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A Model for Preconceptional Prediction of Recurrent Early-Onset Preeclampsia: Derivation and Internal Validation

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Abstract

Objective

To develop a model to identify women at very low risk of recurrent early-onset preeclampsia.

Methods

We enrolled 407 women who had experienced early-onset preeclampsia in their first pregnancy, resulting in a delivery before 34 weeks’ gestation. Preeclampsia was defined as hypertension (systolic blood pressure ≥140 mm Hg and/or diastolic blood pressure ≥90 mm Hg) after 20 weeks’ gestation with de novo proteinuria (≥300 mg urinary protein excretion/day). Based on the previous published evidence and expert opinion, 5 predictors (gestational age at previous birth, prior small-for-gestational-age newborn, fasting blood glucose, body mass index, and hypertension) were entered in a logistic regression model. Discrimination and calibration were evaluated after adjusting for overfitting by bootstrapping techniques.

Results

Early-onset disease recurred in 28 (6.9%) of 407 women. The area under the receiver operating characteristic (ROC) curve of the model was 0.65 (95% CI: 0.56-0.74). Calibration was good, indicated by a nonsignificant Hosmer-Lemeshow test (P = .11). Using a predicted absolute risk threshold of, for example, 4.6% (ie, women identified with an estimated risk either above or below 4.6%), the sensitivity was 100%, with a specificity of 26%. In such a strategy, no women who developed preeclampsia were missed, while 98 of the 407 women would be regarded as low risk of recurrent early-onset preeclampsia, not necessarily requiring intensified antenatal care.

Conclusion

Our model may be helpful in the identification of women at very low risk of recurrent early-onset preeclampsia. Before widespread application, our model should be validated in other populations.

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Authors and Affiliations

  1. Department of Obstetrics and Gynecology, Maastricht University Medical Center, Maastricht, Netherlands

    Sander M. J. van Kuijk MSc, Simone J. S. Sep PhD, Louis L. Peeters MD, PhD, Denise H. J. Delahaije MSc, Marc Spaanderman MD, PhD & Josje Langenveld MD

  2. Department of Epidemiology, Maastricht University, PO Box 616, 6200 MD, Maastricht, Netherlands

    Sander M. J. van Kuijk MSc & Luc Smits PhD

  3. Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht, Netherlands

    Marie-Elise Nijdam MD, Kristel J. M. Janssen PhD & Michiel L. Bots MD, PhD

  4. Department of Clinical Epidemiology and Medical Technology Assessment, Maastricht University Medical Center, Maastricht, Netherlands

    Denise H. J. Delahaije MSc

  5. Department of Obstetrics and Gynecology, University Medical Center Utrecht, Utrecht, Netherlands

    Hein W. Bruinse MD, PhD, Arie Franx MD, PhD & Bas B. van Rijn MD, PhD

  6. Department of Obstetrics and Gynecology, Academic Medical Center, Amsterdam, Netherlands

    Joris van der Post MD, PhD

  7. Department of Obstetrics and Gynecology, St. Antonius Hospital, Nieuwegein, Netherlands

    Bas B. van Rijn MD, PhD

Authors
  1. Sander M. J. van Kuijk MSc
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  2. Marie-Elise Nijdam MD
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  3. Kristel J. M. Janssen PhD
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  4. Simone J. S. Sep PhD
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  5. Louis L. Peeters MD, PhD
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  6. Denise H. J. Delahaije MSc
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  7. Marc Spaanderman MD, PhD
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  8. Hein W. Bruinse MD, PhD
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  9. Arie Franx MD, PhD
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  10. Michiel L. Bots MD, PhD
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  11. Josje Langenveld MD
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  12. Joris van der Post MD, PhD
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  13. Bas B. van Rijn MD, PhD
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  14. Luc Smits PhD
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Corresponding author

Correspondence to Sander M. J. van Kuijk MSc.

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van Kuijk, S.M.J., Nijdam, ME., Janssen, K.J.M. et al. A Model for Preconceptional Prediction of Recurrent Early-Onset Preeclampsia: Derivation and Internal Validation. Reprod. Sci. 18, 1154–1159 (2011). https://doi.org/10.1177/1933719111410708

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  • DOI: https://doi.org/10.1177/1933719111410708

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