Application of desirability of outcome ranking to the milking in non-vigorous infants trial

Document Type

Journal Article

Publication Date

1-5-2024

Journal

Early human development

Volume

189

DOI

10.1016/j.earlhumdev.2023.105928

Keywords

Cluster trials; Cord management; Deferred consent

Abstract

OBJECTIVES: Neonatal trials have traditionally used binary composite short-term (such as death or bronchopulmonary dysplasia) or longer-term (such as death or severe neurodevelopmental impairment) outcomes. We applied the Desirability Of Outcome Ranking (DOOR) method to rank the overall patient outcome by best (no morbidities) to worst (death). STUDY DESIGN: Using a completed large multicenter trial (Milking In Non-Vigorous Infants [MINVI]) of umbilical cord milking (UCM) vs. early cord clamping (ECC), we applied the DOOR methodology to neonatal outcomes. Six outcomes were chosen and ranked: no interventions or NICU admission (most desirable); received initial cardiorespiratory support at birth; neonatal intensive care unit (NICU) admission for predefined criteria; mild hypoxic-ischemic encephalopathy (HIE); moderate to severe HIE; and death (least desirable). RESULTS: 1524 non-vigorous newborns born between 35 and 42 weeks' gestation had data for analysis. The DOOR distribution was different between the UCM and ECC arms, with a significantly greater probability (55.8 % [95 % CI 53.1-58.5 %; p < 0.0001]) of a randomly selected neonate having a more desirable outcome if they were in the UCM arm. DOOR probabilities of averting individual adverse outcomes such as NICU admission for predefined criteria (52.8 %; 95%CI 50.5-55.1 %) and cardiorespiratory support (54.0 %; 95%CI 51.6-56.4 %) were significantly higher among those in the UCM group. CONCLUSION: DOOR provides an overall assessment of the benefits and harms with greater insight than typical binary composite measures to clinicians and parents when evaluating an intervention. Future neonatal trials should consider the a priori use of the DOOR methodology to evaluate trial outcomes.

Department

Biostatistics and Bioinformatics

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