White Matter Microstructure Improves Stroke Risk Prediction in the General Population
BACKGROUND AND PURPOSE—The presence of subclinical vascular brain disease, including white matter lesions and lacunar infarcts, substantially increases the risk of clinical stroke. White matter microstructural integrity is considered an earlier, potentially better, marker of the total burden of vasc...
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| Veröffentlicht in: | Stroke (1970) 2016-11, Vol.47 (11), p.2756-2762 |
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| creator | Evans, Tavia E O’Sullivan, Michael J de Groot, Marius Niessen, Wiro J Hofman, Albert Krestin, Gabriel P van der Lugt, Aad Portegies, Marileen L.P Koudstaal, Peter J Bos, Daniel Vernooij, Meike W Ikram, M Arfan |
| description | BACKGROUND AND PURPOSE—The presence of subclinical vascular brain disease, including white matter lesions and lacunar infarcts, substantially increases the risk of clinical stroke. White matter microstructural integrity is considered an earlier, potentially better, marker of the total burden of vascular brain disease. Its association with risk of stroke, a focal event, remains unknown.
METHODS—From the population-based Rotterdam Study, 4259 stroke-free participants (mean age63.6 years, 55.6% women) underwent brain magnetic resonance imaging, including diffusion magnetic resonance imaging, between 2006 and 2011. All participants were followed up for incident stroke until 2013. Cox proportional hazards models were used to associate markers of the microstructure of normal-appearing white matter with risk of stroke, adjusting for age, sex, white matter lesion volume, lacunar infarcts, and additionally for cardiovascular risk factors. Finally, we assessed the predictive value of white matter microstructural integrity for stroke beyond the Framingham Stroke Risk Profile.
RESULTS—During 18 476 person-years of follow-up, 58 people experienced a stroke. Both lower fractional anisotropy and higher MD increased risk of stroke, independent of age, sex, cardiovascular risk factors, white matter lesion volume, and lacunar infarcts (hazard ratio per SD increase infractional anisotropy0.75 [95% confidence interval, 0.57–0.98] and MD1.50 [95% confidence interval, 1.08–2.09]). MD improved stroke prediction beyond the Framingham Stroke Risk Profile (continuous net reclassification improvement0.52 [95% confidence interval, 0.24–0.81]).
CONCLUSIONS—Future stroke is predicted not only by prevalent vascular lesions but also by subtle alterations in the microstructure of normal-appearing white matter. Inclusion of this effect in risk prediction models produces a significant advantage in stroke prediction compared with the existing Framingham Stroke Risk Profile. |
| doi_str_mv | 10.1161/STROKEAHA.116.014651 |
| format | Article |
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METHODS—From the population-based Rotterdam Study, 4259 stroke-free participants (mean age63.6 years, 55.6% women) underwent brain magnetic resonance imaging, including diffusion magnetic resonance imaging, between 2006 and 2011. All participants were followed up for incident stroke until 2013. Cox proportional hazards models were used to associate markers of the microstructure of normal-appearing white matter with risk of stroke, adjusting for age, sex, white matter lesion volume, lacunar infarcts, and additionally for cardiovascular risk factors. Finally, we assessed the predictive value of white matter microstructural integrity for stroke beyond the Framingham Stroke Risk Profile.
RESULTS—During 18 476 person-years of follow-up, 58 people experienced a stroke. Both lower fractional anisotropy and higher MD increased risk of stroke, independent of age, sex, cardiovascular risk factors, white matter lesion volume, and lacunar infarcts (hazard ratio per SD increase infractional anisotropy0.75 [95% confidence interval, 0.57–0.98] and MD1.50 [95% confidence interval, 1.08–2.09]). MD improved stroke prediction beyond the Framingham Stroke Risk Profile (continuous net reclassification improvement0.52 [95% confidence interval, 0.24–0.81]).
CONCLUSIONS—Future stroke is predicted not only by prevalent vascular lesions but also by subtle alterations in the microstructure of normal-appearing white matter. Inclusion of this effect in risk prediction models produces a significant advantage in stroke prediction compared with the existing Framingham Stroke Risk Profile.</description><identifier>ISSN: 0039-2499</identifier><identifier>EISSN: 1524-4628</identifier><identifier>DOI: 10.1161/STROKEAHA.116.014651</identifier><identifier>PMID: 27703085</identifier><language>eng</language><publisher>United States: American Heart Association, Inc</publisher><subject>Aged ; Cardiovascular Diseases - epidemiology ; Diffusion Magnetic Resonance Imaging - methods ; Female ; Follow-Up Studies ; Humans ; Magnetic Resonance Imaging - methods ; Male ; Middle Aged ; Netherlands - epidemiology ; Prognosis ; Risk Assessment ; Stroke - diagnostic imaging ; Stroke - epidemiology ; Stroke, Lacunar - diagnostic imaging ; Stroke, Lacunar - epidemiology ; White Matter - diagnostic imaging</subject><ispartof>Stroke (1970), 2016-11, Vol.47 (11), p.2756-2762</ispartof><rights>2016 American Heart Association, Inc.</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c5641-610527c842d1769846afbfd8f079bd10ad420b29a00319a3e1f972e872eef47b3</citedby><cites>FETCH-LOGICAL-c5641-610527c842d1769846afbfd8f079bd10ad420b29a00319a3e1f972e872eef47b3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,3685,27923,27924</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/27703085$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Evans, Tavia E</creatorcontrib><creatorcontrib>O’Sullivan, Michael J</creatorcontrib><creatorcontrib>de Groot, Marius</creatorcontrib><creatorcontrib>Niessen, Wiro J</creatorcontrib><creatorcontrib>Hofman, Albert</creatorcontrib><creatorcontrib>Krestin, Gabriel P</creatorcontrib><creatorcontrib>van der Lugt, Aad</creatorcontrib><creatorcontrib>Portegies, Marileen L.P</creatorcontrib><creatorcontrib>Koudstaal, Peter J</creatorcontrib><creatorcontrib>Bos, Daniel</creatorcontrib><creatorcontrib>Vernooij, Meike W</creatorcontrib><creatorcontrib>Ikram, M Arfan</creatorcontrib><title>White Matter Microstructure Improves Stroke Risk Prediction in the General Population</title><title>Stroke (1970)</title><addtitle>Stroke</addtitle><description>BACKGROUND AND PURPOSE—The presence of subclinical vascular brain disease, including white matter lesions and lacunar infarcts, substantially increases the risk of clinical stroke. White matter microstructural integrity is considered an earlier, potentially better, marker of the total burden of vascular brain disease. Its association with risk of stroke, a focal event, remains unknown.
METHODS—From the population-based Rotterdam Study, 4259 stroke-free participants (mean age63.6 years, 55.6% women) underwent brain magnetic resonance imaging, including diffusion magnetic resonance imaging, between 2006 and 2011. All participants were followed up for incident stroke until 2013. Cox proportional hazards models were used to associate markers of the microstructure of normal-appearing white matter with risk of stroke, adjusting for age, sex, white matter lesion volume, lacunar infarcts, and additionally for cardiovascular risk factors. Finally, we assessed the predictive value of white matter microstructural integrity for stroke beyond the Framingham Stroke Risk Profile.
RESULTS—During 18 476 person-years of follow-up, 58 people experienced a stroke. Both lower fractional anisotropy and higher MD increased risk of stroke, independent of age, sex, cardiovascular risk factors, white matter lesion volume, and lacunar infarcts (hazard ratio per SD increase infractional anisotropy0.75 [95% confidence interval, 0.57–0.98] and MD1.50 [95% confidence interval, 1.08–2.09]). MD improved stroke prediction beyond the Framingham Stroke Risk Profile (continuous net reclassification improvement0.52 [95% confidence interval, 0.24–0.81]).
CONCLUSIONS—Future stroke is predicted not only by prevalent vascular lesions but also by subtle alterations in the microstructure of normal-appearing white matter. Inclusion of this effect in risk prediction models produces a significant advantage in stroke prediction compared with the existing Framingham Stroke Risk Profile.</description><subject>Aged</subject><subject>Cardiovascular Diseases - epidemiology</subject><subject>Diffusion Magnetic Resonance Imaging - methods</subject><subject>Female</subject><subject>Follow-Up Studies</subject><subject>Humans</subject><subject>Magnetic Resonance Imaging - methods</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Netherlands - epidemiology</subject><subject>Prognosis</subject><subject>Risk Assessment</subject><subject>Stroke - diagnostic imaging</subject><subject>Stroke - epidemiology</subject><subject>Stroke, Lacunar - diagnostic imaging</subject><subject>Stroke, Lacunar - epidemiology</subject><subject>White Matter - diagnostic imaging</subject><issn>0039-2499</issn><issn>1524-4628</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqFUU1P3DAQtSqqsqX8gwr5yCV0xrFj-7hCsKCCQHyIY-QkE2262c1iOyD-PY6WcmwPo9GT33vjecPYT4QTxAJ_3T_c3fw-m1_MJ3gCKAuFX9gMlZCZLITZYzOA3GZCWrvPvofwBwBEbtQ3ti-0hhyMmrHHp2UXiV-7GMnz6672Q4h-rOPoiV-ut354ocDvox9WxO-6sOK3npqujt2w4d2GxyXxBW3Iu57fDtuxd9PLD_a1dX2gw49-wB7Pzx5OL7Krm8Xl6fwqq1UhMSsQlNC1kaJBXVgjC9dWbWNa0LZqEFwjBVTCurQIWpcTtlYLMqmolbrKD9jxzjf983mkEMt1F2rqe7ehYQwlmlzlyipjE1XuqNOGwVNbbn23dv6tRCinQMvPQCdY7gJNsqOPCWO1puZT9DfBRDA7wuvQpwjDqh9fyZdLcn1c_s9b_kOargW60JAJSA6YUJYKVf4Of9qTdQ</recordid><startdate>201611</startdate><enddate>201611</enddate><creator>Evans, Tavia E</creator><creator>O’Sullivan, Michael J</creator><creator>de Groot, Marius</creator><creator>Niessen, Wiro J</creator><creator>Hofman, Albert</creator><creator>Krestin, Gabriel P</creator><creator>van der Lugt, Aad</creator><creator>Portegies, Marileen L.P</creator><creator>Koudstaal, Peter J</creator><creator>Bos, Daniel</creator><creator>Vernooij, Meike W</creator><creator>Ikram, M Arfan</creator><general>American Heart Association, Inc</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>7X8</scope></search><sort><creationdate>201611</creationdate><title>White Matter Microstructure Improves Stroke Risk Prediction in the General Population</title><author>Evans, Tavia E ; O’Sullivan, Michael J ; de Groot, Marius ; Niessen, Wiro J ; Hofman, Albert ; Krestin, Gabriel P ; van der Lugt, Aad ; Portegies, Marileen L.P ; Koudstaal, Peter J ; Bos, Daniel ; Vernooij, Meike W ; Ikram, M Arfan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c5641-610527c842d1769846afbfd8f079bd10ad420b29a00319a3e1f972e872eef47b3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Aged</topic><topic>Cardiovascular Diseases - epidemiology</topic><topic>Diffusion Magnetic Resonance Imaging - methods</topic><topic>Female</topic><topic>Follow-Up Studies</topic><topic>Humans</topic><topic>Magnetic Resonance Imaging - methods</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Netherlands - epidemiology</topic><topic>Prognosis</topic><topic>Risk Assessment</topic><topic>Stroke - diagnostic imaging</topic><topic>Stroke - epidemiology</topic><topic>Stroke, Lacunar - diagnostic imaging</topic><topic>Stroke, Lacunar - epidemiology</topic><topic>White Matter - diagnostic imaging</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Evans, Tavia E</creatorcontrib><creatorcontrib>O’Sullivan, Michael J</creatorcontrib><creatorcontrib>de Groot, Marius</creatorcontrib><creatorcontrib>Niessen, Wiro J</creatorcontrib><creatorcontrib>Hofman, Albert</creatorcontrib><creatorcontrib>Krestin, Gabriel P</creatorcontrib><creatorcontrib>van der Lugt, Aad</creatorcontrib><creatorcontrib>Portegies, Marileen L.P</creatorcontrib><creatorcontrib>Koudstaal, Peter J</creatorcontrib><creatorcontrib>Bos, Daniel</creatorcontrib><creatorcontrib>Vernooij, Meike W</creatorcontrib><creatorcontrib>Ikram, M Arfan</creatorcontrib><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>Stroke (1970)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Evans, Tavia E</au><au>O’Sullivan, Michael J</au><au>de Groot, Marius</au><au>Niessen, Wiro J</au><au>Hofman, Albert</au><au>Krestin, Gabriel P</au><au>van der Lugt, Aad</au><au>Portegies, Marileen L.P</au><au>Koudstaal, Peter J</au><au>Bos, Daniel</au><au>Vernooij, Meike W</au><au>Ikram, M Arfan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>White Matter Microstructure Improves Stroke Risk Prediction in the General Population</atitle><jtitle>Stroke (1970)</jtitle><addtitle>Stroke</addtitle><date>2016-11</date><risdate>2016</risdate><volume>47</volume><issue>11</issue><spage>2756</spage><epage>2762</epage><pages>2756-2762</pages><issn>0039-2499</issn><eissn>1524-4628</eissn><abstract>BACKGROUND AND PURPOSE—The presence of subclinical vascular brain disease, including white matter lesions and lacunar infarcts, substantially increases the risk of clinical stroke. White matter microstructural integrity is considered an earlier, potentially better, marker of the total burden of vascular brain disease. Its association with risk of stroke, a focal event, remains unknown.
METHODS—From the population-based Rotterdam Study, 4259 stroke-free participants (mean age63.6 years, 55.6% women) underwent brain magnetic resonance imaging, including diffusion magnetic resonance imaging, between 2006 and 2011. All participants were followed up for incident stroke until 2013. Cox proportional hazards models were used to associate markers of the microstructure of normal-appearing white matter with risk of stroke, adjusting for age, sex, white matter lesion volume, lacunar infarcts, and additionally for cardiovascular risk factors. Finally, we assessed the predictive value of white matter microstructural integrity for stroke beyond the Framingham Stroke Risk Profile.
RESULTS—During 18 476 person-years of follow-up, 58 people experienced a stroke. Both lower fractional anisotropy and higher MD increased risk of stroke, independent of age, sex, cardiovascular risk factors, white matter lesion volume, and lacunar infarcts (hazard ratio per SD increase infractional anisotropy0.75 [95% confidence interval, 0.57–0.98] and MD1.50 [95% confidence interval, 1.08–2.09]). MD improved stroke prediction beyond the Framingham Stroke Risk Profile (continuous net reclassification improvement0.52 [95% confidence interval, 0.24–0.81]).
CONCLUSIONS—Future stroke is predicted not only by prevalent vascular lesions but also by subtle alterations in the microstructure of normal-appearing white matter. Inclusion of this effect in risk prediction models produces a significant advantage in stroke prediction compared with the existing Framingham Stroke Risk Profile.</abstract><cop>United States</cop><pub>American Heart Association, Inc</pub><pmid>27703085</pmid><doi>10.1161/STROKEAHA.116.014651</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Aged Cardiovascular Diseases - epidemiology Diffusion Magnetic Resonance Imaging - methods Female Follow-Up Studies Humans Magnetic Resonance Imaging - methods Male Middle Aged Netherlands - epidemiology Prognosis Risk Assessment Stroke - diagnostic imaging Stroke - epidemiology Stroke, Lacunar - diagnostic imaging Stroke, Lacunar - epidemiology White Matter - diagnostic imaging |
| title | White Matter Microstructure Improves Stroke Risk Prediction in the General Population |
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