Prediction of Preeclampsia-Related Adverse Outcomes With the sFlt-1 (Soluble fms-Like Tyrosine Kinase 1)/PlGF (Placental Growth Factor)-Ratio in the Clinical Routine: A Real-World Study.

Abstract

This retrospective real-world study investigated the clinical use of the sFlt-1 (soluble fms-like tyrosine kinase 1)/PlGF (placental growth factor) ratio alone or in combination with other clinical tests to predict an adverse maternal (maternal death, kidney failure, hemolysis elevated liver enzymes low platelets-syndrome, pulmonary edema, disseminated intravascular coagulation, cerebral hemorrhage, or eclampsia) or fetal (delivery before 34 weeks because of preeclampsia and/or intrauterine growth restriction, respiratory distress syndrome, necrotizing enterocolitis, intraventricular hemorrhage, placental abruption or intrauterine fetal death or neonatal death within 7 days post natum) pregnancy outcome in patients with signs and symptoms of preeclampsia. We evaluated the sFlt-1/PlGF-ratio cutoff values of 38 and 85 and evaluated its integration into a multimarker model. Of 1117 subjects, 322 (28.8%) developed an adverse fetal or maternal outcome. Patients with an adverse versus no adverse outcome had a median sFlt-1/PlGF-ratio of 177 (interquartile range, 54-362) versus 14 (4-64). Risk-stratification with the sFlt-1/PlGF cutoff values into high- (>85), intermediate- (38-85), and low-risk (<38) showed a significantly shorter time to delivery in high- and intermediate- versus low-risk patients (4 versus 8 versus 29 days). When integrating all available clinical information into a multimarker model, an area under the curve of 88.7% corresponding to a sensitivity, specificity, positive and negative predictive value of 80.0%, 87.3%, 75.0%, and 90.2% was reached. The sFlt-1/PlGF-ratio alone was inferior to the full model with an area under the curve of 85.7%. As expected, blood pressure and proteinuria were significantly less accurate with an area under the curve of 69.0%. Combining biomarker measurements with all available information in a multimarker modeling approach increased detection of adverse outcomes in women with suspected disease.