Which first-trimester risk assessment method for preeclampsia is most suitable? A model-based impact study.

BACKGROUND: Low-dose aspirin treatment reduces the risk of preeclampsia among high-risk pregnant women. Internationally, several first-trimester risk-calculation methods are applied. OBJECTIVE: This study aimed to assess the costs and benefits of different first-trimester preeclampsia risk estimation algorithms: EXPECT (an algorithmic prediction model based on maternal characteristics), National Institute for Health and Care Excellence (a checklist of risk factors), and the Fetal Medicine Foundation (a prediction model using additional uterine artery Doppler measurement and laboratory testing) models, coupled with low-dose aspirin treatment, in comparison with no risk assessment. STUDY DESIGN: We constructed a decision analytical model estimating the number of cases of preeclampsia with each strategy and the costs of risk assessment for preeclampsia and early aspirin treatment, expressed in euros (€) in a hypothetical population of 100,000 women. We performed 1-way sensitivity analyses to assess the impact of adherence rates on model outcomes. RESULTS: Application of the EXPECT, National Institute for Health and Care Excellence, and Fetal Medicine Foundation models results in respectively 1.98%, 2.55%, and 1.90% of the women developing preeclampsia, as opposed to 3.00% of women in the case of no risk assessment. Overall, the net financial benefits of the EXPECT, National Institute for Health and Care Excellence, and Fetal Medicine Foundation models relative to no risk assessment are €144, €43, and €38 per patient, respectively. The respective percentages of women receiving aspirin treatment are 18.6%, 10.2%, and 6.0% for the 3 risk assessment methods. CONCLUSION: The EXPECT and Fetal Medicine Foundation model are comparable with regard to numbers of prevented preeclampsia cases, and both are superior to the National Institute for Health and Care Excellence model and to no risk assessment. EXPECT is less resource-demanding and results in the highest cost savings, but also requires the highest number of women to be treated with aspirin. When deciding which strategy is preferable, cost savings and easier use have to be weighed against the degree of overtreatment, although low-dose aspirin has no clear disadvantages during pregnancy.

The choice for invasive prenatal tests after subfertility.

The aim of this study was to test whether women who conceived after a period of subfertility are less likely to undergo invasive prenatal testing (IPT) and determine factors of influence in that decision. We conducted a retrospective study at the Maastricht University Medical Centre (MUMC+) to compare the rates of IPT following abnormal results of combined first trimester screening (cFTS) or second trimester screening (STS), or because of advanced maternal age among women tested for the effect of type and duration of subfertility and history of fertility investigations and/or treatment. We included 977 women who underwent IPT between January 2010 and December 2013. The women who conceived after fertility investigations and/or treatment had lower rates of IPT following abnormal STS (12.6% vs. 20.0%, OR = 0.58, 95% CI; 0.34-0.97). The difference was not statistically significant after correction for maternal age and severity of the foetal anomaly. Maternal age was, in contrast to fertility treatment or duration of subfertility, related to the choice of IPT among formerly subfertile women. Therefore, the lower uptake of IPT in women conceiving after a period of subfertility is dependent on the indication for IPT and maternal age and less on the type and duration of subfertility.

Longitudinal changes in placental biomarkers in women with early versus late placental dysfunction.

Objective: To evaluate longitudinal changes of angiogenic biomarkers in early- (EO-PD) versus late-onset (LO-PD) placental dysfunction. Methods: Serum PlGF and sFlt-1 measured at different intervals in EO-PD (n= 43), LO-PD (n= 31) and controls (n = 133). Results: sFlt-1/PlGF ratio was higher at 16 weeks (30.6 vs 17.5), 20 weeks (29.3 vs 8.9) and 30 weeks (16.6 vs 6.7) in EO-PD vs controls (all p< 0.05), but not in LO-PD. Longitudinal changes for all intervals had higher AUC than single measurements. Conclusion: Longitudinal biomarker change between 12 and 30 weeks could improve prediction of EO-PD compared to single measurements.

Can Fetal Growth Velocity and First Trimester Maternal Biomarkers Improve the Prediction of Small-for-Gestational Age and Adverse Neonatal Outcome?

BACKGROUND AND OBJECTIVES: The aim of this study was to evaluate the value of adding fetal growth velocity and first trimester maternal biomarkers to baseline screening, for the prediction of small-for-gestational age (SGA) and adverse neonatal outcomes. METHOD: A retrospective cohort study was conducted of singleton pregnancies in the Maastricht University Medical Centre between 2012 and 2016. The biomarkers PAPP-A, ß-hCG, PlGF, and sFlt-1 were measured at 11-13 weeks of gestational age (GA) and two fetal growth scans were performed (18-22 and 30-34 weeks of GA). Differences in biomarkers and growth velocities were compared between appropriate-for-gestational age (AGA; birth weight percentile 10-90) and SGA (birth weight percentile <10). Combinations of the biomarkers and fetal growth velocity were added to baseline screening for the prediction of SGA and adverse neonatal outcome. RESULTS: We included 296 singleton pregnancies. Compared to AGA (n = 251), SGA neonates (n = 45) had significantly lower growth velocities in the abdominal circumference (mm/week): 10.1 ± 0.98 versus 10.8 ± 0.98, p = 0.001. Compared with AGA, the SGA neonates had higher sFlt-1 multiples of the median (MoM): 0.89 (0.55) versus 0.76 (0.44), p = 0.023, and a higher sFlt-1/PlGF MoM ratio: 1.09 (1.03) versus 0.90 (0.64), p = 0.027. For a 15% false-positive rate, the prediction of SGA neonates increased from 44.8% for the baseline screening model to 56.5% after the addition of fetal growth velocities, and to 73.9% after the further addition of maternal biomarkers (PPV 9.6%, NPV 82.4%). The corresponding AUC for the three models were 0.722, 0.804, and 0.839, respectively. In addition, AGA neonates with reduced fetal growth velocity had more adverse neonatal outcomes compared to the AGA reference group (12.4 vs. 3.9%, p = 0.013). CONCLUSIONS: Combining fetal growth velocity with first trimester biomarkers resulted in a better prediction of SGA compared to baseline screening parameters alone. This approach could possibly result in reduced adverse neonatal outcomes in neonates, who are at a potential risk due to late mild placental dysfunction.