Abstract PS04-08: Sociodemographic Risk Factors and Prediction of Aromatase Inhibitor Non-Adherence in Women with Breast Cancer Enrolled in SWOG S1105

Abstract

Abstract Background: Non-adherence to aromatase inhibitors (AIs) for breast cancer is common and increases risk of recurrence. Few prospective studies have systematically evaluated non-adherence and non-clinical factors associated with it. We analyzed baseline sociodemographic characteristics and financial factors associated with non-adherence to create a baseline composite risk-score for AI non-adherence. Methods: Patients enrolled in S1105 were required to have been on an AI for ≥30 days at enrollment. Patients were assessed for non-adherence of AIs every 3 months for 36 months, with non-adherence defined as urine AI metabolite assay results satisfying any of the following: < 10 ng/mL, undetectable, specimen submitted outside of the ± 21-day follow-up appointment window, or no submitted specimen. Factors included race, Hispanic ethnicity, age, education, income, health insurance type, and prescription cost. We also included socioeconomic deprivation and rural or urban residence using trial participants’ residential zip codes linked to the Area Deprivation Index (ADI) and Rural Urban Continuum codes (RUCC) respectively. For numeric factors and categorical factors with more than two levels, we used cutpoint analysis to determine the highest risk range by optimizing the Chi-squared statistic. For each resulting binary factor, we performed a logistic regression, adjusting for the study stratification factors and stratifying by treatment arm. Factors associated with adherence at the alpha=0.10 level were combined into a composite risk score, with study participants given one point for each baseline adverse risk factor. Secondarily, we examined a composite risk score including all factors, regardless of statistical significance. Results: In total, 724 patients were registered from 40 institutions between May 2012 and September 2013. The median age was 60.9 years, and 64.5% were on AI < 12 months prior to registration. Only 8% had out of pocket (OOP) cost >$30. Observed adherence at 36 months was 35.9%. Patients living in metro areas with populations ≥ 250,000 (RUCC ≤ 3) were more likely to be non-adherent (37.5% vs 28.3%, OR=1.50, p=.08); as were those who were younger, those without a college education, and those with limited (≤$5) OOP cost. ADI, race and ethnicity were not associated with non-adherence. The composite risk score was strongly associated with 36-month adherence. For each 1 unit increase in risk level, the risk of non-adherence increased 47% (OR=1.47, p< .001); the risk increased 64% for those with >2 vs. ≤2 risk factors (OR=1.64, p=.002). Results using all factors regardless of statistical significance were consistent. Conclusions: A composite model comprised of sociodemographic risk factors can identify patients on AI’s at much greater risk of long-term AI non-adherence. In addition to mitigating side effects, targeted interventions to improve adherence should focus on structural barriers among those at highest risk. Non-adherence (+/- 6 months) = factor + AI duration + AI type, stratified by arm Citation Format: Dawn Hershman, Anna Moseley, Kathryn Arnold, Julie Gralow, Alfred Neugut, Scott Ramsey, N. Lynn Henry, Joseph Unger. Sociodemographic Risk Factors and Prediction of Aromatase Inhibitor Non-Adherence in Women with Breast Cancer Enrolled in SWOG S1105 [abstract]. In: Proceedings of the 2023 San Antonio Breast Cancer Symposium; 2023 Dec 5-9; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2024;84(9 Suppl):Abstract nr PS04-08.