Opportunities and challenges with decentralized trials in Neuroscience

Author:

Burger Hans Ulrich1ORCID,Van de Casteele Tom2,Rantell Khadija Rerhou3,Corey‐Lisle Patricia4,Sfikas Nikolaos5,Abt Markus1,

Affiliation:

1. Hoffmann‐La Roche AG Basel Switzerland

2. Lundbeck A/S Copenhagen Denmark

3. MHRA London UK

4. Genentech Inc. South San Francisco California USA

5. Novartis AG Basel Switzerland

Abstract

AbstractDecentralized clinical trials (DCTs), that is, studies integrating elements of telemedicine and mobile/local healthcare providers allowing for home‐based assessments, are an important concept to make studies more resilient and more patient‐centric by taking into consideration participant's views and shifting trial activities to better meet the needs of trial participants. There are however, not only advantages but also challenges associated with DCTs. An area to be addressed by appropriate statistical methodology is the integration of data resulting from a possible mix of home and clinic assessments at different visits for the same variable, especially in adjusting for sources of possible systematic differences. One source of systematic bias may be how a participant perceives their disease and treatment in their home versus in a clinical setting. In this paper, we will discuss these issues with a focus on Neuroscience when participants have the choice between home and clinic assessments to illustrate how to identify systematic biases and describe appropriate approaches to maintain clinical trial scientific rigor. We will describe the benefits and challenges of DCTs in Neuroscience and then describe the relevance of home versus clinic assessments using the estimand framework. We outline several options to enable home assessments in a study. Results of simulations will be presented to help deciding between design and analysis options in a simple scenario where there might be differences in response between clinic and home assessments.

Publisher

Wiley

Subject

Statistics, Probability and Uncertainty,General Medicine,Statistics and Probability

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