title: Reducing multiples: a mathematical formula that accurately predicts rates of singletons, twins, and higher-order multiples in women undergoing in vitro fertilization.
abstract: OBJECTIVE
  To develop a mathematical formula that accurately predicts the probability of a singleton, twin, and higher-order multiple pregnancy according to implantation rate and number of embryos transferred.
  
  
  METHODS
  A total of 12,003 IVF cycles from a single center resulting in ET were analyzed. Using mathematical modeling we developed a formula, the Combined Formula, and tested for the ability of this formula to accurately predict outcomes.
  
  
  METHODS
  Academic hospital.
  
  
  METHODS
  Patients undergoing IVF.
  
  
  METHODS
  None.
  
  
  METHODS
  Goodness of fit of data from our center and previously published data to the Combined Formula and three previous mathematical models.
  
  
  RESULTS
  The Combined Formula predicted the probability of singleton, twin, and higher-order pregnancies more accurately than three previous formulas (1.4% vs. 2.88%, 4.02%, and 5%, respectively) and accurately predicted outcomes from five previously published studies from other centers. An online applet is provided (https://secure.ivf.org/ivf-calculator.html).
  
  
  CONCLUSIONS
  The probability of pregnancy with singletons, twins, and higher-order multiples according to number of embryos transferred is predictable and not random and can be accurately modeled using the Combined Formula. The embryo itself is the major predictor of pregnancy outcomes, but there is an influence from "barriers," such as the endometrium and collaboration between embryos (embryo-embryo interaction). This model can be used to guide the decision regarding number of embryos to transfer after IVF.
authors.affiliation: Ronald O. Perelman and Claudia Cohen Center for Reproductive Medicine, Weill Cornell Medical College, New York, New York 10021, USA.
authors.forename: Zev
authors.initials: Z
authors.lastname: Williams
authors.forename: Eric
authors.initials: E
authors.lastname: Banks
authors.forename: Mario
authors.initials: M
authors.lastname: Bkassiny
authors.forename: Sudharman K
authors.initials: SK
authors.lastname: Jayaweera
authors.forename: Rony
authors.initials: R
authors.lastname: Elias
authors.forename: Lucinda
authors.initials: L
authors.lastname: Veeck
authors.forename: Zev
authors.initials: Z
authors.lastname: Rosenwaks
mesh_terms: D000328:Adult; D000465:Algorithms; D003198:Computer Simulation; D004624:Embryo Transfer / Q000706:statistics & numerical data*; D005260:Female; D005307:Fertilization in Vitro / Q000706:statistics & numerical data*; D006801:Humans; D008875:Middle Aged; D015233:Models, Statistical; D011247:Pregnancy; D011256:Pregnancy Outcome / Q000453:epidemiology*; D011258:Pregnancy Tests / Q000379:methods*; D011272:Pregnancy, Multiple / Q000706:statistics & numerical data*; D011379:Prognosis; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D055815:Young Adult