Clinical and economic evaluation of a proteomic biomarker preterm birth risk predictor: Cost-effectiveness modeling of prenatal interventions applied to predicted higher-risk pregnancies within a large and diverse cohort

Abstract

Objective Evaluate clinical utility and cost effectiveness of identifying pregnancies at increased risk of preterm birth using a validated proteomic biomarker risk predictor to enable proactive intervention Study Design Pregnancies at elevated risk (≥15%) of preterm birth were identified in a cohort from TREETOP (NCT02787213), a study independent of biomarker development. In the screening arm, higher-risk subjects received simulated interventions based on published efficacy of multimodal treatment or care-management alone. Subjects in the non-screening arm received no interventions. Neonatal and maternal length of stay, neonatal mortality and morbidity and neonatal costs were compared between arms. Results Multimodal/care-management modeled treatments predicted reductions in neonatal (30%/22%) and maternal (9.2%/8.5%) hospital stays, neonatal morbidity and mortality (41%/29%), and neonatal costs (34%/16%) for the screening vs. non-screening arm. Conclusion Modeled interventions applied to pregnancies identified as higher-risk by a proteomic biomarker risk predictor demonstrate clinically and economically meaningful improvements in neonatal and maternal outcomes.