# SCH: Prediction of Preterm Birth in Nulliparous Women

> **NIH NIH R01** · COLUMBIA UNIV NEW YORK MORNINGSIDE · 2021 · $246,970

## Abstract

Preterm Birth (PTB) is a major long-lasting public health problem being the leading cause of mortality and
long-term disabilities among neonates, with heavy emotional and financial consequences to families and
society. Prediction of PTB risk has been an exceedingly challenging problem, in particular for first time
mothers (nulliparous women) due to the lack of prior pregnancy history. Most studies to date have
examined individual risk factors, genetic, environmental, or behavioral, through univariate analyses of their
association with PTB, including GWAS identifying modest contribution of common variants across six gene
regions. The challenge of improving PTB prediction is due to the inherent complexity of its multifactorial
etiology and the lack of approaches capable of integrating and interpreting large multidisciplinary data. Our
previous work [NSF Eager 1454855, 1454814] developed predictive models for PTB based on non-genetic
maternal attributes. An important question is to know whether factors other than history of PTB can be used
to identify a nullipara patient at risk. We plan on devising longitudinal risk prediction methods for PTB that
integrate every piece of available data. We will address three important gaps in current literature as our
three project objectives: a focused study of nulliparous women and their risk for PTB; combining genetic
factors with other clinical factors to determine risk ; and using longitudinal data and models to optimize
scheduling of patient visits, testing and treatment. We will focus on a recently released NIH-NICHD dataset
called nuMoM2b, which is a prospective cohort study of a racially/ethnically/geographically diverse
 population of10 ,038 nulliparous women with singleton gestation .
Our aims are as follows: (1) Longitudinal Preterm Birth Prediction ; (2) Combining clinical and genetic
features for risk prediction ; (3) Assessing the effectiveness of the methods in clinical practice.
RELEVANCE (See instructions) .
Over 26 billion dollars are spent annually on the delivery and care of the 12% of infants who are born
preterm in the United States. A crucial challenge is to identify women who are at the highest risk for early
preterm birth and to develop interventions. Equally important, would be the ability to identify women at the
lowest risk to avoid unnecessary and costly interventions. Our project has the potential to advance
knowledge about this long-lasting public health problem.

## Key facts

- **NIH application ID:** 10217258
- **Project number:** 5R01LM013327-03
- **Recipient organization:** COLUMBIA UNIV NEW YORK MORNINGSIDE
- **Principal Investigator:** Alexander M Friedman
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $246,970
- **Award type:** 5
- **Project period:** 2019-09-16 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10217258

## Citation

> US National Institutes of Health, RePORTER application 10217258, SCH: Prediction of Preterm Birth in Nulliparous Women (5R01LM013327-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10217258. Licensed CC0.

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