External validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis: the International Prediction of Pregnancy Complication Network (IPPIC pre-eclampsia) protocol

Show simple item record

dc.contributor.author Allotey, John
dc.contributor.author Snell, Kym I. E.
dc.contributor.author Chan, Claire
dc.contributor.author Hooper, Richard
dc.contributor.author Dodds, Julie
dc.contributor.author Rogozinska, Ewelina
dc.contributor.author Khan, Khalid S.
dc.contributor.author Poston, Lucilla
dc.contributor.author Kenny, Louise C.
dc.contributor.author Myers, Jenny
dc.contributor.author Thilaganathan, Basky
dc.contributor.author Chappell, Lucy
dc.contributor.author Mol, Ben W.
dc.contributor.author Von Dadelszen, Peter
dc.contributor.author Ahmed, Asif
dc.contributor.author Green, Marcus
dc.contributor.author Poon, Liona
dc.contributor.author Khalil, Asma
dc.contributor.author Moons, Karel G. M.
dc.contributor.author Riley, Richard D.
dc.contributor.author Thangaratinam, Shakila
dc.date.accessioned 2017-12-08T13:33:45Z
dc.date.available 2017-12-08T13:33:45Z
dc.date.issued 2017-10-03
dc.identifier.citation Allotey, J., Snell, K. I. E., Chan, C., Hooper, R., Dodds, J., Rogozinska, E., Khan, K. S., Poston, L., Kenny, L., Myers, J., Thilaganathan, B., Chappell, L., Mol, B. W., Von Dadelszen, P., Ahmed, A., Green, M., Poon, L., Khalil, A., Moons, K. G. M., Riley, R. D. and Thangaratinam, S. (2017) 'External validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis: the International Prediction of Pregnancy Complication Network (IPPIC pre-eclampsia) protocol', Diagnostic and Prognostic Research, 1,16 (13pp). doi: 10.1186/s41512-017-0016-z en
dc.identifier.volume 1
dc.identifier.startpage 1
dc.identifier.endpage 13
dc.identifier.uri http://hdl.handle.net/10468/5148
dc.identifier.doi 10.1186/s41512-017-0016-z
dc.description.abstract Background: Pre-eclampsia, a condition with raised blood pressure and proteinuria is associated with an increased risk of maternal and offspring mortality and morbidity. Early identification of mothers at risk is needed to target management. Methods/design: We aim to systematically review the existing literature to identify prediction models for pre-eclampsia. We have established the International Prediction of Pregnancy Complication Network (IPPIC), made up of 72 researchers from 21 countries who have carried out relevant primary studies or have access to existing registry databases, and collectively possess data from more than two million patients. We will use the individual participant data (IPD) from these studies to externally validate these existing prediction models and summarise model performance across studies using random-effects meta-analysis for any, late (after 34 weeks) and early (before 34 weeks) onset pre-eclampsia. If none of the models perform well, we will recalibrate (update), or develop and validate new prediction models using the IPD. We will assess the differential accuracy of the models in various settings and subgroups according to the risk status. We will also validate or develop prediction models based on clinical characteristics only; clinical and biochemical markers; clinical and ultrasound parameters; and clinical, biochemical and ultrasound tests. Discussion: Numerous systematic reviews with aggregate data meta-analysis have evaluated various risk factors separately or in combination for predicting pre-eclampsia, but these are affected by many limitations. Our large-scale collaborative IPD approach encourages consensus towards well developed, and validated prognostic models, rather than a number of competing non-validated ones. The large sample size from our IPD will also allow development and validation of multivariable prediction model for the relatively rare outcome of early onset pre-eclampsia. Trial registration: The project was registered on Prospero on the 27 November 2015 with ID: CRD42015029349. en
dc.description.sponsorship National Institute for Health Research (Health Technology Assessment programme). en
dc.format.mimetype application/pdf en
dc.language.iso en en
dc.publisher BioMed Central en
dc.relation.uri https://diagnprognres.biomedcentral.com/articles/10.1186/s41512-017-0016-z
dc.rights © 2017, the Authors. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. en
dc.rights.uri http://creativecommons.org/licenses/by/4.0/
dc.subject Pre-eclampsia en
dc.subject Prognosis en
dc.subject Prediction model en
dc.subject Maternal en
dc.subject Fetal en
dc.subject IPD en
dc.subject |Individual participant data en
dc.title External validation, update and development of prediction models for pre-eclampsia using an Individual Participant Data (IPD) meta-analysis: the International Prediction of Pregnancy Complication Network (IPPIC pre-eclampsia) protocol en
dc.type Article (peer-reviewed) en
dc.internal.authorcontactother Louise Kenny, Irish Centre for Fetal and Neonatal Translational Research [INFANT], University College Cork, Cork, Ireland, University College Cork, Cork, Ireland. +353-21-490-3000 Email: l.kenny@ucc.ie en
dc.internal.availability Full text available en
dc.description.version Published Version en
dc.contributor.funder National Institute for Health Research
dc.description.status Peer reviewed en
dc.identifier.journaltitle Diagnostic and Prognostic Research en
dc.internal.IRISemailaddress l.kenny@ucc.ie en
dc.identifier.articleid 16


Files in this item

This item appears in the following Collection(s)

Show simple item record

© 2017, the Authors. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated. Except where otherwise noted, this item's license is described as © 2017, the Authors. Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
This website uses cookies. By using this website, you consent to the use of cookies in accordance with the UCC Privacy and Cookies Statement. For more information about cookies and how you can disable them, visit our Privacy and Cookies statement