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Coenrollment of Critically Ill Patients in PROSPECT: A Protocol and Statistical Analysis Plan

Thabane, A.; Heels-Ansdell, D.; Zytaruk, N.; Cook, D. J.; PROSPECT Investigators, ; Canadian Critical Care Trials Group,

2025-03-31 intensive care and critical care medicine
10.1101/2025.03.29.25324889 medRxiv
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IntroductionThe enrollment of a patient into more than one study (i.e., coenrollment) has risks which warrant exploration, particularly with respect to possible effects on trial outcomes. This pre-planned secondary analysis will examine the sensitivity of treatment effects to coenrollment in an international critical care trial (Probiotics: Prevention of Severe Pneumonia and Endotracheal Colonization Trial (PROSPECT). Objective(s)The primary objective is to evaluate the sensitivity of the effect of probiotics on the primary endpoint of VAP to patient coenrollment in at least one other study. The secondary objectives are to describe the characteristics of coenrolled patients and the studies they were coenrolled into; examine any differences in baseline traits; understand differences in center-level characteristics between coenrolling and non-coenrolling centers; identify factors associated with coenrollment; and explore the relationship between coenrollment status and the incidence of adverse events. MethodsWe developed a protocol and statistical analysis plan (SAP) for this secondary analysis involving the conduct of a Cox regression model, including treatment allocation, coenrollment status, and the interaction between the two as independent variables. We also describe our planned statistical analyses for the secondary objectives, involving descriptive statistics, univariable analyses, and multivariable analyses. Ethics and DisseminationThe results of this study will be published in a peer-reviewed journal focused on critical care research or trial methodology, and presented at local, national, and international conferences. As a secondary analysis, this study does not require research ethics board approval. All data will be presented in aggregate and without patient identifiers.

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