Quality of first trimester risk prediction models for pre‐eclampsia: a systematic review. (11th March 2015)

• Record Type: Journal Article
• Authors: Brunelli, VB; Prefumo, F
• Is Part Of: BJOG. Volume 122:Number 7(2015:Jul.)
• Page Start: 904
• Page End: 914
• Publication Date: 2015-03-11
• Subjects: Obstetrics -- Periodicals; Gynecology -- Periodicals; 618
• DOI: 10.1111/1471-0528.13334
• Languages: English
• ISSNs: 1470-0328

Abstract

<abstract abstract-type="main" id="bjo13334-abs-0001"> <title> <x xml:space="preserve">Abstract</x> </title> <sec id="bjo13334-sec-0001" sec-type="section"> <title>Background</title> <p>There is an increasing interest in first trimester risk prediction models for pre‐eclampsia.</p> </sec> <sec id="bjo13334-sec-0002" sec-type="section"> <title>Objectives</title> <p>To systematically review and critically assess the building and reporting of methods used to develop first trimester risk prediction models for pre‐eclampsia.</p> </sec> <sec id="bjo13334-sec-0003" sec-type="section"> <title>Search strategy</title> <p>Search of PubMed and EMBASE databases from inception to July 2013.</p> </sec> <sec id="bjo13334-sec-0004" sec-type="section"> <title>Selection criteria</title> <p>Logistic regression model for predicting the risk of pre‐eclampsia in the first trimester, including uterine artery Doppler among independent variables.</p> </sec> <sec id="bjo13334-sec-0005" sec-type="section"> <title>Data collection and analysis</title> <p>We extracted information on study design, outcome definition, participant recruitment, sample size and number of events, risk predictors and their selection and treatment, model‐building strategies, missing data, overfitting and validation.</p> </sec> <sec id="bjo13334-sec-0006" sec-type="section"> <title>Main results</title> <p>The initial search identified 80 articles. A total of 24 studies were eligible for review, from which 38 predictive models were identified. The median number of study participants was 697 [interquartile range (IQR) 377– 5126]. The median number of cases of pre‐eclampsia per model was 37 (IQR 19–97). The median number of risk predictors was 5 (IQR 3.75–7). In 22% of the models, the number of events per variable was fewer than the commonly recommended value of 10 events per predictor; this proportion increased to 94% in models for early pre‐eclampsia. Treatment and handling of missing data were not reported in 37 models. Only three models reported model validation.</p> </sec> <sec id="bjo13334-sec-0007" sec-type="section"> <title>Conclusions</title> <p>We found frequent methodological deficiencies in studies reporting risk prediction models for pre‐eclampsia. This may limit their reliability and validity.</p> </sec> </abstract>