Evidence map›Paper›PMID 31093545›Full record

ArticleDiagnostic and prognostic research2017

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.

John Allotey, Kym I E Snell, Claire Chan, Richard Hooper, Julie Dodds, Ewelina Rogozinska, Khalid S Khan, Lucilla Poston, Louise Kenny, Jenny Myers and 12 more

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In one paragraph

Article in Diagnostic and prognostic research, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 2 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed, 2 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed, 2 syntheses or guidelines pooled it.

  1. Pooled it
  2. Pooled it
  3. Article
  4. Article
  5. COVID-19 prediction models: a systematic literature review.Osong public health and research perspectives · 2021
    Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

22 authors.

John Allotey1Women's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Kym I E Snell4Research Institute for Primary Care and Health Sciences, Keele University, Keele, UK.
Claire Chan2Pragmatic Clinical Trials Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Richard Hooper2Pragmatic Clinical Trials Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Julie Dodds1Women's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Ewelina Rogozinska1Women's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Khalid S Khan1Women's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
Lucilla Poston5Division of Women's Health, Women's Health Academic Centre, King's College London, London, UK.
Louise Kenny6Irish Centre for Fetal and Neonatal Translational Research [INFANT], University College Cork, Cork, Ireland.
Jenny Myers7Maternal and Fetal Heath Research Centre, Manchester Academic Health Science Centre, University of Manchester, Central Manchester NHS Trust, Manchester, UK.
Basky Thilaganathan8Fetal Medicine Unit, St George's University Hospitals NHS Foundation Trust and Molecular and Clinical Sciences Research Institute, St George's University of London, London, UK.
Lucy Chappell5Division of Women's Health, Women's Health Academic Centre, King's College London, London, UK.
Ben W Mol9The Robinson Research Institute, School of Paediatrics and Reproductive Health, University of Adelaide, Adelaide, Australia.
Peter Von Dadelszen10Institute of Cardiovascular and Cell Sciences, St George's, University of London, London, UK.
Asif Ahmed11Aston Medical School, Aston University, Birmingham, UK.
Marcus GreenAction on Pre-eclampsia (APEC) Charity, Worcestershire, UK.
Liona Poon13Harris Birthright Research Centre for Fetal Medicine, King's College Hospital, London, UK.
Asma Khalil8Fetal Medicine Unit, St George's University Hospitals NHS Foundation Trust and Molecular and Clinical Sciences Research Institute, St George's University of London, London, UK.
Karel G M Moons15Julius Centre for Health Sciences and Primary Care, University Medical Centre Utrecht, Utrecht, the Netherlands.
Richard D Riley4Research Institute for Primary Care and Health Sciences, Keele University, Keele, UK.
Shakila Thangaratinam1Women's Health Research Unit, Barts and the London School of Medicine and Dentistry, Queen Mary University of London, London, UK.
IPPIC Collaborative Network

Funding

Department of Health HTA/14/158/02Department of Health NIHR-CS-011-020Medical Research Council G0701824
6 · The paper itself

Abstract

backgroundPre-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/

designWe 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 registrationThe project was registered on Prospero on the 27 November 2015 with ID: CRD42015029349.

Indexed as

FetalIndividual participant dataIPDMaternalPrediction modelPre-eclampsiaPrognosis

Identifiers

PMID31093545
PMCPMC6460674

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.