Vis enkel innførsel

dc.contributor.authorSnell, Kym I.E.
dc.contributor.authorAllotey, John
dc.contributor.authorSmuk, Melanie
dc.contributor.authorHooper, Richard
dc.contributor.authorChan, Claire
dc.contributor.authorAhmed, Asif
dc.contributor.authorChappell, Lucy C.
dc.contributor.authorVon Dadelszen, Peter
dc.contributor.authorGreen, Marcus
dc.contributor.authorKenny, Louise
dc.contributor.authorKhalil, Asma
dc.contributor.authorKhan, Khalid
dc.contributor.authorMol, Ben W.
dc.contributor.authorMyers, Jenny
dc.contributor.authorPoston, Lucilla
dc.contributor.authorThilaganathan, Basky
dc.contributor.authorStaff, Anne Cathrine
dc.contributor.authorSmith, Gordon C.S.
dc.contributor.authorGanzevoort, Wessel
dc.contributor.authorLaivuori, Hannele
dc.contributor.authorOdibo, Anthony
dc.contributor.authorArenas Ramírez, Javier
dc.contributor.authorKingdom, John
dc.contributor.authorDaskalakis, George
dc.contributor.authorFarrar, Diane
dc.contributor.authorBaschat, Ahmet A.
dc.contributor.authorSeed, Paul T.
dc.contributor.authorPrefumo, Federico
dc.contributor.authorda Silva Costa, Fabricio
dc.contributor.authorGroen, Henk
dc.contributor.authorAudibert, Francois
dc.contributor.authorMasse, Jacques
dc.contributor.authorSkråstad, Ragnhild Bergene
dc.contributor.authorSalvesen, Kjell Å
dc.contributor.authorHaavaldsen, Camilla
dc.contributor.authorNagata, Chie
dc.contributor.authorRumbold, Alice R.
dc.contributor.authorHeinonen, Seppo
dc.contributor.authorAskie, Lisa
dc.contributor.authorSmits, Luc
dc.contributor.authorVinter, Christina
dc.contributor.authorMagnus, Per
dc.contributor.authorEero, Kajantie
dc.contributor.authorVilla, Pia M.
dc.contributor.authorJenum, Anne Karen
dc.contributor.authorAndersen, Louise B.
dc.contributor.authorNorman, Jane E.
dc.contributor.authorOhkuchi, Akihide
dc.contributor.authorEskild, Anne
dc.contributor.authorBhattacharya, Sohinee
dc.contributor.authorMcAuliffe, Fionnuala
dc.contributor.authorGalindo, Alberto
dc.contributor.authorHerraiz, Ignacio
dc.contributor.authorCarbillon, Lionel
dc.contributor.authorKlipstein-Grobusch, Kerstin
dc.contributor.authorYeo, SeonAe
dc.contributor.authorBrowne, Joyce L.
dc.contributor.authorMoons, Karel G.M.
dc.contributor.authorRiley, Richard D.
dc.contributor.authorThangaratinam, Shakila
dc.identifier.citationBMC Medicine. 2020, 18, 1-18.en_US
dc.description.abstractBackground Pre-eclampsia is a leading cause of maternal and perinatal mortality and morbidity. Early identification of women at risk during pregnancy is required to plan management. Although there are many published prediction models for pre-eclampsia, few have been validated in external data. Our objective was to externally validate published prediction models for pre-eclampsia using individual participant data (IPD) from UK studies, to evaluate whether any of the models can accurately predict the condition when used within the UK healthcare setting. Methods IPD from 11 UK cohort studies (217,415 pregnant women) within the International Prediction of Pregnancy Complications (IPPIC) pre-eclampsia network contributed to external validation of published prediction models, identified by systematic review. Cohorts that measured all predictor variables in at least one of the identified models and reported pre-eclampsia as an outcome were included for validation. We reported the model predictive performance as discrimination (C-statistic), calibration (calibration plots, calibration slope, calibration-in-the-large), and net benefit. Performance measures were estimated separately in each available study and then, where possible, combined across studies in a random-effects meta-analysis. Results Of 131 published models, 67 provided the full model equation and 24 could be validated in 11 UK cohorts. Most of the models showed modest discrimination with summary C-statistics between 0.6 and 0.7. The calibration of the predicted compared to observed risk was generally poor for most models with observed calibration slopes less than 1, indicating that predictions were generally too extreme, although confidence intervals were wide. There was large between-study heterogeneity in each model’s calibration-in-the-large, suggesting poor calibration of the predicted overall risk across populations. In a subset of models, the net benefit of using the models to inform clinical decisions appeared small and limited to probability thresholds between 5 and 7%. Conclusions The evaluated models had modest predictive performance, with key limitations such as poor calibration (likely due to overfitting in the original development datasets), substantial heterogeneity, and small net benefit across settings. The evidence to support the use of these prediction models for pre-eclampsia in clinical decision-making is limited. Any models that we could not validate should be examined in terms of their predictive performance, net benefit, and heterogeneity across multiple UK settings before consideration for use in practice.en_US
dc.publisherBioMed Centralen_US
dc.rightsNavngivelse 4.0 Internasjonal*
dc.titleExternal validation of prognostic models predicting pre-eclampsia: individual participant data meta-analysisen_US
dc.typePeer revieweden_US
dc.typeJournal articleen_US
dc.source.journalBMC Medicineen_US
dc.description.localcodeThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit The Creative Commons Public Domain Dedication waiver ( applies to the data made available in this article, unless otherwise stated in a credit line to the data.en_US

Tilhørende fil(er)


Denne innførselen finnes i følgende samling(er)

Vis enkel innførsel

Navngivelse 4.0 Internasjonal
Med mindre annet er angitt, så er denne innførselen lisensiert som Navngivelse 4.0 Internasjonal