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Linear Regression of Postevacuation Serum Human Chorionic Gonadotropin Concentrations Predicts Postmolar Gestational Trophoblastic Neoplasia
  1. Charlotte Lybol, MD, PhD*,,
  2. Fred C. G. J. Sweep, PhD,
  3. Petronella B. Ottevanger, MD, PhD,
  4. Leon F. A. G. Massuger, MD, PhD* and
  5. Chris M. G. Thomas, PhD
  1. *Department of Obstetrics and Gynaecology,
  2. Department of Laboratory Medicine, and
  3. Department of Medical Oncology, Radboud University Nijmegen Medical Centre, Nijmegen, the Netherlands.
  1. Address correspondence and reprint requests to Charlotte Lybol, MD, Department of Obstetrics and Gynaecology, Radboud University Nijmegen Medical Centre, PO Box 9101, 6500 HB Nijmegen, the Netherlands. E-mail: C.Lybol@obgyn.umcn.nl.

Abstract

Objective Currently, human chorionic gonadotropin (hCG) follow-up after evacuation of hydatidiform moles is essential to identify patients requiring chemotherapeutic treatment for gestational trophoblastic neoplasia (GTN). We propose a model based on linear regression of postevacuation serum hCG concentrations for the prediction of GTN.

Methods One hundred thirteen patients with at least 3 serum samples from days 7 to 28 after evacuation were selected from the Dutch Central Registry for Hydatidiform Moles (1994–2009). The slopes of the linear regression lines of the first 3 log-transformed serum hCG and free β-hCG values were calculated. Receiver operating characteristic curves were constructed to calculate areas under curve (AUCs).

Results The slope of the hCG regression line showed an AUC of 0.906 (95% confidence interval, 0.845–0.967). Gestational trophoblastic neoplasia could be predicted in 52% of patients with GTN at 97.5% specificity (cutoff, −0.020). Twenty-one percent of patients with GTN could be predicted before diagnosis according to the International Federation of Gynecology and Obstetrics 2000 criteria. The slope of free β-hCG showed an AUC of 0.844 (95% confidence interval, 0.752–0.935), 69% sensitivity at 97.5% specificity, and 38% of patients with GTN could be predicted before diagnosis according to the International Federation of Gynecology and Obstetrics criteria.

Conclusions The slope of the linear regression line of hCG proved to be a good test to discriminate between patients who will achieve spontaneous disease remission and patients developing GTN. The slope of free β-hCG seems to be a better predictor for GTN than the slope of hCG. Although this model needs further validation for different assays, it seems a promising way to predict the more aggressive cases of GTN.

  • Gestational trophoblastic disease
  • Prediction model
  • Hydatidiform mole
  • hCG
  • Gestational trophoblastic neoplasia

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Footnotes

  • The authors declare no conflicts of interest.