraZeneca, Oregon Health and Science University, Columbia University, the National Heart, Lung, and Blood Institute, and Duke University outside the submitted work. No other disclosures were reported. Funding/Support: The original Prospective Multicenter Imaging Study for Evaluation of Chest Pain trial was supported by National Heart, Lung, and Blood Institute grants R01HL098237, R01HL098236, R01HL98305, and R01HL098235. This study was funded by HeartFlow. Role of the Funder/Sponsor: The funder had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication. Disclaimer: This article does not necessarily represent the official views of the National Heart, Lung, and Blood Institute. 14 12 2020 12 2020 14 12 2020 3 12 e202831214 4 2020 8 10 2020 Copyright 2020 Karády J et al. JAMA Network Open.This is an open access article distributed under the terms of the CC-BY License.jamanetwopen-e2028312.pdfKey Points Question Are first-line anatomic approaches to low-risk stable chest pain evaluation cost-effective compared with functional testing? Findings In this cost-effectiveness analysis using an individual-based Markov microsimulation model based on 10 003 participants in a randomized clinical trial, anatomic approaches were cost-effective compared with functional testing across a wide range of variations in clinical care and patient characteristics. Adding fractional flow reserve to coronary computed tomography angiography resulted in modest improvements after the initially increased costs of care were offset by fewer and more targeted coronary revascularizations. Meaning These findings suggest that anatomic strategies may present a favorable initial diagnostic option in the evaluation of low-risk stable chest pain compared with functional testing. This economic evaluation determines whether anatomic approaches are cost-effective compared with functional tests for the assessment of low-risk stable chest pain. Importance Both noninvasive anatomic and functional testing strategies are now routinely used as initial workup in patients with low-risk stable chest pain (SCP). Objective To determine whether anatomic approaches (ie, coronary computed tomography angiography [CTA] and coronary CTA supplemented with noninvasive fractional flow reserve [FFRCT], performed in patients with 30% to 69% stenosis) are cost-effective compared with functional testing for the assessment of low-risk SCP. Design, Setting, and Participants This cost-effectiveness analysis used an individual-based Markov microsimulation model for low-risk SCP. The model was developed using patient data from the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) trial. The model was validated by comparing model outcomes with outcomes observed in the PROMISE trial for anatomic (coronary CTA) and functional (stress testing) strategies, including diagnostic test results, referral to invasive coronary angiography (ICA), coronary revascularization, incident major adverse cardiovascular event (MACE), and costs during 60 days and 2 years. The validated model was used to determine whether anatomic approaches are cost-effective over a lifetime compared with functional testing. Exposure Choice of index test for evaluation of low-risk SCP. Main Outcomes and Measures Downstream ICA and coronary revascularization, MACE (death, nonfatal myocardial infarction), cost, quality-adjusted life-years (QALYs), and incremental cost-effectiveness ratio (ICER) of competing strategies. Results The model cohort included 10 003 individual patients (median [interquartile range] age, 60.0 [54.4-65.9] years; 5270 [52.7%] women; 7693 [77.4%] White individuals), who entered the model 100 times. The Markov model accurately estimated the test assignment, results of anatomic and functional index testing, referral to ICA, revascularization, MACE, and costs at 60 days and 2 years compared with observed data in PROMISE (eg, coronary CTA: ICA, 12.2% [95% CI, 10.9%-13.5%] vs 12.3% [95% CI, 12.2%-12.4%]; revascularization, 6.2% [95% CI, 5.5%-6.9%] vs 6.4% [95% CI, 6.3%-6.5%]; functional strategy: ICA, 8.1% [95% CI, 7.4%-8.9%] vs 8.2% [95% CI, 8.1%-8.3%]; revascularization, 3.2% [95% CI, 2.7%-3.7%] vs 3.3% [95% CI, 3.2%-3.4%]; 2-year MACE rates: coronary CTA, 2.1% [95% CI, 1.7%-2.5%] vs 2.3% [95% CI, 2.2%-2.4%]; functional strategy, 2.2% [95% CI, 1.8%-2.6%] vs 2.4% [95% CI, 2.3%-2.4%]). Anatomic approaches led to higher ICA and revascularization rates at 60 days, 2 years, and 5 years compared with functional testing but were more effective in patient selection for ICA (eg, 60-day revascularization-to-ICA ratio, CTA: 53.7% [95% CI, 53.3%-54.0%]; CTA with FFRCT: 59.5% [95% CI, 59.2%-59.8%]; functional testing: 40.7% [95% CI, 40.4%-50.0%]). Over a lifetime, anatomic approaches gained an additional 6 months in perfect health compared with functional testing (CTA, 25.16 [95% CI, 25.14-25.19] QALYs; CTA with FFRCT, 25.14 [95% CI, 25.12-25.17] QALYs; functional testing, 24.68 [95% CI, 24.66-24.70] QALYs). Anatomic strategies were less costly and more effective; thus, CTA with FFRCT dominated and CTA alone was cost-effective (ICERs ranged from $1912/QALY for women and $3,559/QALY for men) compared with functional testing. In probabilistic sensitivity analyses, anatomic approaches were cost-effective in more than 65% of scenarios, assuming a willingness-to-pay threshold of $100 000/QALY. Conclusions and Relevance The results of this study suggest that anatomic strategies may present a more favorable initial diagnostic option in the evaluation of low-risk SCP compared with functional testing. ==== Body Introduction Annually, more than 8.7 million patients undergo noninvasive diagnostic testing for suspected coronary artery disease (CAD) at an expense of $15 billion in the United States.1 Nearly all of these tests target functional assessment of myocardial ischemia (64%, nuclear imaging with single photon emission computed tomography [SPECT]; 31%, stress echocardiography).2,3 However, the positive predictive value of these tests for anatomically obstructive CAD in patients referred to invasive coronary angiography (ICA) remains low (38%).4 Meanwhile, coronary computed tomography angiography (CTA), a test permitting noninvasive visualization of CAD, is currently performed in less than 5% of chest pain evaluations. Randomized comparisons between functional and anatomic index testing in low-risk stable chest pain (SCP) (ie, the Prospective Multicenter Imaging Study for Evaluation of Chest Pain [PROMISE]5 and the Scottish Computed Tomography of the Heart [SCOT-HEART]6 trials), have had mixed results. The PROMISE trial5 reported no differences between anatomic and functional evaluation strategies in SCP for incident major adverse cardiovascular events (MACE) after 2 years, while the SCOT-HEART study6 showed a 41% reduction in nonfatal myocardial infarction (MI) for patients randomized to coronary CTA compared with functional testing after 5 years. In addition, both trials reported higher referral rates to invasive coronary angiography (ICA) and subsequent revascularization after 2 years, with SCOT-HEART reporting similar ICA and revascularizations rates between the 2 strategies after 5 years.5,7 Based on these data, the 2019 European Guidelines for the evaluation of patients with SCP8 increased the level of recommendation for coronary CTA to I class B. Recent data support adding fractional flow reserve based on standard resting coronary CTA (FFRCT) in patients with intermediate stenosis (ie, 30%-69%), given that it leads to a 2-fold increase in specificity over anatomic assessment with coronary CTA alone (74% vs 34%) compared with the criterion standard, invasive FFR.9 To clarify the potential long-term health and economic implications of initial anatomic and functional diagnostic approaches to patients with low-risk SCP, we developed a Markov microsimulation model based on individual patient-level data from the PROMISE trial. Methods Model Overview We developed a Markov microsimulation model using individual patient data from the PROMISE trial5 for the following 3 strategies: coronary CTA, coronary CTA with FFRCT, and functional testing. Each patient entered the model 100 times with a health state defined by their underlying CAD status (ie, no CAD, nonobstructive CAD, or obstructive CAD) and underwent different life cycles and disease progression based on probabilities. The likelihood of positive test results, referral to ICA and subsequent revascularization, statin therapy, and related benefits that translated into different risk of MACE were simulated based on the initial correct diagnosis of CAD and CAD progression. The model was validated by comparing model outcomes with outcomes observed in PROMISE. The validated model was used to simulate short-term, mid-term, and long-term health and economic outcomes and cost-effectiveness over a lifetime (Figure 1). The PROMISE trial was accepted by local or central institutional review boards, and all participants provided written informed consent. We applied good modeling practices as suggested by the ISPOR-SMDM modeling task force,10 including calibration to observed data, using approaches developed in prior work and following consensus guidelines, such as the Consolidated Health Economic Evaluation Reporting Standards (CHEERS) reporting guideline.11,12,13,14,15 Figure 1. Individual-Based Markov Microsimulation Model Overview and Lifetime Outcomes Baseline population characteristics, risk factors, and underlying true coronary artery disease (CAD) status was observed in the Prospective Multicenter Imaging Study for Evaluation of Chest Pain (PROMISE) study,5 whereas diagnostic test accuracy, baseline rules for further testing and interventions, major adverse cardiovascular event (MACE) risk associated with the underlying CAD status, treatment effects, and cost of care were taken from the literature. After simulation of the 60-day and 2-year functional testing and coronary computed tomography angiography (CTA) results, model accuracy was validated by comparing model simulated with observed patient management, health outcomes, and costs. Next, simulation of short-term and long-term outcomes of the model population after undergoing the index tests (coronary CTA, functional testing, or CTA with fractional flow reserve based on standard resting CTA [FFRCT]) by modeling health states (no CAD, nonobstructive CAD, or obstructive CAD) and transitions within in monthly cycles until end of life. Model outcomes were downstream diagnostic testing and revascularization rate in the short term; revascularization, health outcomes, and cost during 2 and 5 years; and cost-effectiveness over lifetime. CV indicates cardiovascular; MI, myocardial infarction. This cost-effective analysis is based on individual patient-level demographic characteristics and risk factors from 10 003 real-life US patients from 192 US sites presenting with suspicion of obstructive CAD. This population was represented 100 times in the model baseline population, allowing us to model the course of life for each participant with 100 variations, considering many different scenarios based on the probability for a medical action or an event to occur. Model Input Parameters Patient Demographic Characteristics, Cardiovascular Risk Profile, Index Testing, and CAD Status Baseline patient demographic characteristics, cardiovascular (CV) risk profiles, and CAD status were taken from patient-level data of the 10 003 patients enrolled in the PROMISE trial.5 The true underlying CAD status was determined by using expert core laboratory test readings as the criterion standard. The CAD finding of each index test at baseline was derived based on the diagnostic accuracy, as recommended by the European Society of Cardiology (ESC) Guidelines (eTable 1 in the Supplement).16 Because PROMISE was a randomized trial, input of distribution of presence and extent of CAD was similar for patients randomized to anatomic and functional testing groups (eAppendix in the Supplement). Downstream Testing ICA was indicated in 3 cases. They were (1) large territory of reversible myocardial ischemia by functional testing; (2) 70% luminal stenosis in at least 1 vessel or 50% luminal narrowing in the left main (LM) coronary artery by coronary CTA, and (3) a hemodynamically significant stenosis with an FFRCT of 0.8 or less in patients with at least 1 luminal stenosis of 30% to 69% (eTable 2 in the Supplement).9,16,17 Medical Treatment Medical treatment, with the exception of statin therapy, was similar for all strategies and defined by the American Heart Association/American College of Cardiology (AHA/ACC) Guidelines for the management of SCP18 and thus did not lead to any differences in health outcomes (eTable 3 in the Supplement). We focused on simulating potential differences in outcomes among the 3 index tests to identify the presence and extent of underlying CAD. Patients with a diagnosis of obstructive or nonobstructive CAD (limited to anatomic strategies) were statin eligible. Statin therapy was further indicated for patients with at least a 7.5% atherosclerotic CV disease (ASCVD) risk score, per SCP guidelines. Based on the JUPITER trial,19 the model assumed that lifelong statin therapy was associated with a 65% risk reduction for MI and 20% risk reduction for CV mortality. For all tests, a missed diagnosis of CAD resulted in loss of benefits of statin therapy. The treatment effect was modeled to reflect differences in hazard ratios between no CAD, nonobstructive CAD, and obstructive CAD.17 Coronary Revascularization Based on the 2014 ACC/AHA Guidelines on the treatment of patients with stable ischemic heart disease, patients with significant LM stenosis (>50%) and those with 3-vessel disease in ICA underwent coronary artery bypass grafting (CABG), whereas patients with 1- or 2-vessel disease underwent percutaneous coronary intervention (PCI).18 The treatment effect was considered similar for optimal medical therapy and coronary revascularization based on the COURAGE trial.20 Health States, CAD Progression, and Health Outcomes Each patient entered the model with a health state defined by their underlying CAD status (ie, no CAD, nonobstructive CAD, obstructive CAD). Progression of CAD was modeled as a function of baseline CAD status, age, sex, and National Cholesterol Education Program risk score from a cohort of patients with SCP using a simulated annealing approach (eAppendix and eFigure 1 in the Supplement).21,22 Patients were simulated to either remain in the same health status (no change in CAD) or to transition from 1 health state to another over time depending on the past (progression of CAD) in monthly cycles until the end of life. Findings of the index diagnostic evaluation (dependent on the diagnostic accuracy of each test) and CV risk profile determined downstream testing, statin therapy, and related benefits. The likelihood of experiencing MACE in each monthly cycle with a given CAD status was modeled based on the CONFIRM registry, and the risk of all-cause death was derived from US life tables (eTable 4 in the Supplement).23,24,25,26,27,28,29,30 The risk of periprocedural mortality during diagnostic ICA, PCI, and CABG was simulated for each invasive procedure.31,32,33,34,35,36,37 Costs of Care Cost of diagnostic tests (coronary CTA, $404; functional testing, $174-$1061; ICA, $3656) and interventions (PCI, $12 779; CABG, $32 546) are expressed in 2014 US dollars and were taken from the PROMISE trial.15 The cost of FFRCT was $1450, per current US Centers for Medicare & Medicaid Services website.38 Cost of medications was based on the 2017 edition of the Red Book (eTable 5 in the Supplement).39 Study End Points This study had 4 end points. They were (1) rates of diagnostic ICA and revascularization-to-ICA ratio at 60 days; (2) rate of coronary revascularization (PCI or CABG) at 60 days, 2 years, 5 years, and over lifetime; (3) MACE (MI, CV mortality), all-cause mortality, and the composite endpoint at 2 years, 5 years, and lifetime; and (4) cost-effectiveness, defined as cost and quality-adjusted life-years (QALYs) at 2 years, 5 years, and over a lifetime, and incremental cost-effectiveness ratio (ICER) and life-years gained over lifetime (eAppendix in the Supplement). ICERs were calculated in accordance with cost-effectiveness analysis guidelines and were expressed as cost per QALY. A strategy was considered cost-effective when the ICER was less than $100 000/QALY.40 A strategy that was both less costly and more effective than another was defined as dominant.11,12,13,14,41 ICER values were based on costs and QALYs that were each discounted at 3% per year, as recommended by the US Panel on Cost-effectiveness in Health and Medicine.42,43 Model Validation: Coronary CTA and Functional Testing in PROMISE The model was validated by comparing model outcomes with real-life events reported in PROMISE, including test results, referral to ICA, coronary revascularization, incident MACE, and costs during 60 days and 2 years. The purpose of the validation was to ensure that the model was well calibrated and stable, thereby ensuring confidence for simulations beyond the 2-year follow-up period of PROMISE (Figure 1). Subgroup and Sensitivity Analyses We conducted 2 subgroup analysis; to assess the robustness of ICER analyses, we tested cost-effectiveness outcomes across subgroups, stratified by (1) sex and (2) being younger or older than the median (ie, 60 years).44,45 We also conducted 4 sensitivity analyses: (1) adherence to medical therapy, a scenario of 5 years of full adherence followed by 5 years of declining adherence (in monthly steps with no patients receiving statins after 10 years) and another scenario with full adherence for 5 years and no medical treatment effect afterwards; (2) to assess whether adding functional information to anatomical stenosis would substantially affect the rate of invasive testing among those with luminal narrowing greater than 70%, we expanded the indication of FFRct to include such patients; (3) do nothing strategy, in which patients only received medication according to their risk factor profile46; and (4) to visualize the heterogeneity and thus the uncertainty created by our 1 000 300 microsimulation cases per strategy, we conducted a quasi–probabilistic sensitivity analysis (PSA) and calculated cost-effectiveness acceptability curves for CTA alone and CTA with FFRCT compared with functional testing. Cost and QALY distributions for the quasi-PSA were informed by parameter estimates from our data. Results from the quasi-PSA were then used to calculate cost-effectiveness acceptability curves. Statistical Analysis The model was analyzed from the societal perspective of the United States. For each strategy, we simulated each PROMISE participant 100 times (ie, each of the 10 003 PROMISE patients entered the model 100 times for each strategy, resulting in 1 000 300 observations per strategy). This enabled us to generate standard errors for the cost and effectiveness end points that were small enough to generate stable estimates of the effect sizes of interest, ensuring that the difference in QALYs and costs between the interventions was at least 2 times greater than the standard error of the difference. Thus, all comparisons are reported without P values. The model was programmed in TreeAge Pro Suite (TreeAge Software). All data and statistical analyses were performed using Stata version 14.2 (StataCorp). Results Patient Population The model cohort had identical individual patient demographic characteristics, including age, sex, race, and CV risk factors, as the 10 003 individual patients who participated in the PROMISE trial5 (Table 1). The median (interquartile range) age was 60.0 (54.4-65.9) years, 5270 (52.7%) were women, and 7693 (77.7%) were White individuals. The population had a substantial CV risk factor burden: 2531 (25.3%) had a CAD risk equivalent, and 6697 (67.6%) had a 10-year risk of events of at least 7.5%. The mean (SD) pretest likelihood of obstructive CAD according to a combined Diamond and Forrester and Coronary Artery Surgery Study model was 53.3% (21.4). Table 1. Demographic Characteristics and CV Risk and 2-Year MACE in Patients With Stable Chest Pain in the Markov Modela Variable No. (%) Age, median (IQR), y 60.0 (54.4-65.9) Women 5270 (52.7) Race White 7693 (77.7) Black 1071 (10.8) Other 1239 (12.4) CV risk factors Body mass index, mean (SD)b 30.5 (6.1) Hypertension 6501 (65.0) Diabetes 2144 (21.4) Dyslipidemia 6767 (67.7) Family history of premature CAD 3202 (32.1) PAD or cerebrovascular disease 552 (5.5) CAD risk equivalent 2531 (25.3) Metabolic syndrome 3772 (37.7) Current or past tobacco use 5104 (51.0) Sedentary lifestyle 4866 (48.8) History of depression 2058 (20.6) Risk burden No risk factors 263 (2.6) Risk factors per patient, mean (SD), No. 2.4 (1.1) Combined Diamond and Forrester and Coronary Artery Surgery Study Risk score, mean (SD), % 53.3 (21.4) Framingham risk score categories Low risk, <6% 686 (6.9) Intermediate risk, 6%-20% 5114 (51.2) High risk, >20% 4188 (41.9) Framingham risk score, median (IQR) 17.1 (10.6-28.6) ASCVD risk Low risk, <7.5% 3204 (32.4) Elevated risk, ≥7.5% 6697 (67.6) Median (IQR) 11.3 (6.1-19.8) Chest pain type Angina Typical 1166 (11.7) Atypical 7773 (77.7) Nonanginal pain 1064 (10.6) MACE during a median follow-up of 25 mo CV death or MI 157 (1.6) MI 70 (0.7) CV death 35 (0.4) Death from any cause 149 (1.5) Death or MI 216 (2.2) Abbreviations: ASCVD, atherosclerotic cardiovascular disease; CAD, coronary artery disease; CV, cardiovascular; IQR, interquartile range; MACE, major adverse cardiovascular event; MI, myocardial infarction; PAD, peripheral artery disease. a Patient characteristics of the 1 000 300 modeled individuals were simulated based on individual patient data from the Prospective Multicenter Imaging Study for Evaluation of Chest Pain trial5; therefore, they are identical to the original PROMISE cohort. b Body mass index was calculated as weight in kilograms divided by height in meters squared. Model Validation First, we modeled the assignment of the different functional testing alternatives used in PROMISE, resulting in accurate estimations for stress SPECT (67.5% [95% CI, 66.2%-68.8%] vs 67.2% [95% CI, 67.1%-67.3%]), stress echocardiography (22.4% [95% CI, 21.2%-23.7%] vs 22.5% [95% CI, 22.5%-22.6%]), and exercise treadmill testing (10.2% [95% CI, 8.9%-11.5%] vs 10.4% [95% CI, 10.3%-10.5%]) for modeled vs observed PROMISE data, respectively. Similarly, the model, compared with PROMISE data, accurately simulated test results (eg, coronary CTA with 30%-69% stenosis: 31.6% [95% CI, 30.3%-32.9%] vs 31.4% [95% CI, 31.3%-31.5%]; functional testing with inducible myocardial ischemia: 8.8% [95% CI, 8.0%-9.6%] vs 7.9% [95% CI, 7.8%-8.0%]) (Figure 2A and Figure 2B) and ICA and coronary revascularization rates (coronary CTA: ICA, 12.2% [95% CI, 10.9%-13.5%] vs 12.3% [95% CI, 12.2-12.4%]; revascularization, 6.2% [95% CI, 5.5%-6.9%] vs 6.4% [95% CI, 6.3%-6.5%]; functional strategy: ICA, 8.1% [95% CI, 7.4%-8.9%] vs 8.2% [95% CI, 8.1%-8.3%]; revascularization, 3.2% [95% CI, 2.7%-3.7%] vs 3.3% [95% CI, 3.2%-3.4%]). Lastly, the model accurately predicted costs compared with observed costs (coronary CTA, $2494 vs $2546; functional strategy, $2240 vs $2189) and 2-year MACE rates (coronary CTA, 2.1% [95% CI, 1.7%-2.5%] vs 2.3% [95% CI, 2.2%-2.4%]; functional strategy, 2.2% [95% CI, 1.8%-2.6%] vs 2.4% [95% CI, 2.3-2.4%]) (eTable 6 in the Supplement). Figure 2. Comparison of Observed vs Simulated Rate of Testing and Test Findings for Coronary Computed Tomography Angiography (CTA) Strategy and Test Distribution and Findings for Functional Strategy A,Data based on site and core laboratory test readings. B, Average pathway probabilities as observed in PROMISE vs as model simulated, in which patients underwent pathways according to their risk score, ie, if patient is at lower risk, then there is a higher probability that the given patient will be tested with exercise treadmill test (ETT). An invasive coronary angiography (ICA) finding of severely abnormal indicated coronary artery disease (CAD) with at least 70% stenosis; mildly abnormal, nonobstructive CAD with 1% to 70% stenosis; normal, no stenosis. CTA, single photon emission computed tomography (SPECT), stress echocardiography findings (STECHO), and ETT are defined in eTable 2 in the Supplement.17 CABG indicates coronary artery bypass grafting; LM, left main disease; OMT, optimal medical treatment; PCI, percutaneous coronary intervention; PROMISE, Prospective Multicenter Imaging Study for Evaluation of Chest Pain; and VD, vessel disease. Comparison of Coronary CTA, CTA With FFRCT, and Functional Testing Strategies Short-term Outcomes Overall, 3141 patients (31.4%) had a 30% to 69% stenosis on coronary CTA and underwent CTA with FFRCT. Based on ASCVD risk score and diagnostic test results, 6702 patients (67.0%) per functional strategy, 8539 (85.4%) per coronary CTA, and 8552 (85.5%) per CTA with FFRCT were eligible for statin treatment. Because of the higher sensitivity of coronary CTA to detect CAD, the frequency of ICA and coronary revascularization was higher for patients who underwent coronary CTA and CTA with FFRCT compared with those who underwent functional testing (ICA: 12.3% [95% CI, 12.3%-12.4%] and 10.5% [95% CI, 10.5%-10.6%] vs 8.1% [95% CI, 8.0%-8.1%]; revascularization: 6.6% [95% CI, 6.6%-6.7%] and 6.3% [95% CI, 6.3%-6.4%] vs 3.3% [95% CI, 3.3%-3.4%]) (eFigure 2 in the Supplement). The revascularization-to-ICA ratios for CTA with FFRct and CTA approaches were higher compared with functional testing, indicating a more effective patient selection for ICA (59.5% [95% CI, 59.2%-598.8%] and 53.7% [95% CI, 53.3%-54.0%] vs 40.7% [95% CI, 40.4%-50.0%]) (eFigure 2 in the Supplement). Mid-term Outcomes The 2-year revascularization rates for coronary CTA alone and CTA with FFRCT were nearly twice as high as those for functional testing (6.6% [95% CI, 6.5%-6.6%] and 6.3% [95% CI, 6.3%-6.4%] vs 3.6% [95% CI, 3.6%-3.7%]) and remained higher after 5 years, although the functional strategy saw the highest relative increase (functional testing, 21.0% [95% CI, 20.9%-21.1%]; coronary CTA, 2.9% [95% CI, 2.8%-3.0%]; coronary CTA with FFRCT, 3.1% [95% CI, 3.0%-3.2%]) (Table 2). The MACE rate in this low-risk SCP population was low across all strategies, not exceeding 1.5% after 2 years and 3.9% after 5 years. Higher costs of anatomic approaches after 2 and 5 years were mainly associated with the higher ICA and revascularization rates. The additional cost of FFRCT ($1450) was offset by fewer ICAs and revascularizations after 5 years compared with coronary CTA alone. Anatomic approaches had higher QALYs at both 2 and 5 years: the QALY gains for CTA with FFRCT and for CTA alone were 0.12 (P < .001) and 0.13 (P < .001), respectively, or 1.5 months of longer life in perfect health (Table 2). Table 2. Model-Derived Coronary Revascularization and MACE Rates at 2 and 5 Years and Over Lifetime, by Index Test Strategy Index test 2-y Rate 5-y Rate Lifetime rate Coronary CTA CTA with FFRCTa Functional testing Coronary CTA CTA with FFRCTa Functional testing Coronary CTA CTA with FFRCTa Functional testing Revascularization, % Any revascularization 6.59 6.33 3.62 6.78 6.53 4.38 12.59 12.44 13.33 PCI 4.59 4.33 2.95 4.71 4.45 3.59 8.41 8.24 10.40 CABG 2.00 2.00 0.67 2.07 2.08 0.79 4.18 4.20 2.93 MACE, % CV death or MI 1.11 1.10 1.44 3.05 3.05 3.89 48.61 48.82 51.83 MI 0.75 0.73 0.90 1.92 1.92 2.29 14.34 14.41 15.11 CV death 0.37 0.39 0.55 1.19 1.20 1.68 42.13 42.30 44.89 Death from any cause 1.42 1.42 1.61 4.12 4.11 4.61 100.00 100.00 100.00 Death or MI 2.16 2.13 2.49 5.95 5.93 6.78 100.00 100.00 100.00 Cost/patient (95% CI), $ 2808 (2796-2821) 2998 (2985-3010) 2404 (2396-2413) 3276 (3262-3290) 3251 (3237-3265) 2759 (2749-2770) 8683 (8652-8713) 7222 (7192-7252) 7989 (7958-8020) QALY/patient (95% CI) 1.869 (1.869-1.870) 1.870 (1.869-1.870) 1.867 (1.867-1.867) 4.610 (4.609-4.611) 4.611 (4.610-4.612) 4.598 (4.597-4.599) 25.162 (25.139-25.185) 25.143 (25.120-25.166) 24.680 (24.657-24.704) Abbreviations: CABG, coronary artery bypass grafting; CTA, computed tomography angiography; CV, cardiovascular; FFRCT, noninvasive fractional flow reserve derived from computed tomography; MACE, major adverse cardiovascular event; MI, myocardial infarction; PCI, percutaneous coronary intervention; QALY, quality-adjusted life-years. a FFRCT performed in patients with 30% to 69% stenosis as detected by coronary CTA. Long-term Outcomes There was a significant dynamic in coronary revascularizations, costs, and QALYs between mid-term and lifetime follow-up. Over a lifetime, the model estimated similar frequency of coronary revascularizations across all strategies (Table 2). As a result, differences in costs between the anatomic and functional approaches decreased. Over a lifetime, anatomic approaches had significantly higher QALYs compared with functional testing (QALY gain for CTA with FFRCT: 0.46; CTA alone: 0.48; indicating 6 months of longer life in perfect health). Over a lifetime, the coronary CTA strategy alone was cost-effective compared with functional testing (ICER: $2743/QALY), and the CTA with FFRCT strategy was less costly and more effective and thus dominated functional testing (Table 3). Modeling different accuracies for CTA and FFRCT by assuming worse performance due to the outdated CT technology used in the PROMISE trial did not alter the results of the main analysis. Table 3. Cost, QALYs, ICER, and Life-Years Gained From Coronary CTA and Coronary CTA With FFRCT Compared With Functional Testing Strategy Cost (95% CI), $ QALY (95% CI) Discounted ICER ($/QALY)b Life-years gained (95% CI), y Undiscounted Differencea Undiscounted Differencea Coronary CTA vs functional testing Functional strategy 7989 (7958 to 8020) NA 24.68 (24.66 to 24.70) NA NA 26.51 (26.48 to 26.53) Coronary CTA strategy 8683 (8652 to 8713) 694 (660 to 728) 25.16 (25.14 to 25.19) 0.48 (0.46 to 0.50) 2743c 27.03 (27.00 to 27.05) Coronary CTA with FFRCT vs functional testing Functional strategy 7989 (7958 to 8020) NA 24.68 (24.66 to 24.70) NA Dominatedd 26.51 (26.48 to 26.53) CTA with FFRCT strategy 7222 (7192 to 7252) −767 (−805 to −729) 25.14 (25.12 to 25.17) 0.46 (0.44 to 0.49) NA 27.01 (26.99 to 27.04) Abbreviations: CTA, computed tomography angiography; FFRCT, noninvasive fractional flow reserve derived from computed tomography; ICER, incremental cost-effectiveness ratio; NA, not applicable; QALY, quality-adjusted life-years. a Cost and QALY differences are expressed in reference to functional strategy. b Discounted at 3% annually, as recommended by the US Panel on Cost-Effectiveness in Health and Medicine.42,43 c A strategy is considered cost-effective when the ICER is less than $100 000/QALY.40 d A strategy is considered dominated by the other if the other has lower cost and higher QALY. Sensitivity Analyses Subgroup Analyses Compared with functional strategy, coronary CTA remained cost-effective with an ICER in women and men as well as in individuals older than and younger than the median age of 60 years (ICER range, $1912/QALY for women to $3559/QALY for men). CTA with FFRCT was cost-effective in men (ICER, $192/QALY) but dominated the functional strategy across other subgroups (eTable 7 in the Supplement). Adherence to Medical Therapy Modeling a continuous decline in statin therapy adherence after 5 years, the lifetime cost of coronary CTA strategy decreased to $6438 (95% CI, $6413-$6464) but also resulted in the loss of health benefits and thus yielded lower QALY (QALY difference, 0.12; 95% CI, 0.10-0.14). However, coronary CTA remained cost-effective compared with functional strategy (ICER, $2927/QALY). Similar results were seen for a CTA with FFRCT strategy. Modeling complete nonadherence to statin therapy for anatomical strategies after 5 years resulted in the loss of some of the observed health benefits compared with functional testing but still lower MACE rates for anatomic strategies compared with functional testing (CTA alone and CTA with FFRCT vs functional testing, MACE rate: 52.5% [95% CI, 52.4%-52.6%] and 52.7% [95% CI, 52.6%-52.8%] vs 53.3% [95% CI, 53.2%-53.4%]). However, anatomic approaches were still cost-effective compared with functional testing (CTA alone, $2291/QALY; CTA with FFRCT, $2723/QALY), mostly because of the decreased costs of care. Expanding the Indication of FFRCT to Patients With Greater Than 70% Luminal Narrowing Expanding the use of FFRCT to the 4.4% of patients who had greater than 70% stenosis resulted in a downward reclassification and avoidance of ICA in 17.8% (95% CI, 16.6%-19.0%) of these patients. At 60 days, this would lead to an overall decrease of ICA by 0.8% (from 10.5% [95% CI, 10.3%-10.7%] to 9.7% [95% CI, 9.5%-9.9%]) and coronary revascularizations (from 6.3% [95% CI, 6.1%-6.5%] to 5.5% [95% CI, 5.4%-5.6%]) in the overall population and a 4.4% increase of the size of the FFRCT group. Over a lifetime, results are very similar compared with the main analysis, resulting in lower cost and higher QALYs for coronary CTA and FFRCT strategy compared with the functional testing strategy. Do Nothing Strategy A do nothing strategy resulted in the lowest cost and lowest QALYs compared with all other strategies; all strategies were cost-effective compared with do nothing, assuming a cost-effectiveness threshold of $100 000/QALY. However, functional testing was only slightly below the threshold (functional strategy vs do nothing, $99 678/QALY; CTA with FFRCT vs do nothing, $36 968/QALY; CTA vs do nothing, $59 436/QALY). Quasi-PSA When each outcome was expressed in incremental costs and incremental effects, anatomic approaches remained less costly and more effective compared with functional strategy in 38.6% of scenarios for coronary CTA and in 51.5% of scenarios for CTA with FFRCT (eFigure 3A and eFigure 3B in the Supplement). Assuming the willingness to pay is $100 000/QALY, the probability that the coronary CTA strategy and CTA with FFRCT remained cost-effective compared with functional testing was 69.4%, and 65.4%, respectively (eFigure 3C and eFigure 3D in the Supplement). Discussion There is heterogenous data on the appropriate choice of diagnostic index testing in the evaluation of low-risk SCP.5,6 The results of our analysis, using a Markov model incorporating individual patient-level data from PROMISE, suggest that anatomic approaches are cost-effective compared with functional testing across a wide range of assumptions in clinical care and patient characteristics, mostly because of a higher sensitivity to detect nonobstructive and obstructive CAD and the ability to tailor statin therapy accordingly. Adding FFRCT to coronary CTA resulted in further, although modest, improvements, and the initial higher costs were offset by fewer and more targeted coronary revascularizations. In PSAs, anatomic approaches were cost-effective in most scenarios assuming a willingness-to-pay threshold of $100 000/QALY. Overall, our results support the new ESC guidelines, suggesting that anatomic strategies may present a favorable initial diagnostic option in the evaluation of low-risk SCP compared with functional testing. This analysis sought to illuminate the effects of differences in the diagnostic capability to detect nonobstructive and obstructive CAD between functional and anatomic approaches on identifying patients who are statin eligible and those eligible for referral to coronary revascularization. In addition, our model included FFRCT as an emerging testing option. Our model, similar to PROMISE and SCOT-HEART, showed overall low rates of ICA and coronary revascularization within 2 and 5 years for all strategies but with higher rates for anatomic approaches compared with functional testing (12.3% and 10.5% vs 8.1% for ICA, respectively, and 6.6% and 6.3% vs 3.3% for revascularization, respectively). This observation, in line with widely published data,39,47,48,49 appeared to be driven by the higher sensitivity of anatomic testing to detect CAD. Furthermore, optimized patient selection for ICA and subsequent coronary revascularization was shown for FFRCT, which reclassified intermediate lesions with a luminal narrowing of 30% to 69%9,16,17 (revascularization-to-ICA ratio: CTA with FFRCT, 59.5%; CTA strategy, 53.7%; functional testing, 40.7%), consistent with previous observational studies (revascularization-to-ICA ratio for FFRCT in the ADVANCE registry,50 59.5%; PLATFORM study,51 58.3%). However, a relatively small change was observed for CTA with FFRCT strategy, resulting in a 14.6% reduction of the ICA rate. This observation is may be surprising but can be explained by the fact that only 31% of patients received FFRCT, and the positivity rate was very low—similar to absolute rates of revascularization in this population. Interestingly, the additional cost of FFRCT (ie, $1450) was offset after 5 years by fewer ICAs and revascularizations compared with coronary CTA alone. Expanding the indication of FFRCT for those with luminal narrowing of greater than 70% affected very few patients (0.8%). Hence, although a sizeable portion of those with stenosis (17.8% of these patients) was reclassified and downgraded by FFRCT52 and those patients could avoid ICA and unnecessary coronary revascularization, this affected only 0.8% of all patients. Understandably, this change of management did not alter the results of the cost-effectiveness analysis in the overall population significantly. Our second focus was to determine how tailoring statin therapy to the presence and extent of CAD would affect cost-effectiveness. Assuming similar optimal medical treatment, except for statin therapy, for all strategies constitutes an important simplification of the model but was justified because differences in test findings mainly affected statin therapy. Close to the 41% reduction in MACE observed in SCOT-HEART, our model estimated that MACE at 2 and 5 years was 23.6% and 21.6% higher after functional testing compared with anatomic strategies after 2 and 5 years, respectively. This was associated with the difference in diagnosis of nonobstructive and obstructive CAD (for which anatomic strategies have better diagnostic accuracy16,17,53,54) and consequent differences in statin treatment (67% for functional testing vs 85% for anatomic approaches). Our estimates of the differences of statin effects are possibly conservative because we assumed full adherence of all patients in the functional arm, putting two-thirds of that population already on statin treatment (compared with 57% in SCOT HEART6 and 50% in PROMISE).55 In this context, it is important to compare our assumptions and results with published data. Notably, unlike any other prior cost-effectiveness analyses of statin therapy, we were able to tailor the benefits of statins, ie, an overall reduction in mortality by 20%, to the underlying CAD, assuming 0% mortality reduction for those without CAD, 30% for those with nonobstructive CAD, and 30% for obstructive CAD. Reassuringly, this is in line with reports from several statin trials, including the JUPITER and 4S studies (30% mortality reduction in patients with coronary heart disease).56,57 Moreover, our reported gain of 0.5 additional QALY for anatomical strategies vs functional testing appears to be comparable with the 0.28 additional QALY reported in the 4S cost-effectiveness analysis, once we consider that patients were assumed to receive treatment for only 5 years in 4S and after that no statin effect was modeled. Compared with the JUPITER cost-effectiveness analysis, our discounted (3% per year) lifetime QALY difference was 0.24 (instead of the approximately 0.5 when using undiscounted values) and thus less than the 0.31 reported in JUPITER, in which they compared potent statin therapy with placebo.53 Moreover, the JUPITER cost-effectiveness analysis assumed 15 years of treatment, while we assumed statin treatment over a lifetime. In their sensitivity analyses, a maximum treatment duration of 25 years led to an ICER reduction of 20% (from $25 000 to $20 000). Because the ICER decreased, the incremental QALYs must increase (especially given that longer treatment increases costs). Therefore, the QALY difference in the JUPITER study should be even larger than the reported 0.31 when we apply our assumption of lifetime treatment. Over a lifetime, the model estimated similar frequencies of revascularizations across strategies. Subsequently, differences in costs decreased, and anatomic approaches had significantly higher QALYs compared with functional testing (0.46 and 0.48 additional QALY gain for CTA with FFRCT and CTA alone, respectively) and thus were cost-effective compared with functional testing. This principal finding was consistent across subgroups and sensitivity analyses and was further supported by the quasi-PSA. In all comparisons, anatomic approaches either dominated functional testing and/or were cost-effective, with cost per QALY below $50 000, making it high value according to the ACC/AHA.41 These results compare favorably with established strategies, such as lung cancer screening ($130 000/QALY)58 or screening for CAD in patients with type 2 diabetes or HIV.59,60 Moreover, assuming a willingness-to-pay threshold of $100 000/QALY, the probabilities that coronary CTA strategy and CTA with FFRCT were cost-effective compared with functional testing is 69.4% and 65.4%, respectively. Additionally, our results are consistent with prior cost-effectiveness analysis publications, in which anatomical testing was shown to be cost-effective compared with functional assessment among those with low to intermediate pretest probability, thus, among patients with identical risk profiles as the PROMISE population.46,61 Nevertheless, using ICA-defined anatomical stenosis as a criterion standard puts noninvasive anatomical testing in a superior position; hence, further studies with invasive FFR as a criterion standard are warranted.62 A strength of our analysis is that the model was informed by individual patient demographic characteristics, CV risk factors, and CAD status from the PROMISE trial,5 which enrolled 10 003 patients at 192 US sites. Therefore, PROMISE is representative of the low-risk chest pain population and use of index testing, making the model results generalizable. Because we could accurately reproduce the patient management and clinical outcomes observed in PROMISE after 60 days and 2 years, our model appears to exactly simulate real-life clinical decision-making, including costs and outcomes for the coronary CTA only and the functional testing strategies for the first 2 years after the initial test. The implementation of FFRCT and everything that happened after 2 years was modeled. However, the validity of our long-term model is strengthened by relying on actual clinical decision-making instead of assumptions during the first 2 years. From a medical treatment perspective, only differences in statin treatment between CTA and functional testing were modeled, based on the fact that underlying CAD was known after coronary CTA but not after functional testing. An additional strength was comprehensive validation of the model with observed outcomes in the PROMISE trial,5 including an accurate estimation of the distribution of applied functional tests (eg, SPECT, echo, exercise treadmill test), test findings, ICA and revascularization rates, health care costs, and incident MACE rates. Our study thus represents a high-quality cost-effectiveness analysis, given that other published analyses limit validation to mortality63 or ASCVD event rate64 or do not include model validation but only calibration.65,66,67,68,69 A further strength is that our principal finding that anatomic approaches were cost-effective compared with functional testing was stable over a wide range of assumptions in clinical care and patient characteristics and in most PSAs. Limitations Our study has limitations, although most of these similarly affect all 3 strategies, including assumptions on MACE risk based on CV risk factors and CAD; the effects of medical therapy, except statin therapy; benefits and risks of ICA, PCI, and CABG; and risk of MACE after a first event. Similarly, inherent limitations of diagnostic accuracy values are based on core laboratory test readings, which were the same for all tests and strategies and were similar to published data. Moreover, the main results of this cost-effectiveness analysis are supported by model validation for 60-day and 2-year outcomes with PROMISE real-life observations and by the stability of the results across several sensitivity analyses and subgroups. The generalizability of our results to countries other than the United States is limited, given the differences in the health care systems in general and the differences in management of patients with SCP, including costs and type of diagnostic testing. A further limitation is that FFRCT cannot be performed in all patients, limiting this strategy to a subset of patients. Conclusions The results of this study suggest that anatomic strategies may present a more favorable initial diagnostic option in the evaluation of low-risk SCP compared with functional testing. This study further supports the most recent ESC guidelines on the management of chronic chest pain syndrome. Supplement. eAppendix. Supplementary Methods eTable 1. Accuracy of Noninvasive Diagnostic Tests eTable 2. Strata of Diagnostic Test Results eTable 3. Appropriate Treatment per AHA/ACC Guidelines eTable 4. Morbidity and Mortality eTable 5. Cost of Diagnostic Testing and Intervention eTable 6. Markov Microsimulation Model Validation: Comparison of Test Distribution and Findings, Interventions at 60 Days, Costs at 90 Days, and Health Outcomes at 2 Years Between Observed and Modeled Strategies in the PROMISE Trial eTable 7. Cost, QALYs, Incremental Cost-effectiveness Ratio and Life-Years Gained of Coronary CTA and Coronary CTA With FFRCT Compared With Functional Testing, Stratified by Sex and Median Age of 60 Years eFigure 1. Modeling the Progression of CAD Using a Simulated Annealing Approach eFigure 2. Rate of ICA, Revascularization and Revascularization-to-ICA Ratio Based on Functional Strategy, Coronary CTA Strategy, and CTA With FFRCT Strategy eFigure 3. Incremental Cost-effectiveness Plot and Cost-effectiveness Acceptability Curve for Functional Testing vs Coronary CTA and Functional Testing vs Coronary CTA With FFRCT eReferences. Click here for additional data file. ==== Refs References 1 Benjamin EJ , Virani SS , Callaway CW , ; American Heart Association Council on Epidemiology and Prevention Statistics Committee and Stroke Statistics Subcommittee Heart disease and stroke statistics—2018 update: a report from the American Heart Association . Circulation . 2018 ;137 (12 ):e67 -e492 . doi:10.1161/CIR.0000000000000558 29386200 2 Nakajima K , Okuda K , Momose M , IQ·SPECT technology and its clinical applications using multicenter normal databases . Ann Nucl Med . 2017 ;31 (9 ):649 -659 . doi:10.1007/s12149-017-1210-3 28940141 3 van der Wall EE , Siebelink HM , Bax JJ , Schalij MJ Cardiac magnetic resonance imaging; gatekeeper in suspected CAD? Int J Cardiovasc Imaging . 2011 ;27 (1 ):123 -126 . doi:10.1007/s10554-010-9661-9 20571872 4 Patel MR , Peterson ED , Dai D , Low diagnostic yield of elective coronary angiography . N Engl J Med . 2010 ;362 (10 ):886 -895 . doi:10.1056/NEJMoa0907272 20220183 5 Douglas PS , Hoffmann U , Patel MR , ; PROMISE Investigators Outcomes of anatomical versus functional testing for coronary artery disease . N Engl J Med . 2015 ;372 (14 ):1291 -1300 . doi:10.1056/NEJMoa1415516 25773919 6 Newby DE , Adamson PD , Berry C , ; SCOT-HEART Investigators Coronary CT angiography and 5-year risk of myocardial infarction . N Engl J Med . 2018 ;379 (10 ):924 -933 . doi:10.1056/NEJMoa1805971 30145934 7 SCOT-HEART investigators CT coronary angiography in patients with suspected angina due to coronary heart disease (SCOT-HEART): an open-label, parallel-group, multicentre trial . Lancet . 2015 ;385 (9985 ):2383 -2391 . doi:10.1016/S0140-6736(15)60291-4 25788230 8 Knuuti J , Wijns W , Saraste A , ESC Guidelines for the diagnosis and management of chronic coronary syndromes: The Task Force for the Diagnosis and Management of Chronic Coronary Syndromes of the European Society of Cardiology (ESC) . European Heart Journal . 2020 ;41 (3 ):407 -477 . doi:10.1093/eurheartj/ehz425 31504439 9 Nakazato R , Park HB , Berman DS , Noninvasive fractional flow reserve derived from computed tomography angiography for coronary lesions of intermediate stenosis severity: results from the DeFACTO study . Circ Cardiovasc Imaging . 2013 ;6 (6 ):881 -889 . doi:10.1161/CIRCIMAGING.113.000297 24081777 10 Siebert U , Alagoz O , Bayoumi AM , State-transition modeling: a report of the ISPOR-SMDM Modeling Good Research Practices Task Force-3 . Med Decis Making . 2012 ;32 (5 ):690 -700 . doi:10.1177/0272989X12455463 22990084 11 Kong CY , McMahon PM , Gazelle GS Calibration of disease simulation model using an engineering approach . Value Health . 2009 ;12 (4 ):521 -529 . doi:10.1111/j.1524-4733.2008.00484.x 19900254 12 Weinstein MC Recent developments in decision-analytic modelling for economic evaluation . Pharmacoeconomics . 2006 ;24 (11 ):1043 -1053 . doi:10.2165/00019053-200624110-00002 17067190 13 Weinstein MC , O’Brien B , Hornberger J , ; ISPOR Task Force on Good Research Practices—Modeling Studies Principles of good practice for decision analytic modeling in health-care evaluation: report of the ISPOR Task Force on Good Research Practices—Modeling Studies . Value Health . 2003 ;6 (1 ):9 -17 . doi:10.1046/j.1524-4733.2003.00234.x 12535234 14 Goehler A , Mayrhofer T , Pursnani A , Long-term health outcomes and cost-effectiveness of coronary CT angiography in patients with suspicion for acute coronary syndrome . J Cardiovasc Comput Tomogr . 2020 ;14 (1 ):44 -54 .31303580 15 Husereau D , Drummond M , Petrou S , ; ISPOR Health Economic Evaluation Publication Guidelines-CHEERS Good Reporting Practices Task Force Consolidated Health Economic Evaluation Reporting Standards (CHEERS)—explanation and elaboration: a report of the ISPOR Health Economic Evaluation Publication Guidelines Good Reporting Practices Task Force . Value Health . 2013 ;16 (2 ):231 -250 . doi:10.1016/j.jval.2013.02.002 23538175 16 Montalescot G , Sechtem U , Achenbach S , ; Task Force Members ; ESC Committee for Practice Guidelines ; Document Reviewers 2013 ESC guidelines on the management of stable coronary artery disease: the Task Force on the Management of Stable Coronary Artery Disease of the European Society of Cardiology . Eur Heart J . 2013 ;34 (38 ):2949 -3003 . doi:10.1093/eurheartj/eht296 23996286 17 Hoffmann U , Ferencik M , Udelson JE , ; PROMISE Investigators Prognostic value of noninvasive cardiovascular testing in patients with stable chest pain: insights from the PROMISE Trial (Prospective Multicenter Imaging Study for Evaluation of Chest Pain) . Circulation . 2017 ;135 (24 ):2320 -2332 . doi:10.1161/CIRCULATIONAHA.116.024360 28389572 18 Fihn SD , Blankenship JC , Alexander KP , 2014 ACC/AHA/AATS/PCNA/SCAI/STS focused update of the guideline for the diagnosis and management of patients with stable ischemic heart disease: a report of the American College of Cardiology/American Heart Association Task Force on Practice Guidelines, and the American Association for Thoracic Surgery, Preventive Cardiovascular Nurses Association, Society for Cardiovascular Angiography and Interventions, and Society of Thoracic Surgeons . J Am Coll Cardiol . 2014 ;64 (18 ):1929 -1949 . doi:10.1016/j.jacc.2014.07.017 25077860 19 Ridker PM , Danielson E , Fonseca FA , ; JUPITER Study Group Rosuvastatin to prevent vascular events in men and women with elevated C-reactive protein . N Engl J Med . 2008 ;359 (21 ):2195 -2207 . doi:10.1056/NEJMoa0807646 18997196 20 Boden WE , O’Rourke RA , Teo KK , ; COURAGE Trial Research Group Optimal medical therapy with or without PCI for stable coronary disease . N Engl J Med . 2007 ;356 (15 ):1503 -1516 . doi:10.1056/NEJMoa070829 17387127 21 Chow BJ , Small G , Yam Y , ; CONFIRM Investigators Incremental prognostic value of cardiac computed tomography in coronary artery disease using CONFIRM: Coronary Computed Tomography Angiography Evaluation for Clinical Outcomes: an International Multicenter Registry . Circ Cardiovasc Imaging . 2011 ;4 (5 ):463 -472 . doi:10.1161/CIRCIMAGING.111.964155 21730027 22 Kong CY , McMahon PM , Gazelle GS Calibration of disease simulation model using an engineering approach . Value Health . 2009 ;12 (4 ):521 -529 . doi:10.1111/j.1524-4733.2008.00484.x 19900254 23 Cho I , Al’Aref SJ , Berger A , Prognostic value of coronary computed tomographic angiography findings in asymptomatic individuals: a 6-year follow-up from the prospective multicentre international CONFIRM study . Eur Heart J . 2018 ;39 (11 ):934 -941 . doi:10.1093/eurheartj/ehx774 29365193 24 Pope JH , Aufderheide TP , Ruthazer R , Missed diagnoses of acute cardiac ischemia in the emergency department . N Engl J Med . 2000 ;342 (16 ):1163 -1170 . doi:10.1056/NEJM200004203421603 10770981 25 Armstrong PW , Fu Y , Chang WC , Acute coronary syndromes in the GUSTO-IIb trial: prognostic insights and impact of recurrent ischemia—the GUSTO-IIb Investigators . Circulation . 1998 ;98 (18 ):1860 -1868 . doi:10.1161/01.CIR.98.18.1860 9799205 26 Roe MT , Harrington RA , Prosper DM , Clinical and therapeutic profile of patients presenting with acute coronary syndromes who do not have significant coronary artery disease—the Platelet Glycoprotein IIb/IIIa in Unstable Angina: Receptor Suppression Using Integrilin Therapy (PURSUIT) Trial Investigators . Circulation . 2000 ;102 (10 ):1101 -1106 . doi:10.1161/01.CIR.102.10.1101 10973837 27 Arias E United States life tables, 2010 . Natl Vital Stat Rep . 2014 ;63 (7 ):1 -63 .25383611 28 Chaitman BR , Bourassa MG , Davis K , Angiographic prevalence of high-risk coronary artery disease in patient subsets (CASS) . Circulation . 1981 ;64 (2 ):360 -367 . doi:10.1161/01.CIR.64.2.360 7249303 29 Gandhi SK , Jensen MM , Fox KM , Smolen L , Olsson AG , Paulsson T Cost-effectiveness of rosuvastatin in comparison with generic atorvastatin and simvastatin in a Swedish population at high risk of cardiovascular events . Clinicoecon Outcomes Res . 2012 ;4 :1 -11 . doi:10.2147/CEOR.S26621 22347800 30 Stone GW , Ware JH , Bertrand ME , ; ACUITY Investigators Antithrombotic strategies in patients with acute coronary syndromes undergoing early invasive management: one-year results from the ACUITY trial . JAMA . 2007 ;298 (21 ):2497 -2506 . doi:10.1001/jama.298.21.2497 18056903 31 Peterson ED , Coombs LP , DeLong ER , Haan CK , Ferguson TB Procedural volume as a marker of quality for CABG surgery . JAMA . 2004 ;291 (2 ):195 -201 . doi:10.1001/jama.291.2.195 14722145 32 Birkmeyer JD , Siewers AE , Finlayson EV , Hospital volume and surgical mortality in the United States . N Engl J Med . 2002 ;346 (15 ):1128 -1137 . doi:10.1056/NEJMsa012337 11948273 33 Hannan EL , Racz MJ , Walford G , Long-term outcomes of coronary-artery bypass grafting versus stent implantation . N Engl J Med . 2005 ;352 (21 ):2174 -2183 . doi:10.1056/NEJMoa040316 15917382 34 Anderson HV , Shaw RE , Brindis RG , ; The American College of Cardiology-National Cardiovascular Data Registry (ACC-NCDR) A contemporary overview of percutaneous coronary interventions . J Am Coll Cardiol . 2002 ;39 (7 ):1096 -1103 . doi:10.1016/S0735-1097(02)01733-3 11923031 35 Johnson LW , Lozner EC , Johnson S , Coronary arteriography 1984-1987: a report of the Registry of the Society for Cardiac Angiography and Interventions—I, results and complications . Cathet Cardiovasc Diagn . 1989 ;17 (1 ):5 -10 . doi:10.1002/ccd.1810170103 2720767 36 Morcos SK Review article: acute serious and fatal reactions to contrast media: our current understanding . Br J Radiol . 2005 ;78 (932 ):686 -693 . doi:10.1259/bjr/26301414 16046418 37 Weinberg L , Kandasamy K , Evans SJ , Mathew J Fatal cardiac rupture during stress exercise testing: case series and review of the literature . South Med J . 2003 ;96 (11 ):1151 -1153 . doi:10.1097/01.SMJ.0000055036.73825.E2 14632367 38 Centers for Medicare & Medicaid Services October 2019 correction. Accessed November 16, 2020. https://www.cms.gov/Medicare/Medicare-Fee-for-Service-Payment/HospitalOutpatientPPS/Addendum-A-and-Addendum-B-Updates-Items/2019-Oct-Addendum-B-Correction 39 Tonino PA , De Bruyne B , Pijls NH , ; FAME Study Investigators Fractional flow reserve versus angiography for guiding percutaneous coronary intervention . N Engl J Med . 2009 ;360 (3 ):213 -224 . doi:10.1056/NEJMoa0807611 19144937 40 Hunink MGM. , Weinstein MC , Wittenberg E. , Decision Making in Health and Medicine: Integrating Evidence and Values . Cambridge University Press ; 2014 . doi:10.1017/CBO9781139506779 41 Anderson JL , Heidenreich PA , Barnett PG , ACC/AHA statement on cost/value methodology in clinical practice guidelines and performance measures: a report of the American College of Cardiology/American Heart Association Task Force on Performance Measures and Task Force on Practice Guidelines . J Am Coll Cardiol . 2014 ;63 (21 ):2304 -2322 . doi:10.1016/j.jacc.2014.03.016 24681044 42 Siegel JE , Weinstein MC , Russell LB , Gold MR ; Panel on Cost-Effectiveness in Health and Medicine Recommendations for reporting cost-effectiveness analyses . JAMA . 1996 ;276 (16 ):1339 -1341 . doi:10.1001/jama.1996.03540160061034 8861994 43 Weinstein MC , Siegel JE , Gold MR , Kamlet MS , Russell LB Recommendations of the panel on cost-effectiveness in health and medicine . JAMA . 1996 ;276 (15 ):1253 -1258 . doi:10.1001/jama.1996.03540150055031 8849754 44 Pagidipati NJ , Coles A , Hemal K , ; PROMISE Investigators Sex differences in management and outcomes of patients with stable symptoms suggestive of coronary artery disease: Insights from the PROMISE trial . Am Heart J . 2019 ;208 :28 -36 . doi:10.1016/j.ahj.2018.11.002 30529930 45 Wolk MJ , Bailey SR , Doherty JU , ; American College of Cardiology Foundation Appropriate Use Criteria Task Force ACCF/AHA/ASE/ASNC/HFSA/HRS/SCAI/SCCT/SCMR/STS 2013 multimodality appropriate use criteria for the detection and risk assessment of stable ischemic heart disease: a report of the American College of Cardiology Foundation Appropriate Use Criteria Task Force, American Heart Association, American Society of Echocardiography, American Society of Nuclear Cardiology, Heart Failure Society of America, Heart Rhythm Society, Society for Cardiovascular Angiography and Interventions, Society of Cardiovascular Computed Tomography, Society for Cardiovascular Magnetic Resonance, and Society of Thoracic Surgeons . J Am Coll Cardiol . 2014 ;63 (4 ):380 -406 . doi:10.1016/j.jacc.2013.11.009 24355759 46 Genders TS , Petersen SE , Pugliese F , The optimal imaging strategy for patients with stable chest pain: a cost-effectiveness analysis . Ann Intern Med . 2015 ;162 (7 ):474 -484 . doi:10.7326/M14-0027 25844996 47 De Bruyne B , Pijls NH , Kalesan B , ; FAME 2 Trial Investigators Fractional flow reserve-guided PCI versus medical therapy in stable coronary disease . N Engl J Med . 2012 ;367 (11 ):991 -1001 . doi:10.1056/NEJMoa1205361 22924638 48 Douglas PS , De Bruyne B , Pontone G , ; PLATFORM Investigators 1-Year Outcomes of FFRCT-guided care in patients with suspected coronary disease: the PLATFORM Study . J Am Coll Cardiol . 2016 ;68 (5 ):435 -445 . doi:10.1016/j.jacc.2016.05.057 27470449 49 Patel MR , Nørgaard BL , Fairbairn TA , 1-Year impact on medical practice and clinical outcomes of FFRCT: the ADVANCE Registry. JACC Cardiovasc Imaging . 2019 ;13 (1 ):97 -105 . doi:10.1016/j.jcmg.2019.03.003 50 Fairbairn TA , Nieman K , Akasaka T , Real-world clinical utility and impact on clinical decision-making of coronary computed tomography angiography-derived fractional flow reserve: lessons from the ADVANCE Registry . Eur Heart J . 2018 ;39 (41 ):3701 -3711 . doi:10.1093/eurheartj/ehy530 30165613 51 Douglas PS , Pontone G , Hlatky MA , ; PLATFORM Investigators Clinical outcomes of fractional flow reserve by computed tomographic angiography-guided diagnostic strategies vs. usual care in patients with suspected coronary artery disease: the prospective longitudinal trial of FFR(CT): outcome and resource impacts study . Eur Heart J . 2015 ;36 (47 ):3359 -3367 . doi:10.1093/eurheartj/ehv444 26330417 52 Lu MT , Ferencik M , Roberts RS , Noninvasive FFR derived from coronary CT angiography: management and outcomes in the PROMISE Trial . JACC Cardiovasc Imaging . 2017 ;10 (11 ):1350 -1358 . doi:10.1016/j.jcmg.2016.11.024 28412436 53 Maddox TM , Stanislawski MA , Grunwald GK , Nonobstructive coronary artery disease and risk of myocardial infarction . JAMA . 2014 ;312 (17 ):1754 -1763 . doi:10.1001/jama.2014.14681 25369489 54 Ahmadi N , Nabavi V , Hajsadeghi F , Mortality incidence of patients with non-obstructive coronary artery disease diagnosed by computed tomography angiography . Am J Cardiol . 2011 ;107 (1 ):10 -16 . doi:10.1016/j.amjcard.2010.08.034 21146679 55 Ladapo JA , Hoffmann U , Lee KL , Changes in medical therapy and lifestyle after anatomical or functional testing for coronary artery disease . J Am Heart Assoc . 2016 ;5 (10 ):e003807. doi:10.1161/JAHA.116.003807 27733347 56 Johannesson M , Jönsson B , Kjekshus J , Olsson AG , Pedersen TR , Wedel H ; Scandinavian Simvastatin Survival Study Group Cost effectiveness of simvastatin treatment to lower cholesterol levels in patients with coronary heart disease . N Engl J Med . 1997 ;336 (5 ):332 -336 . doi:10.1056/NEJM199701303360503 9011785 57 Choudhry NK , Patrick AR , Glynn RJ , Avorn J The cost-effectiveness of C-reactive protein testing and rosuvastatin treatment for patients with normal cholesterol levels . J Am Coll Cardiol . 2011 ;57 (7 ):784 -791 . doi:10.1016/j.jacc.2010.07.059 21310313 58 McMahon PM , Kong CY , Bouzan C , Cost-effectiveness of computed tomography screening for lung cancer in the United States . J Thorac Oncol . 2011 ;6 (11 ):1841 -1848 . doi:10.1097/JTO.0b013e31822e59b3 21892105 59 Hayashino Y , Shimbo T , Tsujii S , Cost-effectiveness of coronary artery disease screening in asymptomatic patients with type 2 diabetes and other atherogenic risk factors in Japan: factors influencing on international application of evidence-based guidelines . Int J Cardiol . 2007 ;118 (1 ):88 -96 . doi:10.1016/j.ijcard.2006.03.086 16949690 60 Nolte JE , Neumann T , Manne JM , Cost-effectiveness analysis of coronary artery disease screening in HIV-infected men . Eur J Prev Cardiol . 2014 ;21 (8 ):972 -979 . doi:10.1177/2047487313483607 23539717 61 van Waardhuizen CN , Khanji MY , Genders TSS , Comparative cost-effectiveness of non-invasive imaging tests in patients presenting with chronic stable chest pain with suspected coronary artery disease: a systematic review . Eur Heart J Qual Care Clin Outcomes . 2016 ;2 (4 ):245 -260 . doi:10.1093/ehjqcco/qcw029 29474724 62 Trägårdh E , Tan SS , Bucerius J , ; Endorsed by the European Association of Cardiovascular Imaging Systematic review of cost-effectiveness of myocardial perfusion scintigraphy in patients with ischaemic heart disease: a report from the cardiovascular committee of the European Association of Nuclear Medicine . Eur Heart J Cardiovasc Imaging . 2017 ;18 (8 ):825 -832 . doi:10.1093/ehjci/jex095 28549119 63 Sehested TSG , Bjerre J , Ku S , Cost-effectiveness of canakinumab for prevention of recurrent cardiovascular events . JAMA Cardiol . 2019 ;4 (2 ):128 -135 . doi:10.1001/jamacardio.2018.4566 30649147 64 Kohli-Lynch CN , Bellows BK , Thanassoulis G , Cost-effectiveness of low-density lipoprotein cholesterol level-guided statin treatment in patients with borderline cardiovascular risk . JAMA Cardiol . 2019 ;4 (10 ):969 -977 . doi:10.1001/jamacardio.2019.2851 31461121 65 Richman IB , Fairley M , Jørgensen ME , Schuler A , Owens DK , Goldhaber-Fiebert JD Cost-effectiveness of intensive blood pressure management . JAMA Cardiol . 2016 ;1 (8 ):872 -879 . doi:10.1001/jamacardio.2016.3517 27627731 66 Fonarow GC , Keech AC , Pedersen TR , Cost-effectiveness of evolocumab therapy for reducing cardiovascular events in patients with atherosclerotic cardiovascular disease . JAMA Cardiol . 2017 ;2 (10 ):1069 -1078 . doi:10.1001/jamacardio.2017.2762 28832867 67 Fonarow GC , van Hout B , Villa G , Arellano J , Lindgren P Updated cost-effectiveness analysis of evolocumab in patients with very high-risk atherosclerotic cardiovascular disease . JAMA Cardiol . 2019 ;4 (7 ):691 -695 . doi:10.1001/jamacardio.2019.1647 31166576 68 Pandya A , Sy S , Cho S , Weinstein MC , Gaziano TA Cost-effectiveness of 10-year risk thresholds for initiation of statin therapy for primary prevention of cardiovascular disease . JAMA . 2015 ;314 (2 ):142 -150 . doi:10.1001/jama.2015.6822 26172894 69 Kazi DS , Moran AE , Coxson PG , Cost-effectiveness of PCSK9 inhibitor therapy in patients with heterozygous familial hypercholesterolemia or atherosclerotic cardiovascular disease . JAMA . 2016 ;316 (7 ):743 -753 . doi:10.1001/jama.2016.11004 27533159