Anxiolysis for laceration repair in children: statistical analysis plan for an open-label multicenter adaptive trial (ALICE)
- PMID: 40775649
- PMCID: PMC12333137
- DOI: 10.1186/s13063-025-09009-z
Anxiolysis for laceration repair in children: statistical analysis plan for an open-label multicenter adaptive trial (ALICE)
Abstract
Background: Laceration repairs are a common, yet distressing procedure in children. While a range of strategies is used to treat this distress, there is currently no standard of care. The Anxiolysis for Laceration Repair in Children (ALICE) trial aims to identify the most effective pharmacological agent to manage laceration repair-associated distress. This paper outlines the statistical analysis plan for the ALICE trial. The ALICE trial is a phase III, Bayesian, open-label trial that will identify the optimal agent for reducing distress among intranasal dexmedetomidine (IND), intranasal midazolam (INM), and inhaled nitrous oxide (N2O). The primary outcome, distress, will be measured by the Observational Scale of Behavioural Distress - Revised (OSBD-R). Scores from the OSBD-R will be analyzed using a Bayesian mixed effects model with data-driven prior distributions. Samples from the model's posterior distributions will be used to calculate the probability of being best statistic (Pbest), which will effectively rank the interventions. The trial will also evaluate delayed maladaptive behaviours, need for additional physical restraint, adverse events, and need for additional sedation as secondary outcomes. Furthermore, the trial will determine the costs associated with achieving adequate sedation in each treatment arm.
Discussion: This statistical analysis plan specifies the outcomes and analyses for the ALICE trial. The ALICE trial will provide evidence for the most effective agent for reducing distress in children receiving laceration repairs.
Trial registration: ClinicalTrials.gov NCT05383495. Registered on May 16, 2022.
Keywords: Bayesian clinical trial; Procedural pain; SUCRA; Statistical analysis plan; “Probability of being best”-statistic.
© 2025. The Author(s).
Conflict of interest statement
Ethics approval and consent to participate: Not applicable. Consent for publication: Not applicable. Competing interests: The authors declare that they have no competing interests.
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