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.
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http://dx.doi.org/10.1016/j.jclinepi.2025.111753 | DOI Listing |
J Intensive Care
March 2025
Department of Anaesthesiology and Critical Care, AIIMS, Jodhpur, India.
We commend the authors for their insightful study on inspiratory muscle training (IMT) in mechanically ventilated patients with difficult weaning, highlighting the robust use of maximum inspiratory pressure (MIP) as a key outcome. We suggest that a lower baseline maximum inspiratory pressure cutoff could better target patients with significant inspiratory dysfunction, improving the study's precision. Additionally, alternative imputation techniques, such as multiple imputation, could strengthen the handling of missing data.
View Article and Find Full Text PDFInt J Eat Disord
March 2025
Department of Psychosomatic Medicine and Psychotherapy, Behavioral Medicine Research Unit, Integrated Research and Treatment Center Adiposity Diseases, University of Leipzig Medical Center, Leipzig, Germany.
Objective: To determine the cost-effectiveness of cognitive-behavioral therapy (CBT) for adolescents with binge-eating disorder (BED), focusing on the costs per binge-free episode and per quality-adjusted life year (QALY) gained in comparison to a waitlist (WL) control group.
Method: In the prospective, randomized superiority Binge-Eating Disorder in Adolescents (BEDA) trial, evaluating the efficacy of CBT with 20 individual sessions over 4 months versus WL, clinical and cost data were assessed at baseline and after 4 months. Missing values were imputed using multiple imputation techniques.
J Clin Epidemiol
March 2025
Imperial Clinical Trials Unit, Imperial College London, UK.
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.
Sci Rep
March 2025
College of Resources, Sichuan Agricultural University, Chengdu, 611130, China.
Large sample sizes are crucial for accurately capturing spatial changes in soil properties by spatial interpolation methods. However, soil bulk density (BD) data in historical datasets is often incomplete, and it's uncertain if filled values enhance spatial interpolation accuracy. Using 2,883 cropland soil BD samples from the Sichuan Basin in China, we developed the best prediction models from traditional pedotransfer function (PTF), multiple linear regression (MLR), random forest (RF), and radial basis function neural network (RBFNN) to fill missing BD values for 1,336 samples.
View Article and Find Full Text PDFJ Biomed Inform
March 2025
Department of Biostatistics and Bioinformatics, Duke University, Durham, NC, USA; Duke Clinical Research Institute, Durham, NC, USA. Electronic address:
Objective: We propose FedIMPUTE, a communication-efficient federated learning (FL) based approach for missing value imputation (MVI). Our method enables multiple sites to collaboratively perform MVI in a privacy-preserving manner, addressing challenges of data-sharing constraints and population heterogeneity.
Methods: We begin by conducting MVI locally at each participating site, followed by the application of various FL strategies, ranging from basic to advanced, to federate local MVI models without sharing site-specific data.
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