Using outcome data from one thousand mosaic embryo transfers to formulate an embryo ranking system for clinical use

Objective: To study how the attributes of mosaicism identified during preimplantation genetic testing for aneuploidy relate to clinical outcomes, in order to formulate a ranking system of mosaic embryos for intrauterine transfer. Design: Compiled analysis. Setting: Multi-center. Patient(s): A total of 5,561 euploid blastocysts and 1,000 mosaic blastocysts used in clinical transfers in patients undergoing fertility treatment. Intervention(s): None. Main Outcome Measure(s): Implantation (gestational sac), ongoing pregnancy, birth, and spontaneous abortion (miscarriage before 20 weeks of gestation). Result(s): The euploid group had significantly more favorable rates of implantation and ongoing pregnancy/birth (OP/B) compared with the combined mosaic group or the mosaic group affecting only whole chromosomes (implantation: 57.2% vs. 46.5% vs. 41.8%; OP/B: 52.3% vs. 37.0% vs. 31.3%), as well as lower likelihood of spontaneous abortion (8.6% vs. 20.4% vs. 25%). Whole-chromosome mosaic embryos with level (percent aneuploid cells) <50% had significantly more favorable outcomes than the ≥50% group (implantation: 44.5% vs. 30.4%; OP/B: 36.1% vs. 19.3%). Mosaic type (nature of the aneuploidy implicated in mosaicism) affected outcomes, with a significant correlation between number of affected chromosomes and unfavorable outcomes. This ranged from mosaicism involving segmental abnormalities to complex aneuploidies affecting three or more chromosomes (implantation: 51.6% vs. 30.4%; OP/B: 43.1% vs. 20.8%). Combining mosaic level, type, and embryo morphology revealed the order of subcategories regarding likelihood of positive outcome. Conclusion(s): This compiled analysis revealed traits of mosaicism identified with preimplantation genetic testing for aneuploidy that affected outcomes in a statistically significant manner, enabling the formulation of an evidence-based prioritization scheme for mosaic embryos in the clinic.