Patient and provider determinants associated with the prescription of adjuvant hormonal therapies following a diagnosis of breast cancer in Medicaid-enrolled patients.
PURPOSE: This study examined patient and provider characteristics associated with being prescribed an aromatase inhibitor (AI) vs tamoxifen-only therapy among a cohort of postmenopausal North Carolina Medicaid enrollees diagnosed with hormone receptor-positive breast cancer. METHODS: A logistic regression model was built to determine the odds of an individual ever receiving an AI during the study period using data from the Linked North Carolina Central Cancer Registry-Medicaid Claims database. RESULTS: A total of 452 patients were included, of which 307 (67.9%) and 145 (32.1%) received tamoxifen only and AI (alone or in combination) therapy, respectively. Results of the final logistic model revealed that odds of receiving an AI generally increased over the study period; however, patients who lived in urban areas had 1.86 (95% CI, 1.20-2.89) times the odds of ever receiving some form of AI therapy compared to patients who lived in rural areas. Additionally, patients with distant stage or unstaged breast cancer (opposed to local stage) had 2.15 (95% CI, 1.39-3.32) times the odds of ever receiving an AI. CONCLUSIONS: Results suggest that the use of AI therapy is becoming more widespread over time; however, differences in the type of antiestrogenic treatment prescribed based on urban/rural status may represent disparities in access to advanced care. Furthermore, it may be the case that women with local-stage breast cancer are not being treated aggressively enough with novel antiestrogenic drug therapies.
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- United States
- Tamoxifen
- Public Health
- Middle Aged
- Medicaid
- Logistic Models
- Humans
- Healthcare Disparities
- Female
- Case-Control Studies
Citation
Published In
DOI
ISSN
Publication Date
Volume
Issue
Start / End Page
Location
Related Subject Headings
- United States
- Tamoxifen
- Public Health
- Middle Aged
- Medicaid
- Logistic Models
- Humans
- Healthcare Disparities
- Female
- Case-Control Studies