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

Area of Science:

• Reproductive Medicine
• Biostatistics
• Genetics

Background:

• Preimplantation genetic screening (PGS) is a technique used in assisted reproductive technology to assess the chromosomal status of embryos before uterine transfer.
• The efficacy of PGS, particularly for day 3 cleavage stage embryos, remains a subject of ongoing research and debate.
• Understanding the statistical impact of PGS is crucial for optimizing its application in clinical settings.

Purpose of the Study:

• To statistically analyze the impact of performing preimplantation genetic screening (PGS) on a cohort of day 3 cleavage stage embryos using hypergeometric probability.
• To determine the statistical framework for evaluating the limits of PGS based on the number of available day 3 embryos for biopsy.

Main Methods:

• Statistical mathematical modeling was employed to analyze the data.
• Hypergeometric probability statistics were utilized to assess the impact of PGS.

Main Results:

• The benefit of PGS is significantly influenced by the number of available day 3 embryos for biopsy.
• Aneuploidy rates, mosaicism rates, and the probability of mosaic embryos testing as normal are critical hidden variables affecting PGS outcomes.
• Many combinations of embryo numbers and aneuploidy/mosaicism rates result in marginal benefits or even detrimental outcomes from PGS.
• Increased PGS error rates rapidly diminish its discriminatory information capability.

Conclusions:

• A statistical framework was established to define the limitations of PGS for a given number of day 3 embryos.
• PGS cannot be universally recommended a priori due to statistical uncertainties in key quantitative parameters influencing clinical outcomes.
• The decision to use PGS should be individualized, considering the specific statistical variables relevant to each clinical situation.