title: Predicting probabilities of pregnancy and multiple gestation from in vitro fertilization--a new model.
abstract: OBJECTIVE
  To develop a statistical model that adjusts for variation between patients and adequately predicts the observed distribution of pregnancies among singletons and multiple gestations of various orders.
  
  
  METHODS
  All in vitro fertilization (IVF) cycles from the inception of the IVF program at Women and Infants' Hospital on May 26, 1988, until December 31, 1993, were evaluated using logistic regression in selected subsets.
  
  
  RESULTS
  A new cycle-one specific model uses three different probabilities: P1, the probability of pregnancy (predicted by age and total embryo score); P2/P1, the conditional probability of finding a second implantation in those who had become pregnant with at least one (predicted by total embryo score); and P3/P2, the conditional probability of finding a third implantation in those who had become pregnant with at least two (with no significant predictors). This is the first model to use these three adjusted probabilities.
  
  
  CONCLUSIONS
  P1 increases with increasing total embryo score but decreases with increasing age. P2/P1 increases with increasing total embryo score but does not depend on age. Embryo scoring is useful because the total embryo score is a better predictor of P1 and P2/P1 than the number of embryos alone. By using patient-specific information (age and total embryo score) and cycle-specific tables, an estimate of the probability of pregnancy and multiple gestation can be provided before embryo transfer.
authors.affiliation: Department of Obstetrics and Gynecology, Women and Infants Hospital, Brown University, Providence, Rhode Island 02905, USA. cwheeler@wihri.org
authors.forename: C A
authors.initials: CA
authors.lastname: Wheeler
authors.forename: B F
authors.initials: BF
authors.lastname: Cole
authors.forename: G N
authors.initials: GN
authors.lastname: Frishman
authors.forename: D B
authors.initials: DB
authors.lastname: Seifer
authors.forename: S B
authors.initials: SB
authors.lastname: Lovegreen
authors.forename: R J
authors.initials: RJ
authors.lastname: Hackett
mesh_terms: D000328:Adult; D004624:Embryo Transfer; D005260:Female; D005307:Fertilization in Vitro; D006801:Humans; D016015:Logistic Models; D008875:Middle Aged; D015233:Models, Statistical; D011247:Pregnancy; D011272:Pregnancy, Multiple