Biomarker testing and patient demographic disparities among breast cancer patients across treatment settings.

e13123 Background: Biomarker testing is crucial for personalizing breast cancer (BC) treatment. However, equitable access to biomarker testing and its impact on treatment remains a concern. This study examines real-world biomarker testing rates and patient demographic patterns among BC patients in the US, stratified by treatment setting. Methods: A retrospective analysis of de-identified physician reported patient data from the Ipsos Global Oncology Monitor (Dec 2023-Nov 2024) was conducted. The study surveyed 585 treating oncologists who submitted 10,752 female BC patient records receiving drug therapy in the US across treatment settings (4918 Urban, 5007 Suburban, 827 Rural). Data encompassed demographics, treatment setting, patient engagement in therapy selection, and biomarker testing (HRD, PIK3CA, PD-L1, ESR1); participating oncologists saw a minimum number of cancer patients (all tumors) per month. Results: Disparities in biomarker testing rates were observed across treatment settings. Rural settings consistently exhibited lower testing rates compared to urban and suburban centersFor instance, HRD testing was performed in 56% of urban/suburban versus 35% in rural settings (p < .01). Similarly, PIK3CA testing rates were 60% in urban/suburban versus 41% in rural settings (p < .01). Similar trends were seen for PD-L1 and ESR1 testing rates. Furthermore, demographic variations were evident across settings. Rural centers had a higher representation of older patients, as well as a higher mean patient age (63.22 years vs. 60.96 years) and BMI (27.41 vs 25.75) compared to urban settings. Patient engagement in therapy selection, such as requesting specific treatments by name or feature, was lower in rural settings (6% vs. 14% urban) (p < .01). Conclusions: This study reveals significant disparities in biomarker testing rates for BC patients across US treatment settings, raising concerns about equitable access to quality cancer care. Lower testing rates for HRD, PIK3CA, PD-L1 and ESR1 and patient engagement in rural settings may contribute to suboptimal treatment selection and outcomes. Demographic variations further emphasize the need for tailored interventions to optimize BC care. Addressing these disparities through targeted initiatives, such as increased access to testing resources and patient education programs, is crucial for ensuring optimal outcomes for all BC patients. The future of BC care hinges on continued growth in personalized medicine, but equitable access to biomarker testing and patient engagement across treatment settings will be essential for realizing its full potential. Further analysis of comparator cohorts is warranted.