Townsend, R, Khalil, A, Premakumar, Y, Allotey, J, Snell, KIE, Chan, C, Chappell, LC, Hooper, R, Green, M, Mol, BW, Thilaganathan, B, Thangaratinam, S and IPPIC Network, . (2018) Prediction of pre-eclampsia: review of reviews. Ultrasound in Obstetrics and Gynecology.

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Abstract

OBJECTIVE: Primary studies and systematic reviews provide varied accuracy estimates for prediction of pre-eclampsia. We undertook a review of published systematic reviews to collate published evidence on the ability of available tests to predict pre-eclampsia, to identify high value avenues for future research and to minimise future research waste in this field. METHODS: We searched Medline, Embase, DARE (Database of Abstracts of Reviews of Effectiveness) and Cochrane Library databases (from database inception to March 2017) and bibliographies for systematic reviews and meta-analyses without language restrictions. We assessed the quality of the included reviews using the AMSTAR tool and a modified QUIPS tool. We evaluated the reviews' comprehensiveness of search, size, tests and outcomes evaluated, data synthesis methods and predictive ability estimates and risk of bias related to population studied, measurement of predictors and outcomes, study attrition and adjustment for confounding. RESULTS: From 2444 citations, we included 126 reviews, reporting on over 90 predictors and 52 prediction models. Around a third of all reviews (29.3%, 37/126) investigated biochemical markers for predicting pre-eclampsia; 24.6% (31/126) investigated genetic associations with pre-eclampsia, 36.5% (46/126) reported on clinical characteristics; 3.2% (4/126) evaluated only ultrasound markers; and 4.8% (6/126) studied a combination of tests. Reviews included between two and 265 primary studies, including up to 25,356,688 women in the largest review. Only half (67/126, 53.2%) assessed the quality of the included studies. There was a high risk of bias in many of the included reviews, particularly in relation to population representativeness and study attrition. Over 80% (106/126, 84.1%) summarised the findings with meta-analysis. Thirty-four studies (32/126, 25.4%) lacked a formal statement on funding. The predictors with the best test performance were body mass index (BMI>35 specificity 92%, 95% CI 89-95% and sensitivity 21%, 95% CI: 12-31%; BMI >25 specificity 73% , 95% CI: 64-83% and sensitivity 47% , 95%CI: 33-61%), first trimester uterine artery Doppler PI or RI >90th centile (specificity 93%, 95% CI: 90%-96%) and sensitivity 26% (23-31%)), PLGF (specificity 89% , 95% CI: 89-89% and sensitivity 65% , 95% CI: 63-67%) and PP13 (specificity 88% , 95% CI: 87-89% and sensitivity 37% , 95% CI: 33-41%). No single marker had a test performance suitable for routine clinical use. The models combining markers showed promise, but none of the identified models had undergone external validation. CONCLUSION: Our review of reviews has questioned the need for further aggregate meta-analysis in this area, given the large number of published reviews subject to the common limitations of primary predictive studies. Prospective, well-designed studies of predictive markers, preferably in randomised intervention studies, and combined through IPD (individual patient data) meta-analysis are needed to develop and validate new prediction models to facilitate the prediction of pre-eclampsia and minimise further research waste in this field. This article is protected by copyright. All rights reserved.

Item Type: Article
Additional Information: This is the peer reviewed version of the following article: Prediction of pre-eclampsia: review of reviews, which has been published in final form at 10.1002/uog.20117. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Use of Self-Archived Versions
Uncontrolled Keywords: pre-eclampsia; screening; predicition; hypertension in pregnancy; systematic review
Subjects: R Medicine > R Medicine (General)
R Medicine > RG Gynecology and obstetrics
Divisions: Faculty of Medicine and Health Sciences > Primary Care Health Sciences
Related URLs:
Depositing User: Symplectic
Date Deposited: 30 Apr 2019 08:34
Last Modified: 30 Apr 2019 08:34
URI: http://eprints.keele.ac.uk/id/eprint/6236

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