Development of a Model to Predict 10-Year Risk of Ischemic and Hemorrhagic Stroke and Ischemic Heart Disease Using the China Kadoorie Biobank
Contemporary cardiovascular disease (CVD) risk prediction models are rarely applied in routine clinical practice in China due to substantial regional differences in absolute risks of major CVD types within China. Moreover, the inclusion of blood lipids in most risk prediction models also limits thei...
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Veröffentlicht in: | Neurology 2022-06, Vol.98 (23), p.e2307-e2317 |
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creator | Yang, Songchun Han, Yuting Yu, Canqing Guo, Yu Pang, Yuanjie Sun, Dianjianyi Pei, Pei Yang, Ling Chen, Yiping Du, Huaidong Wang, Hao Massa, M. Sofia Bennett, Derrick Clarke, Robert Chen, Junshi Chen, Zhengming Lv, Jun Li, Liming |
description | Contemporary cardiovascular disease (CVD) risk prediction models are rarely applied in routine clinical practice in China due to substantial regional differences in absolute risks of major CVD types within China. Moreover, the inclusion of blood lipids in most risk prediction models also limits their use in the Chinese population. We developed 10-year CVD risk prediction models excluding blood lipids that may be applicable to diverse regions of China.
We derived sex-specific models separately for ischemic heart disease (IHD), ischemic stroke (IS), and hemorrhagic stroke (HS) in addition to total CVD in the China Kadoorie Biobank. Participants were age 30-79 years without CVD at baseline. Predictors included age, systolic and diastolic blood pressure, use of blood pressure-lowering treatment, current daily smoking, diabetes, and waist circumference. Total CVD risks were combined in terms of conditional probability using the predicted risks of 3 submodels. Risk models were recalibrated in each region by 2 methods (practical and ideal) and risk prediction was estimated before and after recalibration.
Model derivation involved 489,596 individuals, including 45,947 IHD, 43,647 IS, and 11,168 HS cases during 11 years of follow-up. In women, the Harrell C was 0.732 (95% CI 0.706-0.758), 0.759 (0.738-0.779), and 0.803 (0.778-0.827) for IHD, IS, and HS, respectively. The Harrell C for total CVD was 0.734 (0.732-0.736), 0.754 (0.752-0.756), and 0.774 (0.772-0.776) for models before recalibration, after practical recalibration, and after ideal recalibration. The calibration performances improved after recalibration, with models after ideal recalibration showing the best model performances. The results for men were comparable to those for women.
Our CVD risk prediction models yielded good discrimination of IHD and stroke subtypes in addition to total CVD without including blood lipids. Flexible recalibration of our models for different regions could enable more widespread use using resident health records covering the overall Chinese population.
This study provides Class I evidence that a prediction model incorporating accessible clinical variables predicts 10-year risk of IHD, IS, and HS in the Chinese population age 30-79 years. |
doi_str_mv | 10.1212/WNL.0000000000200139 |
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We derived sex-specific models separately for ischemic heart disease (IHD), ischemic stroke (IS), and hemorrhagic stroke (HS) in addition to total CVD in the China Kadoorie Biobank. Participants were age 30-79 years without CVD at baseline. Predictors included age, systolic and diastolic blood pressure, use of blood pressure-lowering treatment, current daily smoking, diabetes, and waist circumference. Total CVD risks were combined in terms of conditional probability using the predicted risks of 3 submodels. Risk models were recalibrated in each region by 2 methods (practical and ideal) and risk prediction was estimated before and after recalibration.
Model derivation involved 489,596 individuals, including 45,947 IHD, 43,647 IS, and 11,168 HS cases during 11 years of follow-up. In women, the Harrell C was 0.732 (95% CI 0.706-0.758), 0.759 (0.738-0.779), and 0.803 (0.778-0.827) for IHD, IS, and HS, respectively. The Harrell C for total CVD was 0.734 (0.732-0.736), 0.754 (0.752-0.756), and 0.774 (0.772-0.776) for models before recalibration, after practical recalibration, and after ideal recalibration. The calibration performances improved after recalibration, with models after ideal recalibration showing the best model performances. The results for men were comparable to those for women.
Our CVD risk prediction models yielded good discrimination of IHD and stroke subtypes in addition to total CVD without including blood lipids. Flexible recalibration of our models for different regions could enable more widespread use using resident health records covering the overall Chinese population.
This study provides Class I evidence that a prediction model incorporating accessible clinical variables predicts 10-year risk of IHD, IS, and HS in the Chinese population age 30-79 years.</description><identifier>ISSN: 0028-3878</identifier><identifier>EISSN: 1526-632X</identifier><identifier>DOI: 10.1212/WNL.0000000000200139</identifier><identifier>PMID: 35410902</identifier><language>eng</language><publisher>United States: Lippincott Williams & Wilkins</publisher><subject>Adult ; Aged ; Biological Specimen Banks ; Cardiovascular Diseases - epidemiology ; China - epidemiology ; Female ; Hemorrhagic Stroke ; Humans ; Male ; Middle Aged ; Myocardial Ischemia - epidemiology ; Risk Factors</subject><ispartof>Neurology, 2022-06, Vol.98 (23), p.e2307-e2317</ispartof><rights>Lippincott Williams & Wilkins</rights><rights>Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.</rights><rights>Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology. 2022 American Academy of Neurology</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3687-1412dc090f389c56be1723a05aefaced8eba86134c74be7860c6028b124a74f23</citedby><cites>FETCH-LOGICAL-c3687-1412dc090f389c56be1723a05aefaced8eba86134c74be7860c6028b124a74f23</cites><orcidid>0000-0003-3651-6693</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>230,314,780,784,885,27923,27924</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/35410902$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Yang, Songchun</creatorcontrib><creatorcontrib>Han, Yuting</creatorcontrib><creatorcontrib>Yu, Canqing</creatorcontrib><creatorcontrib>Guo, Yu</creatorcontrib><creatorcontrib>Pang, Yuanjie</creatorcontrib><creatorcontrib>Sun, Dianjianyi</creatorcontrib><creatorcontrib>Pei, Pei</creatorcontrib><creatorcontrib>Yang, Ling</creatorcontrib><creatorcontrib>Chen, Yiping</creatorcontrib><creatorcontrib>Du, Huaidong</creatorcontrib><creatorcontrib>Wang, Hao</creatorcontrib><creatorcontrib>Massa, M. Sofia</creatorcontrib><creatorcontrib>Bennett, Derrick</creatorcontrib><creatorcontrib>Clarke, Robert</creatorcontrib><creatorcontrib>Chen, Junshi</creatorcontrib><creatorcontrib>Chen, Zhengming</creatorcontrib><creatorcontrib>Lv, Jun</creatorcontrib><creatorcontrib>Li, Liming</creatorcontrib><creatorcontrib>China Kadoorie Biobank Collaborative Group</creatorcontrib><creatorcontrib>on behalf of the China Kadoorie Biobank Collaborative Group</creatorcontrib><title>Development of a Model to Predict 10-Year Risk of Ischemic and Hemorrhagic Stroke and Ischemic Heart Disease Using the China Kadoorie Biobank</title><title>Neurology</title><addtitle>Neurology</addtitle><description>Contemporary cardiovascular disease (CVD) risk prediction models are rarely applied in routine clinical practice in China due to substantial regional differences in absolute risks of major CVD types within China. Moreover, the inclusion of blood lipids in most risk prediction models also limits their use in the Chinese population. We developed 10-year CVD risk prediction models excluding blood lipids that may be applicable to diverse regions of China.
We derived sex-specific models separately for ischemic heart disease (IHD), ischemic stroke (IS), and hemorrhagic stroke (HS) in addition to total CVD in the China Kadoorie Biobank. Participants were age 30-79 years without CVD at baseline. Predictors included age, systolic and diastolic blood pressure, use of blood pressure-lowering treatment, current daily smoking, diabetes, and waist circumference. Total CVD risks were combined in terms of conditional probability using the predicted risks of 3 submodels. Risk models were recalibrated in each region by 2 methods (practical and ideal) and risk prediction was estimated before and after recalibration.
Model derivation involved 489,596 individuals, including 45,947 IHD, 43,647 IS, and 11,168 HS cases during 11 years of follow-up. In women, the Harrell C was 0.732 (95% CI 0.706-0.758), 0.759 (0.738-0.779), and 0.803 (0.778-0.827) for IHD, IS, and HS, respectively. The Harrell C for total CVD was 0.734 (0.732-0.736), 0.754 (0.752-0.756), and 0.774 (0.772-0.776) for models before recalibration, after practical recalibration, and after ideal recalibration. The calibration performances improved after recalibration, with models after ideal recalibration showing the best model performances. The results for men were comparable to those for women.
Our CVD risk prediction models yielded good discrimination of IHD and stroke subtypes in addition to total CVD without including blood lipids. Flexible recalibration of our models for different regions could enable more widespread use using resident health records covering the overall Chinese population.
This study provides Class I evidence that a prediction model incorporating accessible clinical variables predicts 10-year risk of IHD, IS, and HS in the Chinese population age 30-79 years.</description><subject>Adult</subject><subject>Aged</subject><subject>Biological Specimen Banks</subject><subject>Cardiovascular Diseases - epidemiology</subject><subject>China - epidemiology</subject><subject>Female</subject><subject>Hemorrhagic Stroke</subject><subject>Humans</subject><subject>Male</subject><subject>Middle Aged</subject><subject>Myocardial Ischemia - epidemiology</subject><subject>Risk Factors</subject><issn>0028-3878</issn><issn>1526-632X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2022</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdUctu1DAUtRAVHQp_gJCXbFL8iuNskGAKTNUpIKACVpbj3EzMJPFge1rxEfxzPW0ZHt5YPj7n3MdB6Aklx5RR9vzLu-Ux2R9GCOX1PTSjJZOF5OzrfTTLsCq4qtQhehjj90wpWVU_QIe8FJTUhM3QrxO4hMFvRpgS9h02-Ny3MODk8YcArbMJU1J8AxPwRxfXO8pptD2MzmIztXgBow-hN6v8_pSCX8MNvOcssjLhExfBRMAX0U0rnHrA895NBp-Z1vvgAL9yvjHT-hE66MwQ4fHdfYQu3rz-PF8Uy_dvT-cvl4XlUlUFFZS1Ng_QcVXbUjZAK8YNKQ10xkKroDFKUi5sJRqolCRW5lU0lAlTiY7xI_Ti1nezbUZobR4-mEFvghtN-Km9cfrfn8n1euUvdc0IywvOBs_uDIL_sYWY9OiihWEwE_ht1EyKulSlEnWmiluqDT7GAN2-DCV6l6TOSer_k8yyp3-3uBf9ju6P75UfEoS4HrZXEHQPZkj9jZ-kVBS5YUYkqUixgyp-DZpdqck</recordid><startdate>20220607</startdate><enddate>20220607</enddate><creator>Yang, Songchun</creator><creator>Han, Yuting</creator><creator>Yu, Canqing</creator><creator>Guo, Yu</creator><creator>Pang, Yuanjie</creator><creator>Sun, Dianjianyi</creator><creator>Pei, Pei</creator><creator>Yang, Ling</creator><creator>Chen, Yiping</creator><creator>Du, Huaidong</creator><creator>Wang, Hao</creator><creator>Massa, M. 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Sofia ; Bennett, Derrick ; Clarke, Robert ; Chen, Junshi ; Chen, Zhengming ; Lv, Jun ; Li, Liming</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3687-1412dc090f389c56be1723a05aefaced8eba86134c74be7860c6028b124a74f23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2022</creationdate><topic>Adult</topic><topic>Aged</topic><topic>Biological Specimen Banks</topic><topic>Cardiovascular Diseases - epidemiology</topic><topic>China - epidemiology</topic><topic>Female</topic><topic>Hemorrhagic Stroke</topic><topic>Humans</topic><topic>Male</topic><topic>Middle Aged</topic><topic>Myocardial Ischemia - epidemiology</topic><topic>Risk Factors</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Yang, Songchun</creatorcontrib><creatorcontrib>Han, Yuting</creatorcontrib><creatorcontrib>Yu, Canqing</creatorcontrib><creatorcontrib>Guo, Yu</creatorcontrib><creatorcontrib>Pang, Yuanjie</creatorcontrib><creatorcontrib>Sun, Dianjianyi</creatorcontrib><creatorcontrib>Pei, Pei</creatorcontrib><creatorcontrib>Yang, Ling</creatorcontrib><creatorcontrib>Chen, Yiping</creatorcontrib><creatorcontrib>Du, Huaidong</creatorcontrib><creatorcontrib>Wang, Hao</creatorcontrib><creatorcontrib>Massa, M. Sofia</creatorcontrib><creatorcontrib>Bennett, Derrick</creatorcontrib><creatorcontrib>Clarke, Robert</creatorcontrib><creatorcontrib>Chen, Junshi</creatorcontrib><creatorcontrib>Chen, Zhengming</creatorcontrib><creatorcontrib>Lv, Jun</creatorcontrib><creatorcontrib>Li, Liming</creatorcontrib><creatorcontrib>China Kadoorie Biobank Collaborative Group</creatorcontrib><creatorcontrib>on behalf of the China Kadoorie Biobank Collaborative Group</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><collection>PubMed Central (Full Participant titles)</collection><jtitle>Neurology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Yang, Songchun</au><au>Han, Yuting</au><au>Yu, Canqing</au><au>Guo, Yu</au><au>Pang, Yuanjie</au><au>Sun, Dianjianyi</au><au>Pei, Pei</au><au>Yang, Ling</au><au>Chen, Yiping</au><au>Du, Huaidong</au><au>Wang, Hao</au><au>Massa, M. Sofia</au><au>Bennett, Derrick</au><au>Clarke, Robert</au><au>Chen, Junshi</au><au>Chen, Zhengming</au><au>Lv, Jun</au><au>Li, Liming</au><aucorp>China Kadoorie Biobank Collaborative Group</aucorp><aucorp>on behalf of the China Kadoorie Biobank Collaborative Group</aucorp><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Development of a Model to Predict 10-Year Risk of Ischemic and Hemorrhagic Stroke and Ischemic Heart Disease Using the China Kadoorie Biobank</atitle><jtitle>Neurology</jtitle><addtitle>Neurology</addtitle><date>2022-06-07</date><risdate>2022</risdate><volume>98</volume><issue>23</issue><spage>e2307</spage><epage>e2317</epage><pages>e2307-e2317</pages><issn>0028-3878</issn><eissn>1526-632X</eissn><abstract>Contemporary cardiovascular disease (CVD) risk prediction models are rarely applied in routine clinical practice in China due to substantial regional differences in absolute risks of major CVD types within China. Moreover, the inclusion of blood lipids in most risk prediction models also limits their use in the Chinese population. We developed 10-year CVD risk prediction models excluding blood lipids that may be applicable to diverse regions of China.
We derived sex-specific models separately for ischemic heart disease (IHD), ischemic stroke (IS), and hemorrhagic stroke (HS) in addition to total CVD in the China Kadoorie Biobank. Participants were age 30-79 years without CVD at baseline. Predictors included age, systolic and diastolic blood pressure, use of blood pressure-lowering treatment, current daily smoking, diabetes, and waist circumference. Total CVD risks were combined in terms of conditional probability using the predicted risks of 3 submodels. Risk models were recalibrated in each region by 2 methods (practical and ideal) and risk prediction was estimated before and after recalibration.
Model derivation involved 489,596 individuals, including 45,947 IHD, 43,647 IS, and 11,168 HS cases during 11 years of follow-up. In women, the Harrell C was 0.732 (95% CI 0.706-0.758), 0.759 (0.738-0.779), and 0.803 (0.778-0.827) for IHD, IS, and HS, respectively. The Harrell C for total CVD was 0.734 (0.732-0.736), 0.754 (0.752-0.756), and 0.774 (0.772-0.776) for models before recalibration, after practical recalibration, and after ideal recalibration. The calibration performances improved after recalibration, with models after ideal recalibration showing the best model performances. The results for men were comparable to those for women.
Our CVD risk prediction models yielded good discrimination of IHD and stroke subtypes in addition to total CVD without including blood lipids. Flexible recalibration of our models for different regions could enable more widespread use using resident health records covering the overall Chinese population.
This study provides Class I evidence that a prediction model incorporating accessible clinical variables predicts 10-year risk of IHD, IS, and HS in the Chinese population age 30-79 years.</abstract><cop>United States</cop><pub>Lippincott Williams & Wilkins</pub><pmid>35410902</pmid><doi>10.1212/WNL.0000000000200139</doi><orcidid>https://orcid.org/0000-0003-3651-6693</orcidid><oa>free_for_read</oa></addata></record> |
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subjects | Adult Aged Biological Specimen Banks Cardiovascular Diseases - epidemiology China - epidemiology Female Hemorrhagic Stroke Humans Male Middle Aged Myocardial Ischemia - epidemiology Risk Factors |
title | Development of a Model to Predict 10-Year Risk of Ischemic and Hemorrhagic Stroke and Ischemic Heart Disease Using the China Kadoorie Biobank |
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