Evaluating the cost-effectiveness of antenatal screening for major structural anomalies during the first trimester of pregnancy: a decision model - Campbell, H; Karim, J; Papageorgiou, AT; Wilson, E; Rivero-Arias, O (Wiley, 2025)
Objective: To assess the cost-effectiveness of modifying current antenatal screening by adding first trimester structural anomaly screening to standard of care second trimester anomaly screening. Design: Health economic decision model. Setting: NHS in England and Wales. Population: Pregnant women attending for first trimester antenatal screening. Methods: The decision model estimated pregnancy outcomes (maternal and fetal) and 20-year costs for current screening practice and for a policy adding a protocol screening for eight major structural anomalies to the current first trimester ultrasound scan. Event probabilities, costs, and outcomes for the model were informed by meta-analyses, published literature, and expert opinion. Main outcomes measures: Expected numbers of pregnancy outcomes, healthcare costs, and maternal quality adjusted life years (QALYs). Estimation of the incremental costeffectiveness ratio (ICER), likelihood of cost-effectiveness, and a value of information (VoI) analysis assessing if further research is needed before making a decision about screening. Results: First trimester anomaly screening increased mean per woman costs by £11 (95% CI £1 to £29) and maternal QALYs by 0.002065 (95% CI 0.00056 to 0.00358). The ICER was £5,270 per QALY and the probability of cost-effectiveness at a willingness to pay value for a QALY of £20,000, exceeded 95%. VoI analysis showed further research would be unlikely to represent value for money. The protocol would likely lead to a reduction in infant healthcare costs and QALYs. Conclusions: A protocol to screen for eight major structural anomalies during the first trimester appears to represent value for money for the NHS. The opposing implications for mothers and infants however, raise complex, challenging and sensitive issues. Funding: This work was funded by the National Institute for Health Research (NIHR) Health Technology Assessment programme (Grant number 17/19/10).