Development of a duplex-derived velocity risk prediction model of disease progression in patients with moderate asymptomatic carotid artery stenosis
Objective Previously, we described risk factors for disease progression in moderate asymptomatic carotid artery stenosis (ASCAS). The aim of the current study was to develop a risk prediction model for disease progression in this group. Methods All patients presenting between January 2005 and May 20...
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creator | Hicks, Caitlin W., MD, MS Canner, Joseph K., MHS Arhuidese, Isibor, MD, MPH Glebova, Natalia O., MD, PhD Schneider, Eric, PhD Qazi, Umair, MD, MPH Perler, Bruce, MD Malas, Mahmoud B., MD, MHS |
description | Objective Previously, we described risk factors for disease progression in moderate asymptomatic carotid artery stenosis (ASCAS). The aim of the current study was to develop a risk prediction model for disease progression in this group. Methods All patients presenting between January 2005 and May 2012 with moderate (50%-69%) ASCAS, as determined by carotid artery duplex imaging, were included. Cox proportional hazard regression models accounting for measured duplex peak systolic velocity and end-diastolic velocity, and the internal carotid artery (ICA)/common carotid artery (CCA) ratio, with and without previously identified risk factors for progression (age, smoking, dual antiplatelet therapy), were used to develop receiver operating characteristic curves for predicting disease progression. Results The study analyzed 282 patients (52% male), aged 71 ± 9 years, with 2.6 ± 0.1 years follow-up and 25% disease progression at a mean time of 2.02 ± 0.18 years. Initial peak systolic velocity, end-diastolic velocity, and the ICA/CCA ratio were all significant independent predictors of progression. Receiver operating characteristic curve analyses suggested that a prediction model based on ICA/CCA ratio alone had optimal prediction efficacy (hazard ratio, 2.01; Harrell's C, 0.74; P < .001). Patients with ICA/CCA >2.5, 3.3, and 3.8 were found to have >10%, >20%, and >30% risk of disease progression over 2 years, respectively. Model sensitivity and specificity for predicting 10% risk of disease progression at 2 years was 80.7% and 64.0%, respectively (positive predictive value, 22.9%; negative predictive value, 96.1%). Conclusions We propose a clinical prediction model for moderate ASCAS disease progression that can be used to risk-stratify patients with >10% risk of progression at 2 years using ICA/CCA ratios. Implementation of this model may be useful for identifying high-risk patients who would benefit from routine carotid disease surveillance follow-up. |
doi_str_mv | 10.1016/j.jvs.2014.08.056 |
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The aim of the current study was to develop a risk prediction model for disease progression in this group. Methods All patients presenting between January 2005 and May 2012 with moderate (50%-69%) ASCAS, as determined by carotid artery duplex imaging, were included. Cox proportional hazard regression models accounting for measured duplex peak systolic velocity and end-diastolic velocity, and the internal carotid artery (ICA)/common carotid artery (CCA) ratio, with and without previously identified risk factors for progression (age, smoking, dual antiplatelet therapy), were used to develop receiver operating characteristic curves for predicting disease progression. Results The study analyzed 282 patients (52% male), aged 71 ± 9 years, with 2.6 ± 0.1 years follow-up and 25% disease progression at a mean time of 2.02 ± 0.18 years. Initial peak systolic velocity, end-diastolic velocity, and the ICA/CCA ratio were all significant independent predictors of progression. Receiver operating characteristic curve analyses suggested that a prediction model based on ICA/CCA ratio alone had optimal prediction efficacy (hazard ratio, 2.01; Harrell's C, 0.74; P < .001). Patients with ICA/CCA >2.5, 3.3, and 3.8 were found to have >10%, >20%, and >30% risk of disease progression over 2 years, respectively. Model sensitivity and specificity for predicting 10% risk of disease progression at 2 years was 80.7% and 64.0%, respectively (positive predictive value, 22.9%; negative predictive value, 96.1%). Conclusions We propose a clinical prediction model for moderate ASCAS disease progression that can be used to risk-stratify patients with >10% risk of progression at 2 years using ICA/CCA ratios. Implementation of this model may be useful for identifying high-risk patients who would benefit from routine carotid disease surveillance follow-up.</description><identifier>ISSN: 0741-5214</identifier><identifier>EISSN: 1097-6809</identifier><identifier>DOI: 10.1016/j.jvs.2014.08.056</identifier><identifier>PMID: 25238724</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>Aged ; Aged, 80 and over ; Area Under Curve ; Asymptomatic Diseases ; Blood Flow Velocity ; Carotid Artery, Common - diagnostic imaging ; Carotid Artery, Common - physiopathology ; Carotid Artery, Internal - diagnostic imaging ; Carotid Artery, Internal - physiopathology ; Carotid Stenosis - diagnostic imaging ; Carotid Stenosis - physiopathology ; Chi-Square Distribution ; Decision Support Techniques ; Disease Progression ; Female ; Humans ; Male ; Middle Aged ; Multivariate Analysis ; Predictive Value of Tests ; Proportional Hazards Models ; Regional Blood Flow ; Retrospective Studies ; Risk Assessment ; Risk Factors ; ROC Curve ; Surgery ; Time Factors ; Ultrasonography, Doppler, Duplex</subject><ispartof>Journal of vascular surgery, 2014-12, Vol.60 (6), p.1585-1592</ispartof><rights>Society for Vascular Surgery</rights><rights>2014 Society for Vascular Surgery</rights><rights>Copyright © 2014 Society for Vascular Surgery. Published by Elsevier Inc. All rights reserved.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c451t-320d02bade2d315ed666b647e51efad36a756045c88e3de547fac604e7a27c753</citedby><cites>FETCH-LOGICAL-c451t-320d02bade2d315ed666b647e51efad36a756045c88e3de547fac604e7a27c753</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://www.sciencedirect.com/science/article/pii/S074152141401622X$$EHTML$$P50$$Gelsevier$$Hfree_for_read</linktohtml><link.rule.ids>314,776,780,3537,27901,27902,65306</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/25238724$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Hicks, Caitlin W., MD, MS</creatorcontrib><creatorcontrib>Canner, Joseph K., MHS</creatorcontrib><creatorcontrib>Arhuidese, Isibor, MD, MPH</creatorcontrib><creatorcontrib>Glebova, Natalia O., MD, PhD</creatorcontrib><creatorcontrib>Schneider, Eric, PhD</creatorcontrib><creatorcontrib>Qazi, Umair, MD, MPH</creatorcontrib><creatorcontrib>Perler, Bruce, MD</creatorcontrib><creatorcontrib>Malas, Mahmoud B., MD, MHS</creatorcontrib><title>Development of a duplex-derived velocity risk prediction model of disease progression in patients with moderate asymptomatic carotid artery stenosis</title><title>Journal of vascular surgery</title><addtitle>J Vasc Surg</addtitle><description>Objective Previously, we described risk factors for disease progression in moderate asymptomatic carotid artery stenosis (ASCAS). The aim of the current study was to develop a risk prediction model for disease progression in this group. Methods All patients presenting between January 2005 and May 2012 with moderate (50%-69%) ASCAS, as determined by carotid artery duplex imaging, were included. Cox proportional hazard regression models accounting for measured duplex peak systolic velocity and end-diastolic velocity, and the internal carotid artery (ICA)/common carotid artery (CCA) ratio, with and without previously identified risk factors for progression (age, smoking, dual antiplatelet therapy), were used to develop receiver operating characteristic curves for predicting disease progression. Results The study analyzed 282 patients (52% male), aged 71 ± 9 years, with 2.6 ± 0.1 years follow-up and 25% disease progression at a mean time of 2.02 ± 0.18 years. Initial peak systolic velocity, end-diastolic velocity, and the ICA/CCA ratio were all significant independent predictors of progression. Receiver operating characteristic curve analyses suggested that a prediction model based on ICA/CCA ratio alone had optimal prediction efficacy (hazard ratio, 2.01; Harrell's C, 0.74; P < .001). Patients with ICA/CCA >2.5, 3.3, and 3.8 were found to have >10%, >20%, and >30% risk of disease progression over 2 years, respectively. Model sensitivity and specificity for predicting 10% risk of disease progression at 2 years was 80.7% and 64.0%, respectively (positive predictive value, 22.9%; negative predictive value, 96.1%). Conclusions We propose a clinical prediction model for moderate ASCAS disease progression that can be used to risk-stratify patients with >10% risk of progression at 2 years using ICA/CCA ratios. Implementation of this model may be useful for identifying high-risk patients who would benefit from routine carotid disease surveillance follow-up.</description><subject>Aged</subject><subject>Aged, 80 and over</subject><subject>Area Under Curve</subject><subject>Asymptomatic Diseases</subject><subject>Blood Flow Velocity</subject><subject>Carotid Artery, Common - diagnostic imaging</subject><subject>Carotid Artery, Common - physiopathology</subject><subject>Carotid Artery, Internal - diagnostic imaging</subject><subject>Carotid Artery, Internal - physiopathology</subject><subject>Carotid Stenosis - diagnostic imaging</subject><subject>Carotid Stenosis - physiopathology</subject><subject>Chi-Square Distribution</subject><subject>Decision Support Techniques</subject><subject>Disease Progression</subject><subject>Female</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Multivariate Analysis</subject><subject>Predictive Value of Tests</subject><subject>Proportional Hazards Models</subject><subject>Regional Blood Flow</subject><subject>Retrospective Studies</subject><subject>Risk Assessment</subject><subject>Risk Factors</subject><subject>ROC Curve</subject><subject>Surgery</subject><subject>Time Factors</subject><subject>Ultrasonography, Doppler, Duplex</subject><issn>0741-5214</issn><issn>1097-6809</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNp9Uk2L1TAULaI4b0Z_gBvJ0k1rkjZJH4IgM44KAy5UcBfykltNp21qbvq0_8MfbOobXbhwdSHng5tzblE8YbRilMnnfdUfseKUNRVtKyrkvWLH6F6VsqX7-8WOqoaVgrPmrDhH7CllTLTqYXHGBa9bxZtd8fMKjjCEeYQpkdARQ9wyD_CjdBD9ERzZUOvTSqLHWzJHcN4mHyYyBgfDJnEewSBkLHyJgLiBfiKzST6bIvnu09ff7GgSEIPrOKcwZtQSa2JI3hETE8SVYIIpoMdHxYPODAiP7-ZF8en69cfLt-XN-zfvLl_dlLYRLJU1p47yg3HAXc0EOCnlQTYKBIPOuFoaJSRthG1bqB2IRnXG5gdQhiurRH1RPDv55tW_LYBJjx4tDIOZICyomeT7vWxFTTOVnag2BsQInZ6jH01cNaN6K0P3OpehtzI0bXUuI2ue3tkvhxHcX8Wf9DPhxYkA-ZNHD1GjzZnZnHEEm7QL_r_2L_9R28FP3prhFlbAPixxyulpppFrqj9s17AdA2uyH-ef618Mt7PJ</recordid><startdate>20141201</startdate><enddate>20141201</enddate><creator>Hicks, Caitlin W., MD, MS</creator><creator>Canner, Joseph K., MHS</creator><creator>Arhuidese, Isibor, MD, MPH</creator><creator>Glebova, Natalia O., MD, PhD</creator><creator>Schneider, Eric, PhD</creator><creator>Qazi, Umair, MD, MPH</creator><creator>Perler, Bruce, MD</creator><creator>Malas, Mahmoud B., MD, MHS</creator><general>Elsevier Inc</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>7X8</scope></search><sort><creationdate>20141201</creationdate><title>Development of a duplex-derived velocity risk prediction model of disease progression in patients with moderate asymptomatic carotid artery stenosis</title><author>Hicks, Caitlin W., MD, MS ; Canner, Joseph K., MHS ; Arhuidese, Isibor, MD, MPH ; Glebova, Natalia O., MD, PhD ; Schneider, Eric, PhD ; Qazi, Umair, MD, MPH ; Perler, Bruce, MD ; Malas, Mahmoud B., MD, MHS</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c451t-320d02bade2d315ed666b647e51efad36a756045c88e3de547fac604e7a27c753</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Aged</topic><topic>Aged, 80 and over</topic><topic>Area Under Curve</topic><topic>Asymptomatic Diseases</topic><topic>Blood Flow Velocity</topic><topic>Carotid Artery, Common - diagnostic imaging</topic><topic>Carotid Artery, Common - physiopathology</topic><topic>Carotid Artery, Internal - diagnostic imaging</topic><topic>Carotid Artery, Internal - physiopathology</topic><topic>Carotid Stenosis - diagnostic imaging</topic><topic>Carotid Stenosis - physiopathology</topic><topic>Chi-Square Distribution</topic><topic>Decision Support Techniques</topic><topic>Disease Progression</topic><topic>Female</topic><topic>Humans</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Multivariate Analysis</topic><topic>Predictive Value of Tests</topic><topic>Proportional Hazards Models</topic><topic>Regional Blood Flow</topic><topic>Retrospective Studies</topic><topic>Risk Assessment</topic><topic>Risk Factors</topic><topic>ROC Curve</topic><topic>Surgery</topic><topic>Time Factors</topic><topic>Ultrasonography, Doppler, Duplex</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Hicks, Caitlin W., MD, MS</creatorcontrib><creatorcontrib>Canner, Joseph K., MHS</creatorcontrib><creatorcontrib>Arhuidese, Isibor, MD, MPH</creatorcontrib><creatorcontrib>Glebova, Natalia O., MD, PhD</creatorcontrib><creatorcontrib>Schneider, Eric, PhD</creatorcontrib><creatorcontrib>Qazi, Umair, MD, MPH</creatorcontrib><creatorcontrib>Perler, Bruce, MD</creatorcontrib><creatorcontrib>Malas, Mahmoud B., 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>MEDLINE - Academic</collection><jtitle>Journal of vascular surgery</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Hicks, Caitlin W., MD, MS</au><au>Canner, Joseph K., MHS</au><au>Arhuidese, Isibor, MD, MPH</au><au>Glebova, Natalia O., MD, PhD</au><au>Schneider, Eric, PhD</au><au>Qazi, Umair, MD, MPH</au><au>Perler, Bruce, MD</au><au>Malas, Mahmoud B., MD, MHS</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of a duplex-derived velocity risk prediction model of disease progression in patients with moderate asymptomatic carotid artery stenosis</atitle><jtitle>Journal of vascular surgery</jtitle><addtitle>J Vasc Surg</addtitle><date>2014-12-01</date><risdate>2014</risdate><volume>60</volume><issue>6</issue><spage>1585</spage><epage>1592</epage><pages>1585-1592</pages><issn>0741-5214</issn><eissn>1097-6809</eissn><abstract>Objective Previously, we described risk factors for disease progression in moderate asymptomatic carotid artery stenosis (ASCAS). The aim of the current study was to develop a risk prediction model for disease progression in this group. Methods All patients presenting between January 2005 and May 2012 with moderate (50%-69%) ASCAS, as determined by carotid artery duplex imaging, were included. Cox proportional hazard regression models accounting for measured duplex peak systolic velocity and end-diastolic velocity, and the internal carotid artery (ICA)/common carotid artery (CCA) ratio, with and without previously identified risk factors for progression (age, smoking, dual antiplatelet therapy), were used to develop receiver operating characteristic curves for predicting disease progression. Results The study analyzed 282 patients (52% male), aged 71 ± 9 years, with 2.6 ± 0.1 years follow-up and 25% disease progression at a mean time of 2.02 ± 0.18 years. Initial peak systolic velocity, end-diastolic velocity, and the ICA/CCA ratio were all significant independent predictors of progression. Receiver operating characteristic curve analyses suggested that a prediction model based on ICA/CCA ratio alone had optimal prediction efficacy (hazard ratio, 2.01; Harrell's C, 0.74; P < .001). Patients with ICA/CCA >2.5, 3.3, and 3.8 were found to have >10%, >20%, and >30% risk of disease progression over 2 years, respectively. Model sensitivity and specificity for predicting 10% risk of disease progression at 2 years was 80.7% and 64.0%, respectively (positive predictive value, 22.9%; negative predictive value, 96.1%). Conclusions We propose a clinical prediction model for moderate ASCAS disease progression that can be used to risk-stratify patients with >10% risk of progression at 2 years using ICA/CCA ratios. Implementation of this model may be useful for identifying high-risk patients who would benefit from routine carotid disease surveillance follow-up.</abstract><cop>United States</cop><pub>Elsevier Inc</pub><pmid>25238724</pmid><doi>10.1016/j.jvs.2014.08.056</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Aged Aged, 80 and over Area Under Curve Asymptomatic Diseases Blood Flow Velocity Carotid Artery, Common - diagnostic imaging Carotid Artery, Common - physiopathology Carotid Artery, Internal - diagnostic imaging Carotid Artery, Internal - physiopathology Carotid Stenosis - diagnostic imaging Carotid Stenosis - physiopathology Chi-Square Distribution Decision Support Techniques Disease Progression Female Humans Male Middle Aged Multivariate Analysis Predictive Value of Tests Proportional Hazards Models Regional Blood Flow Retrospective Studies Risk Assessment Risk Factors ROC Curve Surgery Time Factors Ultrasonography, Doppler, Duplex |
title | Development of a duplex-derived velocity risk prediction model of disease progression in patients with moderate asymptomatic carotid artery stenosis |
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