Pre-test probability of obstructive coronary stenosis in patients undergoing coronary CT angiography: Comparative performance of the modified diamond-Forrester algorithm versus methods incorporating cardiovascular risk factors

doi:10.1016/j.ijcard.2016.07.180

International Journal of Cardiology

Volume 222, 1 November 2016, Pages 346-351

https://doi.org/10.1016/j.ijcard.2016.07.180 Get rights and content

Abstract

Background

Current guidelines recommend the use of the Modified Diamond-Forrester (MDF) method to assess the pre-test likelihood of obstructive coronary artery disease (CAD). We aimed to compare the performance of the MDF method with two contemporary algorithms derived from multicenter trials that additionally incorporate cardiovascular risk factors: the calculator-based ‘CAD Consortium 2’ method, and the integer-based CONFIRM score.

Methods

We assessed 1069 consecutive patients without known CAD undergoing coronary CT angiography (CCTA) for stable chest pain. Obstructive CAD was defined as the presence of coronary stenosis ≥ 50% on 64-slice dual-source CT. The three methods were assessed for calibration, discrimination, net reclassification, and changes in proposed downstream testing based upon calculated pre-test likelihoods.

Results

The observed prevalence of obstructive CAD was 13.8% (n = 147). Overestimations of the likelihood of obstructive CAD were 140.1%, 9.8%, and 18.8%, respectively, for the MDF, CAD Consortium 2 and CONFIRM methods. The CAD Consortium 2 showed greater discriminative power than the MDF method, with a C-statistic of 0.73 vs. 0.70 (p < 0.001), while the CONFIRM score did not (C-statistic 0.71, p = 0.492).

Reclassification of pre-test likelihood using the ‘CAD Consortium 2’ or CONFIRM scores resulted in a net reclassification improvement of 0.19 and 0.18, respectively, which would change the diagnostic strategy in approximately half of the patients.

Conclusions

Newer risk factor-encompassing models allow for a more precise estimation of pre-test probabilities of obstructive CAD than the guideline-recommended MDF method. Adoption of these scores may improve disease prediction and change the diagnostic pathway in a significant proportion of patients.

Introduction

Estimating the pretest probability of disease is a key step in the evaluation of patients with suspected coronary artery disease (CAD) as this influences clinical decision-making regarding the need for testing, the choice of test, and the interpretation of test results. The current European guidelines on the management of stable CAD recommend a tabular method for estimating pre-test likelihood of obstructive coronary stenosis based exclusively on age, sex and typicality of symptoms. [1] The underlying model uses a modified Diamond-Forrester (MDF) approach, which was extended to include patients older than 70 years, and updated by revising the predictive value of its variables. [2] Despite good internal validation measures, the proposed model was derived entirely from patients referred for invasive coronary angiography (ICA) rather than for non-invasive imaging, for which it is more commonly employed. Further, the MDF method does not account for important cardiovascular risk factors such as diabetes, hypertension or cigarette smoking. To address these shortcomings, new scores that include these risk factors were recently developed from multicenter efforts. The ‘CAD Consortium 2’ was derived from a pooled analysis of 5677 patients undergoing coronary computed tomography angiography (CCTA) and/or ICA in 18 centers in Europe and the United States, [3] while the recent CONFIRM score was developed from a cohort of 9093 patients undergoing CCTA in 8 centers from 6 countries. [4] Importantly, the CAD Consortium 2 score is a calculator-based score, while the CONFIRM score is an integer-based score aimed for easy calculation in the clinical setting.

The aim of this study was to compare the diagnostic performance of these 2 scores against the MDF method in patients referred for non-invasive coronary angiography. The 3 methods were assessed for calibration, discrimination and net reclassification, as well as for their ability to influence clinical decision making for intended downstream testing.

Section snippets

Population

We performed a retrospective analysis on prospectively collected data from a cohort of consecutive patients undergoing CCTA for the evaluation of CAD at our hospital between June 2011 and May 2014. Criteria for referral to CCTA were left to the discretion of the referring physician. Fig. 1 shows patient selection. Age < 30 years, known CAD, suspected acute coronary syndrome, preoperative assessment, and known left ventricular systolic dysfunction were among the exclusion criteria. Asymptomatic

Results

The baseline characteristics of the 1069 symptomatic patients undergoing CCTA for suspected CAD are listed in Table 2. The observed prevalence of obstructive CAD on CCTA was 13.8% (n = 147). Patients with obstructive CAD were more often male, were significantly older and had a higher prevalence of typical angina symptoms and of all the traditional cardiovascular risk factors except for family history. They also had significantly higher CAC scores (median 177, IQR 60–370) than those without

Discussion

In order to be clinically useful, a prediction tool should be well calibrated across the risk spectrum and provide good discrimination between patients with and without the outcome of interest. Overestimation of the likelihood of CAD, in particular, may expose patients to the risks and costs of unnecessary testing and may be partially responsible for the frequently reported low prevalence of obstructive disease in patients undergoing ICA. [2], [11], [12] While several studies have shown

Conclusions

In patients with stable chest pain undergoing CCTA, newer risk factor-encompassing models allow for a more precise estimation of pre-test probabilities of obstructive CAD than the guideline-recommended MDF method. Adoption of these scores may improve disease prediction and change the diagnostic pathway in a significant proportion of patients.

The following are the supplementary data related to this article.

Supplementary tables

. Receiver-operating characteristics curves of the three models

Grant support

None.

Conflicts of interest

The authors report no relationships that could be construed as a conflict of interest.

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Computed tomography coronary angiography (CTCA) is a non-invasive diagnostic modality that provides a comprehensive anatomical assessment of the coronary arteries and coronary atherosclerosis, including plaque burden, composition and morphology. The past decade has witnessed an increase in the role of CTCA for evaluating patients with both stable and acute chest pain, and recent international guidelines have provided increasing support for a first line CTCA diagnostic strategy in select patients. CTCA offers some advantages over current functional tests in the detection of obstructive and non-obstructive coronary artery disease, as well as for ruling out obstructive coronary artery disease. Recent randomised trials have also shown that CTCA improves prognostication and guides the use of guideline-directed preventive therapies, leading to improved clinical outcomes. CTCA technology advances such as fractional flow reserve, plaque quantification and perivascular fat inflammation potentially allow for more personalised risk assessment and targeted therapies. Further studies evaluating demand, supply, and cost-effectiveness of CTCA for evaluating chest pain are required in Australia. This discussion paper revisits the evidence supporting the use of CTCA, provides an overview of its implications and limitations, and considers its potential role for chest pain evaluation pathways in Australia.
The updated pre-test probability model of the 2019 ESC guidelines improves prediction of obstructive coronary artery disease
2022, Revista Portuguesa de Cardiologia
Citation Excerpt :
The use of the same tabular method, including identical variables, probably explains these results. Likewise, in agreement with other reports assessing patients referred for non-invasive imaging, the prevalence of obstructive CAD in our study population of patients referred for CCTA was generally low.23,24 Reclassification of risk using the new PTP method instead of MDF could change the diagnostic strategy in a significant proportion of patients.
The 2019 ESC guidelines on chronic coronary syndromes updated the method for estimating the pre-test probability (PTP) of obstructive coronary artery disease (CAD). We aimed to compare the performance of the new PTP method against the 2013 prediction model in patients with stable chest pain undergoing coronary computed tomography angiography (CCTA) for suspected CAD.
We conducted a single-center cross-sectional study enrolling 320 consecutive patients undergoing CCTA for suspected CAD. Obstructive CAD was defined as any ≥50% luminal stenosis on CCTA. Whenever invasive coronary angiography was subsequently performed, patients were reclassified accordingly. The two PTP prediction models were assessed for calibration, discrimination and the ability to change the downstream diagnostic pathway.
The observed prevalence of obstructive CAD was 16.3% (n=52). The 2013 prediction model significantly overestimated the likelihood of obstructive CAD (relative overestimation of 130%, p=0.005), while the updated 2019 method showed good calibration (relative underestimation of 6.5%, p=0.712). The two approaches showed similar discriminative power, with C-statistics of 0.73 (95% CI: 0.66-0.80) and 0.74 (95% CI: 0.66-0.81) for the 2013 and 2019 methods, respectively (p=0.933). Reclassification of PTP using the new method resulted in a net reclassification improvement of 0.10 (p=0.001).
The updated 2019 prediction model provides a more accurate estimation of pre-test probabilities of obstructive CAD than the previous model. Adoption of this new score may improve disease prediction and influence the selection of non-invasive testing.
As novas guidelines da ESC de síndromes coronárias crónicas de 2019 atualizaram o método para estimar a probabilidade pré-teste (PPT) de doença arterial coronária (DAC) obstrutiva. O objetivo do nosso trabalho foi comparar o desempenho do novo método de estimativa da PPT com o modelo de 2013 em doentes com angina estável submetidos a angiotomografia das artérias coronárias por suspeita de DAC.
Foi realizado um estudo transversal de centro único envolvendo 320 doentes consecutivos submetidos a angiotomografia coronária por suspeita de DAC. DAC obstrutiva foi definida como qualquer estenose ≥50% na angiotomografia. Sempre que realizada angiografia coronária invasiva, os doentes foram reclassificados em conformidade. Os dois modelos de previsão da PPT foram avaliados quanto à calibração, discriminação e capacidade para alterar a marcha diagnóstica subsequente.
A prevalência observada de DAC obstrutiva foi de 16,3% (n=52). O modelo de previsão de 2013 sobrestimou significativamente a probabilidade de DAC obstrutiva (sobrestimação relativa de 130%, valor-p 0,005), enquanto o método de 2019 mostrou uma boa calibração (subestimativa relativa de 6,5%, valor-p 0,712). As duas abordagens mostraram poder discriminativo semelhante, com estatística C de 0,73 (IC 95%: 0,66-0,80) e 0,74 (IC 95%: 0,66-0,81) para os métodos de 2013 e 2019, respetivamente (valor-p 0,933). A reclassificação da PPT usando o novo método resultou numa melhoria de reclassificação líquida de 0,10 (valor-p=0,001).
O modelo de previsão atualizado de 2019 permite uma estimativa mais precisa das probabilidades pré-teste de DAC obstrutiva do que o modelo anterior. A adoção deste novo método pode melhorar a previsão de doença e ter impacto na seleção dos testes diagnósticos não invasivos.
2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines
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This clinical practice guideline for the evaluation and diagnosis of chest pain provides recommendations and algorithms for clinicians to assess and diagnose chest pain in adult patients.
A comprehensive literature search was conducted from November 11, 2017, to May 1, 2020, encompassing randomized and nonrandomized trials, observational studies, registries, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Collaboration, Agency for Healthcare Research and Quality reports, and other relevant databases. Additional relevant studies, published through April 2021, were also considered.
Chest pain is a frequent cause for emergency department visits in the United States. The “2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain” provides recommendations based on contemporary evidence on the assessment and evaluation of chest pain. This guideline presents an evidence-based approach to risk stratification and the diagnostic workup for the evaluation of chest pain. Cost-value considerations in diagnostic testing have been incorporated, and shared decision-making with patients is recommended.
2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain: A Report of the American College of Cardiology/American Heart Association Joint Committee on Clinical Practice Guidelines
2021, Journal of the American College of Cardiology
This clinical practice guideline for the evaluation and diagnosis of chest pain provides recommendations and algorithms for clinicians to assess and diagnose chest pain in adult patients.
A comprehensive literature search was conducted from November 11, 2017, to May 1, 2020, encompassing randomized and nonrandomized trials, observational studies, registries, reviews, and other evidence conducted on human subjects that were published in English from PubMed, EMBASE, the Cochrane Collaboration, Agency for Healthcare Research and Quality reports, and other relevant databases. Additional relevant studies, published through April 2021, were also considered.
Chest pain is a frequent cause for emergency department visits in the United States. The “2021 AHA/ACC/ASE/CHEST/SAEM/SCCT/SCMR Guideline for the Evaluation and Diagnosis of Chest Pain” provides recommendations based on contemporary evidence on the assessment and evaluation of chest pain. This guideline presents an evidence-based approach to risk stratification and the diagnostic workup for the evaluation of chest pain. Cost-value considerations in diagnostic testing have been incorporated, and shared decision-making with patients is recommended.
Comparison of the CAD consortium and updated Diamond-Forrester scores for predicting obstructive coronary artery disease
2021, American Journal of Emergency Medicine
Citation Excerpt :
Our study estimated that the CAD consortium clinical model could result in a two-fold increase in the number of patients who can be categorized as low-risk and subsequently would not require additional clinical examination (53% vs 23%). This result adds to the findings of previous studies suggesting that the updated DF model overestimates the likelihood of CAD and is less discriminative than CAD consortium models [7,16]. CAD consortium models, especially the clinical model, were better calibrated than the updated DF model.
Current guidelines recommend the use of the updated Diamond–Forrester (DF) method and Coronary Artery Disease (CAD) Consortium models to assess the pretest probability of obstructive CAD. The present study aimed to compare the performance of these models among patients with chest pain evaluated in an emergency department (ED).
We compared three scores (DF, CAD consortium basic, and clinical) among 1247 consecutive patients with chest pain who underwent coronary computed tomographic angiography (CTA). Invasive angiography was performed to confirm the stenosis for those who showed obstructive CAD on CTA, if clinically indicated. Primary outcome was the presence of obstructive CAD (≧50% stenosis).
Overall, 426 (34.2%) patients were diagnosed with obstructive CAD. The expected prevalence of CAD was underestimated by the CAD consortium clinical model (23.4%) and overestimated by the DF model (53.1%). For the prediction of obstructive CAD, the CAD consortium clinical model had superior area under the receiver-operating curve (0.754), followed by the CAD consortium basic (0.736), and finally, the DF model (0.718). Whereas the CAD consortium models more accurately classified patients without any CAD or nonobstructive CAD as low-risk patients, the DF model more accurately classified high-risk patients with obstructive CAD. The net reclassification improvement of CAD consortium basic and clinical models were 24.7% and 27.9%, respectively.
Compared with the DF model, the CAD consortium clinical model appears to improve the prediction of low-risk patients with <15% probability of having obstructive CAD. However, this model needs caution when using in high-risk population.
Identifying low-risk chest pain in the emergency department: Obstructive coronary artery disease and major adverse cardiac events
2020, American Journal of Emergency Medicine
Citation Excerpt :
The cardiac troponin I (cTnI-Ultra) assay was performed using Siemens ADVIA Centaur (Siemens, Munich, Germany) with 99th percentile of 0.04 g/L as a cutoff for myocardial necrosis [14]. The pretest probability of obstructive CAD was calculated using three scores: the CAD consortium basic, CAD consortium clinical model, and uDF method [15,16]. We used an updated version of the DF score, which allows the inclusion of patients ≧70 years of age and incorporates age as a continuous variable.
Accurate risk stratification for obstructive coronary artery disease (CAD) and major cardiac adverse events (MACE) is important in emergency departments. We compared six established chest pain risk scores (the HEART score, CAD basic model, CAD clinical model, TIMI, GRACE, uDF) for prediction of obstructive CAD and MACE.
Patients who presented to the emergency department with chest pain or symptoms of suspected CAD and underwent coronary computed tomographic angiography were analyzed. The primary endpoint was adverse outcomes including the presence of obstructive CAD (≥50% stenosis) and the occurrence of MACE within 6 weeks. We compared the risk scores by the area under the receiver-operating characteristic curve (AUC) and calculated their respective net reclassification index (NRI).
Adverse outcomes occurred in 285 (28.4%) out of the 1002 patients included. For the prediction of adverse outcomes, the AUC of the HEART score (0.792) was superior to those of the CAD clinical model (0.760), CAD basic model (0.749), TIMI (0.749), uDF (0.703), and GRACE (0.653). In terms of the NRI, the HEART score significantly improved the reclassification abilities of the uDF (0.39), GRACE score (0.27), CAD basic model (0.11), TIMI (0.10), and CAD clinical model (0.08) (all P < 0.05). The HEART score also had the highest negative predictive value as well (0.893).
The HEART score was superior to other cardiac risk scores in predicting both obstructive CAD and MACE. However, due to the high false-negative rate (11%) of the HEART score, its use for identifying low-risk patients should be considered with caution.

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¹: This author takes responsibility for all aspects of the reliability and freedom from bias of the data presented and their discussed interpretation.

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Pre-test probability of obstructive coronary stenosis in patients undergoing coronary CT angiography: Comparative performance of the modified diamond-Forrester algorithm versus methods incorporating cardiovascular risk factors

Abstract

Background

Methods

Results

Conclusions

Introduction

Section snippets

Population

Results

Discussion

Conclusions

Grant support

Conflicts of interest

Am. J. Med.

J. Am. Coll. Cardiol.

Am. J. Cardiol.

J. Cardiovasc. Comput. Tomogr.

Rev. Port. Cardiol.

J. Cardiovasc. Comput. Tomogr.

Am. J. Cardiol.

Atherosclerosis

Am. J. Cardiol.

Heart

J. Am. Coll. Cardiol.