A prediction algorithm for optimal number of oocytes to fertilize during in vitro fertilization treatment

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Project Summary/Abstract In vitro fertilization (IVF) treatment has become increasingly more common and successful over the last decade. Extra frozen embryos (embryos that couples do not use right away, but continue to store) pose an emotional and financial dilemma to patients. The extra embryos also lead to a logistical and financial dilemma for clinics. One strategy to limit the number of extra embryos in storage is to limit the number of embryos created in the first place. However, there currently is no validated method to determine how many eggs should be fertilized during in vitro fertilization treatment such that enough embryos are formed to have the desired number of children while minimizing the number of extra embryos. Our objective is to develop a prediction tool to aid clinicians and patients in deciding how many eggs should be fertilized during IVF. In Specific Aim 1, we will develop an algorithm using existing data from the national Society for Assisted Reproductive Technology Clinical Outcome Reporting System (SART CORS) database. We propose to develop two separate models, one to predict the number of embryos that will need to be transferred to yield one live birth and the second to predict the proportion of fertilized eggs that will yield transferrable embryos. Both models will consider patient demographics and pre-retrieval cycle characteristics as possible predictors. The final algorithm will involve a function of the ratio of the two predictions. In Specific Aim 2, we will survey IVF patients and providers to assess their interest and perspective in utilizing the prediction tool. Survey responses will help elucidate possible barriers to utilization, informing us on how best to educate patients and providers on the value of the prediction tool. This proposal is of high importance because it has the potential to change the way IVF is conducted, thus limiting the number of eggs that are fertilized and creating less embryos. Having less embryos will minimize the emotional, financial, and logistical tolls that extra embryos pose to patients and providers. With successful completion of the proposed aims, we will have a tool that can help promote safer, effective, more responsible care for IVF patients.