Cost-Effectiveness of a Proteomic Test for Preterm Birth Prediction.

BACKGROUND

Preterm birth (PTB) carries increased risk of short- and long-term health problems as well as higher healthcare costs. Current strategies using clinically accepted maternal risk factors (prior PTB, short cervix) can only identify a minority of singleton PTBs.

OBJECTIVE

We modeled the cost-effectiveness of a risk-screening-and-treat strategy versus usual care for commercially insured pregnant US women without clinically accepted PTB risk factors. The risk-screening-and-treat strategy included use of a novel PTB prognostic blood test (PreTRM

METHODS

We built a cost-effectiveness model using a combined decision-tree/Markov approach and a US payer perspective. We modeled 1-week cycles of pregnancy from week 19 to birth (preterm or term) and assessed costs throughout the pregnancy, and further to 12-months post-delivery in mothers and 30-months in infants. PTB rates and costs were based on >40,000 mothers and infants from the HealthCore Integrated Research Database

RESULTS

In the base case, the risk-screening-and-treat strategy dominated usual care with an estimated 870 fewer PTBs (20% reduction) and $54 million less in total cost ($863 net savings per pregnant woman). Reductions were projected for neonatal intensive care admissions (10%), overall length-of-stay (7%), and births <32 weeks (33%). Treatment effectiveness had the strongest influence on cost-effectiveness estimates. The risk-screening-and-treat strategy remained dominant in the majority of probabilistic sensitivity analysis simulations and model scenarios.

CONCLUSION

Use of a novel prognostic test during pregnancy to identify women at risk of PTB combined with evidence-based treatment is estimated to reduce total costs while preventing PTBs and their consequences.

Informations de copyright

© 2021 Grabner et al.

Déclaration de conflit d'intérêts

Michael Grabner, Chi Nguyen, Haechung Chung, Nilesh Gangan, and Eric Stanek are employees of HealthCore, Inc., an independent research organization that received funding from Sera Prognostics Inc. for the conduct of the study. Michael Grabner and Eric Stanek are stockholders of Anthem, Inc., which has a financial interest in Sera Prognostics. Julja Burchard and Jay Boniface are employees and stockholders of Sera Prognostics Inc. John Zupancic is a consultant to Sera Prognostics Inc. The authors report no other conflicts of interest in this work.