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INTRODUCTION: The use of adjunctive antibiotics directed against exotoxin production in Staphylococcus aureus bacteremia (SAB) is widespread, and is recommended in many guidelines, but there is limited evidence underpinning this. Existing guidelines are based on the theoretical premise of toxin suppression, as many strains of S. aureus produce toxins such as leucocidins (e.g., Panton-Valentine Leucocidin (PVL), toxic shock syndrome toxin 1 (TSST-1), exfoliative toxins, and various enterotoxins). Many clinicians therefore believe that limiting exotoxin production release by S. aureus could reduce its virulence and improve clinical outcomes. Clindamycin, a protein synthesis inhibitor antibiotic, is commonly used for this purpose. We report the domain-specific protocol, embedded in a large adaptive, platform trial, seeking to definitively answer this question. METHODS AND ANALYSIS: The Staphylococcus aureus Network Adaptive Platform (SNAP) trial is a pragmatic, randomized, multi-center adaptive platform trial that aims to compare different SAB therapies, simultaneously, for 90-day mortality. The adjunctive treatment domain aims to test the effectiveness of adjunctive antibiotics, initially comparing clindamycin to no adjunctive antibiotic, but future adaptations may include other agents. Individuals will be randomized to receive either five days of adjunctive clindamycin (or lincomycin) or no adjunctive antibiotic therapy alongside standard of care antibiotics. Most participants with SAB (within 72hr of index blood culture and not contraindicated) will be eligible to participate in this domain. Prespecified analyses are defined in the statistical appendix to the core protocol and domain-specific secondary analyses will be adjusted for resistance to clindamycin, disease phenotype (complicated or uncomplicated SAB) and PVL-positive isolate.
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Importance: There is a recognized unmet need for clinical trials to provide evidence-informed care for infants, children and adolescents. This Special Communication outlines the capacity of 3 distinct trial design strategies, sequential, parallel, and a unified adult-pediatric bayesian adaptive design, to incorporate children into clinical trials and transform this current state of evidence inequity. A unified adult-pediatric whole-of-life clinical trial is demonstrated through the Staphylococcus aureus Network Adaptive Platform (SNAP) trial. Observations: Bayesian methods provide a framework for synthesizing data in the form of a probability model that can be used in the design and analysis of a clinical trial. Three trial design strategies are compared: (1) a sequential adult-pediatric bayesian approach that involves a separate, deferred pediatric trial that incorporates existing adult trial data into the analysis model to potentially reduce the pediatric trial sample size; (2) a parallel adult-pediatric bayesian trial whereby separate pediatric enrollment occurs in a parallel trial, running alongside an adult randomized clinical trial; and (3) a unified adult-pediatric bayesian adaptive design that supports the enrollment of both children and adults simultaneously in a whole-of-life bayesian adaptive randomized clinical trial. The SNAP trial whole-of-life design uses a bayesian hierarchical model that allows information sharing (also known as borrowing) between trial age groups by linking intervention effects of children and adults, thereby improving inference in both groups. Conclusion and Relevance: Bayesian hierarchical models may provide more precision for estimates of safety and efficacy of treatments in trials with heterogenous populations compared to traditional methods of analysis. They facilitate the inclusion of children in clinical trials and a shift from children deemed therapeutic orphans to the vision of no child left behind in clinical trials to ensure evidence for clinical practice exists across the life course. The SNAP trial provides an example of a bayesian adaptive whole-of-life inclusion design that enhances trial population inclusivity and diversity overall, as well as generalizability and translation of findings into clinical practice.