32 citations · 74 across the 9 of their papers we have counts for
9 papers
Individual participant data from digital sources informed and improved precision in the evaluation of predictive biomarkers in Bayesian network meta-analysis
Chinyereugo M Umemneku-Chikere, Lorna Wheaton, Heather Poad +7
Objective: We aimed to develop a meta-analytic model for evaluation of predictive biomarkers and targeted therapies, utilising data from digital sources when individual participant…
Bridging disconnected networks of first and second lines of biologic therapies in rheumatoid arthritis with registry data: Bayesian evidence synthesis with target trial emulation
Sylwia Bujkiewicz, Janharpreet Singh, Lorna Wheaton +4
Objective: We aim to utilise real world data in evidence synthesis to optimise an evidence base for the effectiveness of biologic therapies in rheumatoid arthritis in order to allo…
Use of copula to model within-study association in bivariate meta-analysis of binomial data at the aggregate level a Bayesian approach and application to surrogate endpoint evaluation
Tasos Papanikos, John R Thompson, Keith R Abrams +1
Bivariate meta-analysis provides a useful framework for combining information across related studies and has been utilised to combine evidence from clinical studies to evaluate tre…
The use of registry data to extrapolate overall survival results from randomised controlled trials
Reynaldo Martina, Keith Abrams, Sylwia Bujkiewicz +5
Background: Pre-marketing authorisation estimates of survival are generally restricted to those observed directly in randomised controlled trials (RCTs). However, for regulatory an…
A Bayesian hierarchical meta-analytic method for modelling surrogate relationships that vary across treatment classes using aggregate data
Tasos Papanikos, John Thompson, Keith Abrams +4
Surrogate endpoints play an important role in drug development when they can be used to measure treatment effect early compared to the final clinical outcome and to predict clinica…
Impact of model misspecification in shared frailty survival models
Alessandro Gasparini, Mark S. Clements, Keith R. Abrams +1
Survival models incorporating random effects to account for unmeasured heterogeneity are being increasingly used in biostatistical and applied research. Specifically, unmeasured co…