Abstract

e17012 Background: The overall prognosis for most acute myeloid leukemia (AML) patients remains poor. The majority of adult patients (pts) with AML will ultimately need allogeneic stem cell transplant (allo-SCT). Limited data is available comparing epidemiology and treatment outcomes between uninsured and insured pts with AML. We describe a retrospective analysis of adult pts with AML treated at our institution. Methods: From January 2000 to June 2011 we identified 239 pts with AML, of which 185 met inclusion criteria. Patients were classified as having private insurance, public insurance (Medicaid and Medicare), or no insurance. Primary outcomes were overall survival at follow up (OS), complete remission (CR), and percent of pts receiving allo-SCT. Kaplan-Meier analysis was used to estimate survival rates. Results: Of the 185 pts studied, 146 (81%) were white, 16 (9%) African-American and 11 (6%) were Native American. The median age at diagnosis was 49 years. 75 pts had private insurance at the time of diagnosis, 70 had public insurance, and 33 were uninsured. Of those receiving allo-SCT (n=60; 38 male) 48% had private insurance, 30% public, and 22% were uninsured. Whether a patient underwent allo-SCT did not differ according to insurance source (p=0.2189) nor to status at follow-up (p= 0.6480). The proportion of patients achieving CR was higher among those undergoing allo-SCT (p=0.0002). Median OS was 920 days for those who underwent allo-SCT and 192 days for those who did not (p< 0.0001). Median OS did not differ by insurance type (p = 0.1454). The proportion of patients achieving CR did not differ by insurance type (p=0.2665) (66.7% of those with private, 62.7% of those with public, and 78.8% of those with no insurance). Conclusions: For the population referred to our institution, a tertiary referral center for the state, there were no differences in treatment outcomes or in the percent of pts receiving allo-SCT when pts were stratified according to insurance source. Further analysis of this dataset will identify the impact of pretreatment variables stratified by type of insurance.

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