title: Cost effectiveness of ovarian reserve testing in in vitro fertilization: a Markov decision-analytic model.
abstract: OBJECTIVE
  To compare the cost effectiveness of ovarian reserve testing in in vitro fertilization (IVF).
  
  
  METHODS
  A Markov decision model based on data from the literature and original patient data.
  
  
  METHODS
  Decision analytic framework.
  
  
  METHODS
  Computer-simulated cohort of subfertile women aged 20 to 45 years who are eligible for IVF.
  
  
  METHODS
  [1] No treatment, [2] up to three cycles of IVF limited to women under 41 years and no ovarian reserve testing, [3] up to three cycles of IVF with dose individualization of gonadotropins according to ovarian reserve, and [4] up to three cycles of IVF with ovarian reserve testing and exclusion of expected poor responders after the first cycle, with no treatment scenario as the reference scenario.
  
  
  METHODS
  Cumulative live birth over 1 year, total costs, and incremental cost-effectiveness ratios.
  
  
  RESULTS
  The cumulative live birth was 9.0% in the no treatment scenario, 54.8% for scenario 2, 70.6% for scenario 3 and 51.9% for scenario 4. Absolute costs per woman for these scenarios were €0, €6,917, €6,678, and €5,892 for scenarios 1, 2, 3, and 4, respectively. Incremental cost-effectiveness ratios (ICER) for scenarios 2, 3, and 4 were €15,166, €10,837, and €13,743 per additional live birth. Sensitivity analysis showed the model to be robust over a wide range of values.
  
  
  CONCLUSIONS
  Individualization of the follicle-stimulating hormone dose according to ovarian reserve is likely to be cost effective in women who are eligible for IVF, but this effectiveness needs to be confirmed in randomized clinical trials.
authors.affiliation: Department of Obstetrics and Gynaecology, Center for Reproductive Medicine, Academic Medical Centre, Amsterdam, the Netherlands. L.M.Moolenaar@amc.uva.nl
authors.forename: Lobke M
authors.initials: LM
authors.lastname: Moolenaar
authors.forename: Frank J M
authors.initials: FJ
authors.lastname: Broekmans
authors.forename: Jeroen
authors.initials: J
authors.lastname: van Disseldorp
authors.forename: Bart C J M
authors.initials: BC
authors.lastname: Fauser
authors.forename: Marinus J C
authors.initials: MJ
authors.lastname: Eijkemans
authors.forename: Peter G A
authors.initials: PG
authors.lastname: Hompes
authors.forename: Fulco
authors.initials: F
authors.lastname: van der Veen
authors.forename: Ben Willem J
authors.initials: BW
authors.lastname: Mol
mesh_terms: D000328:Adult; D015331:Cohort Studies; D003362:Cost-Benefit Analysis; D003661:Decision Support Techniques; D005260:Female; D005307:Fertilization in Vitro / Q000191:economics*; D006801:Humans; D008390:Markov Chains; D008875:Middle Aged; D010053:Ovary / Q000502:physiology*; D011247:Pregnancy; D018873:Pregnancy Rate / Q000639:trends; D011446:Prospective Studies; D055815:Young Adult