Prediction of preterm birth with and without preeclampsia using mid-pregnancy immune and growth-related molecular factors and maternal characteristics.

OBJECTIVE:To evaluate if mid-pregnancy immune and growth-related molecular factors predict preterm birth (PTB) with and without (±) preeclampsia. STUDY DESIGN:Included were 400 women with singleton deliveries in California in 2009-2010 (200 PTB and 200 term) divided into training and testing samples at a 2:1 ratio. Sixty-three markers were tested in 15-20 serum samples using multiplex technology. Linear discriminate analysis was used to create a discriminate function. Model performance was assessed using area under the receiver operating characteristic curve (AUC). RESULTS:Twenty-five serum biomarkers along with maternal age <34 years and poverty status identified >80% of women with PTB ± preeclampsia with best performance in women with preterm preeclampsia (AUC = 0.889, 95% confidence interval (0.822-0.959) training; 0.883 (0.804-0.963) testing). CONCLUSION:Together with maternal age and poverty status, mid-pregnancy immune and growth factors reliably identified most women who went on to have a PTB ± preeclampsia

Prediction of preterm pre-eclampsia at midpregnancy using a multivariable screening algorithm

BACKGROUND: Competing risk models used for midpregnancy prediction of preterm pre-eclampsia have shown detection rates (DR) of 85%, at fixed false-positive rate (FPR) of 10%. The full algorithm used between 19+0 and 24+6 weeks includes maternal factors, mean arterial pressure (MAP), mean uterine artery pulsatility index (UtAPI), serum placental growth factor (PlGF) level in multiples of the median (MoM), and soluble Fms-like tyrosine kinase-1 (sFlt-1) level in MoM. AIMS: To assess performance of the Fetal Medicine Foundation (FMF) algorithm at midpregnancy to screen for preterm (<37 weeks) pre-eclampsia. The outcome measured was preterm pre-eclampsia. MATERIALS AND METHODS: This is a prospective study including singleton pregnancies at 19-22 weeks gestation. Maternal bloods were collected and analysed using three different immunoassay platforms. Maternal characteristics, medical history, MAP, mean UtAPI, serum PlGF MoM and serum sFlt-1 MoM were used for risk assessment. DR and FPR were calculated, and receiver operating characteristic curves produced. RESULTS: Five hundred and twelve patients were included. Incidence of preterm pre-eclampsia was 1.6%. Using predicted risk of pre-eclampsia of one in 60 or more and one in 100 or higher, as given by the FMF predictive algorithm, the combination with the best predictive performance for preterm pre-eclampsia included maternal factors, MAP, UtAPI and PlGF MoM, giving DRs of 100% and 100%, respectively, and FPRs of 9.3 for all platforms and 12.9-13.5, respectively. Addition of sFlt-1 to the algorithm did not appear to improve performance. sFlt-1 MoM and PlGF MoM values obtained on the different platforms performed very similarly. CONCLUSIONS: Second trimester combined screening for preterm pre-eclampsia by maternal history, MAP, mean UtAPI and PlGF MoM using the FMF algorithm performed very well in this patient population