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Published on: January 12, 2018
Development and Validation of a Novel Pre-Pregnancy Score Predictive of Preterm Birth in Nulliparous Women Using Data
Ivan Merlo1, Anna Cantarutti1,2, Alessandra Allotta3
1Department of Statistics and Quantitative Methods, University of Milano-Bicocca, 20126 Milan, Italy.
Insights
A new Preterm Birth Score was developed to identify nulliparous women at high risk for preterm delivery. This score helps stratify risk, aiding early identification of mothers needing closer monitoring for improved pregnancy outcomes.
Area of Science:
- Obstetrics and Gynecology
- Public Health
- Biostatistics
Background:
- Preterm birth is a leading cause of infant mortality globally.
- Limited understanding of risk factors hinders early identification of high-risk pregnancies.
- Developing predictive tools for preterm delivery is a critical public health challenge.
Purpose of the Study:
- To develop and validate a novel pre-pregnancy risk score for preterm delivery in nulliparous women.
- To utilize Italian healthcare utilization databases for risk factor identification.
- To create a tool for early identification of women at high risk of preterm birth.
Main Methods:
- A LASSO logistic regression model selected 26 predictive variables from clinical history and socio-demographic data of 126,839 nulliparous women.
- A Preterm Birth Score was created by assigning weights based on model coefficients.
- The score was validated internally (54,359 deliveries) and externally (14,703 and 62,131 deliveries in two regions).
Main Results:
- Preterm delivery rates increased with higher Preterm Birth Score values across all validation regions.
- Calibration was nearly ideal for internal and Marche validation sets; slight differences observed in Sicily for high scores.
- Area under the receiver operating characteristic curve (AUC) ranged from 56% to 61% across validation sets.
Conclusions:
- The Preterm Birth Score effectively stratifies nulliparous women by preterm birth risk.
- Early identification of high-risk mothers is achievable, despite moderate discriminatory power.
- The score offers a valuable tool for targeted prenatal care and intervention strategies.
Abstract:
Background: Preterm birth is a major worldwide public health concern, being the leading cause of infant mortality. Understanding of risk factors remains limited, and early identification of women at high risk of preterm birth is an open challenge. Objective: The aim of the study was to develop and validate a novel pre-pregnancy score for preterm delivery in nulliparous women using information from Italian healthcare utilization databases. Study Design: Twenty-six variables independently able to predict preterm delivery were selected, using a LASSO logistic regression, from a large number of features collected in the 4 years prior to conception, related to clinical history and socio-demographic characteristics of 126,839 nulliparous women from Lombardy region who gave birth between 2012 and 2017. A weight proportional to the coefficient estimated by the model was assigned to each of the selected variables, which contributed to the Preterm Birth Score. Discrimination and calibration of the Preterm Birth Score were assessed using an internal validation set (i.e., other 54,359 deliveries from Lombardy) and two external validation sets (i.e., 14,703 and 62,131 deliveries from Marche and Sicily, respectively). Results: The occurrence of preterm delivery increased with increasing the Preterm Birth Score value in all regions in the study. Almost ideal calibration plots were obtained for the internal validation set and Marche, while expected and observed probabilities differed slightly in Sicily for high Preterm Birth Score values. The area under the receiver operating characteristic curve was 60%, 61% and 56% for the internal validation set, Marche and Sicily, respectively. Conclusions: Despite the limited discriminatory power, the Preterm Birth Score is able to stratify women according to their risk of preterm birth, allowing the early identification of mothers who are more likely to have a preterm delivery.
