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

Abstract

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.

Implementing a Preeclampsia Prediction Model in Obstetrics: Cutoff Determination and Health Care Professionals’ Adherence

“…The addition of these predictors mainly reduces the false-positive rate. 8 However, LDA prophylaxis from 12 weeks of gestation is inexpensive and does not result in adverse fetal effects, which reduces the disadvantages of a high false-positive rate. As a result, it is arguable whether the costs associated with these additional predictors are proportional to their benefits.…”

“…14,15 For women at risk of PE, additional risk-based care includes the recommendation of LDA prophylaxis (80-100 mg) from 12 to 36 weeks of pregnancy. The LOC agreed to use the prediction model of Syngelaki et al, 16 externally validated and recalibrated for their specific region by Meertens et al 8 This model was selected because it was the model with the highest discriminative performance, and its predictors are routinely collected in Dutch obstetric practice. Predictors included in the prediction model are age, body mass index, ethnicity, parity, assisted conception treatment, smoking during pregnancy, family history of PE, and medical history (regarding chronic hypertension, PE, and diabetes mellitus).…”

“…Data of the external validation study were used to calculate these test characteristics per risk-threshold. 8 Health care professionals were asked to answer the statement ''I agree using this cutoff value as threshold determining an elevated PE risk,'' using a 10-point Likert scale (1 = totally disagree to 10 = fully agree).…”

“…7 Multivariable prediction models estimating the risk of PE weigh several risk factors simultaneously and can assist health care professionals in identifying women with increased risk. The results of a recent study comparing several PE prediction models simultaneously in 1 cohort 8 indicated that some of these models are more efficient compared to a list of single risk factors. For a prediction model to serve as a decision tool, a cutoff has to be determined for the discrimination of low and increased risk.…”

Clinical risk assessment in early pregnancy for preeclampsia in nulliparous women: A population based cohort study

“…More complex FMF models include various combinations of biophysical, such as uterine artery Doppler, and biochemical markers, not routinely performed in antenatal care [10]. Since detection rates and cut-off values have shown to vary between populations, depending on differences in healthcare systems, incidence of disease and overfitting of the original model, the performance of these models have to be validated in other populations [16–19]. It has been emphasized that the cost-effectiveness of these more complex models has to be established before widespread use in clinical practice [14, 20].…”