Individual level surrogacy of MRI T2 lesion information for future disease severity: a methodological discussion and application to recent MS Phase II and III trials

Individual level surrogacy of MRI T2 lesion information for future disease severity: a methodological discussion and application to recent MS Phase II and III trials | 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 Research Article Individual level surrogacy of MRI T2 lesion information for future disease severity: a methodological discussion and application to recent MS Phase II and III trials Stefan Buchka, Havla Joachim, Irmak Ön Begüm, Raphael Rehms, Ulrich Mansmann This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3958151/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background: Individual-level surrogacy (ILS) describes settings where individual-patient information on a biomarker captures information on future patient-relevant clinical outcomes. For persons with relapsing-remitting multiple sclerosis (PwRRMS), whether the number of new or newly enlarged hyperintense lesions in T2 magnetic resonance images (MRI) or the T2 lesions’ volume can act as ILS for disability progression and disease activity is of interest. However, ILS of new T2 lesions for individual PwRRMS has not yet been demonstrated, although new T2 lesions already serve as a primary outcome parameter for pivotal trials. Methods: Our synthesis used individual-patient data from ten randomized controlled trials (n = 5673 PwRRMS). Longitudinal data on either the number or volume of new T2 lesions were analyzed as potential ILS for disability progression measured by the expanded disability status scale (EDSS) and disease activity shown by clinical relapses. ILS metrics were calculated: R 2 A ) for the Meta-analytic (MA) and LRF (likelihood reduction factor) for the information theoretic (IT) approach. A simulation study elucidates the approaches’ potential to detect ILS and provides the basis to interpret the results derived from the trial data. Results : The simulation study demonstrates good performance for the IT approach. MA algorithms work well when applied to continuous data. When applied to counting data, the results may numerically be unstable. However, transformations of the counting data allow successful calculations with methods for Gaussian data. Analyses following IT methodology provide in all trial-based settings reliable results on ILS and identified two studies with weak ILS for the combination of T2 Volume and EDSS (LRF = 0.21, CI 95% : 0.16 – 0.26; LRF = 0.28, CI 95% : 0.23 – 0.34). Conclusion : The simulation study showed robust and sensitive results for IT and MA when not applied to counting data outcomes-based ILS strategies. The high potential of these algorithms to detect ILS strengthens the interpretation of our findings. Within most arms of ten pivotal MS trials, ILS measures were close to zero. Evidence on the surrogacy of T2 lesion measures and disease progression and activity as a general principle could not be generated. More research using proper designs and methodology is needed. Individual-level surrogate evaluation information-theoretic methods meta-analytic approach multi-trial data analysis longitudinal Bayesian joint model relapsing-remitting multiple sclerosis MRI T2 lesions MS disability progression MS disease activity Full Text Additional Declarations Competing interest reported. J.H. reports a grant for OCT research from the Friedrich-Baur-Stiftung and Merck, personal fees, and nonfinancial support from “Merck”, “Alexion”, “Novartis”, “Roche”, “Celgene”, “Biogen”, “Bayer” and “Horizon” and nonfinancial support of the Sumaira-Foundation and Guthy-Jackson Charitable Foundation, all outside the submitted work. 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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-3958151","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":273972382,"identity":"b90cf48b-b06e-49c0-b4f4-c42a095d112a","order_by":0,"name":"Stefan Buchka","email":"","orcid":"","institution":"Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, LMU Munich","correspondingAuthor":false,"prefix":"","firstName":"Stefan","middleName":"","lastName":"Buchka","suffix":""},{"id":273972383,"identity":"3af6d344-4eae-45d0-a531-103bb9d4f3d9","order_by":1,"name":"Havla Joachim","email":"","orcid":"","institution":"Institute of Clinical Neuroimmunology, LMU University Hospital, Faculty of Medicine, LMU Munich","correspondingAuthor":false,"prefix":"","firstName":"Havla","middleName":"","lastName":"Joachim","suffix":""},{"id":273972384,"identity":"d77c332b-d8ef-4d0b-a5a6-18521ea33c85","order_by":2,"name":"Irmak Ön Begüm","email":"","orcid":"","institution":"Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, LMU Munich","correspondingAuthor":false,"prefix":"","firstName":"Irmak","middleName":"Ön","lastName":"Begüm","suffix":""},{"id":273972385,"identity":"bf4c2b64-97f7-4f8a-85ce-ef571af9cc48","order_by":3,"name":"Raphael Rehms","email":"","orcid":"","institution":"Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, LMU Munich","correspondingAuthor":false,"prefix":"","firstName":"Raphael","middleName":"","lastName":"Rehms","suffix":""},{"id":273972386,"identity":"50d16fe8-a2c9-41e4-9831-52b3f4d3bf1f","order_by":4,"name":"Ulrich Mansmann","email":"data:image/png;base64,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","orcid":"","institution":"Institute for Medical Information Processing, Biometry, and Epidemiology (IBE), Faculty of Medicine, LMU Munich","correspondingAuthor":true,"prefix":"","firstName":"Ulrich","middleName":"","lastName":"Mansmann","suffix":""}],"badges":[],"createdAt":"2024-02-15 08:59:24","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-3958151/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-3958151/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":65099454,"identity":"d3b78719-57c7-418e-811b-d2202bc34cad","added_by":"auto","created_at":"2024-09-23 15:09:43","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1507520,"visible":true,"origin":"","legend":"","description":"","filename":"ManuscriptBuchkaetal.pdf","url":"https://assets-eu.researchsquare.com/files/rs-3958151/v1_covered_389c0d69-5779-4d16-96ea-c23c1aef135b.pdf"},{"id":51459537,"identity":"1292c8d8-30a4-462d-8cd8-1beef481896a","added_by":"auto","created_at":"2024-02-22 03:45:30","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":6611273,"visible":true,"origin":"","legend":"","description":"","filename":"Additionalfile1.docx","url":"https://assets-eu.researchsquare.com/files/rs-3958151/v1/6752836c0a22216d29cda5af.docx"}],"financialInterests":"Competing interest reported. J.H. reports a grant for OCT research from the Friedrich-Baur-Stiftung and Merck, personal fees, and nonfinancial support from “Merck”, “Alexion”, “Novartis”, “Roche”, “Celgene”, “Biogen”, “Bayer” and “Horizon” and nonfinancial support of the Sumaira-Foundation and Guthy-Jackson Charitable Foundation, all outside the submitted work.","formattedTitle":"Individual level surrogacy of MRI T2 lesion information for future disease severity: a methodological discussion and application to recent MS Phase II and III trials","fulltext":[],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":false,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"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":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Individual-level surrogate evaluation, information-theoretic methods, meta-analytic approach, multi-trial data analysis, longitudinal Bayesian joint model, relapsing-remitting multiple sclerosis, MRI T2 lesions, MS disability progression, MS disease activity","lastPublishedDoi":"10.21203/rs.3.rs-3958151/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3958151/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eIndividual-level surrogacy (ILS) describes settings where individual-patient information on a biomarker captures information on future patient-relevant clinical outcomes. For persons with relapsing-remitting multiple sclerosis (PwRRMS), whether the number of new or newly enlarged hyperintense lesions in T2 magnetic resonance images (MRI) or the T2 lesions’ volume can act as ILS for disability progression and disease activity is of interest. However, ILS of new T2 lesions for individual PwRRMS has not yet been demonstrated, although new T2 lesions already serve as a primary outcome parameter for pivotal trials.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods:\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eOur synthesis used individual-patient data from ten randomized controlled trials (n = 5673 PwRRMS). Longitudinal data on either the number or volume of new T2 lesions were analyzed as potential ILS for disability progression measured by the expanded disability status scale (EDSS) and disease activity shown by clinical relapses. ILS metrics were calculated: R\u003csup\u003e2\u003c/sup\u003e\u003csub\u003eA\u003c/sub\u003e) for the Meta-analytic (MA) and LRF (likelihood reduction factor) for the information theoretic (IT) approach. A simulation study elucidates the approaches’ potential to detect ILS and provides the basis to interpret the results derived from the trial data.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults\u003c/strong\u003e:\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe simulation study demonstrates good performance for the IT approach. MA algorithms work well when applied to continuous data. When applied to counting data, the results may numerically be unstable. However, transformations of the counting data allow successful calculations with methods for Gaussian data. Analyses following IT methodology provide in all trial-based settings reliable results on ILS and identified two studies with weak ILS for the combination of T2 Volume and EDSS (LRF = 0.21, CI\u003csub\u003e95%\u003c/sub\u003e: 0.16 – 0.26; LRF = 0.28, CI\u003csub\u003e95%\u003c/sub\u003e: 0.23 – 0.34).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion\u003c/strong\u003e:\u003c/p\u003e\n\u003cp\u003eThe simulation study showed robust and sensitive results for IT and MA when not applied to counting data outcomes-based ILS strategies. The high potential of these algorithms to detect ILS strengthens the interpretation of our findings. Within most arms of ten pivotal MS trials, ILS measures were close to zero. Evidence on the surrogacy of T2 lesion measures and disease progression and activity as a general principle could not be generated. More research using proper designs and methodology is needed.\u003c/p\u003e","manuscriptTitle":"Individual level surrogacy of MRI T2 lesion information for future disease severity: a methodological discussion and application to recent MS Phase II and III trials","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-02-22 03:45:22","doi":"10.21203/rs.3.rs-3958151/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"889468ea-c48f-4969-b405-52bbc19e1d9c","owner":[],"postedDate":"February 22nd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2024-09-23T15:09:14+00:00","versionOfRecord":[],"versionCreatedAt":"2024-02-22 03:45:22","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3958151","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3958151","identity":"rs-3958151","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}