Externally validated prediction models for pre‐eclampsia: systematic review and meta‐analysis

Objective: This systematic review and meta‐analysis aimed to evaluate the performance of existing externally validated prediction models for pre‐eclampsia (PE) (specifically, any‐onset, early‐onset, late‐onset and preterm PE).

Methods: A systematic search was conducted in five databases (MEDLINE, EMBASE, Emcare, CINAHL and Maternity & Infant Care Database) and using Google Scholar/reference search to identify studies based on the Population, Index prediction model, Comparator, Outcome, Timing and Setting (PICOTS) approach until 20 May 2023. We extracted data using the CHARMS checklist and appraised the risk of bias using the PROBAST tool. A meta‐analysis of discrimination and calibration performance was conducted when appropriate.

Results: Twenty‐three studies reported 52 externally validated prediction models for PE (one preterm, 20 any‐onset, 17 early‐onset and 14 late‐onset PE models). No model had the same set of predictors. Fifteen any‐onset PE models were validated externally once, two were validated twice and three were validated three times, while the Fetal Medicine Foundation (FMF) competing‐risks model for preterm PE prediction was validated widely in 16 different settings. The most common predictors were maternal characteristics (prepregnancy body mass index, prior PE, family history of PE, chronic medical conditions and ethnicity) and biomarkers (uterine artery pulsatility index and pregnancy‐associated plasma protein‐A). The FMF model for preterm PE (triple test plus maternal factors) had the best performance, with a pooled area under the receiver‐operating‐characteristics curve (AUC) of 0.90 (95% prediction interval (PI), 0.76–0.96), and was well calibrated. The other models generally had poor‐to‐good discrimination performance (median AUC, 0.66 (range, 0.53–0.77)) and were overfitted on external validation. Apart from the FMF model, only two models that were validated multiple times for any‐onset PE prediction, which were based on maternal characteristics only, produced reasonable pooled AUCs of 0.71 (95% PI, 0.66–0.76) and 0.73 (95% PI, 0.55–0.86).

Conclusions: Existing externally validated prediction models for any‐, early‐ and late‐onset PE have limited discrimination and calibration performance, and include inconsistent input variables. The triple‐test FMF model had outstanding discrimination performance in predicting preterm PE in numerous settings, but the inclusion of specialized biomarkers may limit feasibility and implementation outside of high‐resource settings. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.