Performance of a validated spontaneous preterm delivery predictor in South Asian and Sub-Saharan African women: a nested case control study

Abstract

Objectives

To address the disproportionate burden of preterm birth (PTB) in low- and middle-income countries, this study aimed to (1) verify the performance of the United States-validated spontaneous PTB (sPTB) predictor, comprised of the IBP4/SHBG protein ratio, in subjects from Bangladesh, Pakistan and Tanzania enrolled in the Alliance for Maternal and Newborn Health Improvement (AMANHI) biorepository study, and (2) discover biomarkers that improve performance of IBP4/SHBG in the AMANHI cohort.

Study design

The performance of the IBP4/SHBG biomarker was first evaluated in a nested case control validation study, then utilized in a follow-on discovery study performed on the same samples. Levels of serum proteins were measured by targeted mass spectrometry. Differences between the AMANHI and U.S. cohorts were adjusted using body mass index (BMI) and gestational age (GA) at blood draw as covariates. Prediction of sPTB < 37 weeks and < 34 weeks was assessed by area under the receiver operator curve (AUC). In the discovery phase, an artificial intelligence method selected additional protein biomarkers complementary to IBP4/SHBG in the AMANHI cohort.

Results

The IBP4/SHBG biomarker significantly predicted sPTB < 37 weeks (n = 88 vs. 171 terms ≥ 37 weeks) after adjusting for BMI and GA at blood draw (AUC= 0.64, 95% CI: 0.57–0.71, p < .001). Performance was similar for sPTB < 34 weeks (n = 17 vs. 184 ≥ 34 weeks): AUC = 0.66, 95% CI: 0.51–0.82, p = .012. The discovery phase of the study showed that the addition of endoglin, prolactin, and tetranectin to the above model resulted in the prediction of sPTB < 37 with an AUC= 0.72 (95% CI: 0.66–0.79, p-value < .001) and prediction of sPTB < 34 with an AUC of 0.78 (95% CI: 0.67–0.90, p < .001).

Conclusion

A protein biomarker pair developed in the U.S. may have broader application in diverse non-U.S. populations.

Keywords:

• Preterm birth
• biomarkers
• low- and middle-income countries
• IBP4
• SHBG

Acknowledgments

We acknowledge the study participants for their essential contributions of time, care, samples and data; the dedicated field and data teams for implementing the AMANHI study; the Sera Clinical Laboratory for data generation; Max T. Dufford, BS, for data management; ChienTing Hsu, MS, Ryan M. Treacy, BS, and Jeff S. Flick, PhD, for preliminary analyses; and Todd L. Randolph, MD and Gregory C. Critchfield, MD, MS for critical review.

Disclosure statement

JJB, JB, TCF, ACF, MBB, ADP, and DEH are stockholders and employees or consultants of Sera Prognostics. JJB, JB, ADP, TCF, MBB and DEH have patents issued and pending related to this work. All other authors report no conflict of interest.

Data availability statement

Deidentified individual participant data will be made available upon approval of the manuscript, including data dictionaries and data that underlie the results reported in this article. Data will be shared with researchers who contact either of the corresponding authors requesting use of the data for research on preterm birth in LMICs. Requestors will need to sign a data access agreement.

Additional information

Funding

This work was funded by the Bill and Melinda Gates Foundation, including a grant to Sera Prognostics (Contract ID OPP1127876) and coordinated by the World Health Organization. The funders had no roles in designing of the biobank study, data collection, and data analysis.