Predictors of Ovarian Insufficiency in Young Breast Cancer Patients (POISE)

More than two million American women are breast cancer survivors. Approximately one-third of these women are premenopausal at diagnosis and face issues related to reproduction as they undergo cancer treatment. Ovarian function after breast cancer diagnosis has implications on breast cancer prognosis, choice of adjuvant therapy and reproductive issues such as desire for fertility or concerns about menopause. Therefore, tools to accurately predict ovarian function in breast cancer survivors could significantly impact physicians and patients in counseling, medical and surgical treatment choices, and consideration of fertility preservation options.

The goal of this proposal is to identify pre-chemotherapy hormonal, genetic and ovarian imaging markers that can predict ovarian failure and characterize the course of ovarian function after chemotherapy. The investigators plan to follow a group of young women from breast cancer diagnosis to five years after chemotherapy. The investigators will study the following risk factors: blood hormone levels that reflect ovarian function, genetic mutations that affect how individuals metabolize chemotherapy, and ovarian size and egg count by MRI and ultrasound. The investigators hypothesize that these biomarkers are related to risk of ovarian insufficiency singly. After examining these individual risk factors for ovarian failure, the investigators will put them together into an Ovarian Failure Clinical Predictive Index. This index will be a tool similar to the Gail Model that can be used to determine individual risk for ovarian failure. This tool would assist young breast cancer patients and their physicians in making treatment decisions that would impact cancer survival and reproduction.