3 citations · 4 across the 6 of their papers we have counts for
6 papers
Comparing Bayesian Dynamic Borrowing and Synthetic Control Methods: Apples to Oranges?
Nicole Cizauskas, Foteini Strimenopoulou, Svetlana S. Cherlin +1
Bayesian dynamic borrowing (BDB) and synthetic control methods (SCM) are strategies to incorporate historical data in clinical trial design when control recruitment is a challenge.…
Augmented Binary Method for Basket Trials (ABBA)
Svetlana Cherlin, James M S Wason
In several clinical areas, traditional clinical trials often use a responder outcome, a composite endpoint that involves dichotomising a continuous measure. An augmented binary met…
Utilising high-dimensional data in randomised clinical trials: a review of methods and practice
Svetlana Cherlin, Theophile Bigirumurame, Michael J Grayling +6
Introduction: Even in effectively conducted randomised trials, the probability of a successful study remains relatively low. With recent advances in the next-generation sequencing…
Cross-validated risk scores adaptive enrichment (CADEN) design
Svetlana Cherlin, James M S Wason
We propose a Cross-validated ADaptive ENrichment design (CADEN) in which a trial population is enriched with a subpopulation of patients who are predicted to benefit from the treat…
Developing a predictive signature for two trial endpoints using the cross-validated risk scores method
Svetlana Cherlin, James M. S. Wason
The existing cross-validated risk scores (CVRS) design has been proposed for developing and testing the efficacy of a treatment in a high-efficacy patient group (the sensitive grou…
The effect of non-reversibility on inferring rooted phylogenies
S. Cherlin, T. M. W. Nye, S. E. Heaps +3
Most phylogenetic models assume that the evolutionary process is stationary and reversible. As a result, the root of the tree cannot be inferred as part of the analysis because the…