A Novel Approach to Assess Advanced Biomarkers for Early Alzheimer's Detection

A Novel Approach to Assess Advanced Biomarkers for Early Alzheimer's Detection | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article A Novel Approach to Assess Advanced Biomarkers for Early Alzheimer's Detection Víctor Miguel Sierra Marquina, M Carmen Pardo Llorente, Alba María Franco Pereira This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9040335/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 11 You are reading this latest preprint version Abstract In a progressive disease such as the Alzheimer’s disease (AD), the availability of suitable biomarkers tracking the stages of its progression could markedly accelerate drug development by providing an earlier indication of drug efficacy. Investigators use diagnostic tests to classify disease stages into probable Alzheimer’s disease, mild cognitive impairment (MCI), and normal cognition aging (\hyperref[Xiong et al., 2006]{Xiong et al., 2006}). In this paper, we focus on developing a proper statistical overlap measure-based method to evaluate the diagnostic accuracy of tests with three diagnostic categories. Parametric and non-parametric approaches for the estimation of the overlap measure (OVL) are presented as well as its bootstrap confidence intervals (CIs). The performance of these estimations and its CIs are evaluated through simulations. Furthermore, it is compared with the Volume Under the ROC Surface (VUS), the most common measure to assess the accuracy of tests with three ordinal diagnostic categories. A neuropsychological data set from a longitudinal cohort study for the detection of biomarkers for identifying stages of Alzheimer's disease is discussed. Health sciences/Biomarkers Health sciences/Diseases Health sciences/Medical research Health sciences/Neurology Biological sciences/Neuroscience Diagnostic accuracy volume under the ROC surface (VUS) overlap measure (OVL) Alzheimer’s disease Full Text Additional Declarations No competing interests reported. Cite Share Download PDF Status: Under Review Version 1 posted Editorial decision: Revision requested 03 Apr, 2026 Reviews received at journal 02 Apr, 2026 Reviews received at journal 01 Apr, 2026 Reviewers agreed at journal 20 Mar, 2026 Reviewers agreed at journal 20 Mar, 2026 Reviewers agreed at journal 19 Mar, 2026 Reviewers invited by journal 18 Mar, 2026 Editor assigned by journal 18 Mar, 2026 Editor invited by journal 11 Mar, 2026 Submission checks completed at journal 09 Mar, 2026 First submitted to journal 09 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9040335","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":609560921,"identity":"f40a1f62-c53a-4b36-8591-b83e1cf5c485","order_by":0,"name":"Víctor Miguel Sierra Marquina","email":"","orcid":"","institution":"Complutense University of Madrid","correspondingAuthor":false,"prefix":"","firstName":"Víctor","middleName":"Miguel Sierra","lastName":"Marquina","suffix":""},{"id":609560922,"identity":"bb72f015-b85a-4a1e-92a1-d6b02e44a2ff","order_by":1,"name":"M Carmen Pardo Llorente","email":"","orcid":"","institution":"Complutense University of Madrid","correspondingAuthor":false,"prefix":"","firstName":"M","middleName":"Carmen Pardo","lastName":"Llorente","suffix":""},{"id":609560923,"identity":"79ec5b75-76e2-41c3-9c96-2dc543bbeaca","order_by":2,"name":"Alba María Franco Pereira","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAAtklEQVRIiWNgGAWjYDACdh6GDyCan3gtzDyMM0C0ZAPJWgwOEKuDv5n3YHNFzR154xvJTzcwVNQR1iJxmC+x8cyxZ4bbbqSZ3WA4c5gIaw7zmD9sYDucYHYjh+0GYxsRzpM/zGPY2PDvcILxDJCWf0Q4zACkpbHtcIKBBEhLAzNhLYYgvzT2HTacceaZ2Y2EY0T4Re5478HGhm+H5fnbk5/d+FBDhMNQQQKpGkbBKBgFo2AUYAcAQFs85MgNAm4AAAAASUVORK5CYII=","orcid":"","institution":"Complutense University of Madrid","correspondingAuthor":true,"prefix":"","firstName":"Alba","middleName":"María Franco","lastName":"Pereira","suffix":""}],"badges":[],"createdAt":"2026-03-05 13:10:34","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9040335/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9040335/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105563954,"identity":"9e40b8dc-e659-48e9-9f78-8afc7b297cb1","added_by":"auto","created_at":"2026-03-27 12:48:17","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":487893,"visible":true,"origin":"","legend":"","description":"","filename":"SierraMarquinaRevisedversion.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9040335/v1_covered_c859adc1-2779-4c37-95e4-7e86b00f8ce8.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"\u003cp\u003eA Novel Approach to Assess Advanced Biomarkers for Early Alzheimer's Detection\u003c/p\u003e","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":true,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":true,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Diagnostic accuracy, volume under the ROC surface (VUS), overlap measure (OVL), Alzheimer’s disease","lastPublishedDoi":"10.21203/rs.3.rs-9040335/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9040335/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"In a progressive disease such as the Alzheimer’s disease (AD), the availability of suitable biomarkers tracking the stages of its progression could markedly accelerate drug development by providing an earlier indication of drug efficacy. 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