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Published on: January 12, 2018
Predictions of Preterm Birth from Early Pregnancy Characteristics: Born in Guangzhou Cohort Study
Jian-Rong He1,2,3, Rema Ramakrishnan4, Yu-Mian Lai5
1Division of Birth Cohort Study, Guangzhou Women and Children's Medical Center, Guangzhou Medical University, Guangzhou 510623, China. jianrong.he@bigcs.org.
Insights
Predicting preterm birth (PTB) is crucial for infant survival. New models using early pregnancy data show moderate predictive ability for PTB, identifying key risk factors like maternal age and smoking.
Area of Science:
- Obstetrics and Gynecology
- Perinatal Epidemiology
- Public Health
Background:
- Preterm birth (PTB) is a leading cause of neonatal mortality globally.
- Effective early risk prediction models for PTB are scarce, particularly in low- and middle-income regions.
- Early identification of PTB risk facilitates timely monitoring and intervention.
Purpose of the Study:
- To develop and validate prediction models for overall and specific subtypes of preterm birth using easily accessible early pregnancy predictors.
- To assess the performance of newly developed models and compare them with existing models from high-income countries.
- To identify significant early pregnancy predictors associated with preterm birth.
Main Methods:
- Utilized data from 9044 women in the Born in Guangzhou Cohort Study.
- Employed Cox proportional hazard models for prediction model construction.
- Evaluated model performance using Harrell's c and D statistics and calibration plots; conducted a systematic review and validation of published models.
Main Results:
- Newly developed models demonstrated moderate discrimination for PTB prediction (Harrell's c: 0.60–0.66).
- Key predictors included maternal age, height, prior PTB history, vaginal bleeding, folic acid intake, and passive smoking.
- Validated models from high-income countries showed poor performance (AUC: 0.50–0.56) in this population; calibration was good for most new models, except for early PTB.
Conclusions:
- Early pregnancy characteristics provide moderate predictive ability for preterm birth.
- The developed models offer a potential tool for PTB risk assessment in similar settings.
- Future research should incorporate laboratory markers to enhance PTB prediction accuracy.
Abstract:
Preterm birth (PTB, <37 weeks) is the leading cause of death in children <5 years of age. Early risk prediction for PTB would enable early monitoring and intervention. However, such prediction models have been rarely reported, especially in low- and middle-income areas. We used data on a number of easily accessible predictors during early pregnancy from 9044 women in Born in Guangzhou Cohort Study, China to generate prediction models for overall PTB and spontaneous, iatrogenic, late (34⁻36 weeks), and early (<34 weeks) PTB. Models were constructed using the Cox proportional hazard model, and their performance was evaluated by Harrell's c and D statistics and calibration plot. We further performed a systematic review to identify published models and validated them in our population. Our new prediction models had moderate discrimination, with Harrell's c statistics ranging from 0.60⁻0.66 for overall and subtypes of PTB. Significant predictors included maternal age, height, history of preterm delivery, amount of vaginal bleeding, folic acid intake before pregnancy, and passive smoking during pregnancy. Calibration plots showed good fit for all models except for early PTB. We validated three published models, all of which were from studies conducted in high-income countries; the area under receiver operating characteristic for these models ranged from 0.50 to 0.56. Based on early pregnancy characteristics, our models have moderate predictive ability for PTB. Future studies should consider inclusion of laboratory markers for the prediction of PTB.
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