Utility of Nontraditional Risk Markers in Atherosclerotic Cardiovascular Disease Risk Assessment
Abstract Background The improvement in discrimination gained by adding nontraditional cardiovascular risk markers cited in the 2013 American College of Cardiology/American Heart Association cholesterol guidelines to the atherosclerotic cardiovascular disease (ASCVD) risk estimator (pooled cohort equ...
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| creator | Yeboah, Joseph, MD, MS Young, Rebekah, PhD McClelland, Robyn L., PhD Delaney, Joseph C., PhD Polonsky, Tamar S., MD, MSci Dawood, Farah Z., MD, MS Blaha, Michael J., MD, MPH Miedema, Michael D., MD, MPH Sibley, Christopher T., MD Carr, J. Jeffrey, MD, MSc Burke, Gregory L., MD, MS Goff, David C., MD, PhD Psaty, Bruce M., MD, PhD Greenland, Philip, MD Herrington, David M., MD, MHS |
| description | Abstract Background The improvement in discrimination gained by adding nontraditional cardiovascular risk markers cited in the 2013 American College of Cardiology/American Heart Association cholesterol guidelines to the atherosclerotic cardiovascular disease (ASCVD) risk estimator (pooled cohort equation [PCE]) is untested. Objectives This study assessed the predictive accuracy and improvement in reclassification gained by the addition of the coronary artery calcium (CAC) score, the ankle–brachial index (ABI), high-sensitivity C-reactive protein (hsCRP) levels, and family history (FH) of ASCVD to the PCE in participants of MESA (Multi-Ethnic Study of Atherosclerosis). Methods The PCE was calibrated (cPCE) and used for this analysis. The Cox proportional hazards survival model, Harrell’s C statistics, and net reclassification improvement analyses were used. ASCVD was defined as myocardial infarction, coronary heart disease–related death, or fatal or nonfatal stroke. Results Of 6,814 MESA participants not prescribed statins at baseline, 5,185 had complete data and were included in this analysis. Their mean age was 61 years; 53.1% were women, 9.8% had diabetes, and 13.6% were current smokers. After 10 years of follow-up, 320 (6.2%) ASCVD events occurred. CAC score, ABI, and FH were independent predictors of ASCVD events in the multivariable Cox models. CAC score modestly improved the Harrell’s C statistic (0.74 vs. 0.76; p = 0.04); ABI, hsCRP levels, and FH produced no improvement in Harrell’s C statistic when added to the cPCE. Conclusions CAC score, ABI, and FH were independent predictors of ASCVD events. CAC score modestly improved the discriminative ability of the cPCE compared with other nontraditional risk markers. |
| doi_str_mv | 10.1016/j.jacc.2015.10.058 |
| format | Article |
| fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_4724058</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>1_s2_0_S0735109715072253</els_id><sourcerecordid>3929366061</sourcerecordid><originalsourceid>FETCH-LOGICAL-c604t-73c2b518900f5953e5febd40c6bfd757fd2420a8d37014182175f28e09156ccf3</originalsourceid><addsrcrecordid>eNp9UsFu1DAQtRCIbgs_wAFF4sIly9iJ40RClVYLBaQCEtCz8ToT6t1sXDzOSvv3OEop0AMXWxq_eZ733jD2jMOSA69ebZdbY-1SAJepsARZP2ALLmWdF7JRD9kCVCFzDo06YadEWwCoat48ZieiUg0H2SzY96voehePme-yT36IwbQuOj-YPvviaJd9NGGHgTI3ZKt4jcGT7dMZnc3WJrTOHwzZsTche-MIDeHctiJCoj0O8Ql71Jme8OntfcauLt5-W7_PLz-_-7BeXea2gjLmqrBiI3ndAHSykQXKDjdtCbbadK2SqmtFKcDUbaGAl7wWXMlO1AgNl5W1XXHGzmfem3Gzx9bipKXXN8HtTThqb5z-92Vw1_qHP-hSiTJZlwhe3hIE_3NEinrvyGLfmwH9SJqrKn1WgBQJ-uIedOvHkDybUDJJEKriCSVmlE2uUcDubhgOegpQb_UUoJ4CnGrzFM__lnHX8juxBHg9AzCZeXAYNFmHg8XWBbRRt979n__8Xrvt3eCs6Xd4RPqjQ5PQoL9OKzRtEJeghJBF8QumYcIb</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>1759002761</pqid></control><display><type>article</type><title>Utility of Nontraditional Risk Markers in Atherosclerotic Cardiovascular Disease Risk Assessment</title><source>MEDLINE</source><source>Elsevier ScienceDirect Journals</source><source>EZB-FREE-00999 freely available EZB journals</source><source>Alma/SFX Local Collection</source><creator>Yeboah, Joseph, MD, MS ; Young, Rebekah, PhD ; McClelland, Robyn L., PhD ; Delaney, Joseph C., PhD ; Polonsky, Tamar S., MD, MSci ; Dawood, Farah Z., MD, MS ; Blaha, Michael J., MD, MPH ; Miedema, Michael D., MD, MPH ; Sibley, Christopher T., MD ; Carr, J. Jeffrey, MD, MSc ; Burke, Gregory L., MD, MS ; Goff, David C., MD, PhD ; Psaty, Bruce M., MD, PhD ; Greenland, Philip, MD ; Herrington, David M., MD, MHS</creator><creatorcontrib>Yeboah, Joseph, MD, MS ; Young, Rebekah, PhD ; McClelland, Robyn L., PhD ; Delaney, Joseph C., PhD ; Polonsky, Tamar S., MD, MSci ; Dawood, Farah Z., MD, MS ; Blaha, Michael J., MD, MPH ; Miedema, Michael D., MD, MPH ; Sibley, Christopher T., MD ; Carr, J. Jeffrey, MD, MSc ; Burke, Gregory L., MD, MS ; Goff, David C., MD, PhD ; Psaty, Bruce M., MD, PhD ; Greenland, Philip, MD ; Herrington, David M., MD, MHS</creatorcontrib><description>Abstract Background The improvement in discrimination gained by adding nontraditional cardiovascular risk markers cited in the 2013 American College of Cardiology/American Heart Association cholesterol guidelines to the atherosclerotic cardiovascular disease (ASCVD) risk estimator (pooled cohort equation [PCE]) is untested. Objectives This study assessed the predictive accuracy and improvement in reclassification gained by the addition of the coronary artery calcium (CAC) score, the ankle–brachial index (ABI), high-sensitivity C-reactive protein (hsCRP) levels, and family history (FH) of ASCVD to the PCE in participants of MESA (Multi-Ethnic Study of Atherosclerosis). Methods The PCE was calibrated (cPCE) and used for this analysis. The Cox proportional hazards survival model, Harrell’s C statistics, and net reclassification improvement analyses were used. ASCVD was defined as myocardial infarction, coronary heart disease–related death, or fatal or nonfatal stroke. Results Of 6,814 MESA participants not prescribed statins at baseline, 5,185 had complete data and were included in this analysis. Their mean age was 61 years; 53.1% were women, 9.8% had diabetes, and 13.6% were current smokers. After 10 years of follow-up, 320 (6.2%) ASCVD events occurred. CAC score, ABI, and FH were independent predictors of ASCVD events in the multivariable Cox models. CAC score modestly improved the Harrell’s C statistic (0.74 vs. 0.76; p = 0.04); ABI, hsCRP levels, and FH produced no improvement in Harrell’s C statistic when added to the cPCE. Conclusions CAC score, ABI, and FH were independent predictors of ASCVD events. CAC score modestly improved the discriminative ability of the cPCE compared with other nontraditional risk markers.</description><identifier>ISSN: 0735-1097</identifier><identifier>EISSN: 1558-3597</identifier><identifier>DOI: 10.1016/j.jacc.2015.10.058</identifier><identifier>PMID: 26791059</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Age ; Aged ; Aged, 80 and over ; Ankle Brachial Index - statistics & numerical data ; ankle–brachial index ; Biomarkers - analysis ; Biomedical research ; C-Reactive Protein - analysis ; Cardiology ; Cardiovascular ; Cardiovascular disease ; Cholesterol ; Cholesterol - analysis ; coronary artery calcium ; Coronary Artery Disease - diagnosis ; Coronary Artery Disease - drug therapy ; Coronary Artery Disease - epidemiology ; Coronary Vessels - metabolism ; Coronary Vessels - pathology ; Diabetes ; Disease Progression ; Ethnic Groups - statistics & numerical data ; Family Health - ethnology ; Family Health - statistics & numerical data ; Family medical history ; Female ; Follow-Up Studies ; Health Status Indicators ; Heart attacks ; high-sensitivity C-reactive protein ; Humans ; Hydroxymethylglutaryl-CoA Reductase Inhibitors - therapeutic use ; Internal Medicine ; Laboratories ; Lipoproteins ; Male ; Medical imaging ; Middle Aged ; pooled cohort equation ; Predictive Value of Tests ; Proportional Hazards Models ; Risk assessment ; Risk Assessment - methods ; Risk Factors ; United States - epidemiology ; Vascular Calcification - epidemiology ; Veins & arteries</subject><ispartof>Journal of the American College of Cardiology, 2016-01, Vol.67 (2), p.139-147</ispartof><rights>American College of Cardiology Foundation</rights><rights>2016 American College of Cardiology Foundation</rights><rights>Copyright © 2016 American College of Cardiology Foundation. Published by Elsevier Inc. All rights reserved.</rights><rights>Copyright Elsevier Limited Jan 19, 2016</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c604t-73c2b518900f5953e5febd40c6bfd757fd2420a8d37014182175f28e09156ccf3</citedby><cites>FETCH-LOGICAL-c604t-73c2b518900f5953e5febd40c6bfd757fd2420a8d37014182175f28e09156ccf3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S0735109715072253$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>230,314,776,780,881,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/26791059$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yeboah, Joseph, MD, MS</creatorcontrib><creatorcontrib>Young, Rebekah, PhD</creatorcontrib><creatorcontrib>McClelland, Robyn L., PhD</creatorcontrib><creatorcontrib>Delaney, Joseph C., PhD</creatorcontrib><creatorcontrib>Polonsky, Tamar S., MD, MSci</creatorcontrib><creatorcontrib>Dawood, Farah Z., MD, MS</creatorcontrib><creatorcontrib>Blaha, Michael J., MD, MPH</creatorcontrib><creatorcontrib>Miedema, Michael D., MD, MPH</creatorcontrib><creatorcontrib>Sibley, Christopher T., MD</creatorcontrib><creatorcontrib>Carr, J. Jeffrey, MD, MSc</creatorcontrib><creatorcontrib>Burke, Gregory L., MD, MS</creatorcontrib><creatorcontrib>Goff, David C., MD, PhD</creatorcontrib><creatorcontrib>Psaty, Bruce M., MD, PhD</creatorcontrib><creatorcontrib>Greenland, Philip, MD</creatorcontrib><creatorcontrib>Herrington, David M., MD, MHS</creatorcontrib><title>Utility of Nontraditional Risk Markers in Atherosclerotic Cardiovascular Disease Risk Assessment</title><title>Journal of the American College of Cardiology</title><addtitle>J Am Coll Cardiol</addtitle><description>Abstract Background The improvement in discrimination gained by adding nontraditional cardiovascular risk markers cited in the 2013 American College of Cardiology/American Heart Association cholesterol guidelines to the atherosclerotic cardiovascular disease (ASCVD) risk estimator (pooled cohort equation [PCE]) is untested. Objectives This study assessed the predictive accuracy and improvement in reclassification gained by the addition of the coronary artery calcium (CAC) score, the ankle–brachial index (ABI), high-sensitivity C-reactive protein (hsCRP) levels, and family history (FH) of ASCVD to the PCE in participants of MESA (Multi-Ethnic Study of Atherosclerosis). Methods The PCE was calibrated (cPCE) and used for this analysis. The Cox proportional hazards survival model, Harrell’s C statistics, and net reclassification improvement analyses were used. ASCVD was defined as myocardial infarction, coronary heart disease–related death, or fatal or nonfatal stroke. Results Of 6,814 MESA participants not prescribed statins at baseline, 5,185 had complete data and were included in this analysis. Their mean age was 61 years; 53.1% were women, 9.8% had diabetes, and 13.6% were current smokers. After 10 years of follow-up, 320 (6.2%) ASCVD events occurred. CAC score, ABI, and FH were independent predictors of ASCVD events in the multivariable Cox models. CAC score modestly improved the Harrell’s C statistic (0.74 vs. 0.76; p = 0.04); ABI, hsCRP levels, and FH produced no improvement in Harrell’s C statistic when added to the cPCE. Conclusions CAC score, ABI, and FH were independent predictors of ASCVD events. CAC score modestly improved the discriminative ability of the cPCE compared with other nontraditional risk markers.</description><subject>Age</subject><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Ankle Brachial Index - statistics & numerical data</subject><subject>ankle–brachial index</subject><subject>Biomarkers - analysis</subject><subject>Biomedical research</subject><subject>C-Reactive Protein - analysis</subject><subject>Cardiology</subject><subject>Cardiovascular</subject><subject>Cardiovascular disease</subject><subject>Cholesterol</subject><subject>Cholesterol - analysis</subject><subject>coronary artery calcium</subject><subject>Coronary Artery Disease - diagnosis</subject><subject>Coronary Artery Disease - drug therapy</subject><subject>Coronary Artery Disease - epidemiology</subject><subject>Coronary Vessels - metabolism</subject><subject>Coronary Vessels - pathology</subject><subject>Diabetes</subject><subject>Disease Progression</subject><subject>Ethnic Groups - statistics & numerical data</subject><subject>Family Health - ethnology</subject><subject>Family Health - statistics & numerical data</subject><subject>Family medical history</subject><subject>Female</subject><subject>Follow-Up Studies</subject><subject>Health Status Indicators</subject><subject>Heart attacks</subject><subject>high-sensitivity C-reactive protein</subject><subject>Humans</subject><subject>Hydroxymethylglutaryl-CoA Reductase Inhibitors - therapeutic use</subject><subject>Internal Medicine</subject><subject>Laboratories</subject><subject>Lipoproteins</subject><subject>Male</subject><subject>Medical imaging</subject><subject>Middle Aged</subject><subject>pooled cohort equation</subject><subject>Predictive Value of Tests</subject><subject>Proportional Hazards Models</subject><subject>Risk assessment</subject><subject>Risk Assessment - methods</subject><subject>Risk Factors</subject><subject>United States - epidemiology</subject><subject>Vascular Calcification - epidemiology</subject><subject>Veins & arteries</subject><issn>0735-1097</issn><issn>1558-3597</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9UsFu1DAQtRCIbgs_wAFF4sIly9iJ40RClVYLBaQCEtCz8ToT6t1sXDzOSvv3OEop0AMXWxq_eZ733jD2jMOSA69ebZdbY-1SAJepsARZP2ALLmWdF7JRD9kCVCFzDo06YadEWwCoat48ZieiUg0H2SzY96voehePme-yT36IwbQuOj-YPvviaJd9NGGHgTI3ZKt4jcGT7dMZnc3WJrTOHwzZsTche-MIDeHctiJCoj0O8Ql71Jme8OntfcauLt5-W7_PLz-_-7BeXea2gjLmqrBiI3ndAHSykQXKDjdtCbbadK2SqmtFKcDUbaGAl7wWXMlO1AgNl5W1XXHGzmfem3Gzx9bipKXXN8HtTThqb5z-92Vw1_qHP-hSiTJZlwhe3hIE_3NEinrvyGLfmwH9SJqrKn1WgBQJ-uIedOvHkDybUDJJEKriCSVmlE2uUcDubhgOegpQb_UUoJ4CnGrzFM__lnHX8juxBHg9AzCZeXAYNFmHg8XWBbRRt979n__8Xrvt3eCs6Xd4RPqjQ5PQoL9OKzRtEJeghJBF8QumYcIb</recordid><startdate>20160119</startdate><enddate>20160119</enddate><creator>Yeboah, Joseph, MD, MS</creator><creator>Young, Rebekah, PhD</creator><creator>McClelland, Robyn L., PhD</creator><creator>Delaney, Joseph C., PhD</creator><creator>Polonsky, Tamar S., MD, MSci</creator><creator>Dawood, Farah Z., MD, MS</creator><creator>Blaha, Michael J., MD, MPH</creator><creator>Miedema, Michael D., MD, MPH</creator><creator>Sibley, Christopher T., MD</creator><creator>Carr, J. Jeffrey, MD, MSc</creator><creator>Burke, Gregory L., MD, MS</creator><creator>Goff, David C., MD, PhD</creator><creator>Psaty, Bruce M., MD, PhD</creator><creator>Greenland, Philip, MD</creator><creator>Herrington, David M., MD, MHS</creator><general>Elsevier Inc</general><general>Elsevier Limited</general><scope>6I.</scope><scope>AAFTH</scope><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>7T5</scope><scope>7TK</scope><scope>H94</scope><scope>K9.</scope><scope>NAPCQ</scope><scope>7X8</scope><scope>5PM</scope></search><sort><creationdate>20160119</creationdate><title>Utility of Nontraditional Risk Markers in Atherosclerotic Cardiovascular Disease Risk Assessment</title><author>Yeboah, Joseph, MD, MS ; Young, Rebekah, PhD ; McClelland, Robyn L., PhD ; Delaney, Joseph C., PhD ; Polonsky, Tamar S., MD, MSci ; Dawood, Farah Z., MD, MS ; Blaha, Michael J., MD, MPH ; Miedema, Michael D., MD, MPH ; Sibley, Christopher T., MD ; Carr, J. Jeffrey, MD, MSc ; Burke, Gregory L., MD, MS ; Goff, David C., MD, PhD ; Psaty, Bruce M., MD, PhD ; Greenland, Philip, MD ; Herrington, David M., MD, MHS</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c604t-73c2b518900f5953e5febd40c6bfd757fd2420a8d37014182175f28e09156ccf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Age</topic><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Ankle Brachial Index - statistics & numerical data</topic><topic>ankle–brachial index</topic><topic>Biomarkers - analysis</topic><topic>Biomedical research</topic><topic>C-Reactive Protein - analysis</topic><topic>Cardiology</topic><topic>Cardiovascular</topic><topic>Cardiovascular disease</topic><topic>Cholesterol</topic><topic>Cholesterol - analysis</topic><topic>coronary artery calcium</topic><topic>Coronary Artery Disease - diagnosis</topic><topic>Coronary Artery Disease - drug therapy</topic><topic>Coronary Artery Disease - epidemiology</topic><topic>Coronary Vessels - metabolism</topic><topic>Coronary Vessels - pathology</topic><topic>Diabetes</topic><topic>Disease Progression</topic><topic>Ethnic Groups - statistics & numerical data</topic><topic>Family Health - ethnology</topic><topic>Family Health - statistics & numerical data</topic><topic>Family medical history</topic><topic>Female</topic><topic>Follow-Up Studies</topic><topic>Health Status Indicators</topic><topic>Heart attacks</topic><topic>high-sensitivity C-reactive protein</topic><topic>Humans</topic><topic>Hydroxymethylglutaryl-CoA Reductase Inhibitors - therapeutic use</topic><topic>Internal Medicine</topic><topic>Laboratories</topic><topic>Lipoproteins</topic><topic>Male</topic><topic>Medical imaging</topic><topic>Middle Aged</topic><topic>pooled cohort equation</topic><topic>Predictive Value of Tests</topic><topic>Proportional Hazards Models</topic><topic>Risk assessment</topic><topic>Risk Assessment - methods</topic><topic>Risk Factors</topic><topic>United States - epidemiology</topic><topic>Vascular Calcification - epidemiology</topic><topic>Veins & arteries</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yeboah, Joseph, MD, MS</creatorcontrib><creatorcontrib>Young, Rebekah, PhD</creatorcontrib><creatorcontrib>McClelland, Robyn L., PhD</creatorcontrib><creatorcontrib>Delaney, Joseph C., PhD</creatorcontrib><creatorcontrib>Polonsky, Tamar S., MD, MSci</creatorcontrib><creatorcontrib>Dawood, Farah Z., MD, MS</creatorcontrib><creatorcontrib>Blaha, Michael J., MD, MPH</creatorcontrib><creatorcontrib>Miedema, Michael D., MD, MPH</creatorcontrib><creatorcontrib>Sibley, Christopher T., MD</creatorcontrib><creatorcontrib>Carr, J. Jeffrey, MD, MSc</creatorcontrib><creatorcontrib>Burke, Gregory L., MD, MS</creatorcontrib><creatorcontrib>Goff, David C., MD, PhD</creatorcontrib><creatorcontrib>Psaty, Bruce M., MD, PhD</creatorcontrib><creatorcontrib>Greenland, Philip, MD</creatorcontrib><creatorcontrib>Herrington, David M., MD, MHS</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Immunology Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Premium</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Journal of the American College of Cardiology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yeboah, Joseph, MD, MS</au><au>Young, Rebekah, PhD</au><au>McClelland, Robyn L., PhD</au><au>Delaney, Joseph C., PhD</au><au>Polonsky, Tamar S., MD, MSci</au><au>Dawood, Farah Z., MD, MS</au><au>Blaha, Michael J., MD, MPH</au><au>Miedema, Michael D., MD, MPH</au><au>Sibley, Christopher T., MD</au><au>Carr, J. Jeffrey, MD, MSc</au><au>Burke, Gregory L., MD, MS</au><au>Goff, David C., MD, PhD</au><au>Psaty, Bruce M., MD, PhD</au><au>Greenland, Philip, MD</au><au>Herrington, David M., MD, MHS</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Utility of Nontraditional Risk Markers in Atherosclerotic Cardiovascular Disease Risk Assessment</atitle><jtitle>Journal of the American College of Cardiology</jtitle><addtitle>J Am Coll Cardiol</addtitle><date>2016-01-19</date><risdate>2016</risdate><volume>67</volume><issue>2</issue><spage>139</spage><epage>147</epage><pages>139-147</pages><issn>0735-1097</issn><eissn>1558-3597</eissn><abstract>Abstract Background The improvement in discrimination gained by adding nontraditional cardiovascular risk markers cited in the 2013 American College of Cardiology/American Heart Association cholesterol guidelines to the atherosclerotic cardiovascular disease (ASCVD) risk estimator (pooled cohort equation [PCE]) is untested. Objectives This study assessed the predictive accuracy and improvement in reclassification gained by the addition of the coronary artery calcium (CAC) score, the ankle–brachial index (ABI), high-sensitivity C-reactive protein (hsCRP) levels, and family history (FH) of ASCVD to the PCE in participants of MESA (Multi-Ethnic Study of Atherosclerosis). Methods The PCE was calibrated (cPCE) and used for this analysis. The Cox proportional hazards survival model, Harrell’s C statistics, and net reclassification improvement analyses were used. ASCVD was defined as myocardial infarction, coronary heart disease–related death, or fatal or nonfatal stroke. Results Of 6,814 MESA participants not prescribed statins at baseline, 5,185 had complete data and were included in this analysis. Their mean age was 61 years; 53.1% were women, 9.8% had diabetes, and 13.6% were current smokers. After 10 years of follow-up, 320 (6.2%) ASCVD events occurred. CAC score, ABI, and FH were independent predictors of ASCVD events in the multivariable Cox models. CAC score modestly improved the Harrell’s C statistic (0.74 vs. 0.76; p = 0.04); ABI, hsCRP levels, and FH produced no improvement in Harrell’s C statistic when added to the cPCE. Conclusions CAC score, ABI, and FH were independent predictors of ASCVD events. CAC score modestly improved the discriminative ability of the cPCE compared with other nontraditional risk markers.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>26791059</pmid><doi>10.1016/j.jacc.2015.10.058</doi><tpages>9</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Age Aged Aged, 80 and over Ankle Brachial Index - statistics & numerical data ankle–brachial index Biomarkers - analysis Biomedical research C-Reactive Protein - analysis Cardiology Cardiovascular Cardiovascular disease Cholesterol Cholesterol - analysis coronary artery calcium Coronary Artery Disease - diagnosis Coronary Artery Disease - drug therapy Coronary Artery Disease - epidemiology Coronary Vessels - metabolism Coronary Vessels - pathology Diabetes Disease Progression Ethnic Groups - statistics & numerical data Family Health - ethnology Family Health - statistics & numerical data Family medical history Female Follow-Up Studies Health Status Indicators Heart attacks high-sensitivity C-reactive protein Humans Hydroxymethylglutaryl-CoA Reductase Inhibitors - therapeutic use Internal Medicine Laboratories Lipoproteins Male Medical imaging Middle Aged pooled cohort equation Predictive Value of Tests Proportional Hazards Models Risk assessment Risk Assessment - methods Risk Factors United States - epidemiology Vascular Calcification - epidemiology Veins & arteries |
| title | Utility of Nontraditional Risk Markers in Atherosclerotic Cardiovascular Disease Risk Assessment |
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