Erica Maffei

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

OBJECTIVES We examined mortality in relation to coronary artery disease (CAD) as assessed by ≥64-detector row coronary computed tomography angiography (CCTA). BACKGROUND Although CCTA has demonstrated high diagnostic performance for detection and exclusion of obstructive CAD, the prognostic findings of CAD by CCTA have not, to date, been examined for age- and sex-specific outcomes. METHODS We evaluated a consecutive cohort of 24,775 patients undergoing ≥64-detector row CCTA between 2005 and 2009 without known CAD who met inclusion criteria. In these patients, CAD by CCTA was defined as none (0% stenosis), mild (1% to 49% stenosis), moderate (50% to 69% stenosis), or severe (≥70% stenosis). CAD severity was judged on a per-patient, per-vessel, and per-segment basis. Time to mortality was estimated using multivariable Cox proportional hazards models. RESULTS At a 2.3 ± 1.1-year follow-up, 404 deaths had occurred. In risk-adjusted analysis, both per-patient obstructive (hazard ratio [HR]: 2.60; 95% confidence interval [CI]: 1.94 to 3.49; p < 0.0001) and nonobstructive (HR: 1.60; 95% CI: 1.18 to 2.16; p = 0.002) CAD conferred increased risk of mortality compared with patients without evident CAD. Incident mortality was associated with a dose-response relationship to the number of coronary vessels exhibiting obstructive CAD, with increasing risk observed for nonobstructive (HR: 1.62; 95% CI: 1.20 to 2.19; p = 0.002), obstructive 1-vessel (HR: 2.00; 95% CI: 1.43 to 2.82; p < 0.0001), 2-vessel (HR: 2.92; 95% CI: 2.00 to 4.25; p < 0.0001), or 3-vessel or left main (HR: 3.70; 95% CI: 2.58 to 5.29; p < 0.0001) CAD. Importantly, the absence of CAD by CCTA was associated with a low rate of incident death (annualized death rate: 0.28%). When stratified by age <65 years versus ≥65 years, younger patients experienced higher hazards for death for 2-vessel (HR: 4.00; 95% CI: 2.16 to 7.40; p < 0.0001 vs. HR: 2.46; 95% CI: 1.51 to 4.02; p = 0.0003) and 3-vessel (HR: 6.19; 95% CI: 3.43 to 11.2; p < 0.0001 vs. HR: 3.10; 95% CI: 1.95 to 4.92; p < 0.0001) CAD. The relative hazard for 3-vessel CAD (HR: 4.21; 95% CI: 2.47 to 7.18; p < 0.0001 vs. HR: 3.27; 95% CI: 1.96 to 5.45; p < 0.0001) was higher for women as compared with men. CONCLUSIONS Among individuals without known CAD, nonobstructive and obstructive CAD by CCTA are associated with higher rates of mortality, with risk profiles differing for age and sex. Importantly, absence of CAD is associated with a very favorable prognosis.

A clinical prediction rule for the diagnosis of coronary artery disease: validation, updating, and extension

AIMS The aim was to validate, update, and extend the Diamond-Forrester model for estimating the probability of obstructive coronary artery disease (CAD) in a contemporary cohort. METHODS AND RESULTS Prospectively collected data from 14 hospitals on patients with chest pain without a history of CAD and referred for conventional coronary angiography (CCA) were used. Primary outcome was obstructive CAD, defined as ≥ 50% stenosis in one or more vessels on CCA. The validity of the Diamond-Forrester model was assessed using calibration plots, calibration-in-the-large, and recalibration in logistic regression. The model was subsequently updated and extended by revising the predictive value of age, sex, and type of chest pain. Diagnostic performance was assessed by calculating the area under the receiver operating characteristic curve (c-statistic) and reclassification was determined. We included 2260 patients, of whom 1319 had obstructive CAD on CCA. Validation demonstrated an overestimation of the CAD probability, especially in women. The updated and extended models demonstrated a c-statistic of 0.79 (95% CI 0.77-0.81) and 0.82 (95% CI 0.80-0.84), respectively. Sixteen per cent of men and 64% of women were correctly reclassified. The predicted probability of obstructive CAD ranged from 10% for 50-year-old females with non-specific chest pain to 91% for 80-year-old males with typical chest pain. Predictions varied across hospitals due to differences in disease prevalence. CONCLUSION Our results suggest that the Diamond-Forrester model overestimates the probability of CAD especially in women. We updated the predictive effects of age, sex, type of chest pain, and hospital setting which improved model performance and we extended it to include patients of 70 years and older.

Prevalence and Severity of Coronary Artery Disease and Adverse Events Among Symptomatic Patients With Coronary Artery Calcification Scores of Zero Undergoing Coronary Computed Tomography Angiography Results From the CONFIRM (Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter) Registry

OBJECTIVES The purpose of this study was to describe the prevalence and severity of coronary artery disease (CAD) in relation to prognosis in symptomatic patients without coronary artery calcification (CAC) undergoing coronary computed tomography angiography (CCTA). BACKGROUND The frequency and clinical relevance of CAD in patients without CAC are unclear. METHODS We identified 10,037 symptomatic patients without CAD who underwent concomitant CCTA and CAC scoring. CAD was assessed as <50%, ≥50%, and ≥70% stenosis. All-cause mortality and the composite endpoint of mortality, myocardial infarction, or late coronary revascularization (≥90 days after CCTA) were assessed. RESULTS Mean age was 57 years, 56% were men, and 51% had a CAC score of 0. Among patients with a CAC score of 0, 84% had no CAD, 13% had nonobstructive stenosis, and 3.5% had ≥50% stenosis (1.4% had ≥70% stenosis) on CCTA. A CAC score >0 had a sensitivity, specificity, and negative and positive predictive values for stenosis ≥50% of 89%, 59%, 96%, and 29%, respectively. During a median of 2.1 years, there was no difference in mortality among patients with a CAC score of 0 irrespective of obstructive CAD. Among 8,907 patients with follow-up for the composite endpoint, 3.9% with a CAC score of 0 and ≥50% stenosis experienced an event (hazard ratio: 5.7; 95% confidence interval: 2.5 to 13.1; p < 0.001) compared with 0.8% of patients with a CAC score of 0 and no obstructive CAD. Receiver-operator characteristic curve analysis demonstrated that the CAC score did not add incremental prognostic information compared with CAD extent on CCTA for the composite endpoint (CCTA area under the curve = 0.825; CAC + CCTA area under the curve = 0.826; p = 0.84). CONCLUSIONS In symptomatic patients with a CAC score of 0, obstructive CAD is possible and is associated with increased cardiovascular events. CAC scoring did not add incremental prognostic information to CCTA.

Coronary Computed Tomographic Angiography and Risk of All-Cause Mortality and Nonfatal Myocardial Infarction in Subjects Without Chest Pain Syndrome From the CONFIRM Registry (Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter Registry)

Background— The predictive value of coronary computed tomographic angiography (cCTA) in subjects without chest pain syndrome (CPS) has not been established. We investigated the prognostic value of coronary artery disease detection by cCTA and determined the incremental risk stratification benefit of cCTA findings compared with clinical risk factor scoring and coronary artery calcium scoring (CACS) for individuals without CPS. Methods and Results— An open-label, 12-center, 6-country observational registry of 27 125 consecutive patients undergoing cCTA and CACS was queried, and 7590 individuals without CPS or history of coronary artery disease met the inclusion criteria. All-cause mortality and the composite of all-cause mortality and nonfatal myocardial infarction were measured. During a median follow-up of 24 months (interquartile range, 18–35 months), all-cause mortality occurred in 136 individuals. After risk adjustment, compared with individuals without evidence of coronary artery disease by cCTA, individuals with obstructive 2- and 3-vessel disease or left main coronary artery disease experienced higher rates of death and composite outcome (P<0.05 for both). Both CACS and cCTA significantly improved the performance of standard risk factor prediction models for all-cause mortality and the composite outcome (likelihood ratio P<0.05 for all), but the incremental discriminatory value associated with their inclusion was more pronounced for the composite outcome and for CACS (C statistic for model with risk factors only was 0.71; for risk factors plus CACS, 0.75; for risk factors plus CACS plus cCTA, 0.77). The net reclassification improvement resulting from the addition of cCTA to a model based on standard risk factors and CACS was negligible. Conclusions— Although the prognosis for individuals without CPS is stratified by cCTA, the additional risk-predictive advantage by cCTA is not clinically meaningful compared with a risk model based on CACS. Therefore, at present, the application of cCTA for risk assessment of individuals without CPS should not be justified.

Coronary Computed Tomographic Angiography as a Gatekeeper to Invasive Diagnostic and Surgical Procedures : Results From the Multicenter CONFIRM (Coronary CT Angiography Evaluation for Clinical Outcomes: An International Multicenter) Registry

OBJECTIVES This study sought to examine patterns of follow-up invasive coronary angiography (ICA) and revascularization (REV) after coronary computed tomography angiography (CCTA). BACKGROUND CCTA is a noninvasive test that permits direct visualization of the extent and severity of coronary artery disease (CAD). Post-CCTA patterns of follow-up ICA and REV are incompletely defined. METHODS We examined 15,207 intermediate likelihood patients from 8 sites in 6 countries; these patients were without known CAD, underwent CCTA, and were followed up for 2.3 ± 1.2 years for all-cause mortality. Coronary artery stenosis was judged as obstructive when ≥50% stenosis was present. A multivariable logistic regression was used to estimate ICA use. A Cox proportional hazards model was used to estimate all-cause mortality. RESULTS During follow-up, ICA rates for patients with no CAD to mild CAD according to CCTA were low (2.5% and 8.3%), with similarly low rates of REV (0.3% and 2.5%). Most ICA procedures (79%) occurred ≤3 months of CCTA. Obstructive CAD was associated with higher rates of ICA and REV for 1-vessel (44.3% and 28.0%), 2-vessel (53.3% and 43.6%), and 3-vessel (69.4% and 66.8%) CAD, respectively. For patients with <50% stenosis, early ICA rates were elevated; over the entirety of follow-up, predictors of ICA were mild left main, mild proximal CAD, respectively, or higher coronary calcium scores. In patients with <50% stenosis, the relative hazard for death was 2.2 (p = 0.011) for ICA versus no ICA. Conversely, for patients with CAD, the relative hazard for death was 0.61 for ICA versus no ICA (p = 0.047). CONCLUSIONS These findings support the concept that CCTA may be used effectively as a gatekeeper to ICA.

Optimized Prognostic Score for Coronary Computed Tomographic Angiography: Results From the CONFIRM Registry (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter Registry)

OBJECTIVES The aim of this study was to analyze the predictive value of coronary computed tomography angiography (CCTA) and to model and validate an optimized score for prognosis of 2-year survival on the basis of a patient population with suspected coronary artery disease (CAD). BACKGROUND Coronary computed tomography angiography carries important prognostic information in addition to the detection of obstructive CAD. But it is still unclear how the results of CCTA should be interpreted in the context of clinical risk predictors. METHODS The analysis is based on a test sample of 17,793 patients and a validation sample of 2,506 patients, all with suspected CAD, from the international CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter) registry. On the basis of CCTA data and clinical risk scores, an optimized score was modeled. The endpoint was all-cause mortality. RESULTS During a median follow-up of 2.3 years, 347 patients died. The best CCTA parameter for prediction of mortality was the number of proximal segments with mixed or calcified plaques (C-index 0.64, p < 0.0001) and the number of proximal segments with a stenosis >50% (C-index 0.56, p = 0.002). In an optimized score including both parameters, CCTA significantly improved overall risk prediction beyond National Cholesterol Education Program Expert Panel on Detection, Evaluation, and Treatment of High Blood Cholesterol in Adults (Adult Treatment Panel III) score as best clinical score. According to this score, a proximal segment with either a mixed or calcified plaque or a stenosis >50% is equivalent to a 5-year increase in age or the risk of smoking. CONCLUSIONS In CCTA, both plaque burden and stenosis, particularly in proximal segments, carry incremental prognostic value. A prognostic score on the basis of this data can improve risk prediction beyond clinical risk scores.

Prediction model to estimate presence of coronary artery disease: Retrospective pooled analysis of existing cohorts

Objectives To develop prediction models that better estimate the pretest probability of coronary artery disease in low prevalence populations. Design Retrospective pooled analysis of individual patient data. Setting 18 hospitals in Europe and the United States. Participants Patients with stable chest pain without evidence for previous coronary artery disease, if they were referred for computed tomography (CT) based coronary angiography or catheter based coronary angiography (indicated as low and high prevalence settings, respectively). Main outcome measures Obstructive coronary artery disease (≥50% diameter stenosis in at least one vessel found on catheter based coronary angiography). Multiple imputation accounted for missing predictors and outcomes, exploiting strong correlation between the two angiography procedures. Predictive models included a basic model (age, sex, symptoms, and setting), clinical model (basic model factors and diabetes, hypertension, dyslipidaemia, and smoking), and extended model (clinical model factors and use of the CT based coronary calcium score). We assessed discrimination (c statistic), calibration, and continuous net reclassification improvement by cross validation for the four largest low prevalence datasets separately and the smaller remaining low prevalence datasets combined. Results We included 5677 patients (3283 men, 2394 women), of whom 1634 had obstructive coronary artery disease found on catheter based coronary angiography. All potential predictors were significantly associated with the presence of disease in univariable and multivariable analyses. The clinical model improved the prediction, compared with the basic model (cross validated c statistic improvement from 0.77 to 0.79, net reclassification improvement 35%); the coronary calcium score in the extended model was a major predictor (0.79 to 0.88, 102%). Calibration for low prevalence datasets was satisfactory. Conclusions Updated prediction models including age, sex, symptoms, and cardiovascular risk factors allow for accurate estimation of the pretest probability of coronary artery disease in low prevalence populations. Addition of coronary calcium scores to the prediction models improves the estimates.

Differences in Prevalence, Extent, Severity, and Prognosis of Coronary Artery Disease Among Patients With and Without Diabetes Undergoing Coronary Computed Tomography Angiography: Results from 10,110 individuals from the CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes): an InteRnational Multicenter Registry

OBJECTIVE We examined the prevalence, extent, severity, and prognosis of coronary artery disease (CAD) in individuals with and without diabetes (DM) who are similar in CAD risk factors. RESEARCH DESIGN AND METHODS We identified 23,643 consecutive individuals without known CAD undergoing coronary computed tomography angiography. A total of 3,370 DM individuals were propensity matched in a 1-to-2 fashion to 6,740 unique non-DM individuals. CAD was defined as none, nonobstructive (1–49% stenosis), or obstructive (≥50% stenosis). All-cause mortality was assessed by risk-adjusted Cox proportional hazards models. RESULTS At a 2.2-year follow-up, 108 (3.2%) and 115 (1.7%) deaths occurred among DM and non-DM individuals, respectively. Compared with non-DM individuals, DM individuals possessed higher rates of obstructive CAD (37 vs. 27%) and lower rates of having normal arteries (28 vs. 36%) (P < 0.0001). CAD extent was higher for DM versus non-DM individuals for obstructive one-vessel disease (19 vs. 14%), two-vessel disease (9 vs. 7%), and three-vessel disease (9 vs. 5%) (P < 0.0001 for comparison), with higher per-segment stenosis in the proximal and mid-segments of every coronary artery (P < 0.001 for all). Compared with non-DM individuals with no CAD, risk of mortality for DM individuals was higher for those with no CAD (hazard ratio 3.63 [95% CI 1.67–7.91]; P = 0.001), nonobstructive CAD (5.25 [2.56–10.8]; P < 0.001), one-vessel disease (6.39 [2.98–13.7]; P < 0.0001), two-vessel disease (12.33 [5.622–27.1]; P < 0.0001), and three-vessel disease (13.25 [6.15–28.6]; P < 0.0001). CONCLUSIONS Compared with matched non-DM individuals, DM individuals possess higher prevalence, extent, and severity of CAD. At comparable levels of CAD, DM individuals experience higher risk of mortality compared with non-DM individuals.

Does coronary CT angiography improve risk stratification over coronary calcium scoring in symptomatic patients with suspected coronary artery disease? Results from the prospective multicenter international CONFIRM registry

AIMS The prognostic value of coronary artery calcium (CAC) scoring is well established and has been suggested for use to exclude significant coronary artery disease (CAD) for symptomatic individuals with CAD. Contrast-enhanced coronary computed tomographic angiography (CCTA) is an alternative modality that enables direct visualization of coronary stenosis severity, extent, and distribution. Whether CCTA findings of CAD add an incremental prognostic value over CAC in symptomatic individuals has not been extensively studied. METHODS AND RESULTS We prospectively identified symptomatic patients with suspected but without known CAD who underwent both CAC and CCTA. Symptoms were defined by the presence of chest pain or dyspnoea, and pre-test likelihood of obstructive CAD was assessed by the method of Diamond and Forrester (D-F). CAC was measured by the method of Agatston. CCTAs were graded for obstructive CAD (>70% stenosis); and CAD plaque burden, distribution, and location. Plaque burden was determined by a segment stenosis score (SSS), which reflects the number of coronary segments with plaque, weighted for stenosis severity. Plaque distribution was established by a segment-involvement score (SIS), which reflects the number of segments with plaque irrespective of stenosis severity. Finally, a modified Duke prognostic index-accounting for stenosis severity, plaque distribution, and plaque location-was calculated. Nested Cox proportional hazard models for a composite endpoint of all-cause mortality and non-fatal myocardial infarction (D/MI) were employed to assess the incremental prognostic value of CCTA over CAC. A total of 8627 symptomatic patients (50% men, age 56 ± 12 years) followed for 25 months (interquartile range 17-40 months) comprised the study cohort. By CAC, 4860 (56%) and 713 (8.3%) patients had no evident calcium or a score of >400, respectively. By CCTA, 4294 (49.8%) and 749 (8.7%) had normal coronary arteries or obstructive CAD, respectively. At follow-up, 150 patients experienced D/MI. CAC improved discrimination beyond D-F and clinical variables (area under the receiver-operator characteristic curve 0.781 vs. 0.788, P = 0.004). When added sequentially to D-F, clinical variables, and CAC, all CCTA measures of CAD improved discrimination of patients at risk for D/MI: obstructive CAD (0.82, P < 0.001), SSS (0.81, P < 0.001), SIS (0.81, P = 0.003), and Duke CAD prognostic index (0.82, P < 0.0001). CONCLUSION In symptomatic patients with suspected CAD, CCTA adds incremental discriminatory power over CAC for discrimination of individuals at risk of death or MI.

Machine learning for prediction of all-cause mortality in patients with suspected coronary artery disease: a 5-year multicentre prospective registry analysis

Aims Traditional prognostic risk assessment in patients undergoing non-invasive imaging is based upon a limited selection of clinical and imaging findings. Machine learning (ML) can consider a greater number and complexity of variables. Therefore, we investigated the feasibility and accuracy of ML to predict 5-year all-cause mortality (ACM) in patients undergoing coronary computed tomographic angiography (CCTA), and compared the performance to existing clinical or CCTA metrics. Methods and results The analysis included 10 030 patients with suspected coronary artery disease and 5-year follow-up from the COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter registry. All patients underwent CCTA as their standard of care. Twenty-five clinical and 44 CCTA parameters were evaluated, including segment stenosis score (SSS), segment involvement score (SIS), modified Duke index (DI), number of segments with non-calcified, mixed or calcified plaques, age, sex, gender, standard cardiovascular risk factors, and Framingham risk score (FRS). Machine learning involved automated feature selection by information gain ranking, model building with a boosted ensemble algorithm, and 10-fold stratified cross-validation. Seven hundred and forty-five patients died during 5-year follow-up. Machine learning exhibited a higher area-under-curve compared with the FRS or CCTA severity scores alone (SSS, SIS, DI) for predicting all-cause mortality (ML: 0.79 vs. FRS: 0.61, SSS: 0.64, SIS: 0.64, DI: 0.62; P< 0.001). Conclusions Machine learning combining clinical and CCTA data was found to predict 5-year ACM significantly better than existing clinical or CCTA metrics alone.