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This study tested whether APOE-stratified disease timelines trained in a case-controlled setting generalize to the Rotterdam Study, using structural MRI biomarkers and co-initialized discriminative event-based modeling. Disease stage estimates and stage change rates were evaluated for diagnostic and prognostic value against clinical outcomes.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/progression-along-data-driven-disease-timelines-is-predictive-of-alzheimers-disease-in-a-population-based-cohort/156462/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/progression-along-data-driven-disease-timelines-is-predictive-of-alzheimers-disease-in-a-population-based-cohort/156462.png","ImageObject",300,407,{"name":92,"@type":93},"8796093062539","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-09-20","2026-08-28",true,{"@type":102,"interactionType":103,"userInteractionCount":34},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"What question does the study address about disease timelines in Alzheimer’s disease?","Question",{"text":112,"@type":113},"It evaluates whether data-driven disease timelines constructed in a case-controlled setting, stratified by APOE status, can be generalized to a population-based cohort and whether progression along these timelines predicts AD development.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What biomarkers and modeling approach are used?",{"text":117,"@type":113},"Seven volumetric biomarkers derived from structural MRI are used, and APOE-specific disease timelines are estimated with co-initialized discriminative event-based modeling (co-init DEBM), which can also infer disease stage for new subjects.",{"name":119,"@type":110,"acceptedAnswer":120},"How is predictive performance assessed across cohorts?",{"text":121,"@type":113},"The diagnostic and prognostic value of estimated disease stage is compared between the ADNI dataset (training and cross-validation) and the Rotterdam Study cohort (testing), including whether the rate of change in disease stage predicts pre-symptomatic AD.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},156462,1787959350,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":66,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":133,"file_id":134,"file_url":135,"file_type":136,"file_size":137,"view_count":34,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":138,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":129,"read_time":41},8796093062539,"Delft University of Technology  \nProgression along data-driven disease timelines is predictive of Alzheimer's disease in a population-based cohort  \nVenkatraghavan, Vikram; Vinke, Elisabeth J. ; Bron, Esther E. ; Niessen, Wiro J. ; Arfan Ikram, M. ; Klein, Stefan; Vernooij, Meike W.  \nDOI  \n10.1016/j.neuroimage.2021.118233  \nPublication date  \n2021  \nDocument Version  \nFinal published version  \nPublished in  \nNeuroImage  \nCitation (APA)  \nVenkatraghavan, V. , Vinke, E. J. , Bron, E. E. , Niessen, W. J. , Arfan Ikram, M. , Klein, S. , & Vernooij, M. W.(2021) . Progression along data-driven disease timelines is predictive of Alzheimer's disease in a populationbased cohort. NeuroImage, 238, Article 118233. [https://doi.org/10.1016/j.neuroimage.2021.118233](https://doi.org/10.1016/j.neuroimage.2021.118233)  \nImportant note  \nTo cite this publication, please use the final published version (if applicable) .  \nPlease check the document version above.  \nCopyright  \nOther than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.  \nTakedown policy  \nPlease contact us and provide details if you believe this document breaches copyrights.  \nWe will remove access to the work immediately and investigate your claim.  \nThis work is downloaded from Delft University of Technology.  \nFor technical reasons the number of authors shown on this cover page is limited to a maximum of 10.  \nNeuroImage 238 (2021) 118233  \nContents lists available at ScienceDirect  \nNeuroImage  \njournal [homepage:](homepage: www.elsevier.com/locate/neuroimage)[ www.elsevier.com/locate/neuroimage](homepage: www.elsevier.com/locate/neuroimage)  \n| Progression along data-driven disease timelines is predictive of Alzheimer’s disease in a population-based cohort\u003Cbr>Vikram Venkatraghavana,1, Elisabeth J. Vinkea,c,1, Esther E. Brona, Wiro J. Niessen a,b, M. Arfan Ikram c, Stefan Klein a,2, Meike W. Vernooija,c,2,∗ , for the Alzheimer’s Disease Neuroimaging Initiative\\#\u003Cbr>a Department of Radiology & Nuclear Medicine, Erasmus MC, University Medical Center Rotterdam, The Netherlands\u003Cbr>b Quantitative Imaging Group, Dept. of Imaging Physics, Faculty of Applied Sciences, Delft University of Technology, Delft, The Netherlands c Department of Epidemiology, Erasmus MC, University Medical Center Rotterdam, The Netherlands |  |  | |\n| --- | --- | --- | --- |\n| a r t i c l e i n f o |  | a b s t r a c t |  |\n| Keywords:\u003Cbr>Disease progression modeling Event-based model Alzheimer’s disease\u003Cbr>APOE\u003Cbr>Population study |  | Data-driven disease progression models have provided important insight into the timeline of brain changes in AD phenotypes. However, their utility in predicting the progression of pre-symptomatic AD in a populationbased setting has not yet been investigated. In this study, we investigated if the disease timelines constructed in a case-controlled setting, with subjects stratified according to APOE status, are generalizable to a populationbased cohort, and if progression along these disease timelines is predictive of AD. Seven volumetric biomarkers derived from structural MRI were considered. We estimated APOE-specific disease timelines of changes in these biomarkers using a recently proposed method called co-initialized discriminative event-based modeling (co-init DEBM). This method can also estimate a disease stage for new subjects by calculating their position along the disease timelines. The model was trained and cross-validated on the Alzheimer’s Disease Neuroimaging Initiative (ADNI) dataset, and tested on the population-based Rotterdam Study (RS) cohort. We compared the diagnostic and prognostic value of the disease stage in the two cohorts. Furthermore, we investigated if the rate of change of disease stage in RS participants with longitudinal MRI data was predictive of AD. In ","cbCaih7GN4ZSfS1C","https://ap.wps.com/l/cbCaih7GN4ZSfS1C","pdf",2164374,12,"English","# Abstract\n## Introduction\n## Methods and Modeling\n## Results and Evaluation\n## Conclusions","[{\"question\":\"What question does the study address about disease timelines in Alzheimer’s disease?\",\"answer\":\"It evaluates whether data-driven disease timelines constructed in a case-controlled setting, stratified by APOE status, can be generalized to a population-based cohort and whether progression along these timelines predicts AD development.\"},{\"question\":\"What biomarkers and modeling approach are used?\",\"answer\":\"Seven volumetric biomarkers derived from structural MRI are used, and APOE-specific disease timelines are estimated with co-initialized discriminative event-based modeling (co-init DEBM), which can also infer disease stage for new subjects.\"},{\"question\":\"How is predictive performance assessed across cohorts?\",\"answer\":\"The diagnostic and prognostic value of estimated disease stage is compared between the ADNI dataset (training and cross-validation) and the Rotterdam Study cohort (testing), including whether the rate of change in disease stage predicts pre-symptomatic AD.\"}]","Progression along data-driven disease timelines is predictive of Alzheimer's disease in a population-based cohort | PDF"]