Exploring the effect of COVID-19 restrictions on the Social Functioning Scale in a clinical trial of Antipsychotic Reduction: using multiple imputation to target a hypothetical estimand
File(s)
Published version
Author(s)
Marston, Louise
Moncrieff, Joanna
Priebe, Stefan
Cro, Suzie
Cornelius, Victoria R
Type
Journal Article
Abstract
Objective
Many trials are affected by unforeseen events after recruitment has commenced. The aim of this study is to explore a hypothetical strategy for dealing with an intercurrent event that occurred during trial follow-up; COVID-19 restrictions.
Study Design and Setting
Secondary analysis of a randomised controlled trial in schizophrenia, comparing antipsychotic reduction versus maintenance medication on the Social Functioning Scale (SFS) score at 12 months’ follow-up. A hypothetical analysis strategy was used to estimate the treatment effect in a COVID-19 restriction-free world. Outcome data were set to missing and multiple imputation was used to replace values affected by COVID-19.
Results
The trial randomised 253 participants, 187 participants had an SFS score at 12 months, 75 of those were collected during COVID-19 restrictions. In the original complete case regression analysis, targeting a treatment policy estimand, the treatment effect was estimated to be 0.51 (95%CI -1.33, 2.35) points higher in the reduction group. After multiple imputation, targeting the hypothetical estimand, the mean SFS score was -3.01 (95%CI -7.22, 1.20) points lower in the reduction group, but varied with different assumptions about the timing of events and in sensitivity analyses to increase the size of difference between randomised groups.
Conclusion
We demonstrated how the intervention effect can change when estimating the intervention effect in a pandemic world (treatment policy estimand) versus a pandemic restriction-free world (hypothetical estimand) and that estimates are sensitive to imputation and input assumptions. Trialists should be aware of potential intercurrent events and plan the analysis to take them into account.
Many trials are affected by unforeseen events after recruitment has commenced. The aim of this study is to explore a hypothetical strategy for dealing with an intercurrent event that occurred during trial follow-up; COVID-19 restrictions.
Study Design and Setting
Secondary analysis of a randomised controlled trial in schizophrenia, comparing antipsychotic reduction versus maintenance medication on the Social Functioning Scale (SFS) score at 12 months’ follow-up. A hypothetical analysis strategy was used to estimate the treatment effect in a COVID-19 restriction-free world. Outcome data were set to missing and multiple imputation was used to replace values affected by COVID-19.
Results
The trial randomised 253 participants, 187 participants had an SFS score at 12 months, 75 of those were collected during COVID-19 restrictions. In the original complete case regression analysis, targeting a treatment policy estimand, the treatment effect was estimated to be 0.51 (95%CI -1.33, 2.35) points higher in the reduction group. After multiple imputation, targeting the hypothetical estimand, the mean SFS score was -3.01 (95%CI -7.22, 1.20) points lower in the reduction group, but varied with different assumptions about the timing of events and in sensitivity analyses to increase the size of difference between randomised groups.
Conclusion
We demonstrated how the intervention effect can change when estimating the intervention effect in a pandemic world (treatment policy estimand) versus a pandemic restriction-free world (hypothetical estimand) and that estimates are sensitive to imputation and input assumptions. Trialists should be aware of potential intercurrent events and plan the analysis to take them into account.
Date Issued
2025-06-01
Date Acceptance
2025-02-28
Citation
Journal of Clinical Epidemiology, 2025, 182
ISSN
0895-4356
Publisher
Elsevier BV
Journal / Book Title
Journal of Clinical Epidemiology
Volume
182
Copyright Statement
© 2025 The Author(s). Published by Elsevier Inc.
License URL
Identifier
https://www.ncbi.nlm.nih.gov/pubmed/40057141
PII: S0895-4356(25)00086-1
Subjects
COVID-19
estimands
missing data
multiple imputation
randomised controlled trial
social functioning
Publication Status
Published
Coverage Spatial
United States
Article Number
111753
Date Publish Online
2025-03-07