Abstract
139 Background: Fertility preservation (FP) prior to therapy is underutilized for those diagnosed with cancer as a child, adolescent or young adult (AYA). This study describes the factors impacting utilization of FP consultations and procedures among childhood and AYA cancer patients at the University of Iowa Health Care (UIHC). Methods: Patients were identified by the oncology registry at UIHC. Disease site, histology, date of diagnosis, sex, race, ethnicity, insurance, and zip code were gathered by the registrars. Disease site and histology were categorized using International Classification of Diseases-Oncology-3 (ICD-O-3). UIHC’s electronic medical record (EMR, Epic) was queried for ICD codes for FP consultation. Data from UIHC’s Reproductive Endocrinology and Infertility clinical database were merged with the primary data set to capture information about those who underwent FP. Rural-Urban Commuting Area codes incorporated a measure of rurality. Descriptive statistics and multivariate linear probability models were used to predict the probability of FP consultation and procedure. Results: From 2008-2017, 3,605 children and AYAs were treated for an invasive malignancy. Of the 637 (18%) who received a FP consultation, 162 (25%) underwent a FP procedure. Multivariate analyses showed that those with public insurance or no insurance, a diagnosis of a CNS tumor, melanoma, or miscellaneous neoplasm, and age over 30 years at diagnosis had a lower probability of having a consultation. The probability of undergoing a procedure was lower for female patients, those with germ cell tumor, melanoma, or carcinoma, seen by a pediatric-based provider, and diagnosed between 15-25 years of age. Conclusions: This study has important implications for survivorship and late effects research. The combination of sample identification via cancer registrars and linkage with EMR data could be used by others. The use of federal data to incorporate rurality is frequently overlooked. The use of this type of publicly available data would help improve the robustness of survivorship and late effects research through the inclusion of measures of rurality, health service availability, and economic indicators at varying levels of geography.
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