التفاصيل البيبلوغرافية
| العنوان: |
Competing-risks model for prediction of small-for-gestational-age neonate from maternal characteristics and serum pregnancy-associated plasma protein-A at 11-13 weeks' gestation. |
| المؤلفون: |
Papastefanou, I.1 (AUTHOR), Wright, D.2 (AUTHOR), Syngelaki, A.1 (AUTHOR), Lolos, M.1 (AUTHOR), Anampousi, K.1 (AUTHOR), Nicolaides, K. H.1 (AUTHOR) kypros@fetalmedicine.com |
| المصدر: |
Ultrasound in Obstetrics & Gynecology. Oct2020, Vol. 56 Issue 4, p541-548. 8p. |
| مصطلحات موضوعية: |
*BAYES' theorem, *PREGNANCY, *NEWBORN infants, *PREDICTION models, *BIRTH weight |
| مستخلص: |
Objectives: To develop a continuous likelihood model for pregnancy-associated plasma protein-A (PAPP-A), in the context of a new competing-risks model for prediction of a small-for-gestational-age (SGA) neonate, and to compare the predictive performance of the new model for SGA to that of previous methods.Methods: This was a prospective observational study of 60 875 women with singleton pregnancy undergoing routine ultrasound examination at 11 + 0 to 13 + 6 weeks' gestation. The dataset was divided randomly into a training dataset and a test dataset. The training dataset was used for PAPP-A likelihood model development. We used Bayes' theorem to combine the previously developed prior model for the joint Gaussian distribution of gestational age (GA) at delivery and birth-weight Z-score with the PAPP-A likelihood to obtain a posterior distribution. This patient-specific posterior joint Gaussian distribution of GA at delivery and birth-weight Z-score allows risk calculation for SGA defined in terms of different birth-weight percentiles and GA. The new model was validated internally in the test dataset and we compared its predictive performance to that of the risk-scoring system of the UK National Institute for Health and Care Excellence (NICE) and that of logistic regression models for different SGA definitions.Results: PAPP-A has a continuous association with both birth-weight Z-score and GA at delivery according to a folded-plane regression. The new model, with the addition of PAPP-A, was equal or superior to several logistic regression models. The new model performed well in terms of risk calibration and consistency across different GAs and birth-weight percentiles. In the test dataset, at a false-positive rate of about 30% using the criteria defined by NICE, the new model predicted 62.7%, 66.5%, 68.1% and 75.3% of cases of a SGA neonate with birth weight < 10th percentile delivered at < 42, < 37, < 34 and < 30 weeks' gestation, respectively, which were significantly higher than the respective values of 46.7%, 55.0%, 55.9% and 52.8% achieved by application of the NICE guidelines.Conclusions: Using Bayes' theorem to combine PAPP-A measurement data with maternal characteristics improves the prediction of SGA and performs better than logistic regression or NICE guidelines, in the context of a new competing-risks model for the joint distribution of birth-weight Z-score and GA at delivery. © 2020 International Society of Ultrasound in Obstetrics and Gynecology. [ABSTRACT FROM AUTHOR] |
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