Optimizing Sedative Dose in Preterm Infants Undergoing Treatment for Respiratory Distress Syndrome

The Intubation-Surfactant-Extubation (INSURE) procedure is used worldwide to treat pre-term newborn infants suffering from respiratory distress syndrome, which is caused by an insufficient amount of the chemical surfactant in the lungs. With INSURE, the infant is intubated, surfactant is administered via the tube to the trachea, and at completion the infant is extubated. This improves the infant's ability to breathe and thus decreases the risk of long term neurological or motor disabilities. To perform the intubation safely, the newborn infant first must be sedated. Despite extensive experience with INSURE, there is no consensus on what sedative dose is best. This paper describes a Bayesian sequentially adaptive design for a multi-institution clinical trial to optimize the sedative dose given to pre-term infants undergoing the INSURE procedure. The design is based on three clinical outcomes, two efficacy and one adverse, using elicited numerical utilities of the eight possible elementary outcomes. A flexible Bayesian parametric trivariate dose-outcome model is assumed, with the prior derived from elicited mean outcome probabilities. Doses are chosen adaptively for successive cohorts of infants using posterior mean utilities, subject to safety and efficacy constraints. A computer simulation study of the design is presented.