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Published on: March 1, 2024
Prediction of term preeclampsia using angiogenic biomarkers at 24-29 weeks gestation
Stina Björkman1, Marie Bladh2, Sara Bergstrand3
1Department of Obstetrics and Gynecology in Norrköping, and Department of Biomedical and Clinical Sciences, Linköping University, Linköping, Sweden.
Objectives:
To evaluate sFlt-1, PlGF and the sFlt-1/PlGF ratio at gestational weeks (GW) 24-29 for predicting hypertensive disorders of pregnancy, especially term preeclampsia, in a general Swedish population.
Study Design:
A retrospective nested case-control study, using samples from a pregnancy biobank.
Main Outcome Measures:
The primary outcome was the analysis of Receiver Operating Characteristics (ROC) curves for sFlt-1, PlGF and the sFlt-1/PlGF ratio, along with cut-offs, sensitivity (including at a fixed false positive rate of 20%) and specificity values and overall efficiency for predicting term preeclampsia. Secondary outcomes included data for predicting preterm preeclampsia and gestational hypertension. Subgroup analyses were performed based on risk factors for preeclampsia.
Results:
PlGF levels were reduced, and the sFlt-1/PlGF ratio was increased at GW 24-29 in women who developed term preeclampsia compared to controls. ROC analysis for predicting term preeclampsia using sFlt-1, PlGF and the sFlt-1/PlGF ratio resulted in areas under the curve (AUC) of 0.49, 0.76, and 0.70, respectively. The predictive accuracy improved for preterm PE, with the corresponding AUCs of 0.58, 0.91 and 0.86. Subgroup analyses of nulliparous individuals with obesity and elevated blood pressure in early pregnancy increased the AUC (0.93) for predicting term preeclampsia using PlGF.
Conclusions:
PlGF alone demonstrated superior predictive performance to sFlt-1 and the sFlt-1/PlGF ratio. Enhanced predictive accuracy was observed in individuals with risk factors for preeclampsia. Hence, measuring PlGF at GW 24-29 in women attending antenatal care could help to identify women at risk of developing term PE, thereby enabling more targeted resource allocation within antenatal care.
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Prediction Intervals
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.

