Group sequential designs using early outcomes in the R package gsearly: implementation and application in randomized clinical trials

Group sequential designs using early outcomes in the R package gsearly: implementation and application in randomized clinical 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 Group sequential designs using early outcomes in the R package gsearly: implementation and application in randomized clinical trials Nick Parsons, Aminul Haque This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9158358/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background : Group sequential clinical trials are widely used for the design of randomized clinical trials as they offer the possibility of stopping a study early for either treatment efficacy or futility. A common feature of many such designs is that the main study outcome is observed at a number of fixed occasions during participant follow-up with inferences being made on the final outcome. In settings where early outcomes are available, they offer the possibility of large gains in efficiency, due to the additional information they provide, compared to conventional group sequential designs based on the final outcome alone. Designing a study incorporating early outcomes currently requires users to undertake simulation studies at the planning stage that can be both time-consuming and costly. However, recently published R software package gsearly allows for the construction of designs in a routine manner, using analytic expressions that do not require users to undertake simulations. A brief description of the methodological approach and key assumptions are presented together with examples explaining implementation in R and code for user application. Methods: A model for longitudinal outcomes, with an assumed approximate multivariate normal distribution and correlation model for repeated outcomes, is described and used to motivate simple analytic expressions for the variance of (information on) the treatment effect at interim time-points for proposed recruitment models during data accrual in a clinical trial. Results: A worked example explains the basic relationships between model inputs and information accrual. Also, a detailed example of how a clinical trial in knee osteoarthritis might be planned is used to describe the use of the main functions within R package gsearly. Data can be simulated from a fitted gsearly model and used to explore potential design options more generally and monitor information accrual in a practical setting. Conclusion: R package gsearly provides an interface for developing and powering clinical trials using group sequential designs with early outcomes. It provides a wide range of options for building designs based on making some simple model assumptions or user inputs and tools for simulating data and monitoring information accrual, making the methods available for those without expert knowledge in this application area. Group sequential designs Early outcomes Randomized controlled trials gsearly Full Text Additional Declarations No competing interests reported. Supplementary Files TrialPlanningMonitoringExamples.r WorkedExamples.r Cite Share Download PDF Status: Under Review Version 1 posted Reviews received at journal 02 May, 2026 Reviewers agreed at journal 31 Mar, 2026 Reviewers invited by journal 24 Mar, 2026 Editor invited by journal 24 Mar, 2026 Editor assigned by journal 19 Mar, 2026 Submission checks completed at journal 19 Mar, 2026 First submitted to journal 18 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-9158358","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":611565789,"identity":"37c11b22-1e8c-4b57-b24e-7bcaec79c3dc","order_by":0,"name":"Nick Parsons","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA+0lEQVRIie2RsWrCQByH/8dBXIKzQTCv8INASoamrxIJOEV8AAsKQlxqXX0Mp+AYOGiWa13dfYGIIE7ixUqp9AyOHe675fjgg99xRAbDf4Sr80N5Y+wHErZ4KKFfCbdvzJ3kqcG3YKtw4E5nYv+chgMUytBrSJC5NgkmlhcxGQdL+dVr91N1EcrQR0z4HGsTCJvnLOVAK/F5P+PwK0NWTljrh12TEdxF4u2DbHRNTvVJxFIB2iRos0xcEmXymmGWh64sACl9Z3Yq8HIx77Ht3Hk+1mLb2q2GcKdvXnmUQzhzZcpD2GnKSL+sovtnQVT3kRVMP9pgMBgM35wBOH9VOFPpn84AAAAASUVORK5CYII=","orcid":"","institution":"University of Warwick","correspondingAuthor":true,"prefix":"","firstName":"Nick","middleName":"","lastName":"Parsons","suffix":""},{"id":611565790,"identity":"4c8be7e5-ad8b-4780-9b72-4b3c296162f0","order_by":1,"name":"Aminul Haque","email":"","orcid":"","institution":"University of Warwick","correspondingAuthor":false,"prefix":"","firstName":"Aminul","middleName":"","lastName":"Haque","suffix":""}],"badges":[],"createdAt":"2026-03-18 10:53:28","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9158358/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9158358/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":105491047,"identity":"cbc3fbac-e433-44a2-be8c-ae3063f29016","added_by":"auto","created_at":"2026-03-26 15:26:58","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":475360,"visible":true,"origin":"","legend":"","description":"","filename":"GSDearlyoutcomesRpackagegsearly.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9158358/v1_covered_bd8453af-3f25-4ba4-bec1-e04d9f924edf.pdf"},{"id":105491003,"identity":"9b4943e5-2006-4bd6-a672-c07363c1b294","added_by":"auto","created_at":"2026-03-26 15:26:52","extension":"r","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":13903,"visible":true,"origin":"","legend":"","description":"","filename":"TrialPlanningMonitoringExamples.r","url":"https://assets-eu.researchsquare.com/files/rs-9158358/v1/f16d49eea878a46527775e60.r"},{"id":105490906,"identity":"e9d8f482-f19c-490a-96cf-f8e8feea8f8f","added_by":"auto","created_at":"2026-03-26 15:26:44","extension":"r","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":6799,"visible":true,"origin":"","legend":"","description":"","filename":"WorkedExamples.r","url":"https://assets-eu.researchsquare.com/files/rs-9158358/v1/79d0a4233d11d0d98ec008a4.r"}],"financialInterests":"No competing interests reported.","formattedTitle":"Group sequential designs using early outcomes in the R package gsearly: implementation and application in randomized clinical trials","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":"bmc-medical-research-methodology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmrm","sideBox":"Learn more about [BMC Medical Research Methodology](http://bmcmedresmethodol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmrm/default.aspx","title":"BMC Medical Research Methodology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Group sequential designs, Early outcomes, Randomized controlled trials, gsearly","lastPublishedDoi":"10.21203/rs.3.rs-9158358/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9158358/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground\u003c/strong\u003e: Group sequential clinical trials are widely used for the design of randomized clinical trials as they offer the possibility of stopping a study early for either treatment efficacy or futility. A common feature of many such designs is that the main study outcome is observed at a number of fixed occasions during participant follow-up with inferences being made on the final outcome. In settings where early outcomes are available, they offer the possibility of large gains in efficiency, due to the additional information they provide, compared to conventional group sequential designs based on the final outcome alone. Designing a study incorporating early outcomes currently requires users to undertake simulation studies at the planning stage that can be both time-consuming and costly. However, recently published R software package gsearly allows for the construction of designs in a routine manner, using analytic expressions that do not require users to undertake simulations. A brief description of the methodological approach and key assumptions are presented together with examples explaining implementation in R and code for user application.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods: \u003c/strong\u003eA model for longitudinal outcomes, with an assumed approximate multivariate normal distribution and correlation model for repeated outcomes, is described and used to motivate simple analytic expressions for the variance of (information on) the treatment effect at interim time-points for proposed recruitment models during data accrual in a clinical trial.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults:\u003c/strong\u003e A worked example explains the basic relationships between model inputs and information accrual. Also, a detailed example of how a clinical trial in knee osteoarthritis might be planned is used to describe the use of the main functions within R package gsearly. Data can be simulated from a fitted gsearly model and used to explore potential design options more generally and monitor information accrual in a practical setting.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusion:\u003c/strong\u003e R package gsearly provides an interface for developing and powering clinical trials using group sequential designs with early outcomes. It provides a wide range of options for building designs based on making some simple model assumptions or user inputs and tools for simulating data and monitoring information accrual, making the methods available for those without expert knowledge in this application area.\u003c/p\u003e","manuscriptTitle":"Group sequential designs using early outcomes in the R package gsearly: implementation and application in randomized clinical trials","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-26 15:26:09","doi":"10.21203/rs.3.rs-9158358/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"editorInvitedReview","content":"","date":"2026-05-02T22:40:59+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"31791437092413751298193372644419242148","date":"2026-04-01T00:58:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-24T12:20:15+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-24T10:13:22+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-03-19T09:08:58+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-19T09:08:22+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Medical Research Methodology","date":"2026-03-18T10:42:09+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-medical-research-methodology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bmrm","sideBox":"Learn more about [BMC Medical Research Methodology](http://bmcmedresmethodol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bmrm/default.aspx","title":"BMC Medical Research Methodology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"c95f26de-1ddc-4b6a-98ab-b222f7fcb6c1","owner":[],"postedDate":"March 26th, 2026","published":true,"recentEditorialEvents":[{"type":"editorInvitedReview","content":"","date":"2026-05-02T22:40:59+00:00","index":26,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[],"tags":[],"updatedAt":"2026-03-26T15:26:09+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-26 15:26:09","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9158358","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9158358","identity":"rs-9158358","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}