Meta-Analysis and Systematic Review to Assess the Role of Soluble FMS-Like Tyrosine Kinase-1 and Placenta Growth Factor Ratio in Prediction of Preeclampsia: The SaPPPhirE Study

被引:131
作者
Agrawal, Swati [1 ]
Cerdeira, Ana Sofia [1 ]
Redman, Christopher [1 ]
Vatish, Manu [1 ]
机构
[1] Univ Oxford, Nuffield Dept Obstet & Gynaecol, Oxford OX3 9RT, England
基金
英国医学研究理事会;
关键词
biomarkers; placenta growth factor; preeclampsia; pregnancy; sFLT-1; protein; human; MATERNAL PLASMA-CONCENTRATIONS; LATE-ONSET PREECLAMPSIA; EVIDENCE-BASED MEDICINE; UTERINE ARTERY DOPPLER; ANGIOGENIC FACTORS; SFLT-1/PLGF RATIO; PROSPECTIVE COHORT; DIAGNOSTIC-TEST; STATISTICAL-METHODS; TEST ACCURACY;
D O I
10.1161/HYPERTENSIONAHA.117.10182
中图分类号
R6 [外科学];
学科分类号
1002 ; 100210 ;
摘要
Preeclampsia is a major cause of morbidity and mortality worldwide. Numerous candidate biomarkers have been proposed for diagnosis and prediction of preeclampsia. Measurement of maternal circulating angiogenesis biomarker as the ratio of sFlt-1 (soluble FMS-like tyrosine kinase-1; an antiangiogenic factor)/PlGF (placental growth factor; an angiogenic factor) reflects the antiangiogenic balance that characterizes incipient or overt preeclampsia. The ratio increases before the onset of the disease and thus may help in predicting preeclampsia. We conducted a meta-analysis to explore the predictive accuracy of sFlt-1/PlGF ratio in preeclampsia. We included 15 studies with 534 cases with preeclampsia and 19587 controls. The ratio has a pooled sensitivity of 80% (95% confidence interval, 0.68-0.88), specificity of 92% (95% confidence interval, 0.87-0.96), positive likelihood ratio of 10.5 (95% confidence interval, 6.2-18.0), and a negative likelihood ratio of 0.22 (95% confidence interval, 0.13-0.35) in predicting preeclampsia in both high- and low-risk patients. Most of the studies have not made a distinction between early- and late-onset disease, and therefore, the analysis for it could not be done. It can prove to be a valuable screening tool for preeclampsia and may also help in decision-making, treatment stratification, and better resource allocation.
引用
收藏
页码:306 / 316
页数:11
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