Allotey, J, Snell, KIE, Chan, C, Hooper, R, Dodds, J, Rogozinska, E, Khan, KS, Poston, L, Kenny, L, Myers, J, Thilaganathan, B, Chappell, L, Mol, BW, Von Dadelszen, P, Ahmed, A, Green, M, Poon, L, Khalil, A, Moons, KGM, Riley, RD, Thangaratinam, S and Collaborative Network, IPPIC (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 - ?. ISSN 2397-7523

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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.

Item Type: Article
Additional Information: Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, 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 ( applies to the data made available in this article, unless otherwise stated.
Uncontrolled Keywords: pre-eclampsia, individual participant data, meta-analysis, pregnancy complication, protocol.
Subjects: Q Science > Q Science (General)
R Medicine > R Medicine (General)
R Medicine > RA Public aspects of medicine
Divisions: Faculty of Medicine and Health Sciences > School of Primary, Community and Social Care
Related URLs:
Depositing User: Symplectic
Date Deposited: 24 Jan 2020 12:07
Last Modified: 01 Mar 2021 16:47

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