{"id":2463,"date":"2021-06-24T00:00:00","date_gmt":"2021-06-24T04:00:00","guid":{"rendered":"https:\/\/icesontario.wpengine.com\/journal-articles\/development-and-validation-of-a-predictive-algorithm-for-risk-of-dementia-in-the-community-setting\/"},"modified":"2023-06-14T20:13:48","modified_gmt":"2023-06-15T00:13:48","slug":"development-and-validation-of-a-predictive-algorithm-for-risk-of-dementia-in-the-community-setting","status":"publish","type":"journal_article","link":"https:\/\/www.ices.on.ca\/fr\/publications\/journal-articles\/development-and-validation-of-a-predictive-algorithm-for-risk-of-dementia-in-the-community-setting\/","title":{"rendered":"Development and validation of a predictive algorithm for risk of dementia in the community setting"},"content":{"rendered":"<p><strong>Background<\/strong> &#x2014; Most dementia algorithms are unsuitable for population-level assessment and planning as they are designed for use in the clinical setting. A predictive risk algorithm to estimate 5-year dementia risk in the community setting was developed.<\/p>\n<p><strong>Methods<\/strong> &#x2014; The Dementia Population Risk Tool (DemPoRT) was derived using Ontario respondents to the Canadian Community Health Survey (survey years 2001 to 2012). Five-year incidence of physician-diagnosed dementia was ascertained by individual linkage to administrative healthcare databases and using a validated case ascertainment definition with follow-up to March 2017. Sex-specific proportional hazards regression models considering competing risk of death were developed using self-reported risk factors including information on socio-demographic characteristics, general and chronic health conditions, health behaviours and physical function.<\/p>\n<p><strong>Results<\/strong> &#x2014; Among 75 460 respondents included in the combined derivation and validation cohorts, there were 8448 cases of incident dementia in 348 677 person-years of follow-up (5-year cumulative incidence, men: 0.044, 95% CI: 0.042 to 0.047; women: 0.057, 95% CI: 0.055 to 0.060). The final full models each include 90 df (65 main effects and 25 interactions) and 28 predictors (8 continuous). The DemPoRT algorithm is discriminating (C-statistic in validation data: men 0.83 (95% CI: 0.81 to 0.85); women 0.83 (95% CI: 0.81 to 0.85)) and well-calibrated in a wide range of subgroups including behavioural risk exposure categories, socio-demographic groups and by diabetes and hypertension status.<\/p>\n<p><strong>Conclusions<\/strong> &#x2014; This algorithm will support the development and evaluation of population-level dementia prevention strategies, support decision-making for population health and can be used by individuals or their clinicians for individual risk assessment.<\/p>\n","protected":false},"excerpt":{"rendered":"<p>Background &#x2014; Most dementia algorithms are unsuitable for population-level assessment and planning as they are designed for use in the clinical setting. A predictive risk algorithm to estimate 5-year dementia risk in the community setting was developed. Methods &#x2014; The Dementia Population Risk Tool (DemPoRT) was derived using Ontario respondents to the Canadian Community Health [&hellip;]<\/p>\n","protected":false},"template":"","migration-helper-automated":[],"migration-manual":[],"topic":[],"migration-helper-qa-sample-set":[],"class_list":["post-2463","journal_article","type-journal_article","status-publish","hentry"],"acf":{"citation":"Fisher S, Manuel DG, Hsu AT, Bennett C, Tuna M, Eddeen AB, Sequeira Y, Jessri M, Taljaard M, Anderson GM, Tanuseputro P. <em>J Epidemiol Community Health<\/em>. 2021; 75(9):843-53. Epub 2021 Jun 24.","source_url":"https:\/\/jech.bmj.com\/content\/early\/2021\/06\/10\/jech-2020-214797","ices_scientist":[1107,1323,1382],"site":[6734],"research_program":[],"news_release":[],"journal_article":[],"atlas":[],"research_report":[],"infographic":[],"video":[],"downloads":null,"links":null,"sitecore_item_id":"C5CB6375-C69E-4D56-9C8D-FD05910B389B","sitecore_item_name":"Development-and-validation-of-a-predictive-algorithm-for-risk-of-dementia-in-the-community-setting","sitecore_field_values":"{\n  \"Title\": \"Development and validation of a predictive algorithm for risk of dementia in the community setting\",\n  \"Short title\": \"Development and validation of a\",\n  \"Summary\": \"This algorithm will support the development and evaluation of population-level dementia prevention strategies.\",\n  \"Citation\": \"<p>Fisher S, Manuel DG, Hsu AT, Bennett C, Tuna M, Eddeen AB, Sequeira Y, Jessri M, Taljaard M, Anderson GM, Tanuseputro P. <em>J Epidemiol Community Health<\/em>. 2021; 75(9):843-53. Epub 2021 Jun 24. DOI: <a href=\"https:\/\/doi.org\/10.1136\/jech-2020-214797\" title=\"opens external link\">https:\/\/doi.org\/10.1136\/jech-2020-214797<\/a><\/p>\",\n  \"Abstract\": \"<p><strong>Background<\/strong> &mdash; Most dementia algorithms are unsuitable for population-level assessment and planning as they are designed for use in the clinical setting. A predictive risk algorithm to estimate 5-year dementia risk in the community setting was developed.<\/p>n<p><strong>Methods<\/strong> &mdash; The Dementia Population Risk Tool (DemPoRT) was derived using Ontario respondents to the Canadian Community Health Survey (survey years 2001 to 2012). Five-year incidence of physician-diagnosed dementia was ascertained by individual linkage to administrative healthcare databases and using a validated case ascertainment definition with follow-up to March 2017. Sex-specific proportional hazards regression models considering competing risk of death were developed using self-reported risk factors including information on socio-demographic characteristics, general and chronic health conditions, health behaviours and physical function.<\/p>n<p><strong>Results<\/strong> &mdash; Among 75 460 respondents included in the combined derivation and validation cohorts, there were 8448 cases of incident dementia in 348 677 person-years of follow-up (5-year cumulative incidence, men: 0.044, 95% CI: 0.042 to 0.047; women: 0.057, 95% CI: 0.055 to 0.060). The final full models each include 90 df (65 main effects and 25 interactions) and 28 predictors (8 continuous). The DemPoRT algorithm is discriminating (C-statistic in validation data: men 0.83 (95% CI: 0.81 to 0.85); women 0.83 (95% CI: 0.81 to 0.85)) and well-calibrated in a wide range of subgroups including behavioural risk exposure categories, socio-demographic groups and by diabetes and hypertension status.<\/p>n<p><strong>Conclusions<\/strong> &mdash; This algorithm will support the development and evaluation of population-level dementia prevention strategies, support decision-making for population health and can be used by individuals or their clinicians for individual risk assessment.<\/p>n<p><a href=\"https:\/\/jech.bmj.com\/content\/early\/2021\/06\/10\/jech-2020-214797\" title=\"opens external link\">View full text<\/a><\/p>\",\n  \"Research Programs\": \"{5B1AF319-EC9B-4BF0-A9CD-D066ABE49D71}\",\n  \"ICES Locations\": \"{0AD77E2C-C883-4E93-8B9A-40B82D50E3A5}\",\n  \"ICES Scientists\": \"{B9979611-1657-47B5-B80F-08815BA48831}|{3178B170-580F-4CCA-A2D4-687D1150C87C}|{38899D1B-38E7-4517-8DA3-0BDDF1F9944D}\",\n  \"Posted Date\": \"20210624T000000\",\n  \"Show on Publications Landing Page\": \"1\",\n  \"In The News\": \"{C2FE5990-26B0-4213-9A28-2BA131C53C8F}\"\n}","previous_url":"https:\/\/www.ices.on.ca\/Publications\/Journal-Articles\/2021\/June\/Development-and-validation-of-a-predictive-algorithm-for-risk-of-dementia-in-the-community-setting"},"yoast_head":"<!-- This site is optimized with the Yoast SEO plugin v28.0 - https:\/\/yoast.com\/product\/yoast-seo-wordpress\/ -->\n<title>ICES | Development and validation of a predictive algorithm for risk of dementia in the community setting<\/title>\n<meta name=\"description\" content=\"Background &#x2014; 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