Granger, Emily; Todd, Jonathan; Charman, Susan; Cromwell, Elizabeth; Davies, Gwyneth; Frost, Freddy; Gifford, Alex; Huang, Bin; Mayer-Hamblett, Nicole; Naehrlich, Lutz; +5 more... Ostrenga, Josh; Stanojevic, Sanja; Szczesniak, Rhonda; Keogh, Ruth; CF-Trial Emulation Network; (2024) A protocol for emulating a published randomised controlled trial using registry data: effects of azithromycin in young adults with cystic fibrosis. Other. London School of Hygiene & Tropical Medicine, London. DOI: https://doi.org/10.17037/PUBS.04673143
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Abstract
INTRODUCTION: Target trial emulation is a framework for evaluating the effects of treatments using observational data. The trial emulation approach involves specifying key elements of a protocol for a target trial (a randomised controlled trial designed to address the question of interest) and then describing how best to emulate the trial using observational data. Recent years have seen an uptake of target trial emulation in several disease areas, although there are limited examples in cystic fibrosis (CF). This protocol describes a study which aims to assess the applicability of target trial emulation in CF. We aim to emulate an existing trial in CF and assess to what extent the results from the trial can be replicated using registry data. METHODS AND ANALYSIS: The target trial is a published randomised controlled trial which found evidence for beneficial effects of azithromycin use on lung function in young adults with CF. Two emulated trials are planned: one using data from the UK CF Registry and one using data from the US CF Registry. The inclusion and exclusion criteria, treatment and outcome definitions, follow-up period, and estimand of interest are all designed to match the published trial as closely as possible. The analysis step of the trial emulations will use causal inference methods to control for confounding. Results obtained in the emulated trials using registry data will be compared to those from the target trial.
Item Type | Monograph |
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Faculty and Department | Faculty of Epidemiology and Population Health > Dept of Medical Statistics |
Elements ID | 207849 |
Funder Name | UK Research and Innovation, Cystic Fibrosis Foundation, National Institutes of Health |
Grant number | MR/T041285/1, MR/S017968/1, StatNet SZCZES18Y7, SZCZES22A0-LAD, R01 HL141286 |
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Filename: Granger_etal_2024_a-protocol-for-emulating-a-published.pdf
Licence: Creative Commons: Attribution 4.0
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