# Coenrollment of critically ill patients in PROSPECT: A protocol and statistical analysis plan

**Authors:** Alex Thabane, Diane Heels-Ansdell, Nicole Zytaruk, Deborah Cook

PMC · DOI: 10.1371/journal.pone.0345656 · PLOS One · 2026-03-23

## TL;DR

This paper outlines a study to assess how enrolling patients in multiple clinical trials might affect the results of a critical care trial on probiotics.

## Contribution

The study introduces a pre-planned secondary analysis protocol to evaluate the impact of coenrollment on trial outcomes in critical care.

## Key findings

- A Cox regression model will assess the effect of coenrollment on treatment outcomes.
- Baseline and center-level differences between coenrolled and non-coenrolled patients will be analyzed.
- Factors associated with coenrollment and its relationship to adverse events will be explored.

## Abstract

The 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).

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.

We 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.

The 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 will not undergo secondary research ethics board approval. Data will be presented in aggregate and without patient identifiers.

## Full-text entities

- **Diseases:** death (MESH:D003643), bicuspid aortic valve (MESH:D000082882), Pneumonia (MESH:D011014), mitral valve prolapse (MESH:D008945), infection (MESH:D007239), trauma (MESH:D014947), purulent sputum (MESH:D003234), rheumatic heart disease (MESH:D012214), ARDS (MESH:D012128), Frailty (MESH:D000073496), congenital heart disease (MESH:D006330), VAP (MESH:D053717), congenital valve disease (MESH:D006349), endocarditis (MESH:D004696), PROSPECT (MESH:D045169), acute pancreatitis (MESH:D010195), ThromboEmbolism (MESH:D013923), Critical Care (MESH:D016638), fever (MESH:D005334)
- **Chemicals:** microcrystalline cellulose (MESH:C109691)
- **Species:** Human immunodeficiency virus 1 (no rank) [taxon 11676], Lacticaseibacillus rhamnosus GG (strain) [taxon 568703], Homo sapiens (human, species) [taxon 9606]

## Full text

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## References

18 references — full list in the complete paper: https://tomesphere.com/paper/PMC13008073/full.md

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Source: https://tomesphere.com/paper/PMC13008073