Estimands and their Estimators for Clinical Trials Impacted by the COVID-19 Pandemic: A Report from the NISS Ingram Olkin Forum Series on Unplanned Clinical Trial Disruptions

Abstract

The COVID-19 pandemic continues to affect the conduct of clinical trials globally. Complications may arise from pandemic-related operational challenges such as site closures, travel limitations and interruptions to the supply chain for the investigational product, or from health-related challenges such as COVID-19 infections. Some of these complications lead to unforeseen intercurrent events in the sense that they affect either the interpretation or the existence of the measurements associated with the clinical question of interest. In this article, we demonstrate how the ICH E9(R1) Addendum on estimands and sensitivity analyses provides a rigorous basis to discuss potential pandemic-related trial disruptions and to embed these disruptions in the context of study objectives and design elements. We introduce several hypothetical estimand strategies and review various causal inference and missing data methods, as well as a statistical method that combines unbiased and possibly biased estimators for estimation. To illustrate, we describe the features of a stylized trial, and how it may have been impacted by the pandemic. This stylized trial will then be revisited by discussing the changes to the estimand and the estimator to account for pandemic disruptions. Finally, we outline considerations for designing future trials in the context of unforeseen disruptions.

Keywords:

• Causal inference
• Hypothetical estimands
• Intercurrent events
• Missing data
• Treatment policy

Supplementary Materials

An AIPW estimator for the neuroscience trial and a Monte-Carlo study on combining unbiased and possibly biased estimators can be found in the Supplementary Materials.

Acknowledgments

The authors thank the National Institute of Statistical Sciences for facilitating Session 3 of the Ingram Olkin forum series on “Estimands and Missing Data.” The authors would also like to recognize the organizers of this forum series (those who are not an author on this article): Chris Jennison and Adam Lane as well as the speakers at the motivating workshop (those who are not an author on this article): Mouna Akacha and David Murray. We are grateful for feedback of Marcel Wolbers and Kaspar Rufibach on earlier versions of this manuscript.

Disclosure Statement

J.B.’s institution has received consultancy fees for the author’s advice on statistical methodology from AstraZeneca, Bayer, Novartis, Roche. J.B. has received consultancy fees from Bayer and Roche, and fees for provision of online courses from Roche.

Agentschap Innoveren en Ondernemen; Medical Research Council (MRC) International Centre for Genomic Medicine in Neuromuscular Disease; National Institute of Health Research;

Additional information

Funding

K.V.L. is supported by Fulbright Belgium, Belgian American Educational Foundation and VLAIO (Flemish Innovation and Entrepreneurship) under the Baekeland grant agreement HBC.2017.0219. S.T. is partially supported by the Department of Health and Human Services of the National Institutes of Health under award number R40MC41748. J.B. and C.O.P. are supported by UK Medical Research Council under grant agreement MR/T023953/1. H.M. is supported by VLAIO under Baekeland grant agreement HBC.2019.2155. S.C. is supported by an NIHR advanced research fellowship (NIHR 300593). The views expressed are those of the authors and not necessarily those of Fulbright Belgium, Belgian American Educational Foundation, VLAIO, the National Institutes of Health, the UK Medical Research Council, the NIHR or the Department of Health and Social Care.