External validation and comparison of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in the first trimester : multicenter cohort study

Objectives: To examine the predictive performance of the Fetal Medicine Foundation (FMF) competing-risks model for the first-trimester prediction of a small-for-gestational-age (SGA) neonate in a large, independent, unselected European cohort and to compare the competing-risks algorithm with previou...

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Autores: Chaveeva, P., Papastefanou, I., Dagklis, T., Valiño, N., Revello, R., Adiego, B., Delgado, J. L., Kalev, V., Tsakiridis, I., Triano, C., Pertegal, M., Siargkas, A., Santacruz, B., de Paco Matallana, C., Gil, M. M.
Tipo de recurso: artículo
Fecha de publicación:2025
País:España
Institución:Universidad Francisco de Vitoria
Repositorio:DDFV. Repositorio Institucional de la Universidad Francisco de Vitoria
Idioma:inglés
OAI Identifier:oai:ddfv.ufv.es:10641/6899
Acceso en línea:https://hdl.handle.net/10641/6899
Access Level:acceso abierto
Palabra clave:Bayes' theorem
FMF
Fetal Medicine Foundation
SGA
algorithm
biomarker
fetal growth restriction
prediction model
small-for-gestational age
survival model
Radiological and Ultrasound Technology
Reproductive Medicine
Radiology Nuclear Medicine and imaging
Obstetrics and Gynecology
Journal Article
Multicenter Study
Comparative Study
Validation Study
Research Support, Non-U.S. Gov't
Yes
yes
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oai_identifier_str oai:ddfv.ufv.es:10641/6899
network_acronym_str ES
network_name_str España
repository_id_str
spelling External validation and comparison of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in the first trimester : multicenter cohort studyChaveeva, P.Papastefanou, I.Dagklis, T.Valiño, N.Revello, R.Adiego, B.Delgado, J. L.Kalev, V.Tsakiridis, I.Triano, C.Pertegal, M.Siargkas, A.Santacruz, B.de Paco Matallana, C.Gil, M. M.Bayes' theoremFMFFetal Medicine FoundationSGAalgorithmbiomarkerfetal growth restrictionprediction modelsmall-for-gestational agesurvival modelRadiological and Ultrasound TechnologyReproductive MedicineRadiology Nuclear Medicine and imagingObstetrics and GynecologyJournal ArticleMulticenter StudyComparative StudyValidation StudyResearch Support, Non-U.S. Gov'tYesyesObjectives: To examine the predictive performance of the Fetal Medicine Foundation (FMF) competing-risks model for the first-trimester prediction of a small-for-gestational-age (SGA) neonate in a large, independent, unselected European cohort and to compare the competing-risks algorithm with previously published logistic-regression models. Methods: This was a retrospective, non-interventional, multicenter cohort study including 35 170 women with a singleton pregnancy who underwent a first-trimester ultrasound assessment between 11 + 0 and 13 + 6 weeks' gestation. We used the default FMF competing-risks model for the prediction of SGA combining maternal factors, uterine artery pulsatility index (UtA-PI), pregnancy-associated plasma protein-A (PAPP-A) and placental growth factor (PlGF) to obtain risks for different cut-offs of birth-weight percentile and gestational age at delivery. We examined the predictive performance in terms of discrimination and calibration and compared it with the published data on the model's development population and with published logistic-regression equations. Results: At a 10% false-positive rate, maternal factors and UtA-PI predicted 42.2% and 51.5% of SGA < 10th percentile delivered < 37 weeks and < 32 weeks, respectively. The respective values for SGA < 3rd percentile were 44.7% and 51.7%. Also at a 10% false-positive rate, maternal factors, UtA-PI and PAPP-A predicted 42.2% and 51.5% of SGA < 10th percentile delivered < 37 weeks and < 32 weeks, respectively. The respective values for SGA < 3rd percentile were 46.2% and 51.7%. At a 10% false-positive rate, maternal factors, UtA-PI, PAPP-A and PlGF predicted 47.6% and 66.7% of SGA < 10th percentile delivered < 37 weeks and < 32 weeks, respectively. The respective values for SGA < 3rd percentile were 50.0% and 69.0%. These data were similar to those reported in the original model's development study and substantially better than those calculated using pre-existing logistic-regression models (McNemar's test, P < 0.001). The FMF competing-risks model was well calibrated. Conclusions: The FMF competing-risks model for the first-trimester prediction of SGA is reproducible in an independent, unselected low-risk cohort and superior to logistic-regression approaches.Facultad de Medicina20252025-06-0120252025-06-01journal articlehttp://purl.org/coar/resource_type/c_6501info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10641/6899reponame:DDFV. Repositorio Institucional de la Universidad Francisco de Vitoriainstname:Universidad Francisco de VitoriaInglésengopen accesshttp://purl.org/coar/access_right/c_abf2http://creativecommons.org/licenses/by-nc-nd/4.0/info:eu-repo/semantics/openAccessoai:ddfv.ufv.es:10641/68992026-06-11T12:44:57Z
dc.title.none.fl_str_mv External validation and comparison of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in the first trimester : multicenter cohort study
title External validation and comparison of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in the first trimester : multicenter cohort study
spellingShingle External validation and comparison of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in the first trimester : multicenter cohort study
Chaveeva, P.
Bayes' theorem
FMF
Fetal Medicine Foundation
SGA
algorithm
biomarker
fetal growth restriction
prediction model
small-for-gestational age
survival model
Radiological and Ultrasound Technology
Reproductive Medicine
Radiology Nuclear Medicine and imaging
Obstetrics and Gynecology
Journal Article
Multicenter Study
Comparative Study
Validation Study
Research Support, Non-U.S. Gov't
Yes
yes
title_short External validation and comparison of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in the first trimester : multicenter cohort study
title_full External validation and comparison of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in the first trimester : multicenter cohort study
title_fullStr External validation and comparison of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in the first trimester : multicenter cohort study
title_full_unstemmed External validation and comparison of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in the first trimester : multicenter cohort study
title_sort External validation and comparison of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in the first trimester : multicenter cohort study
dc.creator.none.fl_str_mv Chaveeva, P.
Papastefanou, I.
Dagklis, T.
Valiño, N.
Revello, R.
Adiego, B.
Delgado, J. L.
Kalev, V.
Tsakiridis, I.
Triano, C.
Pertegal, M.
Siargkas, A.
Santacruz, B.
de Paco Matallana, C.
Gil, M. M.
author Chaveeva, P.
author_facet Chaveeva, P.
Papastefanou, I.
Dagklis, T.
Valiño, N.
Revello, R.
Adiego, B.
Delgado, J. L.
Kalev, V.
Tsakiridis, I.
Triano, C.
Pertegal, M.
Siargkas, A.
Santacruz, B.
de Paco Matallana, C.
Gil, M. M.
author_role author
author2 Papastefanou, I.
Dagklis, T.
Valiño, N.
Revello, R.
Adiego, B.
Delgado, J. L.
Kalev, V.
Tsakiridis, I.
Triano, C.
Pertegal, M.
Siargkas, A.
Santacruz, B.
de Paco Matallana, C.
Gil, M. M.
author2_role author
author
author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.none.fl_str_mv Facultad de Medicina
dc.subject.none.fl_str_mv Bayes' theorem
FMF
Fetal Medicine Foundation
SGA
algorithm
biomarker
fetal growth restriction
prediction model
small-for-gestational age
survival model
Radiological and Ultrasound Technology
Reproductive Medicine
Radiology Nuclear Medicine and imaging
Obstetrics and Gynecology
Journal Article
Multicenter Study
Comparative Study
Validation Study
Research Support, Non-U.S. Gov't
Yes
yes
topic Bayes' theorem
FMF
Fetal Medicine Foundation
SGA
algorithm
biomarker
fetal growth restriction
prediction model
small-for-gestational age
survival model
Radiological and Ultrasound Technology
Reproductive Medicine
Radiology Nuclear Medicine and imaging
Obstetrics and Gynecology
Journal Article
Multicenter Study
Comparative Study
Validation Study
Research Support, Non-U.S. Gov't
Yes
yes
description Objectives: To examine the predictive performance of the Fetal Medicine Foundation (FMF) competing-risks model for the first-trimester prediction of a small-for-gestational-age (SGA) neonate in a large, independent, unselected European cohort and to compare the competing-risks algorithm with previously published logistic-regression models. Methods: This was a retrospective, non-interventional, multicenter cohort study including 35 170 women with a singleton pregnancy who underwent a first-trimester ultrasound assessment between 11 + 0 and 13 + 6 weeks' gestation. We used the default FMF competing-risks model for the prediction of SGA combining maternal factors, uterine artery pulsatility index (UtA-PI), pregnancy-associated plasma protein-A (PAPP-A) and placental growth factor (PlGF) to obtain risks for different cut-offs of birth-weight percentile and gestational age at delivery. We examined the predictive performance in terms of discrimination and calibration and compared it with the published data on the model's development population and with published logistic-regression equations. Results: At a 10% false-positive rate, maternal factors and UtA-PI predicted 42.2% and 51.5% of SGA < 10th percentile delivered < 37 weeks and < 32 weeks, respectively. The respective values for SGA < 3rd percentile were 44.7% and 51.7%. Also at a 10% false-positive rate, maternal factors, UtA-PI and PAPP-A predicted 42.2% and 51.5% of SGA < 10th percentile delivered < 37 weeks and < 32 weeks, respectively. The respective values for SGA < 3rd percentile were 46.2% and 51.7%. At a 10% false-positive rate, maternal factors, UtA-PI, PAPP-A and PlGF predicted 47.6% and 66.7% of SGA < 10th percentile delivered < 37 weeks and < 32 weeks, respectively. The respective values for SGA < 3rd percentile were 50.0% and 69.0%. These data were similar to those reported in the original model's development study and substantially better than those calculated using pre-existing logistic-regression models (McNemar's test, P < 0.001). The FMF competing-risks model was well calibrated. Conclusions: The FMF competing-risks model for the first-trimester prediction of SGA is reproducible in an independent, unselected low-risk cohort and superior to logistic-regression approaches.
publishDate 2025
dc.date.none.fl_str_mv 2025
2025-06-01
2025
2025-06-01
dc.type.none.fl_str_mv journal article
http://purl.org/coar/resource_type/c_6501
dc.type.openaire.fl_str_mv info:eu-repo/semantics/article
format article
dc.identifier.none.fl_str_mv https://hdl.handle.net/10641/6899
url https://hdl.handle.net/10641/6899
dc.language.none.fl_str_mv Inglés
eng
language_invalid_str_mv Inglés
language eng
dc.rights.none.fl_str_mv open access
http://purl.org/coar/access_right/c_abf2

http://creativecommons.org/licenses/by-nc-nd/4.0/
dc.rights.openaire.fl_str_mv info:eu-repo/semantics/openAccess
rights_invalid_str_mv open access
http://purl.org/coar/access_right/c_abf2

http://creativecommons.org/licenses/by-nc-nd/4.0/
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.source.none.fl_str_mv reponame:DDFV. Repositorio Institucional de la Universidad Francisco de Vitoria
instname:Universidad Francisco de Vitoria
instname_str Universidad Francisco de Vitoria
reponame_str DDFV. Repositorio Institucional de la Universidad Francisco de Vitoria
collection DDFV. Repositorio Institucional de la Universidad Francisco de Vitoria
repository.name.fl_str_mv
repository.mail.fl_str_mv
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score 15,811543

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