Automated Breast Arterial Calcification Score Is Associated With Cardiovascular Outcomes and Mortality
Breast arterial calcification (BAC) on mammograms has emerged as a biomarker of women’s cardiovascular disease (CVD) risk, but there is a lack of quantification tools and clinical outcomes studies. This study assessed the association of BAC (both presence and quantity) with CVD outcomes. This single...
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description | Breast arterial calcification (BAC) on mammograms has emerged as a biomarker of women’s cardiovascular disease (CVD) risk, but there is a lack of quantification tools and clinical outcomes studies.
This study assessed the association of BAC (both presence and quantity) with CVD outcomes.
This single-center, retrospective study included women with a screening mammogram from 2007 to 2016. BAC was quantified using an artificial intelligence-generated score, which was assessed as both a binary and continuous variable. Regression analyses evaluated the association between BAC and mortality and a composite of acute myocardial infarction, heart failure, stroke, and mortality. Analyses were adjusted for age, race, diabetes, smoking, blood pressure, cholesterol, and history of CVD and chronic kidney disease.
A total of 18,092 women were included in this study (mean age 56.8 ± 11.0 years; diabetes [13%], hypertension [36%], hyperlipidemia [40%], and smoking [5%]). BAC was present in 4,223 (23%). Over a median follow-up of 6 years, death occurred in 7.8% and 2.3% of women with and without BAC, respectively. The composite occurred in 12.4% and 4.3% of women with and without BAC, respectively. Compared to those without, women with BAC had adjusted HRs of 1.49 (95% CI: 1.33-1.67) for mortality and 1.56 (95% CI: 1.41-1.72) for the composite. Each 10-point increase in the BAC score was associated with higher risk of mortality (HR: 1.08 [95% CI: 1.06-1.11]) and the composite (HR: 1.08 [95% CI: 1.06-1.10]). BAC was especially predictive of future events among younger women.
BAC is independently associated with mortality and CVD, especially among younger women. Measurement of BAC beyond presence adds incremental risk stratification. Quantifying BAC using an artificial intelligence algorithm is feasible, clinically relevant, and may improve personalized CVD risk stratification.
[Display omitted] |
doi_str_mv | 10.1016/j.jacadv.2024.101283 |
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fullrecord | <record><control><sourceid>proquest_pubme</sourceid><recordid>TN_cdi_pubmedcentral_primary_oai_pubmedcentral_nih_gov_11470245</recordid><sourceformat>XML</sourceformat><sourcesystem>PC</sourcesystem><els_id>S2772963X24005490</els_id><sourcerecordid>3116338375</sourcerecordid><originalsourceid>FETCH-LOGICAL-c2125-44f3c60d4a7426eedae319212a60f023a605cba7b6a81d6f263c68f4cb25f9b23</originalsourceid><addsrcrecordid>eNp9kU9v1DAQxS1ERau23wAhH7ns4j-Jk1xAy6pApaIeWgQ3a2KPqVdJXGxnpX57vKRU5cJpLM_vvRnNI-Q1Z2vOuHq3W-_AgN2vBRPV4Uu08gU5EU0jVp2SP14-ex-T85R2jDHRdVJV8hU5lp3supq3J8Rt5hxGyGjpx4iQMt3EjNHDQLcwGO-8gezDRG9MiEgvE92kFIz_o_ju813BovVhD8nMA0R6PWcTRkwUJku_hphh8PnhjBw5GBKeP9ZT8u3Txe32y-rq-vPldnO1MoKLelVVThrFbAVNJRSiBZS8Ky1QzDEhS6lND02voOVWOaEK3rrK9KJ2XS_kKfmw-N7P_YjW4JQjDPo--hHigw7g9b-dyd_pn2GvOa-acsq6OLx9dIjh14wp69Eng8MAE4Y5acm5krKVzQGtFtTEkFJE9zSHM32ISe_0EpM-xKSXmIrszfMdn0R_QynA-wXAcqm9x6iT8TgZtD6iydoG__8JvwG30Kct</addsrcrecordid><sourcetype>Open Access Repository</sourcetype><iscdi>true</iscdi><recordtype>article</recordtype><pqid>3116338375</pqid></control><display><type>article</type><title>Automated Breast Arterial Calcification Score Is Associated With Cardiovascular Outcomes and Mortality</title><source>DOAJ Directory of Open Access Journals</source><source>PubMed Central</source><source>Alma/SFX Local Collection</source><creator>Allen, Tara Shrout ; Bui, Quan M. ; Petersen, Gregory M. ; Mantey, Richard ; Wang, Junhao ; Nerlekar, Nitesh ; Eghtedari, Mohammad ; Daniels, Lori B.</creator><creatorcontrib>Allen, Tara Shrout ; Bui, Quan M. ; Petersen, Gregory M. ; Mantey, Richard ; Wang, Junhao ; Nerlekar, Nitesh ; Eghtedari, Mohammad ; Daniels, Lori B.</creatorcontrib><description>Breast arterial calcification (BAC) on mammograms has emerged as a biomarker of women’s cardiovascular disease (CVD) risk, but there is a lack of quantification tools and clinical outcomes studies.
This study assessed the association of BAC (both presence and quantity) with CVD outcomes.
This single-center, retrospective study included women with a screening mammogram from 2007 to 2016. BAC was quantified using an artificial intelligence-generated score, which was assessed as both a binary and continuous variable. Regression analyses evaluated the association between BAC and mortality and a composite of acute myocardial infarction, heart failure, stroke, and mortality. Analyses were adjusted for age, race, diabetes, smoking, blood pressure, cholesterol, and history of CVD and chronic kidney disease.
A total of 18,092 women were included in this study (mean age 56.8 ± 11.0 years; diabetes [13%], hypertension [36%], hyperlipidemia [40%], and smoking [5%]). BAC was present in 4,223 (23%). Over a median follow-up of 6 years, death occurred in 7.8% and 2.3% of women with and without BAC, respectively. The composite occurred in 12.4% and 4.3% of women with and without BAC, respectively. Compared to those without, women with BAC had adjusted HRs of 1.49 (95% CI: 1.33-1.67) for mortality and 1.56 (95% CI: 1.41-1.72) for the composite. Each 10-point increase in the BAC score was associated with higher risk of mortality (HR: 1.08 [95% CI: 1.06-1.11]) and the composite (HR: 1.08 [95% CI: 1.06-1.10]). BAC was especially predictive of future events among younger women.
BAC is independently associated with mortality and CVD, especially among younger women. Measurement of BAC beyond presence adds incremental risk stratification. Quantifying BAC using an artificial intelligence algorithm is feasible, clinically relevant, and may improve personalized CVD risk stratification.
[Display omitted]</description><identifier>ISSN: 2772-963X</identifier><identifier>EISSN: 2772-963X</identifier><identifier>DOI: 10.1016/j.jacadv.2024.101283</identifier><identifier>PMID: 39399518</identifier><language>eng</language><publisher>United States: Elsevier Inc</publisher><subject>artificial intelligence ; Original Research ; personalized risk stratification ; prevention ; subclinical atherosclerosis ; women’s health</subject><ispartof>JACC. Advances (Online), 2024-11, Vol.3 (11), p.101283, Article 101283</ispartof><rights>2024 The Authors</rights><rights>2024 The Authors.</rights><rights>2024 The Authors 2024</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><cites>FETCH-LOGICAL-c2125-44f3c60d4a7426eedae319212a60f023a605cba7b6a81d6f263c68f4cb25f9b23</cites><orcidid>0000-0002-4818-6719</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11470245/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC11470245/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,27903,27904,53769,53771</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/39399518$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Allen, Tara Shrout</creatorcontrib><creatorcontrib>Bui, Quan M.</creatorcontrib><creatorcontrib>Petersen, Gregory M.</creatorcontrib><creatorcontrib>Mantey, Richard</creatorcontrib><creatorcontrib>Wang, Junhao</creatorcontrib><creatorcontrib>Nerlekar, Nitesh</creatorcontrib><creatorcontrib>Eghtedari, Mohammad</creatorcontrib><creatorcontrib>Daniels, Lori B.</creatorcontrib><title>Automated Breast Arterial Calcification Score Is Associated With Cardiovascular Outcomes and Mortality</title><title>JACC. Advances (Online)</title><addtitle>JACC Adv</addtitle><description>Breast arterial calcification (BAC) on mammograms has emerged as a biomarker of women’s cardiovascular disease (CVD) risk, but there is a lack of quantification tools and clinical outcomes studies.
This study assessed the association of BAC (both presence and quantity) with CVD outcomes.
This single-center, retrospective study included women with a screening mammogram from 2007 to 2016. BAC was quantified using an artificial intelligence-generated score, which was assessed as both a binary and continuous variable. Regression analyses evaluated the association between BAC and mortality and a composite of acute myocardial infarction, heart failure, stroke, and mortality. Analyses were adjusted for age, race, diabetes, smoking, blood pressure, cholesterol, and history of CVD and chronic kidney disease.
A total of 18,092 women were included in this study (mean age 56.8 ± 11.0 years; diabetes [13%], hypertension [36%], hyperlipidemia [40%], and smoking [5%]). BAC was present in 4,223 (23%). Over a median follow-up of 6 years, death occurred in 7.8% and 2.3% of women with and without BAC, respectively. The composite occurred in 12.4% and 4.3% of women with and without BAC, respectively. Compared to those without, women with BAC had adjusted HRs of 1.49 (95% CI: 1.33-1.67) for mortality and 1.56 (95% CI: 1.41-1.72) for the composite. Each 10-point increase in the BAC score was associated with higher risk of mortality (HR: 1.08 [95% CI: 1.06-1.11]) and the composite (HR: 1.08 [95% CI: 1.06-1.10]). BAC was especially predictive of future events among younger women.
BAC is independently associated with mortality and CVD, especially among younger women. Measurement of BAC beyond presence adds incremental risk stratification. Quantifying BAC using an artificial intelligence algorithm is feasible, clinically relevant, and may improve personalized CVD risk stratification.
[Display omitted]</description><subject>artificial intelligence</subject><subject>Original Research</subject><subject>personalized risk stratification</subject><subject>prevention</subject><subject>subclinical atherosclerosis</subject><subject>women’s health</subject><issn>2772-963X</issn><issn>2772-963X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2024</creationdate><recordtype>article</recordtype><recordid>eNp9kU9v1DAQxS1ERau23wAhH7ns4j-Jk1xAy6pApaIeWgQ3a2KPqVdJXGxnpX57vKRU5cJpLM_vvRnNI-Q1Z2vOuHq3W-_AgN2vBRPV4Uu08gU5EU0jVp2SP14-ex-T85R2jDHRdVJV8hU5lp3supq3J8Rt5hxGyGjpx4iQMt3EjNHDQLcwGO-8gezDRG9MiEgvE92kFIz_o_ju813BovVhD8nMA0R6PWcTRkwUJku_hphh8PnhjBw5GBKeP9ZT8u3Txe32y-rq-vPldnO1MoKLelVVThrFbAVNJRSiBZS8Ky1QzDEhS6lND02voOVWOaEK3rrK9KJ2XS_kKfmw-N7P_YjW4JQjDPo--hHigw7g9b-dyd_pn2GvOa-acsq6OLx9dIjh14wp69Eng8MAE4Y5acm5krKVzQGtFtTEkFJE9zSHM32ISe_0EpM-xKSXmIrszfMdn0R_QynA-wXAcqm9x6iT8TgZtD6iydoG__8JvwG30Kct</recordid><startdate>202411</startdate><enddate>202411</enddate><creator>Allen, Tara Shrout</creator><creator>Bui, Quan M.</creator><creator>Petersen, Gregory M.</creator><creator>Mantey, Richard</creator><creator>Wang, Junhao</creator><creator>Nerlekar, Nitesh</creator><creator>Eghtedari, Mohammad</creator><creator>Daniels, Lori B.</creator><general>Elsevier Inc</general><general>Elsevier</general><scope>6I.</scope><scope>AAFTH</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0002-4818-6719</orcidid></search><sort><creationdate>202411</creationdate><title>Automated Breast Arterial Calcification Score Is Associated With Cardiovascular Outcomes and Mortality</title><author>Allen, Tara Shrout ; Bui, Quan M. ; Petersen, Gregory M. ; Mantey, Richard ; Wang, Junhao ; Nerlekar, Nitesh ; Eghtedari, Mohammad ; Daniels, Lori B.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c2125-44f3c60d4a7426eedae319212a60f023a605cba7b6a81d6f263c68f4cb25f9b23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2024</creationdate><topic>artificial intelligence</topic><topic>Original Research</topic><topic>personalized risk stratification</topic><topic>prevention</topic><topic>subclinical atherosclerosis</topic><topic>women’s health</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Allen, Tara Shrout</creatorcontrib><creatorcontrib>Bui, Quan M.</creatorcontrib><creatorcontrib>Petersen, Gregory M.</creatorcontrib><creatorcontrib>Mantey, Richard</creatorcontrib><creatorcontrib>Wang, Junhao</creatorcontrib><creatorcontrib>Nerlekar, Nitesh</creatorcontrib><creatorcontrib>Eghtedari, Mohammad</creatorcontrib><creatorcontrib>Daniels, Lori B.</creatorcontrib><collection>ScienceDirect Open Access Titles</collection><collection>Elsevier:ScienceDirect:Open Access</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>JACC. Advances (Online)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Allen, Tara Shrout</au><au>Bui, Quan M.</au><au>Petersen, Gregory M.</au><au>Mantey, Richard</au><au>Wang, Junhao</au><au>Nerlekar, Nitesh</au><au>Eghtedari, Mohammad</au><au>Daniels, Lori B.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Automated Breast Arterial Calcification Score Is Associated With Cardiovascular Outcomes and Mortality</atitle><jtitle>JACC. Advances (Online)</jtitle><addtitle>JACC Adv</addtitle><date>2024-11</date><risdate>2024</risdate><volume>3</volume><issue>11</issue><spage>101283</spage><pages>101283-</pages><artnum>101283</artnum><issn>2772-963X</issn><eissn>2772-963X</eissn><abstract>Breast arterial calcification (BAC) on mammograms has emerged as a biomarker of women’s cardiovascular disease (CVD) risk, but there is a lack of quantification tools and clinical outcomes studies.
This study assessed the association of BAC (both presence and quantity) with CVD outcomes.
This single-center, retrospective study included women with a screening mammogram from 2007 to 2016. BAC was quantified using an artificial intelligence-generated score, which was assessed as both a binary and continuous variable. Regression analyses evaluated the association between BAC and mortality and a composite of acute myocardial infarction, heart failure, stroke, and mortality. Analyses were adjusted for age, race, diabetes, smoking, blood pressure, cholesterol, and history of CVD and chronic kidney disease.
A total of 18,092 women were included in this study (mean age 56.8 ± 11.0 years; diabetes [13%], hypertension [36%], hyperlipidemia [40%], and smoking [5%]). BAC was present in 4,223 (23%). Over a median follow-up of 6 years, death occurred in 7.8% and 2.3% of women with and without BAC, respectively. The composite occurred in 12.4% and 4.3% of women with and without BAC, respectively. Compared to those without, women with BAC had adjusted HRs of 1.49 (95% CI: 1.33-1.67) for mortality and 1.56 (95% CI: 1.41-1.72) for the composite. Each 10-point increase in the BAC score was associated with higher risk of mortality (HR: 1.08 [95% CI: 1.06-1.11]) and the composite (HR: 1.08 [95% CI: 1.06-1.10]). BAC was especially predictive of future events among younger women.
BAC is independently associated with mortality and CVD, especially among younger women. Measurement of BAC beyond presence adds incremental risk stratification. Quantifying BAC using an artificial intelligence algorithm is feasible, clinically relevant, and may improve personalized CVD risk stratification.
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subjects | artificial intelligence Original Research personalized risk stratification prevention subclinical atherosclerosis women’s health |
title | Automated Breast Arterial Calcification Score Is Associated With Cardiovascular Outcomes and Mortality |
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