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3283 Acute Myelogenous Leukemia: Insurance Status, Race and Comorbidities, but Not Distance from Treatment Center Determine Outcome

Health Services and Outcomes Research – Malignant Diseases
Program: Oral and Poster Abstracts
Session: 902. Health Services and Outcomes Research – Malignant Diseases: Poster II
Sunday, December 6, 2015, 6:00 PM-8:00 PM
Hall A, Level 2 (Orange County Convention Center)

Samip Master, MD1, Zhenzhen Shi2*, Srinivas S. Devarakonda, MD3, Reinhold Munker, MD4 and Runhua Shi, MD PhD MPH3*

1Feist-Weiller Cancer Center, LSU Medical Center, Shreveport, LA
2Tulane University, New Orleans, LA
3Department of Hematology/Oncology, LSU Health Sciences Center, Shreveport, LA
4Department of Hematology/Oncology, LSUHSC-Shreveport, Shreveport, LA

Background:  The treatment of acute myeloid leukemia (AML) has made major progress in the last 30 years. Well-known risk factors are age, cytogenetics and treatment intensity. Many other factors including access to healthcare modify treatment outcomes. According to smaller studies, the type of insurance (payer status) may or may not influence treatment outcomes.  In the wake of the Affordable Care Act and its impact on insurance coverage, evaluating the effect of insurance status on health outcomes is urgently necessary. This study characterizes the relationship between payer status and overall survival for AML patients by analyzing data from the large National Cancer Data Base (NCDB).

Methods  Data was analyzed from 67,443 men and women (≥ 18 years of age) registered in the NCDB who were diagnosed with AML between 1998 and 2011 and had follow-ups to end of 2012.  The primary predictor variable was payer status and the outcome variable was overall survival.  Additional variables addressed and adjusted for included sex, age, race, Charleson Comorbidity index, level of education, income, distance traveled, facility type, diagnosing/treating facility, treatment delay, and chemotherapy.

Results:  Among these 67,433 patients, the mean age at diagnosis was 61 years (median, 64 years) with a median survival of 7.98 months. The mean ages at diagnosis were 46.8, 51.8, 44.6, 73.6, and 57.9 years old for uninsured, private, Medicaid, Medicare and unknown payer status, respectively.  In multivariate analysis, after adjusting for secondary predictor variables, payer status was a statistically significant predictor of overall survival from AML. Relative to privately insured patients, patients with Medicaid had a 17% increased risk, no insurance had a 21% increased risk, Medicare had a 19% increased risk, and unknown insurance had a 22% increased risk of mortality from AML. The percentage of patients surviving from AML after 24 months  was 37.6%, 31.4%, 32.3%, 31.8%, and 33.1% for private, unknown, Medicare, uninsured, and Medicaid payer status, respectively. All factors investigated were found to be significant predictors of AML survival except distance travelled. Patients aged 65-74 were 2.9 times more likely to die compared to those aged 19-49. Patients who received chemotherapy were 22% less likely to die compared to those who did not. In the more recent time period (2005-2011 versus 1998- 2004, the prognosis of AML has improved, however the imbalance as per payer status did not change significantly.    

Conclusion:  We observed that payer status has a statistically significant relationship with overall survival from AML. This remained true after adjusting for other predictive factors. Medicaid and uninsured patients had the highest mortality while privately insured patients had the lowest mortality. Further research is necessary how the disparities associated with different types of insurance result in inferior treatment outcomes and how they can be addressed. 

Multivariate Cox regression, hazard ratio of death by factors

Factor

Level

HR*

Lower

Upper

Age

18-49

1.00

50-64

1.96

1.90

2.02

65-74

2.86

2.75

2.98

75+

4.14

3.96

4.32

Insurance

Private

1.00

Uninsured

1.21

1.14

1.28

Medicaid

1.16

1.11

1.21

Medicare

1.19

1.16

1.23

Unknown

1.23

1.15

1.31

Year of diagnosis

98-04

1

 

 

05-11

0.85

0.82

0.87

Race

White

1.00

 

 

Black

1.08

1.04

1.12

Asian

0.92

0.86

0.98

Charleson Comorbidity index

0

1.00

 

 

1

1.22

1.18

1.26

2

1.49

1.42

1.56

Unknown

1.352

1.321

1.384

Chemotherapy

No Chemo

1

Single Agent

0.78

0.74

0.83

Multiple Agent

0.62

0.58

0.65

*Adjusted for sex, income, education, distance traveled, facility type, diagnosing/treating facility, and treatment delay.

Disclosures: No relevant conflicts of interest to declare.

*signifies non-member of ASH