Differential risk reclassification improvement by exercise testing and myocardial perfusion imaging in patients with suspected and known coronary artery disease
The objective of this study is to compare the incremental prognostic and net risk reclassification value of exercise testing alone vs exercise myocardial perfusion imaging (MPI) for estimating the risk of death in patients with suspected and known coronary artery disease (CAD). 6702 patients with su...
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| Veröffentlicht in: | Journal of nuclear cardiology 2016-06, Vol.23 (3), p.366-378 |
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| creator | Koh, Angela S. Gao, Fei Chin, C.T. Keng, Felix Y.J. Tan, Ru-San Chua, Terrance S.J. |
| description | The objective of this study is to compare the incremental prognostic and net risk reclassification value of exercise testing alone vs exercise myocardial perfusion imaging (MPI) for estimating the risk of death in patients with suspected and known coronary artery disease (CAD).
6702 patients with suspected CAD and 2008 with known CAD had treadmill exercise MPI and were followed for 2.5 ± 0.9 years for the occurrence of all-cause death. The estimation of risk of death and net reclassification improvement (NRI) were examined in three models. Model 1: clinical variables; Model 2: model 1+Duke Treadmill Score; and Model 3: model 2+ MPI variables. Risk estimates were categorized as 3% risk of death per year.
In patients with suspected CAD, the global Chi-square for predicting risk of death increased significantly for Model 2 compared to Model 1 (74.78 vs 63.86 to (P = .001). However, adding MPI variables in Model 3 did not further improve predictive value (Chi-square 79.38, P = .10). In patients with suspected CAD risk, reclassification improved significantly in Model 2 over Model 1 (NRI = 0.12, 95% CI 0.02 to 0.22, P = .019), but not in Model 3 (NRI = 0.0009, 95% CI −0.072 to 0.070; P = .98). In contrast, in patients with known CAD Model 2 did not yield significant improvements for predicting risk and risk reclassification compared to Model 1. However, global Chi-square of Model 3 was significantly higher than that of Model 2 (30.03 vs 6.56, P < .0001) with associated significant reclassification improvement (NRI = 0.26 95% CI 0.067 to 0.46. P = .0084).
Risk reclassification by diagnostic testing is importantly influenced by baseline characteristics of patient cohorts. In patients with suspected CAD, NRI is predominately achieved by exercise variables, whereas in patients with known CAD, greatest NRI is obtained by MPI variables. |
| doi_str_mv | 10.1007/s12350-015-0253-x |
| format | Article |
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6702 patients with suspected CAD and 2008 with known CAD had treadmill exercise MPI and were followed for 2.5 ± 0.9 years for the occurrence of all-cause death. The estimation of risk of death and net reclassification improvement (NRI) were examined in three models. Model 1: clinical variables; Model 2: model 1+Duke Treadmill Score; and Model 3: model 2+ MPI variables. Risk estimates were categorized as <1%, 1-3%, and >3% risk of death per year.
In patients with suspected CAD, the global Chi-square for predicting risk of death increased significantly for Model 2 compared to Model 1 (74.78 vs 63.86 to (P = .001). However, adding MPI variables in Model 3 did not further improve predictive value (Chi-square 79.38, P = .10). In patients with suspected CAD risk, reclassification improved significantly in Model 2 over Model 1 (NRI = 0.12, 95% CI 0.02 to 0.22, P = .019), but not in Model 3 (NRI = 0.0009, 95% CI −0.072 to 0.070; P = .98). In contrast, in patients with known CAD Model 2 did not yield significant improvements for predicting risk and risk reclassification compared to Model 1. However, global Chi-square of Model 3 was significantly higher than that of Model 2 (30.03 vs 6.56, P < .0001) with associated significant reclassification improvement (NRI = 0.26 95% CI 0.067 to 0.46. P = .0084).
Risk reclassification by diagnostic testing is importantly influenced by baseline characteristics of patient cohorts. In patients with suspected CAD, NRI is predominately achieved by exercise variables, whereas in patients with known CAD, greatest NRI is obtained by MPI variables.</description><identifier>ISSN: 1071-3581</identifier><identifier>EISSN: 1532-6551</identifier><identifier>DOI: 10.1007/s12350-015-0253-x</identifier><identifier>PMID: 26358085</identifier><language>eng</language><publisher>New York: Elsevier Inc</publisher><subject>Cardiology ; Coronary Artery Disease - diagnostic imaging ; Coronary Artery Disease - mortality ; Death, Sudden, Cardiac - epidemiology ; diagnostic and prognostic application ; Exercise Test - statistics & numerical data ; exercise: stress testing ; Female ; Humans ; Imaging ; Male ; Medicine ; Medicine & Public Health ; Middle Aged ; Myocardial Perfusion Imaging - methods ; Myocardial Perfusion Imaging - statistics & numerical data ; Myocardial perfusion imaging: SPECT ; Nuclear Medicine ; Original Article ; Prevalence ; Prognosis ; Proportional Hazards Models ; Radiology ; Reproducibility of Results ; Risk Assessment - methods ; Risk Factors ; Sensitivity and Specificity ; Singapore - epidemiology ; Survival Analysis ; Tomography, Emission-Computed, Single-Photon - statistics & numerical data</subject><ispartof>Journal of nuclear cardiology, 2016-06, Vol.23 (3), p.366-378</ispartof><rights>2016 American Society of Nuclear Cardiology. Published by ELSEVIER INC. All rights reserved.</rights><rights>American Society of Nuclear Cardiology 2015</rights><rights>American Society of Nuclear Cardiology 2016</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c424t-ee3d6f45cb0ee1a0e765e49629474b414a2ee156c208d32467a0c9de8ce73a663</citedby><cites>FETCH-LOGICAL-c424t-ee3d6f45cb0ee1a0e765e49629474b414a2ee156c208d32467a0c9de8ce73a663</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://link.springer.com/content/pdf/10.1007/s12350-015-0253-x$$EPDF$$P50$$Gspringer$$H</linktopdf><linktohtml>$$Uhttps://link.springer.com/10.1007/s12350-015-0253-x$$EHTML$$P50$$Gspringer$$H</linktohtml><link.rule.ids>314,776,780,27901,27902,41464,42533,51294</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26358085$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Koh, Angela S.</creatorcontrib><creatorcontrib>Gao, Fei</creatorcontrib><creatorcontrib>Chin, C.T.</creatorcontrib><creatorcontrib>Keng, Felix Y.J.</creatorcontrib><creatorcontrib>Tan, Ru-San</creatorcontrib><creatorcontrib>Chua, Terrance S.J.</creatorcontrib><title>Differential risk reclassification improvement by exercise testing and myocardial perfusion imaging in patients with suspected and known coronary artery disease</title><title>Journal of nuclear cardiology</title><addtitle>J. Nucl. Cardiol</addtitle><addtitle>J Nucl Cardiol</addtitle><description>The objective of this study is to compare the incremental prognostic and net risk reclassification value of exercise testing alone vs exercise myocardial perfusion imaging (MPI) for estimating the risk of death in patients with suspected and known coronary artery disease (CAD).
6702 patients with suspected CAD and 2008 with known CAD had treadmill exercise MPI and were followed for 2.5 ± 0.9 years for the occurrence of all-cause death. The estimation of risk of death and net reclassification improvement (NRI) were examined in three models. Model 1: clinical variables; Model 2: model 1+Duke Treadmill Score; and Model 3: model 2+ MPI variables. Risk estimates were categorized as <1%, 1-3%, and >3% risk of death per year.
In patients with suspected CAD, the global Chi-square for predicting risk of death increased significantly for Model 2 compared to Model 1 (74.78 vs 63.86 to (P = .001). However, adding MPI variables in Model 3 did not further improve predictive value (Chi-square 79.38, P = .10). In patients with suspected CAD risk, reclassification improved significantly in Model 2 over Model 1 (NRI = 0.12, 95% CI 0.02 to 0.22, P = .019), but not in Model 3 (NRI = 0.0009, 95% CI −0.072 to 0.070; P = .98). In contrast, in patients with known CAD Model 2 did not yield significant improvements for predicting risk and risk reclassification compared to Model 1. However, global Chi-square of Model 3 was significantly higher than that of Model 2 (30.03 vs 6.56, P < .0001) with associated significant reclassification improvement (NRI = 0.26 95% CI 0.067 to 0.46. P = .0084).
Risk reclassification by diagnostic testing is importantly influenced by baseline characteristics of patient cohorts. In patients with suspected CAD, NRI is predominately achieved by exercise variables, whereas in patients with known CAD, greatest NRI is obtained by MPI variables.</description><subject>Cardiology</subject><subject>Coronary Artery Disease - diagnostic imaging</subject><subject>Coronary Artery Disease - mortality</subject><subject>Death, Sudden, Cardiac - epidemiology</subject><subject>diagnostic and prognostic application</subject><subject>Exercise Test - statistics & numerical data</subject><subject>exercise: stress testing</subject><subject>Female</subject><subject>Humans</subject><subject>Imaging</subject><subject>Male</subject><subject>Medicine</subject><subject>Medicine & Public Health</subject><subject>Middle Aged</subject><subject>Myocardial Perfusion Imaging - methods</subject><subject>Myocardial Perfusion Imaging - statistics & numerical data</subject><subject>Myocardial perfusion imaging: SPECT</subject><subject>Nuclear Medicine</subject><subject>Original Article</subject><subject>Prevalence</subject><subject>Prognosis</subject><subject>Proportional Hazards Models</subject><subject>Radiology</subject><subject>Reproducibility of Results</subject><subject>Risk Assessment - methods</subject><subject>Risk Factors</subject><subject>Sensitivity and Specificity</subject><subject>Singapore - epidemiology</subject><subject>Survival Analysis</subject><subject>Tomography, Emission-Computed, Single-Photon - statistics & numerical data</subject><issn>1071-3581</issn><issn>1532-6551</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>BENPR</sourceid><recordid>eNp9kc1u1TAQhSMEoqXwAGyQJTZsArZjO4lYoZY_qRIbWFu-9uTiNnGCJ2nvfRselQkpCLHoaiz7O2c8c4riueCvBef1GxSy0rzkQpdc6qo8PChOha5kabQWD-nMa1FWuhEnxRPEK855W7Xt4-JEGrrljT4tfl7EroMMaY6uZzniNcvge4cYu-jdHMfE4jDl8QYGgtjuyOAA2UcENgPOMe2ZS4ENx9G7HFaTCXK34CZ0-xWIiU1kRXpkt3H-znDBCfwM4bf2Oo23ifkxj8nlI3N5BiqBWjiEp8WjzvUIz-7qWfHtw_uv55_Kyy8fP5-_uyy9kmouAapgOqX9jgMIx6E2GlRrZKtqtVNCOUn32njJm1BJZWrHfRug8VBXzpjqrHi1-dKsPxaazA4RPfS9SzAuaEXdtFy1vOaEvvwPvRqXnOh3K9WYtlG6IUpslM8jYobOTpkWko9WcLvGZ7f4LMVn1_jsgTQv7pyX3QDhr-JPXgTIDUB6SnvI_7S-x_XtJgLa300kEXoKw0OIlPVswxjvUf8CWim9ow</recordid><startdate>20160601</startdate><enddate>20160601</enddate><creator>Koh, Angela S.</creator><creator>Gao, Fei</creator><creator>Chin, C.T.</creator><creator>Keng, Felix Y.J.</creator><creator>Tan, Ru-San</creator><creator>Chua, Terrance S.J.</creator><general>Elsevier Inc</general><general>Springer US</general><general>Springer Nature B.V</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88E</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M1P</scope><scope>NAPCQ</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>7X8</scope></search><sort><creationdate>20160601</creationdate><title>Differential risk reclassification improvement by exercise testing and myocardial perfusion imaging in patients with suspected and known coronary artery disease</title><author>Koh, Angela S. ; Gao, Fei ; Chin, C.T. ; Keng, Felix Y.J. ; Tan, Ru-San ; Chua, Terrance S.J.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c424t-ee3d6f45cb0ee1a0e765e49629474b414a2ee156c208d32467a0c9de8ce73a663</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Cardiology</topic><topic>Coronary Artery Disease - diagnostic imaging</topic><topic>Coronary Artery Disease - mortality</topic><topic>Death, Sudden, Cardiac - epidemiology</topic><topic>diagnostic and prognostic application</topic><topic>Exercise Test - statistics & numerical data</topic><topic>exercise: stress testing</topic><topic>Female</topic><topic>Humans</topic><topic>Imaging</topic><topic>Male</topic><topic>Medicine</topic><topic>Medicine & Public Health</topic><topic>Middle Aged</topic><topic>Myocardial Perfusion Imaging - methods</topic><topic>Myocardial Perfusion Imaging - statistics & numerical data</topic><topic>Myocardial perfusion imaging: SPECT</topic><topic>Nuclear Medicine</topic><topic>Original Article</topic><topic>Prevalence</topic><topic>Prognosis</topic><topic>Proportional Hazards Models</topic><topic>Radiology</topic><topic>Reproducibility of Results</topic><topic>Risk Assessment - methods</topic><topic>Risk Factors</topic><topic>Sensitivity and Specificity</topic><topic>Singapore - epidemiology</topic><topic>Survival Analysis</topic><topic>Tomography, Emission-Computed, Single-Photon - statistics & numerical data</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Koh, Angela S.</creatorcontrib><creatorcontrib>Gao, Fei</creatorcontrib><creatorcontrib>Chin, C.T.</creatorcontrib><creatorcontrib>Keng, Felix Y.J.</creatorcontrib><creatorcontrib>Tan, Ru-San</creatorcontrib><creatorcontrib>Chua, Terrance S.J.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>ProQuest Nursing and Allied Health Journals</collection><collection>Proquest Health & Medical Complete</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Medical Database (Alumni Edition)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>ProQuest Central (Alumni)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Medical Database</collection><collection>Nursing & Allied Health Premium</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>MEDLINE - Academic</collection><jtitle>Journal of nuclear cardiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Koh, Angela S.</au><au>Gao, Fei</au><au>Chin, C.T.</au><au>Keng, Felix Y.J.</au><au>Tan, Ru-San</au><au>Chua, Terrance S.J.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Differential risk reclassification improvement by exercise testing and myocardial perfusion imaging in patients with suspected and known coronary artery disease</atitle><jtitle>Journal of nuclear cardiology</jtitle><stitle>J. Nucl. Cardiol</stitle><addtitle>J Nucl Cardiol</addtitle><date>2016-06-01</date><risdate>2016</risdate><volume>23</volume><issue>3</issue><spage>366</spage><epage>378</epage><pages>366-378</pages><issn>1071-3581</issn><eissn>1532-6551</eissn><abstract>The objective of this study is to compare the incremental prognostic and net risk reclassification value of exercise testing alone vs exercise myocardial perfusion imaging (MPI) for estimating the risk of death in patients with suspected and known coronary artery disease (CAD).
6702 patients with suspected CAD and 2008 with known CAD had treadmill exercise MPI and were followed for 2.5 ± 0.9 years for the occurrence of all-cause death. The estimation of risk of death and net reclassification improvement (NRI) were examined in three models. Model 1: clinical variables; Model 2: model 1+Duke Treadmill Score; and Model 3: model 2+ MPI variables. Risk estimates were categorized as <1%, 1-3%, and >3% risk of death per year.
In patients with suspected CAD, the global Chi-square for predicting risk of death increased significantly for Model 2 compared to Model 1 (74.78 vs 63.86 to (P = .001). However, adding MPI variables in Model 3 did not further improve predictive value (Chi-square 79.38, P = .10). In patients with suspected CAD risk, reclassification improved significantly in Model 2 over Model 1 (NRI = 0.12, 95% CI 0.02 to 0.22, P = .019), but not in Model 3 (NRI = 0.0009, 95% CI −0.072 to 0.070; P = .98). In contrast, in patients with known CAD Model 2 did not yield significant improvements for predicting risk and risk reclassification compared to Model 1. However, global Chi-square of Model 3 was significantly higher than that of Model 2 (30.03 vs 6.56, P < .0001) with associated significant reclassification improvement (NRI = 0.26 95% CI 0.067 to 0.46. P = .0084).
Risk reclassification by diagnostic testing is importantly influenced by baseline characteristics of patient cohorts. In patients with suspected CAD, NRI is predominately achieved by exercise variables, whereas in patients with known CAD, greatest NRI is obtained by MPI variables.</abstract><cop>New York</cop><pub>Elsevier Inc</pub><pmid>26358085</pmid><doi>10.1007/s12350-015-0253-x</doi><tpages>13</tpages></addata></record> |
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| subjects | Cardiology Coronary Artery Disease - diagnostic imaging Coronary Artery Disease - mortality Death, Sudden, Cardiac - epidemiology diagnostic and prognostic application Exercise Test - statistics & numerical data exercise: stress testing Female Humans Imaging Male Medicine Medicine & Public Health Middle Aged Myocardial Perfusion Imaging - methods Myocardial Perfusion Imaging - statistics & numerical data Myocardial perfusion imaging: SPECT Nuclear Medicine Original Article Prevalence Prognosis Proportional Hazards Models Radiology Reproducibility of Results Risk Assessment - methods Risk Factors Sensitivity and Specificity Singapore - epidemiology Survival Analysis Tomography, Emission-Computed, Single-Photon - statistics & numerical data |
| title | Differential risk reclassification improvement by exercise testing and myocardial perfusion imaging in patients with suspected and known coronary artery disease |
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