Quantitative decision-making in preimplantation genetic (aneuploidy) screening (PGS).

PURPOSE: To analyze using hypergeometric probability statistics the impact of performing preimplantation genetic screening (PGS) on a cohort of day 3 cleavage stage embryos.
METHODS: Statistical mathematical modeling.
RESULTS: We find the benefit of performing PGS is highly dependent on the number of day 3 embryos available for biopsy. Additional hidden variables that determine the outcome of PGS are the rates of aneuploidy and mosaicism, and the probability of a chromosomally mosaic embryo to test "normal". If PGS is performed, our analysis shows that many combinations of the number of biopsiable embryos, and the rates of aneuploidy and mosaicism results in a marginal benefit from the intervention. Other combinations are detrimental if PGS is actually undertaken. Finally, increases in PGS error rates lead to a rapid loss in the ability of PGS to provide useful discriminatory information.
CONCLUSION: We set out the statistical framework to determine the limits of PGS when a specific number of day 3 preimplantation embryos are available for biopsy. In general, PGS cannot be recommended a priori for a specific clinical situation due to the statistical uncertainties associated with the different hidden variable quantitative parameters considered important to the clinical outcome.