COroNary CT Angiography Evaluation For Clinical Outcomes: An InteRnational Multicenter Registry (CONFIRM)
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Publication
Journal: Journal of Cardiovascular Computed Tomography
August/10/2011
Abstract
BACKGROUND
Coronary computed tomographic angiography (CCTA) of 64-detector rows or greater represents a novel noninvasive anatomic method for evaluation of patients with suspected coronary artery disease (CAD). Early studies suggest a potential for prognostic risk assessment by CCTA findings but were limited by small patient cohorts or single centers. The CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter) registry is a large, prospective, multinational dynamic observational study of patients undergoing CCTA. The primary aim of CONFIRM is to determine the prognostic value of CCTA findings for the prediction of future adverse CAD events.
METHODS
The CONFIRM registry currently represents 27,125 consecutive patients at 12 cluster sites in 6 countries in North America, Europe, and Asia. CONFIRM sites were chosen on the basis of adequate CCTA volume, site CCTA proficiency, and local demographic characteristics and medical facilities to ensure a broad-based sample of patients. Patients comprising the present CONFIRM cohort include those with suspected but without known CAD, with known CAD, or asymptomatic persons undergoing CAD evaluation. A data dictionary comprising a wide array of demographic, clinical, and CCTA findings was developed by the CONFIRM investigators and is uniformly used for all patients. Patients are followed up after CCTA performance to identify adverse CAD events, including death, myocardial infarction, unstable angina, target vessel revascularization, and CAD-related hospitalization.
CONCLUSIONS
From a number of countries worldwide, the information collected from the CONFIRM registry will add incremental and important insights into CCTA findings that confer prognostic value beyond demographic and clinical characteristics. The results of the CONFIRM registry will provide valuable information about the optimal methods for using CCTA findings.
Publication
Journal: Journal of Cardiovascular Computed Tomography
August/26/2018
Abstract
BACKGROUND
Machine learning (ML) is a field in computer science that demonstrated to effectively integrate clinical and imaging data for the creation of prognostic scores. The current study investigated whether a ML score, incorporating only the 16 segment coronary tree information derived from coronary computed tomography angiography (CCTA), provides enhanced risk stratification compared with current CCTA based risk scores.
METHODS
From the multi-center CONFIRM registry, patients were included with complete CCTA risk score information and ≥3 year follow-up for myocardial infarction and death (primary endpoint). Patients with prior coronary artery disease were excluded. Conventional CCTA risk scores (conventional CCTA approach, segment involvement score, duke prognostic index, segment stenosis score, and the Leaman risk score) and a score created using ML were compared for the area under the receiver operating characteristic curve (AUC). Only 16 segment based coronary stenosis (0%, 1-24%, 25-49%, 50-69%, 70-99% and 100%) and composition (calcified, mixed and non-calcified plaque) were provided to the ML model. A boosted ensemble algorithm (extreme gradient boosting; XGBoost) was used and the entire data was randomly split into a training set (80%) and testing set (20%). First, tuned hyperparameters were used to generate a trained model from the training data set (80% of data). Second, the performance of this trained model was independently tested on the unseen test set (20% of data).
RESULTS
In total, 8844 patients (mean age 58.0 ± 11.5 years, 57.7% male) were included. During a mean follow-up time of 4.6 ± 1.5 years, 609 events occurred (6.9%). No CAD was observed in 48.7% (3.5% event), non-obstructive CAD in 31.8% (6.8% event), and obstructive CAD in 19.5% (15.6% event). Discrimination of events as expressed by AUC was significantly better for the ML based approach (0.771) vs the other scores (ranging from 0.685 to 0.701), P < 0.001. Net reclassification improvement analysis showed that the improved risk stratification was the result of down-classification of risk among patients that did not experience events (non-events).
CONCLUSIONS
A risk score created by a ML based algorithm, that utilizes standard 16 coronary segment stenosis and composition information derived from detailed CCTA reading, has greater prognostic accuracy than current CCTA integrated risk scores. These findings indicate that a ML based algorithm can improve the integration of CCTA derived plaque information to improve risk stratification.
Publication
Journal: European Heart Journal
March/15/2018
Abstract
UNASSIGNED
The long-term prognostic benefit of coronary computed tomographic angiography (CCTA) findings of coronary artery disease (CAD) in asymptomatic populations is unknown.
UNASSIGNED
From the prospective multicentre international CONFIRM long-term study, we evaluated asymptomatic subjects without known CAD who underwent both coronary artery calcium scoring (CACS) and CCTA (n = 1226). Coronary computed tomographic angiography findings included the severity of coronary artery stenosis, plaque composition, and coronary segment location. Using the C-statistic and likelihood ratio tests, we evaluated the incremental prognostic utility of CCTA findings over a base model that included a panel of traditional risk factors (RFs) as well as CACS to predict long-term all-cause mortality. During a mean follow-up of 5.9 ± 1.2 years, 78 deaths occurred. Compared with the traditional RF alone (C-statistic 0.64), CCTA findings including coronary stenosis severity, plaque composition, and coronary segment location demonstrated improved incremental prognostic utility beyond traditional RF alone (C-statistics range 0.71-0.73, all P < 0.05; incremental χ2 range 20.7-25.5, all P < 0.001). However, no added prognostic benefit was offered by CCTA findings when added to a base model containing both traditional RF and CACS (C-statistics P>> 0.05, for all).
UNASSIGNED
Coronary computed tomographic angiography improved prognostication of 6-year all-cause mortality beyond a set of conventional RF alone, although, no further incremental value was offered by CCTA when CCTA findings were added to a model incorporating RF and CACS.
Publication
Journal: European Heart Journal
September/12/2019
Abstract
Symptom-based pretest probability scores that estimate the likelihood of obstructive coronary artery disease (CAD) in stable chest pain have moderate accuracy. We sought to develop a machine learning (ML) model, utilizing clinical factors and the coronary artery calcium score (CACS), to predict the presence of obstructive CAD on coronary computed tomography angiography (CCTA).The study screened 35 281 participants enrolled in the CONFIRM registry, who underwent ≥64 detector row CCTA evaluation because of either suspected or previously established CAD. A boosted ensemble algorithm (XGBoost) was used, with data split into a training set (80%) on which 10-fold cross-validation was done and a test set (20%). Performance was assessed of the (1) ML model (using 25 clinical and demographic features), (2) ML + CACS, (3) CAD consortium clinical score, (4) CAD consortium clinical score + CACS, and (5) updated Diamond-Forrester (UDF) score. The study population comprised of 13 054 patients, of whom 2380 (18.2%) had obstructive CAD (≥50% stenosis). Machine learning with CACS produced the best performance [area under the curve (AUC) of 0.881] compared with ML alone (AUC of 0.773), CAD consortium clinical score (AUC of 0.734), and with CACS (AUC of 0.866) and UDF (AUC of 0.682), P < 0.05 for all comparisons. CACS, age, and gender were the highest ranking features.A ML model incorporating clinical features in addition to CACS can accurately estimate the pretest likelihood of obstructive CAD on CCTA. In clinical practice, the utilization of such an approach could improve risk stratification and help guide downstream management.
Publication
Journal: American Journal of Cardiology
September/24/2019
Abstract
The 2018 American College of Cardiology (ACC)/American Heart Association (AHA) cholesterol management guideline recommends risk enhancers in the borderline-risk and statin recommended/intermediate-risk groups. We determined the risk reclassification by the presence and severity of coronary computed tomography angiography (CCTA)-visualized coronary artery disease (CAD) according to statin eligibility groups. Of 35,281 individuals who underwent CCTA, 1,303 asymptomatic patients (age 59, 65% male) were identified. Patients were categorized as low risk, borderline risk, statin recommended/intermediate risk or statin recommended/high risk according to the guideline. CCTA-visualized CAD was categorized as no CAD, nonobstructive, or obstructive. Major adverse cardiovascular events (MACE) were defined as a composite outcome of all-cause mortality, nonfatal myocardial infarction, and late coronary revascularization (>90 days). We tested a reclassification wherein no CAD reclassifies downward, and the presence of any CAD reclassifies upward. During a median follow-up of 2.9 years, 93 MACE events (7.1%) were observed. Among the borderline-risk and statin-recommended/intermediate-risk groups eligible for risk enhancers, the presence or absence of any CCTA-visualized CAD led to a net increase of 2.3% of cases and 22.4% of controls correctly classified (net reclassification index [NRI] 0.27, 95% CI 0.13 to 0.41, p = 0.0002). The NRI was not significant among low- or statin-recommended/high-risk patients (all p >0.05). The presence or absence of CCTA-visualized CAD, including both obstructive and nonobstructive CAD, significantly improves reclassification in patients eligible for risk enhancers in 2018 ACC/AHA guidelines. Patients in low- and high-risk groups derive no significant improvement in risk reclassification from CCTA.
Publication
Journal: European Heart Journal Cardiovascular Imaging
March/30/2017
Abstract
UNASSIGNED
To investigate the long-term performance of the CONFIRM score for prediction of all-cause mortality in a large patient cohort undergoing coronary computed tomography angiography (CCTA).
UNASSIGNED
Patients with a 5-year follow-up from the international multicentre CONFIRM registry were included. The primary endpoint was all-cause mortality. The predictive value of the CONFIRM score over clinical risk scores (Morise, Framingham, and NCEP ATP III score) was studied in the entire patient population as well as in subgroups. Improvement in risk prediction and patient reclassification were assessed using categorical net reclassification index (NRI) and integrated discrimination improvement (IDI). During a median follow-up period of 5.3 years, 982 (6.5%) of 15 219 patients died. The CONFIRM score outperformed the prognostic value of the studied three clinical risk scores (c-indices: CONFIRM score 0.696, NCEP ATP III score 0.675, Framingham score 0.610, Morise score 0.606; c-index for improvement CONFIRM score vs. NCEP ATP III score 0.650, P < 0.0001). Application of the CONFIRM score allowed reclassification of 34% of patients when compared with the NCEP ATP III score, which was the best clinical risk score. Reclassification was significant as revealed by categorical NRI (0.06 with 95% CI 0.02 and 0.10, P = 0.005) and IDI (0.013 with 95% CI 0.01 and 0.015, P < 0.001). Subgroup analysis revealed a comparable performance in a variety of patient subgroups.
UNASSIGNED
The CONFIRM score permits a significantly improved prediction of mortality over clinical risk scores for >5 years after CCTA. These findings are consistent in a large variety of patient subgroups.
Publication
Journal: PLoS ONE
December/12/2018
Abstract
<AbstractText>The extent to which the presence and extent of subclinical atherosclerosis by coronary computed tomography angiography influences a potential mortality benefit of statin is unknown. We evaluated the relationship between statin therapy, mortality, and subclinical atherosclerosis.</AbstractText><AbstractText>In the CONFIRM study, patients with normal or non-obstructive plaque (<50% diameter stenosis) for whom data on baseline statin use was available were included. Coronary artery calcium (CAC) was quantified using the Agatston score. The extent of non-obstructive coronary atherosclerosis was quantified using the segment involvement score (SIS). 8,016 patients were followed for a median of 2.5 years with analysis of all-cause mortality and major adverse cardiac events (MACE) including all-cause mortality, myocardial infarction, unstable angina, target vessel revascularization, and coronary artery disease-related hospitalization.</AbstractText><AbstractText>1.2% of patients experienced all-cause mortality. Patients not on baseline statin therapy had a stepwise increased risk of all-cause mortality by CAC (relative to CAC = 0; CAC 1-99: hazard ratio [HR] 1.65, CAC 100-299: HR 2.19, and CAC≥300: HR 2.98) or SIS (relative to SIS = 0; SIS 1: HR 1.62, SIS 2-3: 2.48 and SIS≥4: 2.95). Conversely, in patients on baseline statin therapy, there was no significant increase in mortality risk with increasing CAC (p value for interaction = 0.049) or SIS (p value for interaction = 0.007). The incidence of MACE was 2.1%. Similar to the all-cause mortality, the risk of MACE was increased with CAC or SIS strata in patient not on baseline statin therapy. However, this relation was not observed in patient on baseline statin therapy.</AbstractText><AbstractText>In individuals with non-obstructive coronary artery disease, increased risk of adverse events occurs with increasing CAC or SIS who are not on baseline statin therapy. Statin therapy is associated with a mitigation of risk of cardiac events in the presence of increasing atherosclerosis, with no particular threshold of disease burden.</AbstractText>
Publication
Journal: European Heart Journal Cardiovascular Imaging
August/22/2017
Abstract
UNASSIGNED
To identify the effect of early revascularization on 5-year survival in patients with CAD diagnosed by coronary-computed tomographic angiography (CCTA).
UNASSIGNED
We examined 5544 stable patients with suspected CAD undergoing CCTA who were followed a median of 5.5 years in a large international registry. Patients were categorized as having low-, intermediate-, or high-risk CAD based on CCTA findings. Two treatment groups were defined: early revascularization within 90 days of CCTA (n = 1171) and medical therapy (n = 4373). To account for the non-randomized referral to revascularization, we developed a propensity score by logistic regression. This score was incorporated into Cox proportional hazard models to calculate the effect of revascularization on all-cause mortality. Death occurred in 363 (6.6%) patients and was more frequent in medical therapy. In multivariable models, when compared with medical therapy, the mortality benefit of revascularization varied significantly over time and by CAD risk (P for interaction 0.04). In high-risk CAD, revascularization was significantly associated with lower mortality at 1 year (hazard ratio [HR] 0.22, 95% confidence interval [CI] 0.11-0.47) and 5 years (HR 0.31, 95% CI 0.18-0.54). For intermediate-risk CAD, revascularization was associated with reduced mortality at 1 year (HR 0.45, 95% CI 0.22-0.93) but not 5 years (HR 0.63, 95% CI 0.33-1.20). For low-risk CAD, there was no survival benefit at either time point.
UNASSIGNED
Early revascularization was associated with reduced 1-year mortality in intermediate- and high-risk CAD detected by CCTA, but this association only persisted for 5-year mortality in high-risk CAD.
Publication
Journal: American Journal of Cardiology
March/9/2019
Abstract
The prognostic performance of coronary artery calcium score (CACS) for predicting adverse outcomes in patients with decreased renal function remains unclear. We aimed to examine whether CACS improves risk stratification by demonstrating incremental value beyond a traditional risk score according to renal function status. 9,563 individuals without known coronary artery disease were enrolled. Estimated glomerular filtration rate (eGFR, ml/min/1.73 m2) was ascertained using the modified Modification of Diet in Renal Disease formula, and was categorized as: ≥90, 60 to 89, and <60. CACS was categorized as 0, 1 to 100, 101 to 400, and >400. Multivariable Cox regression was used to estimate hazard ratios (HR) with 95% confidence intervals (95% CI) for major adverse cardiac events (MACE), comprising all-cause mortality, myocardial infarction, and late revascularization (>90 days). Mean age was 55.8 ± 11.5 years (52.8% male). In total, 261 (2.7%) patients experienced MACE over a median follow-up of 24.5 months (interquartile range: 16.9 to 41.1). Incident MACE increased with higher CACS across each eGFR category, with the highest rate observed among patients with CACS >400 and eGFR <60 (95.1 per 1,000 person-years). A CACS >400 increased MACE risk with HR 4.46 (95% CI 1.68 to 11.85), 6.63 (95% CI 4.03 to 10.92), and 6.14 (95% CI 2.85 to 13.21) for eGFR ≥90, 60 to 89, and <60, respectively, as compared with CACS 0. Further, CACS improved discrimination and reclassification beyond Framingham 10-year risk score (FRS) (AUC: 0.70 vs 0.64; category free-NRI: 0.51, all p <0.001) for predicting MACE in patients with impaired renal function (eGFR < 90). In conclusion, CACS improved risk stratification and provided incremental value beyond FRS for predicting MACE, irrespective of eGFR status.
Publication
Journal: Clinical Cardiology
October/14/2018
Abstract
Our objective was to assess the prognostic value of symptom typicality in patients without obstructive coronary artery disease (CAD), determined by coronary computed tomographic angiography (CCTA). We identified 4215 patients without prior history of CAD and without obstructive CAD (<50% CCTA stenosis). CAD severity was categorized as nonobstructive (1%-49%) and none (0%). Based upon the Diamond-Forrester criteria for angina pectoris, symptom typicality was classified as asymptomatic, nonanginal, atypical, and typical. Multivariable Cox proportional hazards models were used to assess the risk of major adverse cardiac events (MACE), comprising all-cause mortality, myocardial infarction, unstable angina, and late revascularization, according to symptom typicality. Mean patient age was 57.0 ±12.0 years (54.9% male). During a median follow-up of 5.3 years (interquartile range, 4.6-5.9 years), MACE were reported in 312 (7.4%) patients. Among patients with nonobstructive CAD, there was an association between symptom typicality and MACE (P for interaction = 0.05), driven by increased risk of MACE among those with typical angina and nonobstructive CAD (hazard ratio: 1.62, 95% confidence interval: 1.06-2.48, P = 0.03). No consistent relationship was found between symptom typicality and MACE among patients without any CAD (hazard ratio: 0.73, 95% confidence interval: 0.34-1.57, P = 0.08). In the CONFIRM registry, patients who presented with concomitant typical angina and nonobstructive CAD had a higher rate of MACE than did asymptomatic patients with nonobstructive CAD. However, the presence of typical angina did not appear to portend worse prognosis in patients with no CAD.
Publication
Journal: European Heart Journal Cardiovascular Imaging
April/17/2019
Abstract
The long-term prognostic value of coronary computed tomography angiography (CCTA)-identified coronary artery disease (CAD) has not been evaluated in elderly patients (≥70 years). We compared the ability of coronary CCTA to predict 5-year mortality in older vs. younger populations.From the prospective CONFIRM (COronary CT Angiography EvaluatioN For Clinical Outcomes: An InteRnational Multicenter) registry, we analysed CCTA results according to age <70 years (n = 7198) vs. ≥70 years (n = 1786). The severity of CAD was classified according to: (i) maximal stenosis degree per vessel: none, non-obstructive (1-49%), or obstructive (>50%); (ii) segment involvement score (SIS): number of segments with plaque. Cox-proportional hazard models assessed the relationship between CCTA findings and time to mortality. At a mean 5.6 ± 1.1 year follow-up, CCTA-identified CAD predicted increased mortality compared with patients with a normal CCTA in both <70 years [non-obstructive hazard ratio (HR) confidence interval (CI): 1.70 (1.19-2.41); one-vessel: 1.65 (1.03-2.67); two-vessel: 2.24 (1.21-4.15); three-vessel/left main: 4.12 (2.27-7.46), P < 0.001] and ≥70 years [non-obstructive: 1.84 (1.15-2.95); one-vessel: HR (CI): 2.28 (1.37-3.81); two-vessel: 2.36 (1.33-4.19); three-vessel/left main: 2.41 (1.33-4.36), P = 0.014]. Similarly, SIS was predictive of mortality in both <70 years [SIS 1-3: 1.57 (1.10-2.24); SIS ≥4: 2.42 (1.65-3.57), P < 0.001] and ≥70 years [SIS 1-3: 1.73 (1.07-2.79); SIS ≥4: 2.45 (1.52-3.93), P < 0.001]. CCTA findings similarly predicted long-term major adverse cardiovascular outcomes (MACE) (all-cause mortality, myocardial infarction, and late revascularization) in both groups compared with patients with no CAD.The presence and extent of CAD is a meaningful stratifier of long-term mortality and MACE in patients aged <70 years and ≥70 years old. The presence of obstructive and non-obstructive disease and the burden of atherosclerosis determined by SIS remain important predictors of prognosis in older populations.