Design and Analysis of Basket and Umbrella Trials

Lead Research Organisation: Lancaster University
Department Name: Mathematics and Statistics

Abstract

Prior to treatments' release onto the market, they undergo rigorous testing in clinical trials. Patients responses to such treatments can vary based on their intrinsic factors, and thus it is desirable to target treatments to patient's presenting different characteristics. To address this issue, so-called basket and umbrella trials are proposed. Basket trials consist of a single treatment applied to different patient groups who share a common characteristic but suffer from different diseases. Umbrella trials are composed of multiple treatments tested in parallel on patients who share the same disease but present a different genetic make-up.

We must also consider that, although the primary goal of a trial is to identify the most effective treatment, a secondary goal is to deliver the best treatment to patients within the trial. This is achieved through response-adaptive randomisation, a technique that alters the chance of being allocated a treatment on the basis of data from previously treated patients within the trial.

STOR-i and Roche have collaborated to create a project that aims to answer the following questions: How do we borrow information between treatment groups in basket trials? How can we utilize response-adaptive randomisation to improve the number of patients benefiting from the trial? And finally, how can we change the study populations of sub-studies within umbrella trials in order to incorporate newly identified targeted treatments? To tackle these problems, we first focus in on borrowing information between sub-studies and how to efficiently add a sub-group to a basket trial within this borrowing structure. Adding a sub-group is a highly beneficial feature of the aforementioned trial designs, as a new patient population may be identified part way through the trial. Following this, we will explore the operating characteristics of response-adaptive randomisation and how it is impacted on by temporal changes in the disease or health care provision.

In partnership with Roche.

Publications

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Studentship Projects

Project Reference Relationship Related To Start End Student Name
EP/S022252/1 01/10/2019 31/03/2028
2284124 Studentship EP/S022252/1 01/10/2019 31/03/2024 Elizabeth Daniells