First trimester screening for pre-eclampsia and targeted aspirin prophylaxis: a cost-effectiveness cohort study.

OBJECTIVE: Investigate cost-effectiveness of first trimester pre-eclampsia screening using the Fetal Medicine Foundation (FMF) algorithm and targeted aspirin prophylaxis in comparison with standard care. DESIGN: Retrospective observational study. SETTING: London tertiary hospital. POPULATION: 5957 pregnancies screened for pre-eclampsia using the National Institute for Health and Care Excellence (NICE) method. METHODS: Differences in pregnancy outcomes between those who developed pre-eclampsia, term pre-eclampsia and preterm pre-eclampsia were compared by the Kruskal-Wallis and Chi-square tests. The FMF algorithm was applied retrospectively to the cohort. A decision analytic model was used to estimate costs and outcomes for pregnancies screened using NICE and those screened using the FMF algorithm. The decision point probabilities were calculated using the included cohort. MAIN OUTCOME MEASURES: Incremental healthcare costs and QALY gained per pregnancy screened. RESULTS: Of 5957 pregnancies, 12.8% and 15.9% were screen-positive for development of pre-eclampsia using the NICE and FMF methods, respectively. Of those who were screen-positive by NICE recommendations, aspirin was not prescribed in 25%. Across the three groups, namely, pregnancies without pre-eclampsia, term pre-eclampsia and preterm pre-eclampsia there was a statistically significant trend in rates of emergency caesarean (respectively 21%, 43% and 71.4%; P < 0.001), admission to neonatal intensive care unit (NICU) (5.9%, 9.4%, 41%; P < 0.001) and length of stay in NICU. The FMF algorithm was associated with seven fewer cases of preterm pre-eclampsia, cost saving of £9.06 and QALY gain of 0.00006/pregnancy screened. CONCLUSIONS: Using a conservative approach, application of the FMF algorithm achieved clinical benefit and an economic cost saving.

Screening for pre-eclampsia with competing-risks model using placental growth factor measurement in blood samples collected before 11 weeks' gestation.

OBJECTIVES: To describe the distributional properties and assess the performance of placental growth factor (PlGF) measured in blood samples collected before 11 weeks' gestation in the prediction of pre-eclampsia (PE). METHODS: The study population consisted of pregnant women included in the Pre-eclampsia Screening in Denmark (PRESIDE) study with a PlGF measurement from the routine combined first-trimester screening (cFTS) blood sample collected at 8-14 weeks' gestation. PRESIDE was a prospective multicenter study investigating the predictive performance of the Fetal Medicine Foundation (FMF) first-trimester screening algorithm for PE in a Danish population. In the current study, serum concentration of PlGF in the cFTS blood samples was analyzed in batches between January and June 2021. RESULTS: A total of 8386 pregnant women were included. The incidence of PE was 0.7% at < 37 weeks' gestation and 3.0% at ≥ 37 weeks. In blood samples collected at 10 weeks' gestation, PlGF multiples of the median (MoM) were significantly lower in pregnancies with preterm PE < 37 weeks compared to unaffected pregnancies. However, PlGF MoM did not differ significantly between pregnancies with PE and unaffected pregnancies in samples collected before 10 weeks' gestation. CONCLUSIONS: The gestational-age range for PlGF sampling may be expanded from 11-14 to 10-14 weeks when assessing the risk for PE using the FMF first-trimester screening model. There is little evidence to support the use of PlGF in blood samples collected before 10 weeks' gestation. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Validation of Fetal Medicine Foundation competing-risks model for small-for-gestational-age neonate in early third trimester.

OBJECTIVE: To evaluate the new 36-week Fetal Medicine Foundation (FMF) competing-risks model for the prediction of small-for-gestational age (SGA) at an earlier gestation of 30 + 0 to 34 + 0 weeks. METHODS: This was a retrospective multicenter cohort study of prospectively collected data on 3012 women with a singleton pregnancy undergoing ultrasound examination at 30 + 0 to 34 + 0 weeks' gestation as part of a universal screening program. We used the default FMF competing-risks model for prediction of SGA at 36 weeks' gestation combining maternal factors (age, obstetric and medical history, weight, height, smoking status, race, mode of conception), estimated fetal weight (EFW) and uterine artery pulsatility index (UtA-PI) to calculate risks for different cut-offs of birth-weight percentile and gestational age at delivery. We examined the accuracy of the model by means of discrimination and calibration. RESULTS: The prediction of SGA < 3rd percentile improved with the addition of UtA-PI and with a shorter examination-to-delivery interval. For a 10% false-positive rate, maternal factors, EFW and UtA-PI predicted 88.0%, 74.4% and 72.8% of SGA < 3rd percentile delivered at < 37, < 40 and < 42 weeks' gestation, respectively. The respective values for SGA < 10th percentile were 86.1%, 69.3% and 66.2%. In terms of population stratification, if the biomarkers used are EFW and UtA-PI and the aim is to detect 90% of SGA < 10th percentile, then 10.8% of the population should be scanned within 2 weeks after the initial assessment, an additional 7.2% (total screen-positive rate (SPR), 18.0%) should be scanned within 2-4 weeks after the initial assessment and an additional 11.7% (total SPR, 29.7%) should be examined within 4-6 weeks after the initial assessment. The new model was well calibrated. CONCLUSIONS: The 36-week FMF competing-risks model for SGA is also applicable and accurate at 30 + 0 to 34 + 0 weeks and provides effective risk stratification, especially for cases leading to delivery < 37 weeks of gestation. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Comparison of different methods of first-trimester screening for preterm pre-eclampsia: cohort study.

OBJECTIVE: To compare the predictive performance of three different mathematical models for first-trimester screening of pre-eclampsia (PE), which combine maternal risk factors with mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI) and serum placental growth factor (PlGF), and two risk-scoring systems. METHODS: This was a prospective cohort study performed in eight fetal medicine units in five different regions of Spain between September 2017 and December 2019. All pregnant women with singleton pregnancy and a non-malformed live fetus attending their routine ultrasound examination at 11 + 0 to 13 + 6 weeks' gestation were invited to participate in the study. Maternal characteristics and medical history were recorded and measurements of MAP, UtA-PI, serum PlGF and pregnancy-associated plasma protein-A (PAPP-A) were converted into multiples of the median (MoM). Risks for term PE, preterm PE (< 37 weeks' gestation) and early PE (< 34 weeks' gestation) were calculated according to the FMF competing-risks model, the Crovetto et al. logistic regression model and the Serra et al. Gaussian model. PE classification was also performed based on the recommendations of the National Institute for Health and Care Excellence (NICE) and the American College of Obstetricians and Gynecologists (ACOG). We estimated detection rates (DR) with their 95% CIs at a fixed 10% screen-positive rate (SPR), as well as the area under the receiver-operating-characteristics curve (AUC) for preterm PE, early PE and all PE for the three mathematical models. For the scoring systems, we calculated DR and SPR. Risk calibration was also assessed. RESULTS: The study population comprised 10 110 singleton pregnancies, including 32 (0.3%) that developed early PE, 72 (0.7%) that developed preterm PE and 230 (2.3%) with any PE. At a fixed 10% SPR, the FMF, Crovetto et al. and Serra et al. models detected 82.7% (95% CI, 69.6-95.8%), 73.8% (95% CI, 58.7-88.9%) and 79.8% (95% CI, 66.1-93.5%) of early PE; 72.7% (95% CI, 62.9-82.6%), 69.2% (95% CI, 58.8-79.6%) and 74.1% (95% CI, 64.2-83.9%) of preterm PE; and 55.1% (95% CI, 48.8-61.4%), 47.1% (95% CI, 40.6-53.5%) and 53.9% (95% CI, 47.4-60.4%) of all PE, respectively. The best correlation between predicted and observed cases was achieved by the FMF model, with an AUC of 0.911 (95% CI, 0.879-0.943), a slope of 0.983 (95% CI, 0.846-1.120) and an intercept of 0.154 (95% CI, -0.091 to 0.397). The NICE criteria identified 46.7% (95% CI, 35.3-58.0%) of preterm PE at 11% SPR and ACOG criteria identified 65.9% (95% CI, 55.4-76.4%) of preterm PE at 33.8% SPR. CONCLUSIONS: The best performance of screening for preterm PE is achieved by mathematical models that combine maternal factors with MAP, UtA-PI and PlGF, as compared to risk-scoring systems such as those of NICE and ACOG. While all three algorithms show similar results in terms of overall prediction, the FMF model showed the best performance at an individual level. © 2024 International Society of Ultrasound in Obstetrics and Gynecology.

Evaluation of screening performance of first-trimester competing-risks prediction model for small-for-gestational age in Asian population.

OBJECTIVE: To examine the external validity of the Fetal Medicine Foundation (FMF) competing-risks model for the prediction of small-for-gestational age (SGA) at 11-14 weeks' gestation in an Asian population. METHODS: This was a secondary analysis of a multicenter prospective cohort study in 10 120 women with a singleton pregnancy undergoing routine assessment at 11-14 weeks' gestation. We applied the FMF competing-risks model for the first-trimester prediction of SGA, combining maternal characteristics and medical history with measurements of mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI) and serum placental growth factor (PlGF) concentration. We calculated risks for different cut-offs of birth-weight percentile (< 10th , < 5th or < 3rd percentile) and gestational age at delivery (< 37 weeks (preterm SGA) or SGA at any gestational age). Predictive performance was examined in terms of discrimination and calibration. RESULTS: The predictive performance of the competing-risks model for SGA was similar to that reported in the original FMF study. Specifically, the combination of maternal factors with MAP, UtA-PI and PlGF yielded the best performance for the prediction of preterm SGA with birth weight < 10th percentile (SGA < 10th ) and preterm SGA with birth weight < 5th percentile (SGA < 5th ), with areas under the receiver-operating-characteristics curve (AUCs) of 0.765 (95% CI, 0.720-0.809) and 0.789 (95% CI, 0.736-0.841), respectively. Combining maternal factors with MAP and PlGF yielded the best model for predicting preterm SGA with birth weight < 3rd percentile (SGA < 3rd ) (AUC, 0.797 (95% CI, 0.744-0.850)). After excluding cases with pre-eclampsia, the combination of maternal factors with MAP, UtA-PI and PlGF yielded the best performance for the prediction of preterm SGA < 10th and preterm SGA < 5th , with AUCs of 0.743 (95% CI, 0.691-0.795) and 0.762 (95% CI, 0.700-0.824), respectively. However, the best model for predicting preterm SGA < 3rd without pre-eclampsia was the combination of maternal factors and PlGF (AUC, 0.786 (95% CI, 0.723-0.849)). The FMF competing-risks model including maternal factors, MAP, UtA-PI and PlGF achieved detection rates of 42.2%, 47.3% and 48.1%, at a fixed false-positive rate of 10%, for the prediction of preterm SGA < 10th , preterm SGA < 5th and preterm SGA < 3rd , respectively. The calibration of the model was satisfactory. CONCLUSION: The screening performance of the FMF first-trimester competing-risks model for SGA in a large, independent cohort of Asian women is comparable with that reported in the original FMF study in a mixed European population. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Pre-eclampsia screening in Denmark (PRESIDE): national validation study.

OBJECTIVES: To investigate the predictive performance of the Fetal Medicine Foundation (FMF) first-trimester screening algorithm for pre-eclampsia in a Danish population and compare screening performance with that of the current Danish strategy, which is based on maternal risk factors. METHODS: This was a prospective study of women with a singleton pregnancy attending for their first-trimester ultrasound scan and screening for aneuploidies at six Danish university hospitals between May 2019 and December 2020. Prenatal data on maternal characteristics and medical history were recorded, and measurements of mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI), serum pregnancy-associated plasma protein-A (PAPP-A) and serum placental growth factor (PlGF) were collected without performing a risk assessment for pre-eclampsia. Information on acetylsalicylic acid use was recorded. After delivery, pregnancy outcome, including gestational age at delivery and pre-eclampsia diagnosis, was recorded. Pre-eclampsia risk assessment for each woman was calculated blinded to outcome using the FMF screening algorithm following adjustment to the Danish population. Detection rates (DRs) of the FMF algorithm were calculated for a fixed screen-positive rate (SPR) of 10% and for the SPR achieved in the current Danish screening. RESULTS: A total of 8783 pregnant women were included, with a median age of 30.8 (interquartile range (IQR), 28.1-33.9) years. The majority were white (95%), naturally conceiving (90%), non-smokers (97%) and had no family history of pre-eclampsia (96%). The median body mass index was 23.4 (IQR, 21.2-26.6) kg/m2 . A complete risk assessment including maternal characteristics, MAP, UtA-PI, PlGF and PAPP-A was available for 8156 women (92.9%). In these women, UtA-PI was measured bilaterally with a median value of 1.58 (IQR, 1.27-1.94) and the median resting MAP of 80.5 (IQR, 76.1-85.4) mmHg in two consecutive measurements. Among these, 303 (3.7%) developed pre-eclampsia, including 55 (0.7%) cases of pre-eclampsia with delivery < 37 weeks of gestation and 16 (0.2%) cases of pre-eclampsia with delivery < 34 weeks. At a SPR of 10%, combined screening using the FMF algorithm based on maternal characteristics, MAP, UtA-PI, PlGF and PAPP-A had a DR of 77.4% (95% CI, 57.6-97.2%) for pre-eclampsia with delivery < 34 weeks, 66.8% (95% CI, 54.4-79.1%) for pre-eclampsia with delivery < 37 weeks and 44.1% (95% CI, 38.5-49.7%) for pre-eclampsia with delivery at any gestational age. The current Danish screening strategy using maternal risk factors detected 25.0% of women with pre-eclampsia with delivery < 34 weeks and 19.6% of women with pre-eclampsia with delivery < 37 weeks at a SPR of 3.4%. When applying the FMF algorithm including maternal characteristics, MAP, UtA-PI and PlGF at the fixed SPR of 3.4%, the DRs were 60.5% (95% CI, 36.9-84.1%) for PE with delivery < 34 weeks and 45.2% (95% CI, 32.0-58.5%) for PE with delivery < 37 weeks. CONCLUSION: In this large Danish multicenter study, the FMF algorithm based on maternal characteristics, MAP, UtA-PI, PlGF and PAPP-A predicted 77.4% of cases with pre-eclampsia with delivery < 34 weeks and 66.8% of cases with pre-eclampsia with delivery < 37 weeks of gestation at a SPR of 10%, suggesting that the performance of the algorithm in a Danish cohort matches that in other populations. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Performance of first-trimester combined screening for preterm pre-eclampsia: findings from cohort of 10 110 pregnancies in Spain.

OBJECTIVE: To evaluate the diagnostic accuracy of the Fetal Medicine Foundation (FMF) competing-risks model, incorporating maternal characteristics, mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI) and placental growth factor (PlGF) (the 'triple test'), for the prediction at 11-13 weeks' gestation of preterm pre-eclampsia (PE) in a Spanish population. METHODS: This was a prospective cohort study performed in eight fetal medicine units in five different regions of Spain between September 2017 and December 2019. All pregnant women with a singleton pregnancy and a non-malformed live fetus attending a routine ultrasound examination at 11 + 0 to 13 + 6 weeks' gestation were invited to participate. Maternal demographic characteristics and medical history were recorded and MAP, UtA-PI, serum PlGF and pregnancy-associated plasma protein-A (PAPP-A) were measured following standardized protocols. Treatment with aspirin during pregnancy was also recorded. Raw values of biomarkers were converted into multiples of the median (MoM), and audits were performed periodically to provide regular feedback to operators and laboratories. Patient-specific risks for term and preterm PE were calculated according to the FMF competing-risks model, blinded to pregnancy outcome. The performance of screening for PE, taking into account aspirin use, was assessed by calculating the area under the receiver-operating-characteristics curve (AUC) and detection rate (DR) at a 10% fixed screen-positive rate (SPR). Risk calibration of the model was assessed. RESULTS: The study population comprised 10 110 singleton pregnancies, including 72 (0.7%) that developed preterm PE. In the preterm PE group, compared to those without PE, median MAP MoM and UtA-PI MoM were significantly higher, and median serum PlGF MoM and PAPP-A MoM were significantly lower. In women with PE, the deviation from normal in all biomarkers was inversely related to gestational age at delivery. Screening for preterm PE by a combination of maternal characteristics and medical history with MAP, UtA-PI and PlGF had a DR, at 10% SPR, of 72.7% (95% CI, 62.9-82.6%). An alternative strategy of replacing PlGF with PAPP-A in the triple test was associated with poorer screening performance for preterm PE, giving a DR of 66.5% (95% CI, 55.8-77.2%). The calibration plot showed good agreement between predicted risk and observed incidence of preterm PE, with a slope of 0.983 (95% CI, 0.846-1.120) and an intercept of 0.154 (95% CI, -0.091 to 0.397). CONCLUSIONS: The FMF model is effective in predicting preterm PE in the Spanish population at 11-13 weeks' gestation. This method of screening is feasible to implement in routine clinical practice, but it should be accompanied by a robust audit and monitoring system, in order to maintain high-quality screening. © 2023 International Society of Ultrasound in Obstetrics and Gynecology.

Glycosylated fibronectin improves first-trimester prediction of pre-eclampsia.

OBJECTIVE: To determine whether maternal serum glycosylated fibronectin (GlyFn) level in the first trimester increases the sensitivity of the Fetal Medicine Foundation (FMF) triple test, which incorporates mean arterial pressure, uterine artery pulsatility index and placental growth factor, when screening for pre-eclampsia (PE) in an Asian population. METHODS: This was a nested case-control study of Chinese women with a singleton pregnancy who were screened for PE at 11-13 weeks' gestation as part of a non-intervention study between December 2016 and June 2018. GlyFn levels were measured retrospectively in archived serum from 1685 pregnancies, including 101 with PE, using an enzyme-linked immunosorbent assay (ELISA), and from 448 pregnancies, including 101 with PE, using a point-of-care (POC) device. Concordance between ELISA and POC tests was assessed using Lin's correlation coefficient and Passing-Bablok and Bland-Altman analyses. GlyFn was transformed into multiples of the median (MoM) to adjust for maternal and pregnancy characteristics. GlyFn MoM was compared between PE and non-PE pregnancies, and the association between GlyFn MoM and gestational age at delivery with PE was assessed. Risk for developing PE was estimated using the FMF competing-risks model. Screening performance for preterm and any-onset PE using different biomarker combinations was quantified by area under the receiver-operating-characteristics curve (AUC) and detection rate (DR) at a 10% fixed false-positive rate (FPR). Differences in AUC between biomarker combinations were compared using the DeLong test. RESULTS: The concordance correlation coefficient between ELISA and POC measurements was 0.86 (95% CI, 0.83-0.88). Passing-Bablok analysis indicated proportional bias (slope, 1.08 (95% CI, 1.04-1.14)), with POC GlyFn being significantly higher compared with ELISA GlyFn. ELISA GlyFn in non-PE pregnancies was independent of gestational age at screening (P = 0.11), but significantly dependent on maternal age (P < 0.003), weight (P < 0.0002), height (P = 0.001), parity (P < 0.02) and smoking status (P = 0.002). Compared with non-PE pregnancies, median GlyFn MoM using ELISA and POC testing was elevated significantly in those with preterm PE (1.23 vs 1.00; P < 0.0001 and 1.18 vs 1.00; P < 0.0001, respectively) and those with term PE (1.26 vs 1.00; P < 0.0001 and 1.22 vs 1.00; P < 0.0001, respectively). GlyFn MoM was not correlated with gestational age at delivery with PE (P = 0.989). Adding GlyFn to the FMF triple test for preterm PE increased significantly the AUC from 0.859 to 0.896 (P = 0.012) and increased the DR at 10% FPR from 64.9% (95% CI, 48.7-81.1%) to 82.9% (95% CI, 66.4-93.4%). The corresponding DRs at 10% FPR for any-onset PE were 52.5% (95% CI, 42.3-62.5%) and 65.4% (95% CI, 55.2-74.5%), respectively. CONCLUSIONS: Adding GlyFn to the FMF triple test increased the screening sensitivity for both preterm and any-onset PE in an Asian population. Prospective non-intervention studies are needed to confirm these initial findings. © 2023 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of International Society of Ultrasound in Obstetrics and Gynecology.

Prevention of preeclampsia with aspirin.

Preeclampsia is defined as hypertension arising after 20 weeks of gestational age with proteinuria or other signs of end-organ damage and is an important cause of maternal and perinatal morbidity and mortality, particularly when of early onset. Although a significant amount of research has been dedicated in identifying preventive measures for preeclampsia, the incidence of the condition has been relatively unchanged in the last decades. This could be attributed to the fact that the underlying pathophysiology of preeclampsia is not entirely understood. There is increasing evidence suggesting that suboptimal trophoblastic invasion leads to an imbalance of angiogenic and antiangiogenic proteins, ultimately causing widespread inflammation and endothelial damage, increased platelet aggregation, and thrombotic events with placental infarcts. Aspirin at doses below 300 mg selectively and irreversibly inactivates the cyclooxygenase-1 enzyme, suppressing the production of prostaglandins and thromboxane and inhibiting inflammation and platelet aggregation. Such an effect has led to the hypothesis that aspirin could be useful for preventing preeclampsia. The first possible link between the use of aspirin and the prevention of preeclampsia was suggested by a case report published in 1978, followed by the first randomized controlled trial published in 1985. Since then, numerous randomized trials have been published, reporting the safety of the use of aspirin in pregnancy and the inconsistent effects of aspirin on the rates of preeclampsia. These inconsistencies, however, can be largely explained by a high degree of heterogeneity regarding the selection of trial participants, baseline risk of the included women, dosage of aspirin, gestational age of prophylaxis initiation, and preeclampsia definition. An individual patient data meta-analysis has indicated a modest 10% reduction in preeclampsia rates with the use of aspirin, but later meta-analyses of aggregate data have revealed a dose-response effect of aspirin on preeclampsia rates, which is maximized when the medication is initiated before 16 weeks of gestational age. Recently, the Aspirin for Evidence-Based Preeclampsia Prevention trial has revealed that aspirin at a daily dosage of 150 mg, initiated before 16 weeks of gestational age, and given at night to a high-risk population, identified by a combined first trimester screening test, reduces the incidence of preterm preeclampsia by 62%. A secondary analysis of the Aspirin for Evidence-Based Preeclampsia Prevention trial data also indicated a reduction in the length of stay in the neonatal intensive care unit by 68% compared with placebo, mainly because of a reduction in births before 32 weeks of gestational age with preeclampsia. The beneficial effect of aspirin has been found to be similar in subgroups according to different maternal characteristics, except for the presence of chronic hypertension, where no beneficial effect is evident. In addition, the effect size of aspirin has been found to be more pronounced in women with good compliance to treatment. In general, randomized trials are underpowered to investigate the treatment effect of aspirin on the rates of other placental-associated adverse outcomes such as fetal growth restriction and stillbirth. This article summarizes the evidence around aspirin for the prevention of preeclampsia and its complications.

First trimester preeclampsia screening and prediction.

Preeclampsia is a major cause of maternal and perinatal morbidity and mortality. Early-onset disease requiring preterm delivery is associated with a higher risk of complications in both mothers and babies. Evidence suggests that the administration of low-dose aspirin initiated before 16 weeks' gestation significantly reduces the rate of preterm preeclampsia. Therefore, it is important to identify pregnant women at risk of developing preeclampsia during the first trimester of pregnancy, thus allowing timely therapeutic intervention. Several professional organizations such as the American College of Obstetricians and Gynecologists (ACOG) and National Institute for Health and Care Excellence (NICE) have proposed screening for preeclampsia based on maternal risk factors. The approach recommended by ACOG and NICE essentially treats each risk factor as a separate screening test with additive detection rate and screen-positive rate. Evidence has shown that preeclampsia screening based on the NICE and ACOG approach has suboptimal performance, as the NICE recommendation only achieves detection rates of 41% and 34%, with a 10% false-positive rate, for preterm and term preeclampsia, respectively. Screening based on the 2013 ACOG recommendation can only achieve detection rates of 5% and 2% for preterm and term preeclampsia, respectively, with a 0.2% false-positive rate. Various first trimester prediction models have been developed. Most of them have not undergone or failed external validation. However, it is worthy of note that the Fetal Medicine Foundation (FMF) first trimester prediction model (namely the triple test), which consists of a combination of maternal factors and measurements of mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, has undergone successful internal and external validation. The FMF triple test has detection rates of 90% and 75% for the prediction of early and preterm preeclampsia, respectively, with a 10% false-positive rate. Such performance of screening is superior to that of the traditional method by maternal risk factors alone. The use of the FMF prediction model, followed by the administration of low-dose aspirin, has been shown to reduce the rate of preterm preeclampsia by 62%. The number needed to screen to prevent 1 case of preterm preeclampsia by the FMF triple test is 250. The key to maintaining optimal screening performance is to establish standardized protocols for biomarker measurements and regular biomarker quality assessment, as inaccurate measurement can affect screening performance. Tools frequently used to assess quality control include the cumulative sum and target plot. Cumulative sum is a sensitive method to detect small shifts over time, and point of shift can be easily identified. Target plot is a tool to evaluate deviation from the expected multiple of median and the expected median of standard deviation. Target plot is easy to interpret and visualize. However, it is insensitive to detecting small deviations. Adherence to well-defined protocols for the measurements of mean arterial pressure, uterine artery pulsatility index, and placental growth factor is required. This article summarizes the existing literature on the different methods, recommendations by professional organizations, quality assessment of different components of risk assessment, and clinical implementation of the first trimester screening for preeclampsia.

Prospective evaluation of screening performance of first-trimester prediction models for preterm preeclampsia in an Asian population.

BACKGROUND: The administration of aspirin <16 weeks gestation to women who are at high risk for preeclampsia has been shown to reduce the rate of preterm preeclampsia by 65%. The traditional approach to identify such women who are at risk is based on risk factors from maternal characteristics, obstetrics, and medical history as recommended by the American College of Obstetricians and Gynecologists and the National Institute for Health and Care Excellence. An alternative approach to screening for preeclampsia has been developed by the Fetal Medicine Foundation. This approach allows the estimation of patient-specific risks of preeclampsia that requires delivery before a specified gestational age with the use of Bayes theorem-based model. OBJECTIVE: The purpose of this study was to examine the diagnostic accuracy of the Fetal Medicine Foundation Bayes theorem-based model, the American College of Obstetricians and Gynecologists, and the National Institute for Health and Care Excellence recommendations for the prediction of preterm preeclampsia at 11-13+6 weeks gestation in a large Asian population STUDY DESIGN: This was a prospective, nonintervention, multicenter study in 10,935 singleton pregnancies at 11-13+6 weeks gestation in 11 recruiting centers across 7 regions in Asia between December 2016 and June 2018. Maternal characteristics and medical, obstetric, and drug history were recorded. Mean arterial pressure and uterine artery pulsatility indices were measured according to standardized protocols. Maternal serum placental growth factor concentrations were measured by automated analyzers. The measured values of mean arterial pressure, uterine artery pulsatility index, and placental growth factor were converted into multiples of the median. The Fetal Medicine Foundation Bayes theorem-based model was used for the calculation of patient-specific risk of preeclampsia at <37 weeks gestation (preterm preeclampsia) and at any gestation (all preeclampsia) in each participant. The performance of screening for preterm preeclampsia and all preeclampsia by a combination of maternal factors, mean arterial pressure, uterine artery pulsatility index, and placental growth factor (triple test) was evaluated with the adjustment of aspirin use. We examined the predictive performance of the model by the use of receiver operating characteristic curve and calibration by measurements of calibration slope and calibration in the large. The detection rate of screening by the Fetal Medicine Foundation Bayes theorem-based model was compared with the model that was derived from the application of American College of Obstetricians and Gynecologists and National Institute for Health and Care Excellence recommendations. RESULTS: There were 224 women (2.05%) who experienced preeclampsia, which included 73 cases (0.67%) of preterm preeclampsia. In pregnancies with preterm preeclampsia, the mean multiples of the median values of mean arterial pressure and uterine artery pulsatility index were significantly higher (mean arterial pressure, 1.099 vs 1.008 [P<.001]; uterine artery pulsatility index, 1.188 vs 1.063[P=.006]), and the mean placental growth factor multiples of the median was significantly lower (0.760 vs 1.100 [P<.001]) than in women without preeclampsia. The Fetal Medicine Foundation triple test achieved detection rates of 48.2%, 64.0%, 71.8%, and 75.8% at 5%, 10%, 15%, and 20% fixed false-positive rates, respectively, for the prediction of preterm preeclampsia. These were comparable with those of previously published data from the Fetal Medicine Foundation study. Screening that used the American College of Obstetricians and Gynecologists recommendations achieved detection rate of 54.6% at 20.4% false-positive rate. The detection rate with the use of National Institute for Health and Care Excellence guideline was 26.3% at 5.5% false-positive rate. CONCLUSION: Based on a large number of women, this study has demonstrated that the Fetal Medicine Foundation Bayes theorem-based model is effective in the prediction of preterm preeclampsia in an Asian population and that this method of screening is superior to the approach recommended by American College of Obstetricians and Gynecologists and the National Institute for Health and Care Excellence. We have also shown that the Fetal Medicine Foundation prediction model can be implemented as part of routine prenatal care through the use of the existing infrastructure of routine prenatal care.

First-Trimester Combined Multimarker Prospective Study for the Detection of Pregnancies at a High Risk of Developing Preeclampsia Using the Fetal Medicine Foundation-Algorithm.

OBJECTIVE: To evaluate the Fetal Medicine Foundation (FMF) algorithm prospectively at 11-13 weeks' gestation in the prediction of preeclampsia (PE). METHODS: Single-center prospective screening study for PE of singleton pregnancies at 11-13 weeks. The FMF algorithm takes into account maternal characteristics and biomarkers. Detection rate (DR) for a 10% false-positive rate (FPR) for delivery with preterm and term PE was estimated. RESULTS: Between January 2011 and December 2013, of 3,239 patients available for final analysis, 36 (1.1%) subsequently developed preterm and 44 (1.4%) term PE. In combined screening by maternal factors, mean arterial pressure, uterine artery pulsatility index, and serum placental growth factor, the DR was 80.6% (95% CI 64.0-91.8) for PE at <37 weeks and 31.8% (95% CI 18.6-47.6) for PE at ≥37 weeks, at a 10% FPR. CONCLUSION: Our data suggest that the FMF algorithm provides effective first-trimester screening for preterm PE.

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.

Accuracy of the FMF Bayes theorem-based model for predicting preeclampsia at 11-13 weeks of gestation in a Japanese population.

This study aimed to investigate the diagnostic accuracy of the Fetal Medicine Foundation (FMF) Bayes theorem-based model for the prediction of preeclampsia (PE) at 11-13 weeks of gestation in the Japanese population. In this prospective cohort study, we invited 2655 Japanese women with singleton pregnancies at 11-13 weeks of gestation to participate, of whom 1036 women provided written consent. Finally, we included 913 women for whom all measurements and perinatal outcomes were available. Data on maternal characteristics and medical history were recorded. Mean arterial pressure (MAP), uterine artery pulsatility index, and maternal serum placental growth factor (PlGF) were measured. The patients delivered their babies at Showa University Hospital between June 2017 and December 2019. Participants were classified into high- and low-risk groups according to the FMF Bayes theorem-based model. Frequencies of PE were compared between groups. The screening performance of the model was validated using the area under receiver operating characteristic (AUROC) curve. A total of 26 patients (2.8%) developed PE, including 11 patients (1.2%) with preterm PE (delivery at <37 weeks). The frequency of preterm PE was significantly higher in the high-risk group than in the low-risk group (3.8% vs. 0.2%, p < 0.05). This population model achieved a 91% detection rate for the prediction of preterm PE at a screen-positive rate of 10% by a combination of maternal characteristics, MAP, and PlGF. The AUROC curve for the prediction of preterm PE was 0.962 (0.927-0.981). In conclusion, the prediction of preterm PE using the FMF Bayes theorem-based model is feasible in the Japanese population.

Validation of Fetal Medicine Foundation algorithm for prediction of pre-eclampsia in the first trimester in an unselected Brazilian population.

OBJECTIVE: The objective of this study is to evaluate the predictive performance of the Fetal Medicine Foundation (FMF) algorithm for prediction of preeclampsia (PE) between 11 and 14 weeks of gestation in an unselected Brazilian population. METHODS: We conducted a prospective cohort study with 617 singleton pregnancies of unselected risk. Biophysical markers (mean pulsatility index, mean arterial pressure) and biochemical markers (placental growth factor (PLGF) and PAPP-A) were inserted into the FMF software and converted into multiples of the median (MoM). The subjects were divided into five groups: early-onset PE, parturition <34 weeks' gestation; preterm PE, parturition <37 weeks; PE, parturition at any gestational age; gestational hypertension (GH); and control group. Areas under the receiver operating characteristics curve (AUC) were calculated for the outcomes. RESULTS: Among 617 patients, seven developed early-onset PE, 18 developed preterm PE (seven early PE plus 11 delivered between 34 and 36 + 6 weeks gestation), 34 developed PE (18 preterm PE plus 16 delivered after 37-week gestation), 12 pregnant women developed GH, and 517 women comprised the control group. The best predictive performance using the FMF algorithm occurred in the early-onset PE group, with AUC = 0.946 (95% CI 0.919-0.973) and the detection rate of 28.6% and 85.7% for 5% and 10% false-positive (FP), respectively. CONCLUSIONS: The FMF algorithm to predict PE was effective in a Brazilian population, mainly in the early-onset form of the disease at 10% FP.

Validación de la calculadora de la Fundación de Medicina Fetal para tamiz de preeclampsia adaptada a población mexicana / Validation of the Fetal Medicine Foundation calculator for pre-eclampsia screening test adapted to a Mexican population

Resumen OBJETIVO: Validar el rendimiento de la calculadora de la Fundación de Medicina Fetal 4.0 adaptada a población mexicana. MATERIALES Y MÉTODOS: Estudio de cohorte efectuado en embarazos con feto único, según el modelo de riesgos en competencia para preeclampsia en un centro de medicina fetal de la Ciudad de México. El riesgo a priori se calculó de acuerdo con la historia clínica. La presión arterial media, el índice de pulsatilidad medio de la arteria uterina y la proteína plasmática A asociada al embarazo se midieron a las 11 a 14 semanas de gestación con metodología estandarizada. El valor de cada marcador se transformó en múltiplos de la mediana adaptados a la población local. Se aplicaron la distribución normal multivariante y el teorema de Bayes para obtener las probabilidades posprueba individuales, que se utilizaron como clasificadores para el área bajo la curva de característica receptor-operador. RESULTADOS: La incidencia de preeclampsia fue del 5.0% (54/1078). El área bajo la curva de característica receptor-operador fue de 0.784 (0.712; 0.856) para preeclampsia a menos de 37 semanas y de 0.807 (0.762; 0.852) para preeclampsia global. CONCLUSIONES: La calculadora FMF 4.0 adaptada a población mexicana resultó válida. Si bien tuvo menor rendimiento al esperado para preeclampsia a menos de 37 semanas, el rendimiento para preeclampsia global fue satisfactorio. Se justifica desarrollar la calculadora local.

Abstract OBJECTIVE: To validate the performance of the Fetal Medicine Foundation 4.0 calculator adapted to the Mexican population. MATERIALS AND METHODS: Cohort study performed in singleton pregnancies, according to the competing risk model for preeclampsia in a fetal medicine center in Mexico City. The a priori risk was calculated according to the clinical history. Mean arterial pressure, mean uterine artery pulsatility index and pregnancy-associated plasma protein A were measured at 11 to 14 weeks of gestation with standardized methodology. The value of each marker was transformed into multiples of the median adapted to the local population. Multivariate normal distribution and Bayes' theorem were applied to obtain individual posttest probabilities, which were used as classifiers for the area under the receiver-operator characteristic curve. RESULTS: The incidence of preeclampsia was 5.0% (54/1078). The area under the receiver-operator characteristic curve was 0.784 (0.712; 0.856) for preeclampsia at less than 37 weeks and 0.807 (0.762; 0.852) for global preeclampsia. CONCLUSIONS: The FMF 4.0 calculator adapted to Mexican population proved valid. Although it had lower performance than expected for preeclampsia at less than 37 weeks, the performance for global preeclampsia was satisfactory. The development of the local calculator is justified.