The performance of risk prediction models for pre-eclampsia using routinely collected maternal characteristics and comparison with models that include specialised tests and with clinical guideline decision rules: a systematic review

External validation of prognostic models for preeclampsia in a Dutch multicenter prospective cohort

OBJECTIVE

To perform an external validation of all published prognostic models for first-trimester prediction of the risk of developing preeclampsia (PE).

METHODS

Women <14 weeks of pregnancy were recruited in the Netherlands. All systematically identified prognostic models for PE that contained predictors commonly available were eligible for external validation.

RESULTS

3,736 women were included; 87 (2.3%) developed PE. Calibration was poor due to overestimation. Discrimination of 9 models for LO-PE ranged from 0.58 to 0.71 and of 9 models for all PE from 0.55 to 0.75.

CONCLUSION

Only a few easily applicable prognostic models for all PE showed discrimination above 0.70, which is considered an acceptable performance.

Maternity Log study: a longitudinal lifelog monitoring and multiomics analysis for the early prediction of complicated pregnancy

PURPOSE

A prospective cohort study for pregnant women, the Maternity Log study, was designed to construct a time-course high-resolution reference catalogue of bioinformatic data in pregnancy and explore the associations between genomic and environmental factors and the onset of pregnancy complications, such as hypertensive disorders of pregnancy, gestational diabetes mellitus and preterm labour, using continuous lifestyle monitoring combined with multiomics data on the genome, transcriptome, proteome, metabolome and microbiome.

PARTICIPANTS

Pregnant women were recruited at the timing of first routine antenatal visits at Tohoku University Hospital, Sendai, Japan, between September 2015 and November 2016. Of the eligible women who were invited, 65.4% agreed to participate, and a total of 302 women were enrolled. The inclusion criteria were age ≥20 years and the ability to access the internet using a smartphone in the Japanese language.

FINDINGS TO DATE

Study participants uploaded daily general health information including quality of sleep, condition of bowel movements and the presence of nausea, pain and uterine contractions. Participants also collected physiological data, such as body weight, blood pressure, heart rate and body temperature, using multiple home healthcare devices. The mean upload rate for each lifelog item was ranging from 67.4% (fetal movement) to 85.3% (physical activity), and the total number of data points was over 6 million. Biospecimens, including maternal plasma, serum, urine, saliva, dental plaque and cord blood, were collected for multiomics analysis.

FUTURE PLANS

Lifelog and multiomics data will be used to construct a time-course high-resolution reference catalogue of pregnancy. The reference catalogue will allow us to discover relationships among multidimensional phenotypes and novel risk markers in pregnancy for the future personalised early prediction of pregnancy complications.

External validation and clinical usefulness of first-trimester prediction models for small- and large-for-gestational-age infants: a prospective cohort study

Objective

To assess the external validity of all published first‐trimester prediction models based on routinely collected maternal predictors for the risk of small‐ and large‐for‐gestational‐age (SGA and LGA) infants. Furthermore, the clinical potential of the best‐performing models was evaluated.

Design

Multicentre prospective cohort.

Setting

Thirty‐six midwifery practices and six hospitals (in the Netherlands).

Population

Pregnant women were recruited at <16 weeks of gestation between 1 July 2013 and 31 December 2015.

Methods

Prediction models were systematically selected from the literature. Information on predictors was obtained by a web‐based questionnaire. Birthweight centiles were corrected for gestational age, parity, fetal sex, and ethnicity.

Main outcome measures

Predictive performance was assessed by means of discrimination (C‐statistic) and calibration.

Results

The validation cohort consisted of 2582 pregnant women. The outcomes of SGA <10th percentile and LGA >90th percentile occurred in 203 and 224 women, respectively. The C‐statistics of the included models ranged from 0.52 to 0.64 for SGA (n = 6), and from 0.60 to 0.69 for LGA (n = 6). All models yielded higher C‐statistics for more severe cases of SGA (<5th percentile) and LGA (>95th percentile). Initial calibration showed poor‐to‐moderate agreement between the predicted probabilities and the observed outcomes, but this improved substantially after recalibration.

Conclusion

The clinical relevance of the models is limited because of their moderate predictive performance, and because the definitions of SGA and LGA do not exclude constitutionally small or large infants. As most clinically relevant fetal growth deviations are related to ‘vascular’ or ‘metabolic’ factors, models predicting hypertensive disorders and gestational diabetes are likely to be more specific.

Tweetable abstract

The clinical relevance of prediction models for the risk of small‐ and large‐for‐gestational‐age is limited.

The clinical relevance of prediction models for the risk of small‐ and large‐for‐gestational‐age is limited.

Discriminatory Accuracy of Preeclampsia Risk Factors in Primary Care

BACKGROUND

Although it is common to use risk factors in the screening for preeclampsia, they do not always accurately identify patients who truly have this condition.

AIM OF THE STUDY

To determine the discriminatory accuracy of known preeclampsia risk factors, both individually and in combination.

METHODS

We studied patients undergoing prenatal care who were diagnosed with preeclampsia or eclampsia (n = 160 cases) in primary care and those who were not (n = 430 controls). Data on history of preeclampsia, type 2 diabetes, chronic hypertension, multiple gestation, first pregnancy, pregnancy interval ≥10 years, overweight/obesity, mean arterial pressure (MAP) ≥80 mmHg, and age (<20 years and ≥40 years) were obtained using a dichotomous scale. Discriminatory accuracy indicators were true-positive (TP) and false-positive (FP) rates, positive and negative likelihood ratios (LR+ and LR-), diagnostic odds ratio (DOR), and the area under the receiver-operating characteristic (AUROC) curve; stratified by parity. The case-control status was the reference standard.

RESULTS

Certain combinations performed better than individual factors, independent of parity status. Among multiparous women, MAP ≥80 mmHg together with previous preeclampsia and overweight/obesity accumulated the greatest number of discriminatory accuracy indicators, with acceptable values: TP, 72.2%; FP, 1.5%; LR+, 48.4; LR-, 0.3; DOR, 171.6; and AUROC, 0.85.

CONCLUSIONS

Discriminatory accuracy was low for almost all individual preeclampsia risk factors. However, the accuracy improved after some factors were combined. To the best of our knowledge, this is the first study to examine the discriminatory accuracy of preeclampsia risk factors used for screening high-risk pregnancies in primary care in Mexico.

External Validation and Clinical Usefulness of First Trimester Prediction Models for the Risk of Preeclampsia: A Prospective Cohort Study

INTRODUCTION

This study assessed the external validity of all published first trimester prediction models for the risk of preeclampsia (PE) based on routinely collected maternal predictors. Moreover, the potential utility of the best-performing models in clinical practice was evaluated.

MATERIAL AND METHODS

Ten prediction models were systematically selected from the literature. We performed a multicenter prospective cohort study in the Netherlands between July 1, 2013, and December 31, 2015. Eligible pregnant women completed a web-based questionnaire before 16 weeks' gestation. The outcome PE was established using postpartum questionnaires and medical records. Predictive performance of each model was assessed by means of discrimination (c-statistic) and a calibration plot. Clinical usefulness was evaluated by means of decision curve analysis and by calculating the potential impact at different risk thresholds.

RESULTS

The validation cohort contained 2,614 women of whom 76 developed PE (2.9%). Five models showed moderate discriminative performance with c-statistics ranging from 0.73 to 0.77. Adequate calibration was obtained after refitting. The best models were clinically useful over a small range of predicted probabilities.

DISCUSSION

Five of the ten included first trimester prediction models for PE showed moderate predictive performance. The best models may provide more benefit compared to risk selection as used in current guidelines.

Recent advances in the diagnosis and management of pre-eclampsia

Pre-eclampsia is a leading cause of maternal mortality, responsible annually for over 60,000 maternal deaths around the globe. Pre-eclampsia is a multisystem disease featuring hypertension, proteinuria, and renal, hepatic, and neurological involvement. Diagnosis is often elusive, as clinical presentation is highly variable. Even those with severe disease can remain asymptomatic. Angiogenic factors are emerging as having a role in the diagnosis of pre-eclampsia and in prognostication of established disease. In this article, we summarize new developments and focus on angiogenic biomarkers for prediction of disease onset. We also discuss recent advances in management strategies for patients with hypertensive disorders of pregnancy.

Prediction and prevention of pre-eclampsia in Asian subpopulation

The benefit of the early administration of aspirin to reduce preterm pre-eclampsia among screened positive European women from multivariate algorithmic approach (ASPRE trial) has opened an intense debate on the feasibility of universal screening. This review aims to assess the new perspectives in the combined screening of pre-eclampsia in the first trimester of pregnancy and the chances for prevention using low-dose aspirin with special emphasis on the particularities of the Asian population. PubMed, CENTRAL and Embase databases were searched from inception until 15 November 2017 using combinations of the search terms: preeclampsia, Asian, prenatal screening, early prediction, ultrasonography, pregnancy, biomarker, mean arterial pressure, soluble fms-like tyrosine kinase-1, placental growth factor, pregnancy-associated plasma protein-A and pulsatility index. This is not a systematic review or meta-analysis, so the risk of bias of the selected published articles and heterogeneity among the studies need to be considered. The prevalence of pre-eclampsia and serum levels of biochemical markers in Asian are different from Caucasian women; hence, Asian ethnicity needs to be corrected for in the algorithmic assessment of multiple variables to improve the screening performance. Aspirin prophylaxis may still be viable in Asian women, but resource implication needs to be considered. Asian ethnicity should be taken into account before implementing pre-eclampsia screening strategies in the region. The variables included can be mixed and matched to achieve an optimal performance that is appropriate for economical restriction in individual countries.

Prediction of adverse maternal outcomes from pre-eclampsia and other hypertensive disorders of pregnancy: A systematic review

BACKGROUND

The hypertensive disorders of pregnancy are a leading cause of maternal and perinatal mortality and morbidity. The ability to predict these complications using simple tests could aid in management and improve outcomes. We aimed to systematically review studies that reported on potential predictors of adverse maternal outcomes among women with a hypertensive disorder of pregnancy.

METHODS

We searched MEDLINE, Embase and CINAHL (inception - December 2016) for studies of predictors of severe maternal complications among women with a hypertensive disorder of pregnancy. Studies were selected in a two-stage process by two independent reviewers, excluding those reporting only on adverse fetal outcomes. We extracted data on study and test(s) characteristics and outcomes. Accuracy of prediction was assessed using sensitivity, specificity, likelihood ratios and area under the receiver operating curve (AUROC). Strong evidence of prediction was taken to be a positive likelihood ratio >10 or a negative likelihood ratio <0.1, and for multivariable models, an AUROC ≥0.70. Bivariate random effects models were used to summarise performance when possible.

RESULTS

Of 32 studies included, 28 presented only model development and four examined external validation. Tests included symptoms and signs, laboratory tests and biomarkers. No single test was a strong independent predictor of outcome. The most promising prediction was with multivariable models, especially when oxygen saturation, or chest pain/dyspnea were included.

CONCLUSION

Future studies should investigate combinations of tests in multivariable models (rather than single predictors) to improve identification of women at high risk of adverse outcomes in the setting of the hypertensive disorders of pregnancy.

Simple approach based on maternal characteristics and mean arterial pressure for the prediction of preeclampsia in the first trimester of pregnancy

AIM

To propose a simple model for predicting preeclampsia (PE) in the 1st trimester of pregnancy on the basis of maternal characteristics (MC) and mean arterial pressure (MAP).

METHODS

A prospective cohort was performed to predict PE between 11 and 13+6 weeks of gestation. The MC evaluated were maternal age, skin color, parity, previous PE, smoking, family history of PE, hypertension, diabetes mellitus and body mass index (BMI). Mean arterial blood pressure (MAP) was measured at the time of the 1st trimester ultrasound. The outcome measures were the incidences of total PE, preterm PE (delivery <37 weeks) and term PE (delivery ≥37 weeks). We performed logistic regression analysis to determine which factors made significant contributions for the prediction of the three outcomes.

RESULTS

We analyzed 733 pregnant women; 55 developed PE, 21 of those developed preterm PE and 34 term PE. For total PE, the best model was MC+MAP, which had an area under the receiver operating characteristic curve (AUC ROC) of 0.79 [95% confidence interval (CI)=0.76-0.82]. For preterm PE, the best model was MC+MAP, with an AUC ROC of 0.84 (95% CI=0.81-0.87). For term PE, the best model was MC, with an AUC ROC of 0.75 (0.72-0.79). The MC+MAP model demonstrated a detection rate of 67% cases of preterm PE, with a false-positive rate of 10%, positive predictive value of 17% and negative predictive value of 99%.

CONCLUSION

The MC+MAP model showed good accuracy in predicting preterm PE in the 1st trimester of gestation.

External Validation Study of First Trimester Obstetric Prediction Models (Expect Study I): Research Protocol and Population Characteristics

BACKGROUND

A number of first-trimester prediction models addressing important obstetric outcomes have been published. However, most models have not been externally validated. External validation is essential before implementing a prediction model in clinical practice.

OBJECTIVE

The objective of this paper is to describe the design of a study to externally validate existing first trimester obstetric prediction models, based upon maternal characteristics and standard measurements (eg, blood pressure), for the risk of pre-eclampsia (PE), gestational diabetes mellitus (GDM), spontaneous preterm birth (PTB), small-for-gestational-age (SGA) infants, and large-for-gestational-age (LGA) infants among Dutch pregnant women (Expect Study I). The results of a pilot study on the feasibility and acceptability of the recruitment process and the comprehensibility of the Pregnancy Questionnaire 1 are also reported.

METHODS

A multicenter prospective cohort study was performed in The Netherlands between July 1, 2013 and December 31, 2015. First trimester obstetric prediction models were systematically selected from the literature. Predictor variables were measured by the Web-based Pregnancy Questionnaire 1 and pregnancy outcomes were established using the Postpartum Questionnaire 1 and medical records. Information about maternal health-related quality of life, costs, and satisfaction with Dutch obstetric care was collected from a subsample of women. A pilot study was carried out before the official start of inclusion. External validity of the models will be evaluated by assessing discrimination and calibration.

RESULTS

Based on the pilot study, minor improvements were made to the recruitment process and online Pregnancy Questionnaire 1. The validation cohort consists of 2614 women. Data analysis of the external validation study is in progress.

CONCLUSIONS

This study will offer insight into the generalizability of existing, non-invasive first trimester prediction models for various obstetric outcomes in a Dutch obstetric population. An impact study for the evaluation of the best obstetric prediction models in the Dutch setting with respect to their effect on clinical outcomes, costs, and quality of life-Expect Study II-is being planned.

TRIAL REGISTRATION

Netherlands Trial Registry (NTR): NTR4143; http://www.trialregister.nl/trialreg/admin/rctview.asp?TC=4143 (Archived by WebCite at http://www.webcitation.org/6t8ijtpd9).

Performance of first trimester biochemical markers and mean arterial pressure in prediction of early-onset pre-eclampsia

OBJECTIVE

To develop a predictive risk model for early-onset pre-eclampsia (EO-PE) using maternal characteristics, combined screening markers, previously reported biomarkers for PE and mean arterial pressure (MAP).

METHODS

This retrospective study was conducted at Oulu University hospital between 2006 and 2010. Maternal serum from first trimester combined screening was further analyzed for alpha fetoprotein (AFP), placental growth factor (PlGF), soluble tumor necrosis factor receptor-1 (sTNFR1), retinol binding protein-4 (RBP4), a disintegrin and metalloprotease-12 (ADAM12), soluble P-selectin (sP-selectin), follistatin like-3 (FSTL3), adiponectin, angiopoietin-2 (Ang-2) and sex hormone binding globulin (SHBG). First, the training sample set with 29 cases of EO-PE and 652 controls was developed to study whether these biomarkers separately or in combination with prior risk (maternal characteristics, first trimester pregnancy associated plasma protein-A (PAPP-A) and free beta human chorionic gonadotrophin (fβ-hCG)) could be used to predict the development of EO-PE. Second, the developed risk models were validated with a test sample set of 42 EO-PE and 141 control subjects. For the test set MAP data was also available.

RESULTS

Single marker statistically significant (ANOVA p<0.05) changes between control and EO-PE pregnancies were observed with AFP, RBP4 and sTNFR1 with both training and test sample sets. Based on the test sample set performances, the best detection rate, 47% for a 10% false positive rate, was achieved with PlGF and sTNFR1 added with prior risk and MAP.

CONCLUSION

Based on our results, the best first trimester biomarkers to predict the subsequent EO-PE were AFP, PlGF, RBP4 and sTNFR1. The risk models that performed best for the prediction of EO-PE included prior risk, MAP, sTNFR1 and AFP or PlGF or RBP4.

A simple clinical method to identify women at higher risk of preeclampsia

An outstanding issue is how to efficiently identify women at high risk of preeclampsia. This retrospective cohort study included 8672 pregnancies at a single centre in Toronto. We tested our simple method - presence vs. absence of≥1 major (pre-pregnancy BMI>30kg/m², chronic hypertension, pre-pregnancy diabetes mellitus and assisted reproductive therapy) or≥2 minor (prior stillbirth, age>40years, nulliparity, multifetal pregnancy, chronic kidney disease, and SLE) risk factors for PE. The RR of PE was 8.4 (95% CI 5.3-13.2) and the model C-statistic 0.74 (95% CI 0.69-0.79). Further testing of this method elsewhere is warranted.

Estimated reductions in provider-initiated preterm births and hospital length of stay under a universal acetylsalicylic acid prophylaxis strategy: a retrospective cohort study

BACKGROUND

Hypertensive disorders, especially preeclampsia, are the leading reason for provider-initiated preterm birth. We estimated how universal acetylsalicylic acid (ASA) prophylaxis might reduce rates of provider-initiated preterm birth associated with preeclampsia and intrauterine growth restriction, which are related conditions.

METHODS

We performed a cohort study of singleton hospital births in 2013 in Canada, excluding Quebec. We estimated the proportion of term births and provider-initiated preterm births affected by preeclampsia and/or intrauterine growth restriction, and the corresponding mean maternal and newborn hospital length of stay. We projected the potential number of cases reduced and corresponding hospital length of stay if ASA prophylaxis lowered cases of preeclampsia and intrauterine growth restriction by a relative risk reduction (RRR) of 10% (lowest) or 53% (highest), as suggested by randomized clinical trials.

RESULTS

Of the 269 303 singleton live births and stillbirths in our cohort, 4495 (1.7%) were provider-initiated preterm births. Of the 4495, 1512 (33.6%) had a diagnosis of preeclampsia and/or intrauterine growth restriction. The mean maternal length of stay was 2.0 (95% confidence interval [CI] 2.0-2.0) days among term births unaffected by either condition and 7.3 (95% CI 6.1-8.6) days among provider-initiated preterm births with both conditions. The corresponding values for mean newborn length of stay were 1.9 (95% CI 1.8-1.9) days and 21.8 (95% CI 17.4-26.2) days. If ASA conferred a 53% RRR against preeclampsia and/or intrauterine growth restriction, 3365 maternal and 11 591 newborn days in hospital would be averted. If ASA conferred a 10% RRR, 635 maternal and 2187 newborn days in hospital would be averted.

INTERPRETATION

A universal ASA prophylaxis strategy could substantially reduce the burden of long maternal and newborn hospital stays associated with provider-initiated preterm birth. However, until there is compelling evidence that administration of ASA to all, or most, pregnant women reduces the risk of preeclampsia and/or intrauterine growth restriction, clinicians should continue to follow current clinical practice guidelines.