Factors that impact aromatase inhibitor adherence in early-stage hormone receptor positive breast cancer.

person Angela Yang Mount Sinai Hospital, New York, NY info_outline Angela Yang, Elena Baldwin, Nicole Casasanta, Amy Tiersten, Melanie Wain Kier

Authors person Angela Yang Mount Sinai Hospital, New York, NY info_outline Angela Yang, Elena Baldwin, Nicole Casasanta, Amy Tiersten, Melanie Wain Kier Organizations Mount Sinai Hospital, New York, NY, Icahn School of Medicine at Mount Sinai, New York, NY, Department of Medicine, Icahn School of Medicine at Mount Sinai, New York, NY, Mount Sinai Health System, New York, NY Abstract Disclosures Research Funding No funding sources reported Background: Despite efficacy of aromatase inhibitors (AI) in improving survival for patients with hormone receptor positive (HR+) breast cancer, adherence to AI remains suboptimal. The aim of this study is to evaluate factors that may affect patient adherence to first-line AI. Methods: We retrospectively reviewed records of 195 female patients with HR+, HER2 negative early-stage breast cancer who were started on first-line adjuvant AI between 2011-2020 at our academic institution. We collected information on recurrence risk (defined by Oncotype score, with low risk ≤ 15, moderate risk 16-25, high risk ≥ 26), AI-related side effects, supportive therapy use for side effects, and socioeconomic demographics (i.e. income, insurance type, and race). We linked median family income with zip codes based on national census data and sorted them based on the Pew Research Center categorization. The primary end point was the rate of first-line AI adherence at 4 years. The Kruskal-Wallis rank sum test, Fisher’s exact test, and Pearson’s chi-squared test were used to compare AI adherence when varying patient profiles. Results: In our cohort, 50% (n=98) were adherent to first-line AI at 4 years, 9% (n=17) were still taking first-line AI but have not yet reached 4 years, and 41% (n=80) discontinued first-line AI early. Of those who discontinued first-line AI early, 68% (n=54) switched to an alternate endocrine treatment due to side effects, 4% (n=3) stopped all endocrine treatment, and 28% (n=23) were lost to follow up. AI-related side effects were common; 83% (n=162) reported AI-related side effects, yet only 27% of those patients received supportive therapy. Supportive therapy use was not significantly different when varying patients’ recurrence risk and socioeconomic demographics. In addition, adherence did not differ based on side effect frequency or supportive therapy use. The population’s Oncotypes included 36% (n=70) low risk, 36% (n=70) moderate risk and 12% (n=24) high risk; the remaining had no Oncotype sent. There was no significant difference in adherence among the risk groups. In evaluating demographics, the cohort’s median age was 62 and it included 9% Asian, 13% Black, 5% Hispanic, 54% White, and 19% Other/Unknown. The majority (62%) of patients were of middle income ($52,000-145,000), followed by 29% in upper and 9% in lower income. The minority (22%) of patients were on Medicaid. Those with a lower discontinuation rate were older (64 vs. 61, p=0.019), while there was no significant difference based on race, income, or insurance. Conclusions: Despite the small sample, it is reassuring that at our institution, long term adherence to first-line AI and supportive therapy use did not vary among socioeconomic demographics. However, a gap persists between the prevalence of AI-related side effects and usage of proven supportive treatments. Further study on strategies to enhance AI tolerance and adherence is needed.