Better Estimation of Spontaneous Preterm Birth Prediction Performance through Improved Gestational Age Dating

Julja Burchard; George R Saade; Kim A Boggess; Glenn R Markenson; Jay D Iams; Dean V Coonrod; Leonardo M Pereira; Matthew K Hoffman; Ashoka D Polpitiya; Ryan Treacy; Angela C Fox; Todd L Randolph; Tracey C Fleischer; Max T Dufford; Thomas J Garite; Gregory C Critchfield; J Jay Boniface; Paul E Kearney

doi:10.3390/jcm11102885

Better Estimation of Spontaneous Preterm Birth Prediction Performance through Improved Gestational Age Dating

J Clin Med. 2022 May 19;11(10):2885. doi: 10.3390/jcm11102885.

Authors

Julja Burchard¹, George R Saade², Kim A Boggess³, Glenn R Markenson⁴, Jay D Iams⁵, Dean V Coonrod⁶, Leonardo M Pereira⁷, Matthew K Hoffman⁸, Ashoka D Polpitiya¹, Ryan Treacy¹, Angela C Fox¹, Todd L Randolph¹, Tracey C Fleischer¹, Max T Dufford¹, Thomas J Garite¹, Gregory C Critchfield¹, J Jay Boniface¹, Paul E Kearney¹

Affiliations

¹ Sera Prognostics, Incorporated, Salt Lake City, UT 84109, USA.
² Department of Obstetrics & Gynecology, The University of Texas Medical Branch, Galveston, TX 77555, USA.
³ Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of North Carolina, Chapel Hill, NC 27599, USA.
⁴ Maternal Fetal Medicine, Boston University School of Medicine, Boston, MA 02118, USA.
⁵ Department of Obstetrics & Gynecology, The Ohio State University, Columbus, OH 43210, USA.
⁶ Department of Obstetrics and Gynecology, Valleywise Health, Phoenix, AZ 85008, USA.
⁷ Division of Maternal-Fetal Medicine, Oregon Health & Science University, Portland, OR 97239, USA.
⁸ Department of Obstetrics & Gynecology, Christiana Care Health System, Newark, DE 19718, USA.

Abstract

The clinical management of pregnancy and spontaneous preterm birth (sPTB) relies on estimates of gestational age (GA). Our objective was to evaluate the effect of GA dating uncertainty on the observed performance of a validated proteomic biomarker risk predictor, and then to test the generalizability of that effect in a broader range of GA at blood draw. In a secondary analysis of a prospective clinical trial (PAPR; NCT01371019), we compared two GA dating categories: both ultrasound and dating by last menstrual period (LMP) (all subjects) and excluding dating by LMP (excluding LMP). The risk predictor's performance was observed at the validated risk predictor threshold both in weeks 19^1/7-20^6/7 and extended to weeks 18^0/7-20^6/7. Strict blinding and independent statistical analyses were employed. The validated biomarker risk predictor showed greater observed sensitivity of 88% at 75% specificity (increases of 17% and 1%) in more reliably dated (excluding-LMP) subjects, relative to all subjects. Excluding dating by LMP significantly improved the sensitivity in weeks 19^1/7-20^6/7. In the broader blood draw window, the previously validated risk predictor threshold significantly stratified higher and lower risk of sPTB, and the risk predictor again showed significantly greater observed sensitivity in excluding-LMP subjects. These findings have implications for testing the performance of models aimed at predicting PTB.

Keywords: gestational age; gestational age dating; preterm birth; proteomic biomarker risk predictor; spontaneous preterm birth.

Grants and funding

This study was funded by Sera Prognostics, Inc. Sera Prognostics employees and consultants played a role in the study design, data collection and analysis, manuscript preparation, and the decision to submit.