Timing of Antenatal Corticosteroids for Optimal Neonatal Outcomes: A Markov Decision Analysis Model

Antenatal corticosteroids (ACSs) are administered to pregnant individuals at high risk of preterm delivery to reduce neonatal morbidity and mortality. ACSs have a limited timeframe of effectiveness, and timing of administration can be difficult because of uncertainty surrounding the likelihood of preterm delivery. The objective of the current study was to design a decision analysis model to optimize the timing of ACS administration and identify important model variables that impact administration timing preference.

We created a Markov decision analysis model with a base case of a patient at 24⁰ weeks gestation with antepartum hemorrhage. Decision strategies included immediate, delayed, and no ACS administration. Outcomes were based on the neonatal perspective and consisted of lifetime quality adjusted life years (QALYs). Data for model inputs were derived from current literature and clinical recommendations.

Our base case analysis revealed a preferred strategy of delaying ACSs for 2 weeks, which maximized QALYs (39.18 lifetime discounted), driven by reduced neonatal morbidity at the expense of 0.1% more neonatal deaths, when compared with immediate ACS administration. Sensitivity analyses identified that, if the probability of delivery within the next week was >6.19%, then immediate steroids were preferred. Other important variables included gestational age, ACS effectiveness, and ACS adverse effects.

ACS timing involves a trade-off between morbidity and mortality, and optimal timing depends on probability of delivery, gestational age, and risks and benefits of ACSs. Clinicians should carefully consider these factors prior to ACS administration.