News Release

Study validates two-protein test for spontaneous preterm birth prediction

Peer-Reviewed Publication

Society for Maternal-Fetal Medicine

ATLANTA (Feb. 1, 2016)--In a study to be presented on Feb. 4 at 1:15 p.m. EST, at the Society for Maternal-Fetal Medicine's annual meeting, The Pregnancy Meeting™, in Atlanta, researchers will present findings from the Proteomic Assessment of Preterm Risk study (PAPPR study, #NCT01371019) with the title Clinical validation of a two-protein test for spontaneous preterm birth (sPTB) prediction in a large multicenter prospective study of asymptomatic women.

Pre-term birth is a birth that takes place before 37 weeks of pregnancy. According to the Centers for Disease Control and Prevention, in 2014, preterm birth affected one out of every 10 infants. In the U.S., preterm birth is the largest contributor to infant death with most preterm related deaths occurring among babies born very preterm (before 32 weeks). It is also a leading cause of long-term neurological disabilities in children. For these reasons, it is critical to identify key indicators of preterm birth.

This study performed a blind evaluation of the performance of a two-protein test for spontaneous preterm birth prediction. The study was conducted at 11 sites between 2011 and 2013, with 5501 pregnant women (representative of the U.S. population) enrolled at 17-28 weeks of gestational age. By examining specimens from PAPR, researchers identified an optimal gestational age window in pregnancy (19-21 weeks) and two highly performing proteins for predicting subsequent spontaneous preterm birth.

Following the discovery and verifications steps, the novel classifier (IBP4 and SHBG) was validated in an independent group of women, with excellent performance and an area under the ROC curve of 93% for preterm delivery before 35 weeks and 75% for delivery before 37 weeks.

"The performance of this proteomic classifier was excellent," said George R. Saade, M.D. professor of Obstetrics and Gynecology at the University of Texas Medical Branch in Galveston and lead investigator. "Having a classifier to help physicians risk-stratify patients for preterm birth in early pregnancy would be extremely valuable in guiding levels of care and employing preventive strategies for their patients," added Saade.

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The Proteomic Assessment of Preterm Birth study was supported by Sera Prognostics.

A copy of the abstract is available at http://www.smfmnewsroom.org and below. For interviews please contact Vicki Bendure at Vicki@bendurepr.com 202-374-9259 (cell).

The Society for Maternal-Fetal Medicine (est. 1977) is the premiere membership organization for obstetricians/gynecologists who have additional formal education and training in maternal-fetal medicine. The society is devoted to reducing high-risk pregnancy complications by sharing expertise through continuing education to its 2,000 members on the latest pregnancy assessment and treatment methods. It also serves as an advocate for improving public policy, and expanding research funding and opportunities for maternal-fetal medicine. The group hosts an annual meeting in which groundbreaking new ideas and research in the area of maternal-fetal medicine are shared and discussed. For more information visit http://www.smfm.org.

Abstract 17 Clinical validation of a two-protein test for spontaneous preterm birth (sPTB) prediction in a large multicenter prospective study of asymptomatic women

Authors: George Saade1, Kim Boggess2, Scott Sullivan3, Glenn Markenson4, Jay Iams5, Dean Coonrod6, Leonardo Pereira7, M. Sean Esplin8, Larry Cousins9, Garrett Lam10, Matthew K. Hoffman11, Angela Fox12, Chad Bradford12, Tracey Fleischer12, Ilia Ichetovkin12, Ashoka Polpitiya12, Paul Kearney13, Jay Boniface12, Durlin Hickok12
1University of Texas Medical Branch, Galveston, TX, 2Department of Obstetrics and Gynecology, Division of Maternal-Fetal Medicine, University of North Carolina, Chapel Hill, NC, 3Department of Obstetrics and Gynecology, Medical University of South Carolina, Charleston, SC, 4Maternal Fetal Medicine Baystate Medical Center, Obstetrics and Gynecology Tufts University School of Medicine, Springfield, MA, 5Department of Obstetrics and Gynecology, The Ohio State University, Columbus, OH, 6Department of Obstetrics and Gynecology, Maricopa Integrated Health System and University of Arizona College of Medicine, Phoenix, AZ, 7Division of Maternal-Fetal Medicine, Oregon Health and Science University, Portland, OR, 8Division of Maternal Fetal Medicine, Intermountain Healthcare and University of Utah Health Sciences Center, Salt Lake City, UT, 9Maternal Fetal Medicine Division, San Diego Perinatal Center, Childrens Specialists of San Diego, San Diego, CA, 10Regional Obstetrical Consultants and University of Tennessee College of Medicine, Chattanooga, TN, 11Department of Obstetrics and Gynecology, Christiana Care Health System, Newark, DE, 12Sera Prognostics, Inc., Salt Lake City, UT, 13Integrated Diagnostics, Inc., Seattle, WA

Objective: To perform a blinded evaluation of the performance of a two-protein test for spontaneous preterm birth (sPTB) prediction

Study Design: Pregnant women representative of the U.S. population were enrolled at 17-28 weeks of gestational age (GA) in the Proteomic Assessment of Preterm Risk (PAPR) study at 11 sites between 2011 and 2013. Biospecimens were collected at enrollment and outcomes ascertained following birth. Intensity values from a LC-MS (MRM) method were measured for 2 predictive analytes, insulin-like growth factor binding protein 4 (IBP4) and sex-hormone binding globulin (SHBG), that had been previously discovered and verified in separate studies with best performance in the 19-21 week GA interval. Strict blinding and double validation protocols were utilized consistent with the Institute of Medicine guidelines for classifier validation.

Results: All cases eligible for validation (those not used for classifier training, discovery or verification) and their respective independent matched controls drawn during the 19-21 week GA interval were analyzed (18 cases, 36 controls). The classifier performance was excellent (Table 1), with statistically significant AUC values and Odds Ratios. Addition of pregnancy and medical history variables did not improve the proteomic classifier performance.

Conclusion: We validated a novel maternal serum proteomic classifier consisting of IBP4 and SHBG for prediction of sPTB. This proteomic classifier can risk-stratify patients to test PTB preventive strategies or guide levels of care.


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