Revised competing-risks model in screening for pre-eclampsia in twin pregnancy by maternal characteristics and medical history

The correlation between maternal serum sST2, IL-33 and NT-proBNP concentrations and occurrence of pre-eclampsia in twin pregnancies: A longitudinal study

The primary objective of this study was to determine the longitudinal profile of serum sST2 (soluble suppression of tumorigenicity 2), IL‐33 (interleukin‐33) and NT‐proBNP (N‐terminal pro‐brain natriuretic peptide) concentrations in twin pregnancies with pre‐eclampsia (PE) and those normotensive twins. The secondary objective was to test whether the change of serum sST2,IL‐33 and NT‐proBNP is related to PE in twin pregnancies. This is a longitudinal nested case–control study and all 156 dichorionic (DC) pregnancies were from a prospective cohort of twin pregnancies who received antenatal care and gave two live births at Peking University Third Hospital between October 2017 and September 2020. Four to five milliliters of peripheral blood of each pregnant woman were collected during the following three intervals: (1) 6–11⁺⁶ weeks; (2) 24–27⁺⁶ weeks; (3) 28–31⁺⁶ weeks. We found that sST2 and NT‐proBNP levels increased as pregnancy progressed in normotensive twin pregnancies and further increased in PE group, while no differences were found in IL‐33 levels throughout pregnancy. Then the correlation of biomarker levels with the occurrence of PE was assessed. Our results indicated that combining maternal serum sST2 and NT‐proBNP levels yielded the highest predictive value on the occurrence of PE significantly higher than the predictive value of any markers alone. Interestingly, the predictive value of second trimester (AUC = 0.876, 95%CI 0.824–0.928, LR−0.338, LR+7.67, p < 0.001)was higher than that of early‐third trimester (AUC = 0.832, 95%CI 0.769–0.896, LR−0.29, LR+3.845, p < 0.001). Serum sST2 and NT‐proBNP concentrations during second and early‐third trimester were associated with the occurrence of PE in twin pregnancies.

Screening for preeclampsia in twin pregnancies

Twin pregnancies are an important risk factor for preeclampsia, a hypertensive disorder of pregnancy that is associated with a significant risk of maternal and perinatal morbidity. Given the burden of preeclampsia, the identification of women at high risk in early pregnancy is essential to allow for preventive strategies and close monitoring. In singleton pregnancies, the risk factors for preeclampsia are well established, and a combined first-trimester prediction model has been shown to adequately predict preterm disease. Furthermore, intervention with low-dose aspirin at 150 mg/day in those identified as high-risk reduces the rate of preterm preeclampsia by 62%. In contrast, risk factors for preeclampsia in twin pregnancies are less established, the proposed screening models have shown poor performance with high false-positive rates, and the benefit of aspirin for the prevention of preeclampsia is not clearly demonstrated. In this review, we examine the literature assessing prediction and prevention of preeclampsia in twin pregnancies.

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.

Prediction of pre-eclampsia in twin pregnancy by maternal factors and biomarkers at 11-13 weeks' gestation: data from EVENTS trial

OBJECTIVES

First, to validate a previously developed model for screening for pre-eclampsia (PE) by maternal characteristics and medical history in twin pregnancies; second, to compare the distributions of mean arterial pressure (MAP), uterine artery pulsatility index (UtA-PI), serum placental growth factor (PlGF) and serum pregnancy-associated plasma protein-A (PAPP-A) in twin pregnancies that delivered with PE to those in singleton pregnancies and to develop new models based on these results; and, third, to examine the predictive performance of these models in screening for PE with delivery at < 32 and < 37 weeks' gestation.

METHODS

Two datasets of prospective non-intervention multicenter screening studies for PE in twin pregnancies at 11 + 0 to 13 + 6 weeks' gestation were used. The first dataset was from the EVENTS (Early vaginal progesterone for the preVention of spontaneous prEterm birth iN TwinS) trial and the second was from a previously reported study that examined the distributions of biomarkers in twin pregnancies. Maternal demographic characteristics and medical history from the EVENTS-trial dataset were used to assess the validity of risks from our previously developed model. The combined data from the first and second datasets were used to compare the distributional properties of log₁₀ multiples of the median (MoM) values of UtA-PI, MAP, PlGF and PAPP-A in twin pregnancies that delivered with PE to those in singleton pregnancies and develop new models based on these results. The competing-risks model was used to estimate the individual patient-specific risks of delivery with PE at < 32 and < 37 weeks' gestation. Screening performance was measured by detection rates (DR) and areas under the receiver-operating-characteristics curve.

RESULTS

The EVENTS-trial dataset comprised 1798 pregnancies, including 168 (9.3%) that developed PE. In the validation of the prior model based on maternal characteristics and medical history, calibration plots demonstrated very good agreement between the predicted risks and the observed incidence of PE (calibration slope and intercept for PE < 32 weeks were 0.827 and 0.009, respectively, and for PE < 37 weeks they were 0.942 and -0.207, respectively). In the combined data, there were 3938 pregnancies, including 339 (8.6%) that developed PE and 253 (6.4%) that delivered with PE at < 37 weeks' gestation. In twin pregnancies that delivered with PE, MAP, UtA-PI and PlGF were, at earlier gestational ages, more discriminative than in singleton pregnancies and at later gestational ages they were less so. For PAPP-A, there was little difference between PE and unaffected pregnancies. The best performance of screening for PE was achieved by a combination of maternal factors, MAP, UtA-PI and PlGF. In screening by maternal factors alone, the DR, at a 10% false-positive rate, was 30.6% for delivery with PE at < 32 weeks' gestation and this increased to 86.4% when screening by the combined test; the respective values for PE < 37 weeks were 24.9% and 41.1%.

CONCLUSIONS

In the assessment of risk for PE in twin pregnancy, we can use the same prior model based on maternal characteristics and medical history as reported previously, but in the calculation of posterior risks it is necessary to use the new distributions of log₁₀ MoM values of UtA-PI, MAP and PlGF according to gestational age at delivery with PE. © 2020 International Society of Ultrasound in Obstetrics and Gynecology.

PLACENTAL HEMODYNAMIC ASSESSMENT IN WOMEN WITH SEVERE PREECLAMPSIA IN SECOND- AND THIRD-TRIMESTER PREGNANCY BY 3D POWER QUANTITATIVE DOPPLER ULTRASOUND

Objective: The present study analyzed the fetal–placental hemodynamic parameters in women with severe preeclampsia in second- and third-trimester pregnancy with a view to developing effective predictive indicators for preeclampsia and providing support for the prenatal clinical treatment of preeclampsia. Materials and Methods: From January 2015 to January 2019, 160 pregnant women diagnosed with severe preeclampsia at Xiangyang First People’s Hospital were recruited as the study group. The diagnostic criteria for preeclampsia were in accordance with the guidelines of the International Society for the Study of Hypertension in Pregnancy (ISSHP). A sample of 160 healthy pregnant women with normal blood pressure were selected as the control group. The GE Voluson E8 and E10 four-dimensional (4D) ultrasonic diagnostic instruments and the three-dimensional (3D) power Doppler in angio-quantitative mode were used to measure the hemodynamic parameters of the placenta, left uterine artery (LUA), right uterine artery (RUA), middle cerebral artery (MCA), umbilical artery (UA), and ductus venosus (DV) in the two groups. The above parameters were analyzed statistically using SPSS 22.0. Results: The systolic/diastolic velocity ratio (S/D), pulsatility index (PI), and resistance index (RI) of the MCA in the study group were lower than those of normal subjects of the same gestational age (P < 0.05). These parameters in the UA were higher in the study group than those in normal subjects (P < 0.05). The ratios between the peak ventricular systolic velocity and the peak atrial systolic velocity (S/A), pulsatility index for the vein (PIV), pre-load index (PLI), and peak velocity index for the vein (PVIV) in the DV were significantly different between the study and normal groups (P < 0.05). The placental vascularization index (VI), flow index (FI), and vascularization flow index (VFI) were lower in the study group than those in normal subjects of the same gestational age (P < 0.05). There were good correlations between VI, VFI and RUA, PI, with correlation coefficients of −0.697 and −0.702, respectively. FI was the indicator that had the highest diagnostic efficacy for severe preeclampsia. The predictive sensitivity of the FI with a cut-off value of 34.92 was 96.3%, and the corresponding specificity was 86.9%. Conclusions: Placental FI had the highest predictive efficacy for severe preeclampsia and provides a reliable quantitative indicator and data support for preeclampsia management. 3D power quantitative Doppler ultrasound provides a novel avenue for the study of severe preeclampsia.

The competing risk approach for prediction of preeclampsia

The established method of the assessment of the risk for development of preeclampsia is to identify risk factors from maternal demographic characteristics and medical history; in the presence of such factors, the patient is classified as high risk and in their absence as low risk. Although this approach is simple to perform, it has poor performance of the prediction of preeclampsia and does not provide patient-specific risks. This review describes a new approach that allows the estimation of patient-specific risks of delivery with preeclampsia before any specified gestational age by maternal demographic characteristics and medical history with biomarkers obtained either individually or in combination at any stage in pregnancy. In the competing risks approach, every woman has a personalized distribution of gestational age at delivery with preeclampsia; whether she experiences preeclampsia or not before a specified gestational age depends on competition between delivery before or after the development of preeclampsia. The personalized distribution comes from the application of Bayes theorem to combine a previous distribution, which is determined from maternal factors, with likelihoods from biomarkers. As new data become available, what were posterior probabilities take the role as the previous probability, and data collected at different stages are combined by repeating the application of Bayes theorem to form a new posterior at each stage, which allows for dynamic prediction of preeclampsia. The competing risk model can be used for precision medicine and risk stratification at different stages of pregnancy. In the first trimester, the model has been applied to identify a high-risk group that would benefit from preventative therapeutic interventions. In the second trimester, the model has been used to stratify the population into high-, intermediate-, and low-risk groups in need of different intensities of subsequent monitoring, thereby minimizing unexpected adverse perinatal events. The competing risks model can also be used in surveillance of women presenting to specialist clinics with signs or symptoms of hypertensive disorders; combination of maternal factors and biomarkers provide patient-specific risks for preeclampsia that lead to personalized stratification of the intensity of monitoring, with risks updated on each visit on the basis of biomarker measurements.

Systematic review of prediction models for gestational hypertension and preeclampsia

INTRODUCTION

Prediction models for gestational hypertension and preeclampsia have been developed with data and assumptions from developed countries. Their suitability and application for low resource settings have not been tested. This review aimed to identify and assess the methodological quality of prediction models for gestational hypertension and pre-eclampsia with reference to their application in low resource settings.

METHODS

Using combinations of keywords for gestational hypertension, preeclampsia and prediction models seven databases were searched to identify prediction models developed with maternal data obtained before 20 weeks of pregnancy and including at least three predictors (Prospero registration CRD 42017078786). Prediction model characteristics and performance measures were extracted using the CHARMS, STROBE and TRIPOD checklists. The National Institute of Health quality assessment tools for observational cohort and cross-sectional studies were used for study quality appraisal.

RESULTS

We retrieved 8,309 articles out of which 40 articles were eligible for review. Seventy-seven percent of all the prediction models combined biomarkers with maternal clinical characteristics. Biomarkers used as predictors in most models were pregnancy associated plasma protein-A (PAPP-A) and placental growth factor (PlGF). Only five studies were conducted in a low-and middle income country.

CONCLUSIONS

Most of the studies evaluated did not completely follow the CHARMS, TRIPOD and STROBE guidelines in prediction model development and reporting. Adherence to these guidelines will improve prediction modelling studies and subsequent application of prediction models in clinical practice. Prediction models using maternal characteristics, with good discrimination and calibration, should be externally validated for use in low and middle income countries where biomarker assays are not routinely available.

Early prediction of preeclampsia via machine learning

BACKGROUND

Early prediction of preeclampsia is challenging because of poorly understood causes, various risk factors, and likely multiple pathogenic phenotypes of preeclampsia. Statistical learning methods are well-equipped to deal with a large number of variables, such as patients' clinical and laboratory data, and to select the most informative features automatically.

OBJECTIVE

Our objective was to use statistical learning methods to analyze all available clinical and laboratory data that were obtained during routine prenatal visits in early pregnancy and to use them to develop a prediction model for preeclampsia.

STUDY DESIGN

This was a retrospective cohort study that used data from 16,370 births at Lucile Packard Children Hospital at Stanford, CA, from April 2014 to January 2018. Two statistical learning algorithms were used to build a predictive model: (1) elastic net and (2) gradient boosting algorithm. Models for all preeclampsia and early-onset preeclampsia (<34 weeks gestation) were fitted with the use of patient data that were available at <16 weeks gestational age. The 67 variables that were considered in the models included maternal characteristics, medical history, routine prenatal laboratory results, and medication intake. The area under the receiver operator curve, true-positive rate, and false-positive rate were assessed via cross-validation.

RESULTS

Using the elastic net algorithm, we developed a prediction model that contained a subset of the most informative features from all variables. The obtained prediction model for preeclampsia yielded an area under the curve of 0.79 (95% confidence interval, 0.75-0.83), sensitivity of 45.2%, and false-positive rate of 8.1%. The prediction model for early-onset preeclampsia achieved an area under the curve of 0.89 (95% confidence interval, 0.84-0.95), true-positive rate of 72.3%, and false-positive rate of 8.8%.

CONCLUSION

Statistical learning methods in a retrospective cohort study automatically identified a set of significant features for prediction and yielded high prediction performance for preeclampsia risk from routine early pregnancy information.

Impact of new definitions of pre-eclampsia on incidence and performance of first-trimester screening

OBJECTIVE

The traditional definition of pre-eclampsia (PE) is based on the development of hypertension and proteinuria. This has been revised recently to include cases without proteinuria but with evidence of renal, hepatic or hematological dysfunction. The aim of this study was to examine the impact of new definitions of PE on, first, the incidence and severity of the disease and, second, the performance of the competing-risks model for first-trimester assessment of risk for PE.

METHODS

This was a retrospective study of 66 964 singleton pregnancies that were classified as having PE, gestational hypertension (GH) or no PE or GH, according to the traditional criteria of the International Society for the Study of Hypertension in Pregnancy (ISSHP-old), which defines PE as the presence of both hypertension and proteinuria. We reviewed the records of pregnancies with GH, and those cases with high creatinine or liver enzymes or low platelet count were reclassified as having PE, according to the new criteria of ISSHP (ISSHP-new) and the new criteria of the American College of Obstetricians and Gynecologists (ACOG). The groups of PE according to the traditional and new criteria were compared for, first, gestational age at delivery, birth-weight percentile and incidence of a small-for-gestational-age (SGA) neonate with birth weight < 10^th percentile and perinatal death, and, second, the predictive performance for preterm PE of the competing-risks model based on the combination of maternal risk factors, uterine artery pulsatility index, mean arterial pressure and serum placental growth factor at 11-13 weeks' gestation (triple test).

RESULTS

According to ISSHP-old, 1870 (2.8%) cases had PE, 2182 (3.3%) had GH and 62 912 (94.0%) had no PE or GH. The incidence of PE according to ACOG was 3.0% (2029/66 964) and ISSHP-new was 3.4% (2301/66 964). Median gestational age at delivery in the extra cases of PE according to ACOG (difference, 1.3 weeks; 95% CI, 0.71-1.71 weeks) and in the extra cases of PE according to ISSHP-new (difference, 1.5 weeks; 95% CI, 1.29-1.71 weeks) was higher than in cases with PE according to ISSHP-old (38.4 weeks). The incidence of a SGA neonate in the extra cases of PE according to ACOG (relative risk, 0.57; 95% CI, 0.42-0.79) and in the extra cases of PE according to ISSHP-new (relative risk, 0.52; 95% CI, 0.42-0.65) was lower than in the cases of PE according to ISSHP-old (33.64%). In first-trimester screening for preterm PE by the triple test, the detection rate, at a 10% false-positive rate, was 75.9% (95% CI, 70.8-80.6%) for ISSHP-old, 74.3% (95% CI, 69.2-79.0%) for ACOG and 74.0% (95% CI, 68.9-78.6%) for ISSHP-new.

CONCLUSIONS

The new definitions of PE resulted in, first, an increase in pregnancies classified as having PE but the additional cases had milder disease, and, second, a non-significant decrease in the performance of first-trimester screening for PE. © 2019 The Authors. Ultrasound in Obstetrics & Gynecology published by John Wiley & Sons Ltd on behalf of the International Society of Ultrasound in Obstetrics and Gynecology.