Please use this identifier to cite or link to this item: http://hdl.handle.net/2440/84742
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Type: Journal article
Title: Development of a prognostic model for predicting spontaneous singleton preterm birth
Author: Schaaf, J.
Ravelli, A.
Mol, B.
Abu-Hanna, A.
Citation: European Journal of Obstetrics Gynecology and Reproductive Biology, 2012; 164(2):150-155
Publisher: Elsevier Ireland
Issue Date: 2012
ISSN: 0301-2115
1872-7654
Statement of
Responsibility: 
Jelle M. Schaaf, Anita C.J. Ravelli, Ben Willem J. Mol, Ameen Abu-Hanna
Abstract: OBJECTIVE: To develop and validate a prognostic model for prediction of spontaneous preterm birth. STUDY DESIGN: Prospective cohort study using data of the nationwide perinatal registry in The Netherlands. We studied 1,524,058 singleton pregnancies between 1999 and 2007. We developed a multiple logistic regression model to estimate the risk of spontaneous preterm birth based on maternal and pregnancy characteristics. We used bootstrapping techniques to internally validate our model. Discrimination (AUC), accuracy (Brier score) and calibration (calibration graphs and Hosmer-Lemeshow C-statistic) were used to assess the model's predictive performance. Our primary outcome measure was spontaneous preterm birth at <37 completed weeks. RESULTS: Spontaneous preterm birth occurred in 57,796 (3.8%) pregnancies. The final model included 13 variables for predicting preterm birth. The predicted probabilities ranged from 0.01 to 0.71 (IQR 0.02-0.04). The model had an area under the receiver operator characteristic curve (AUC) of 0.63 (95% CI 0.63-0.63), the Brier score was 0.04 (95% CI 0.04-0.04) and the Hosmer Lemeshow C-statistic was significant (p<0.0001). The calibration graph showed overprediction at higher values of predicted probability. The positive predictive value was 26% (95% CI 20-33%) for the 0.4 probability cut-off point. CONCLUSIONS: The model's discrimination was fair and it had modest calibration. Previous preterm birth, drug abuse and vaginal bleeding in the first half of pregnancy were the most important predictors for spontaneous preterm birth. Although not applicable in clinical practice yet, this model is a next step towards early prediction of spontaneous preterm birth that enables caregivers to start preventive therapy in women at higher risk.
Keywords: Prediction model; Prognostic model; Risk assessment; Preterm birth; Spontaneous; Screening
Rights: Copyright © 2012 Elsevier Ireland Ltd. All rights reserved.
RMID: 0020136731
DOI: 10.1016/j.ejogrb.2012.07.007
Appears in Collections:Obstetrics and Gynaecology publications

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