Medical History for Prognostic Risk Assessment and Diagnosis of Stable Patients with Suspected Coronary Artery Disease

James K. Min, Allison Dunning, Heidi Gransar, Stephan Achenbach, Fay Y. Lin, Mouaz Al-Mallah, Matthew J. Budoff, Tracy Q. Callister, Hyuk Jae Chang, Filippo Cademartiri, Erica Maffei, Kavitha Chinnaiyan, Benjamin J.W. Chow, Ralph D'Agostino, Augustin Delago, John Friedman, Martin Hadamitzky, Joerg Hausleiter, Sean W. Hayes, Philipp KaufmannGilbert L. Raff, Leslee J. Shaw, Louise Thomson, Todd Villines, Ricardo C. Cury, Gudrun Feuchtner, Yong Jin Kim, Jonathon Leipsic, Hugo Marques, Daniel S. Berman, Michael Pencina

Research output: Contribution to journalArticle

19 Citations (Scopus)

Abstract

Objective To develop a clinical cardiac risk algorithm for stable patients with suspected coronary artery disease based upon angina typicality and coronary artery disease risk factors. Methods Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9093 patients for coronary computed tomography angiography (CCTA) followed for 2.0 years (CCTA-1); 2) 2132 patients for CCTA followed for 1.6 years (CCTA-2); and 3) 2779 patients for exercise myocardial perfusion scintigraphy (MPS) followed for 5.0 years. A best-fit model from CCTA-1 for prediction of death or myocardial infarction was developed, with integer values proportional to regression coefficients. Discrimination was assessed using C-statistic. The validated model was tested for estimation of the likelihood of obstructive coronary artery disease, defined as ≥50% stenosis, as compared with the method of Diamond and Forrester. Primary outcomes included all-cause mortality and nonfatal myocardial infarction. Secondary outcomes included prevalent angiographically obstructive coronary artery disease. Results In CCTA-1, best-fit model discriminated individuals at risk of death or myocardial infarction (C-statistic 0.76). The integer model ranged from 3 to 13, corresponding to 3-year death risk or myocardial infarction of 0.25% to 53.8%. When applied to CCTA-2 and MPS cohorts, the model demonstrated C-statistics of 0.71 and 0.77, respectively. Both best-fit (C = 0.76; 95% confidence interval [CI], 0.746-0.771) and integer models (C = 0.71; 95% CI, 0.693-0.719) performed better than Diamond and Forrester (C = 0.64; 95% CI, 0.628-0.659) for estimating obstructive coronary artery disease. Conclusions For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease.

Original languageEnglish
Pages (from-to)871-878
Number of pages8
JournalAmerican Journal of Medicine
Volume128
Issue number8
DOIs
Publication statusPublished - 2015 Aug 1

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Coronary Artery Disease
Myocardial Infarction
Diamond
Myocardial Perfusion Imaging
Perfusion Imaging
Confidence Intervals
Computed Tomography Angiography
Pathologic Constriction
History
Exercise
Mortality

All Science Journal Classification (ASJC) codes

  • Medicine(all)

Cite this

Min, James K. ; Dunning, Allison ; Gransar, Heidi ; Achenbach, Stephan ; Lin, Fay Y. ; Al-Mallah, Mouaz ; Budoff, Matthew J. ; Callister, Tracy Q. ; Chang, Hyuk Jae ; Cademartiri, Filippo ; Maffei, Erica ; Chinnaiyan, Kavitha ; Chow, Benjamin J.W. ; D'Agostino, Ralph ; Delago, Augustin ; Friedman, John ; Hadamitzky, Martin ; Hausleiter, Joerg ; Hayes, Sean W. ; Kaufmann, Philipp ; Raff, Gilbert L. ; Shaw, Leslee J. ; Thomson, Louise ; Villines, Todd ; Cury, Ricardo C. ; Feuchtner, Gudrun ; Kim, Yong Jin ; Leipsic, Jonathon ; Marques, Hugo ; Berman, Daniel S. ; Pencina, Michael. / Medical History for Prognostic Risk Assessment and Diagnosis of Stable Patients with Suspected Coronary Artery Disease. In: American Journal of Medicine. 2015 ; Vol. 128, No. 8. pp. 871-878.
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abstract = "Objective To develop a clinical cardiac risk algorithm for stable patients with suspected coronary artery disease based upon angina typicality and coronary artery disease risk factors. Methods Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9093 patients for coronary computed tomography angiography (CCTA) followed for 2.0 years (CCTA-1); 2) 2132 patients for CCTA followed for 1.6 years (CCTA-2); and 3) 2779 patients for exercise myocardial perfusion scintigraphy (MPS) followed for 5.0 years. A best-fit model from CCTA-1 for prediction of death or myocardial infarction was developed, with integer values proportional to regression coefficients. Discrimination was assessed using C-statistic. The validated model was tested for estimation of the likelihood of obstructive coronary artery disease, defined as ≥50{\%} stenosis, as compared with the method of Diamond and Forrester. Primary outcomes included all-cause mortality and nonfatal myocardial infarction. Secondary outcomes included prevalent angiographically obstructive coronary artery disease. Results In CCTA-1, best-fit model discriminated individuals at risk of death or myocardial infarction (C-statistic 0.76). The integer model ranged from 3 to 13, corresponding to 3-year death risk or myocardial infarction of 0.25{\%} to 53.8{\%}. When applied to CCTA-2 and MPS cohorts, the model demonstrated C-statistics of 0.71 and 0.77, respectively. Both best-fit (C = 0.76; 95{\%} confidence interval [CI], 0.746-0.771) and integer models (C = 0.71; 95{\%} CI, 0.693-0.719) performed better than Diamond and Forrester (C = 0.64; 95{\%} CI, 0.628-0.659) for estimating obstructive coronary artery disease. Conclusions For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease.",
author = "Min, {James K.} and Allison Dunning and Heidi Gransar and Stephan Achenbach and Lin, {Fay Y.} and Mouaz Al-Mallah and Budoff, {Matthew J.} and Callister, {Tracy Q.} and Chang, {Hyuk Jae} and Filippo Cademartiri and Erica Maffei and Kavitha Chinnaiyan and Chow, {Benjamin J.W.} and Ralph D'Agostino and Augustin Delago and John Friedman and Martin Hadamitzky and Joerg Hausleiter and Hayes, {Sean W.} and Philipp Kaufmann and Raff, {Gilbert L.} and Shaw, {Leslee J.} and Louise Thomson and Todd Villines and Cury, {Ricardo C.} and Gudrun Feuchtner and Kim, {Yong Jin} and Jonathon Leipsic and Hugo Marques and Berman, {Daniel S.} and Michael Pencina",
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Min, JK, Dunning, A, Gransar, H, Achenbach, S, Lin, FY, Al-Mallah, M, Budoff, MJ, Callister, TQ, Chang, HJ, Cademartiri, F, Maffei, E, Chinnaiyan, K, Chow, BJW, D'Agostino, R, Delago, A, Friedman, J, Hadamitzky, M, Hausleiter, J, Hayes, SW, Kaufmann, P, Raff, GL, Shaw, LJ, Thomson, L, Villines, T, Cury, RC, Feuchtner, G, Kim, YJ, Leipsic, J, Marques, H, Berman, DS & Pencina, M 2015, 'Medical History for Prognostic Risk Assessment and Diagnosis of Stable Patients with Suspected Coronary Artery Disease', American Journal of Medicine, vol. 128, no. 8, pp. 871-878. https://doi.org/10.1016/j.amjmed.2014.10.031

Medical History for Prognostic Risk Assessment and Diagnosis of Stable Patients with Suspected Coronary Artery Disease. / Min, James K.; Dunning, Allison; Gransar, Heidi; Achenbach, Stephan; Lin, Fay Y.; Al-Mallah, Mouaz; Budoff, Matthew J.; Callister, Tracy Q.; Chang, Hyuk Jae; Cademartiri, Filippo; Maffei, Erica; Chinnaiyan, Kavitha; Chow, Benjamin J.W.; D'Agostino, Ralph; Delago, Augustin; Friedman, John; Hadamitzky, Martin; Hausleiter, Joerg; Hayes, Sean W.; Kaufmann, Philipp; Raff, Gilbert L.; Shaw, Leslee J.; Thomson, Louise; Villines, Todd; Cury, Ricardo C.; Feuchtner, Gudrun; Kim, Yong Jin; Leipsic, Jonathon; Marques, Hugo; Berman, Daniel S.; Pencina, Michael.

In: American Journal of Medicine, Vol. 128, No. 8, 01.08.2015, p. 871-878.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Medical History for Prognostic Risk Assessment and Diagnosis of Stable Patients with Suspected Coronary Artery Disease

AU - Min, James K.

AU - Dunning, Allison

AU - Gransar, Heidi

AU - Achenbach, Stephan

AU - Lin, Fay Y.

AU - Al-Mallah, Mouaz

AU - Budoff, Matthew J.

AU - Callister, Tracy Q.

AU - Chang, Hyuk Jae

AU - Cademartiri, Filippo

AU - Maffei, Erica

AU - Chinnaiyan, Kavitha

AU - Chow, Benjamin J.W.

AU - D'Agostino, Ralph

AU - Delago, Augustin

AU - Friedman, John

AU - Hadamitzky, Martin

AU - Hausleiter, Joerg

AU - Hayes, Sean W.

AU - Kaufmann, Philipp

AU - Raff, Gilbert L.

AU - Shaw, Leslee J.

AU - Thomson, Louise

AU - Villines, Todd

AU - Cury, Ricardo C.

AU - Feuchtner, Gudrun

AU - Kim, Yong Jin

AU - Leipsic, Jonathon

AU - Marques, Hugo

AU - Berman, Daniel S.

AU - Pencina, Michael

PY - 2015/8/1

Y1 - 2015/8/1

N2 - Objective To develop a clinical cardiac risk algorithm for stable patients with suspected coronary artery disease based upon angina typicality and coronary artery disease risk factors. Methods Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9093 patients for coronary computed tomography angiography (CCTA) followed for 2.0 years (CCTA-1); 2) 2132 patients for CCTA followed for 1.6 years (CCTA-2); and 3) 2779 patients for exercise myocardial perfusion scintigraphy (MPS) followed for 5.0 years. A best-fit model from CCTA-1 for prediction of death or myocardial infarction was developed, with integer values proportional to regression coefficients. Discrimination was assessed using C-statistic. The validated model was tested for estimation of the likelihood of obstructive coronary artery disease, defined as ≥50% stenosis, as compared with the method of Diamond and Forrester. Primary outcomes included all-cause mortality and nonfatal myocardial infarction. Secondary outcomes included prevalent angiographically obstructive coronary artery disease. Results In CCTA-1, best-fit model discriminated individuals at risk of death or myocardial infarction (C-statistic 0.76). The integer model ranged from 3 to 13, corresponding to 3-year death risk or myocardial infarction of 0.25% to 53.8%. When applied to CCTA-2 and MPS cohorts, the model demonstrated C-statistics of 0.71 and 0.77, respectively. Both best-fit (C = 0.76; 95% confidence interval [CI], 0.746-0.771) and integer models (C = 0.71; 95% CI, 0.693-0.719) performed better than Diamond and Forrester (C = 0.64; 95% CI, 0.628-0.659) for estimating obstructive coronary artery disease. Conclusions For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease.

AB - Objective To develop a clinical cardiac risk algorithm for stable patients with suspected coronary artery disease based upon angina typicality and coronary artery disease risk factors. Methods Between 2004 and 2011, 14,004 adults with suspected coronary artery disease referred for cardiac imaging were followed: 1) 9093 patients for coronary computed tomography angiography (CCTA) followed for 2.0 years (CCTA-1); 2) 2132 patients for CCTA followed for 1.6 years (CCTA-2); and 3) 2779 patients for exercise myocardial perfusion scintigraphy (MPS) followed for 5.0 years. A best-fit model from CCTA-1 for prediction of death or myocardial infarction was developed, with integer values proportional to regression coefficients. Discrimination was assessed using C-statistic. The validated model was tested for estimation of the likelihood of obstructive coronary artery disease, defined as ≥50% stenosis, as compared with the method of Diamond and Forrester. Primary outcomes included all-cause mortality and nonfatal myocardial infarction. Secondary outcomes included prevalent angiographically obstructive coronary artery disease. Results In CCTA-1, best-fit model discriminated individuals at risk of death or myocardial infarction (C-statistic 0.76). The integer model ranged from 3 to 13, corresponding to 3-year death risk or myocardial infarction of 0.25% to 53.8%. When applied to CCTA-2 and MPS cohorts, the model demonstrated C-statistics of 0.71 and 0.77, respectively. Both best-fit (C = 0.76; 95% confidence interval [CI], 0.746-0.771) and integer models (C = 0.71; 95% CI, 0.693-0.719) performed better than Diamond and Forrester (C = 0.64; 95% CI, 0.628-0.659) for estimating obstructive coronary artery disease. Conclusions For stable symptomatic patients with suspected coronary artery disease, we developed a history-based method for prediction of death and obstructive coronary artery disease.

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