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.
Louise Marston, Joanna Moncrieff, Stefan Priebe, Suzie Cro, Victoria R Cornelius
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引用次数: 0
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.
期刊介绍:
The Journal of Clinical Epidemiology strives to enhance the quality of clinical and patient-oriented healthcare research by advancing and applying innovative methods in conducting, presenting, synthesizing, disseminating, and translating research results into optimal clinical practice. Special emphasis is placed on training new generations of scientists and clinical practice leaders.