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dc.contributor.authorBanerjee, Soumya
dc.contributor.authorSofack, Ghislain
dc.contributor.authorPapakonstantinou, Thodoris
dc.contributor.authorAvraam, Demetris
dc.contributor.authorBurton, Paul
dc.contributor.authorZoeller, Daniella
dc.contributor.authorBishop, Tom
dc.date.accessioned2022-05-25T23:30:48Z
dc.date.available2022-05-25T23:30:48Z
dc.identifier.issn1756-0500
dc.identifier.urihttps://www.repository.cam.ac.uk/handle/1810/337489
dc.description.abstractObjective Achieving sufficient statistical power in a survival analysis usually requires large amounts of data from different sites. Sensitivity of individual-level data, ethical and practical considerations regarding data sharing across institutions could be a potential challenge for achieving this added power. Hence we implemented a federated meta-analysis approach of survival models in DataSHIELD, where only anonymous aggregated data are shared across institutions, while simultaneously allowing for exploratory, interactive modelling. In this case, meta-analysis techniques to combine analysis results from each site are a solution, but an analytic workflow involving local analysis undertaken at individual studies hinders exploration. Thus, the aim is to provide a framework for performing meta-analysis of Cox regression models across institutions without manual analysis steps for the data providers. Results We introduce a package (dsSurvival) which allows privacy preserving meta-analysis of survival models, including the calculation of hazard ratios. Our tool can be of great use in biomedical research where there is a need for building survival models and there are privacy concerns about sharing data.
dc.publisherBioMed Central
dc.rightsAttribution 4.0 International
dc.rights.urihttps://creativecommons.org/licenses/by/4.0/
dc.titledsSurvival: Privacy preserving survival models for federated individual patient meta-analysis in DataSHIELD
dc.typeArticle
dc.publisher.departmentMrc Epidemiology Unit
dc.date.updated2022-05-25T05:32:20Z
prism.publicationNameBMC Research Notes
dc.identifier.doi10.17863/CAM.84903
dcterms.dateAccepted2022-05-25
rioxxterms.versionofrecord10.1186/s13104-022-06085-1
rioxxterms.versionVoR
dc.contributor.orcidBanerjee, Soumya [0000-0001-7748-9885]
rioxxterms.typeJournal Article/Review
cam.issuedOnline2022-06-03
cam.orpheus.success2022-06-07: VoR added to Apollo record
cam.depositDate2022-05-25
pubs.licence-identifierapollo-deposit-licence-2-1
pubs.licence-display-nameApollo Repository Deposit Licence Agreement


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Attribution 4.0 International
Except where otherwise noted, this item's licence is described as Attribution 4.0 International