Abstract
Introduction:
Burkitt lymphoma (BL) is an aggressive non-Hodgkin lymphoma with an estimated 1480 new cases diagnosed in the United States in 2016. BL is simultaneously one of the most aggressive lymphomas, with a tumor volume doubling time of just 24 hours, and one of the most curable, with several clinical trials showing 3-year survival rates over 80%. However, recent studies have identified a significant discrepancy between clinical trial and "real-world" survival, implying access to care may play an important role in BL outcomes. A patient's insurance status represents a major factor in the utilization of cancer therapies and outcomes in the United States. Underinsured patients are more likely to be diagnosed at an advanced stage, receive substandard therapy, and have worse outcomes. We examined the effect of insurance status on survival in adults with BL and compared the impact of insurance status on BL outcomes to that seen in plasmablastic lymphoma (PBL), an aggressive lymphoma that has poor outcomes regardless of treatment.
Methods:
We used data from the National Cancer Database (NCDB), a nationwide, hospital-based cancer registry jointly sponsored by the American Cancer Society and American College of Surgeons that contains 34 million historical records and captures 75% of newly diagnosed cancer cases in the United States. Commission on Cancer (CoC)-accredited facilities report patients' vital status and date of death to the NCDB annually.
We included patients > 18 years old diagnosed 2004-2014 with BL or PBL as the primary tumor who received all or part of initial course of treatment at the reporting facility. Patients missing information on insurance status or survival were excluded, as were those who had non-Medicare/Medicaid government insurance (VA, Indian Health Services). Chi-square tests were used to compare sociodemographic and clinical characteristics by insurance status. All analyses were performed for both BL and PBL and stratified on age 65, due to changes in eligibility for Medicare at that age. Kaplan-Meier survival curves were stratified by insurance status, and log-rank tests were performed. Univariate Cox proportional hazard models were generated to describe the unadjusted associations for the covariables, and multivariable Cox proportional hazard models were generated to estimate the hazard ratio (HR) associated with insurance status when adjusted for prognostic factors.
Results:
We identified 7,073 BL patients and 475 PBL patients in the NCDB who met inclusion criteria. Of the 5235 BL patients < 65 years, 65.0% had private insurance, 17.2% had Medicaid, 7.6% had Medicare, and 10.2% had no insurance. Of the 1838 BL patients ≥ 65 years, 12.9% had private insurance, 1.5% had Medicaid, 85% had Medicare, and 0.65% had no insurance. Uninsured and Medicaid-insured patients were more likely to be Hispanic or black, have lower socioeconomic status (SES), have B symptoms, be HIV-positive, and have a Charlson-Deyo comorbidity score ≥ 2 when compared with privately insured patients. Medicare patients were more likely to be female, have ≥1 comorbidity, and not receive chemotherapy treatment when compared to privately insured patients. BL patients without private insurance had significantly worse overall survival compared to those with private insurance, regardless of age group (adjusted HR age <65: uninsured 1.41 [95% confidence interval 1.2,1.7], Medicaid 1.17 [1,1.4], Medicare 1.5 [1.2,1.8]; adjusted HR age ≥ 65: uninsured 6 [2.1,17.3], Medicare 1.33 [1,1.8]; see Figure). Conversely, Cox regression models demonstrated that PBL patients without private insurance experienced no significant differences in overall survival in either age group. For BL patients age <65, low SES, presence of B symptoms, advanced stage, HIV-positive status, comorbidity score ≥ 2, and lack of treatment were significant, independent predictors of worse outcomes and contributed to the disparities in survival by insurance status. For BL age > 65, B symptoms, comorbidity score ≥ 2, and lack of treatment were significant, independent predictors of worse outcomes.
Conclusion:
We identified insurance status as an important predictor of clinical outcomes for BL. Our findings suggest that expanding access to care may improve survival disparities in BL, for which curative therapy exists, but not PBL, where more effective therapies are needed to improve outcomes.
Disclosures
Flowers: Celgene: Consultancy, Research Funding; Bayer: Consultancy; V Foundation: Research Funding; Research to Practice: Research Funding; Infinity: Research Funding; Acerta: Research Funding; National Institutes Of Health: Research Funding; Clinical Care Options: Research Funding; Educational Concepts: Research Funding; Abbvie: Consultancy, Research Funding; Pharmacyclics LLC, an AbbVie Company: Research Funding; OptumRx: Consultancy; Spectrum: Consultancy; Genentech/Roche: Consultancy, Research Funding; National Cancer Institute: Research Funding; Eastern Cooperative Oncology Group: Research Funding; Onyx: Research Funding; Burroughs Welcome Fund: Research Funding; TG Therapeutics: Research Funding; Prime Oncology: Research Funding; Millennium/Takeda: Research Funding; Janssen Pharmaceutical: Research Funding; Seattle Genetics: Consultancy; Gilead: Consultancy.
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