Predicting personalized multiple birth risks after in vitro fertilization-double embryo transfer

Fertil Steril. 2012 Jul;98(1):69-76. doi: 10.1016/j.fertnstert.2012.04.011. Epub 2012 Jun 4.


Objective: To report and evaluate the performance and utility of an approach to predicting IVF-double embryo transfer (DET) multiple birth risks that is evidence-based, clinic-specific, and considers each patient's clinical profile.

Design: Retrospective prediction modeling.

Setting: An outpatient university-affiliated IVF clinic.

Patient(s): We used boosted tree methods to analyze 2,413 independent IVF-DET treatment cycles that resulted in live births. The IVF cycles were retrieved from a database that comprised more than 33,000 IVF cycles.

Intervention(s): None.

Main outcome measure(s): The performance of this prediction model, MBP-BIVF, was validated by an independent data set, to evaluate predictive power, discrimination, dynamic range, and reclassification.

Result(s): Multiple birth probabilities ranging from 11.8% to 54.8% were predicted by the model and were significantly different from control predictions in more than half of the patients. The prediction model showed an improvement of 146% in predictive power and 16.0% in discrimination over control. The population standard error was 1.8%.

Conclusion(s): We showed that IVF patients have inherently different risks of multiple birth, even when DET is specified, and this risk can be predicted before ET. The use of clinic-specific prediction models provides an evidence-based and personalized method to counsel patients.

Publication types

  • Evaluation Study
  • Validation Study

MeSH terms

  • Adult
  • Embryo Transfer / adverse effects*
  • Embryo Transfer / methods
  • Female
  • Fertilization in Vitro / adverse effects*
  • Fertilization in Vitro / methods
  • Forecasting / methods
  • Humans
  • Individuality
  • Infertility / diagnosis*
  • Infertility / epidemiology
  • Infertility / therapy*
  • Male
  • Models, Statistical*
  • Multiple Birth Offspring* / statistics & numerical data
  • Pregnancy
  • Pregnancy, Multiple / statistics & numerical data
  • Probability
  • Prognosis
  • Retrospective Studies
  • Risk Factors
  • Treatment Outcome