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Related Experiment Video

Updated: Jun 6, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

Development and validation of nomograms for predicting preterm delivery.

Mickaël Allouche1, Cyril Huissoud, Béatrice Guyard-Boileau

  • 1Service de Gynécologie Obstétrique, Hôpital Paule de Viguier, Centre Hospitalier Universitaire de Toulouse, 330 Avenue de Grande-Bretagne, Toulouse, France.

American Journal of Obstetrics and Gynecology
|November 25, 2010
PubMed
Summary
This summary is machine-generated.

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This study developed validated nomograms to predict the individual probability of preterm birth for women transferred due to threatened preterm delivery. These tools aid in managing high-risk pregnancies and improving outcomes.

Area of Science:

  • Perinatology
  • Maternal-Fetal Medicine
  • Biostatistics

Background:

  • Preterm delivery remains a leading cause of neonatal morbidity and mortality.
  • Accurate risk prediction is crucial for optimizing management of threatened preterm delivery, especially following inter-hospital transfer.

Purpose of the Study:

  • To develop and validate statistical models (nomograms) for predicting the risk of preterm birth in patients transferred for threatened preterm delivery.
  • To create an accessible tool for clinicians to estimate individual probabilities of delivery.

Main Methods:

  • Observational study of 906 patients transferred for threatened preterm delivery.
  • Logistic regression models were constructed using clinical and sonographic data.
  • Models were validated on an independent dataset, and an internet-based tool was developed.

Related Experiment Videos

Last Updated: Jun 6, 2026

Establishing a Competing Risk Regression Nomogram Model for Survival Data
04:57

Establishing a Competing Risk Regression Nomogram Model for Survival Data

Published on: October 23, 2020

Main Results:

  • Two nomograms were developed: one predicting delivery within 48 hours and another predicting delivery before 32 weeks gestation.
  • The predictive models demonstrated good discrimination and calibration in the validation set (concordance index 0.73 and 0.72).

Conclusions:

  • Validated nomograms effectively predict the individual probability of preterm birth post-transfer for threatened preterm delivery.
  • These tools can assist in clinical decision-making and resource allocation for high-risk pregnancies.