246 citations · 384 across the 27 of their papers we have counts for
32 papers
Optimal Biological Dose Combination Finding: A Design Roadmap and Robust Cross-Indication Bayesian Borrowing
Ayon Mukherjee, Kentaro Takeda, James M. S. Wason
Early-phase combination oncology trials increasingly seek the optimal biological dose combination (OBDC) rather than a maximum tolerated dose combination, in line with the FDA's Pr…
Evaluating the impact of outcome delay on the efficiency of two-arm group-sequential trials
Aritra Mukherjee, Michael J. Grayling, James M. S. Wason
Adaptive designs(AD) are a broad class of trial designs that allow preplanned modifications based on patient data providing improved efficiency and flexibility. However, a delay in…
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…
Online multiple hypothesis testing
David S. Robertson, James M. S. Wason, Aaditya Ramdas
Modern data analysis frequently involves large-scale hypothesis testing, which naturally gives rise to the problem of maintaining control of a suitable type I error rate, such as t…
Bayesian sample size determination in basket trials borrowing information between subsets
Haiyan Zheng, Michael J. Grayling, Pavel Mozgunov +2
Basket trials are increasingly used for the simultaneous evaluation of a new treatment in various patient subgroups under one overarching protocol. We propose a Bayesian approach t…
Online error control for platform trials
David S. Robertson, James M. S. Wason, Franz König +2
Platform trials evaluate multiple experimental treatments under a single master protocol, where new treatment arms are added to the trial over time. Given the multiple treatment co…
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…
Bayesian sample size determination using commensurate priors to leverage pre-experimental data
Haiyan Zheng, Thomas Jaki, James M. S. Wason
This paper develops Bayesian sample size formulae for experiments comparing two groups. We assume the experimental data will be analysed in the Bayesian framework, where pre-experi…
Conditional Power and Friends: The Why and How of (Un)planned, Unblinded Sample Size Recalculations in Confirmatory Trials
Kevin Kunzmann, Michael J. Grayling, Kim M. Lee +3
Adapting the final sample size of a trial to the evidence accruing during the trial is a natural way to address planning uncertainty. Designs with adaptive sample size need to acco…
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…
A review of Bayesian perspectives on sample size derivation for confirmatory trials
Kevin Kunzmann, Michael J. Grayling, Kim May Lee +3
Sample size derivation is a crucial element of the planning phase of any confirmatory trial. A sample size is typically derived based on constraints on the maximal acceptable type…
Graphical approaches for the control of generalised error rates
David S. Robertson, James M. S. Wason, Frank Bretz
When simultaneously testing multiple hypotheses, the usual approach in the context of confirmatory clinical trials is to control the familywise error rate (FWER), which bounds the…
Two-Stage Penalized Regression Screening to Detect Biomarker-Treatment Interactions in Randomized Clinical Trials
Jixiong Wang, Ashish Patel, James M. S. Wason +1
High-dimensional biomarkers such as genomics are increasingly being measured in randomized clinical trials. Consequently, there is a growing interest in developing methods that imp…
Sample Size Estimation using a Latent Variable Model for Mixed Outcome Co-Primary, Multiple Primary and Composite Endpoints
Martina McMenamin, Jessica K. Barrett, Anna Berglind +1
Mixed outcome endpoints that combine multiple continuous and discrete components to form co-primary, multiple primary or composite endpoints are often employed as primary outcome m…
Bayesian design and analysis of external pilot trials for complex interventions
Duncan T. Wilson, James M. S. Wason, Julia Brown +2
External pilot trials of complex interventions are used to help determine if and how a confirmatory trial should be undertaken, providing estimates of parameters such as recruitmen…
Borrowing of information across patient subgroups in a basket trial based on distributional discrepancy
Haiyan Zheng, James M. S. Wason
Basket trials have emerged as a new class of efficient approaches in oncology to evaluate a new treatment in several patient subgroups simultaneously. In this paper, we extend the…
A web application for the design of multi-arm clinical trials
Michael J Grayling, James MS Wason
Multi-arm designs provide an effective means of evaluating several treatments within the same clinical trial. Given the large number of treatments now available for testing in many…
Employing latent variable models to improve efficiency in composite endpoint analysis
Martina McMenamin, Jessica K. Barrett, Anna Berglind +1
Composite endpoints that combine multiple outcomes on different scales are common in clinical trials, particularly in chronic conditions. In many of these cases, patients will have…
Online control of the false discovery rate in biomedical research
David S. Robertson, James M. S. Wason
Modern biomedical research frequently involves testing multiple related hypotheses, while maintaining control over a suitable error rate. In many applications the false discovery r…
Blinded and unblinded sample size re-estimation in crossover trials balanced for period
Michael Grayling, Adrian Mander, James Wason
The determination of the sample size required by a crossover trial typically depends on the specification of one or more variance components. Uncertainty about the value of these p…
Design optimisation and post-trial analysis in group sequential stepped-wedge cluster randomised trials
Michael Grayling, David Robertson, James Wason +1
Recently, methodology was presented to facilitate the incorporation of interim analyses in stepped-wedge (SW) cluster randomised trials (CRTs). Here, we extend this previous discus…
Familywise error control in multi-armed response-adaptive trials
David S. Robertson, James M. S. Wason
Response-adaptive designs allow the randomization probabilities to change during the course of a trial based on cumulated response data, so that a greater proportion of patients ca…
Efficient determination of optimised multi-arm multi-stage experimental designs with control of generalised error-rates
Michael Grayling, James Wason, Adrian Mander
Primarily motivated by the drug development process, several publications have now presented methodology for the design of multi-arm multi-stage experiments with normally distribut…
A two-stage Fisher exact test for multi-arm studies with binary outcome variables
Michael Grayling, Adrian Mander, James Wason
In small sample studies with binary outcome data, use of a normal approximation for hypothesis testing can lead to substantial inflation of the type-I error-rate. Consequently, exa…