The Impact of Marital and Socioeconomic Status on Outcomes of Patients with Acute Promyelocytic Leukemia
Authors: Huntington Scott F , Shah Nirav N. , Epstein Andrew , Loren Alison W. 
Published: October 2019

Background:

Marital status, social support, and socioeconomic status (SES) have been long identified as factors that have a role in outcomes in patient care and health. In patients with solid malignancies, both marital status and socioeconomic status influence the timing and stage of disease presentation. In such malignancies, late presentations are often consistent with incurable metastatic disease. In contrast, patients with hematological malignancies are often considered to have curable disease independent of their stage or timing of presentation. Given this discrepancy, we set out to determine the impact of marital status and SES on outcomes in patients with highly curable hematological malignancies such as acute promyelocytic leukemia (APML).

Methods:

We used the Surveillance, Epidemiology, and End Results (SEER) program to identify patients diagnosed with APML between 1999 and 2010. Linkage of SEER to Area Health Resources Files (AHRF) allowed county-level evaluation of socioeconomic factors. The association of individual patient factors on both 30-day mortality and long-term survival were analyzed to evaluate for differing influence on early-versus-delayed APML mortality.

Results:

A total of 2,635 individuals had baseline and follow-up information available for multivariable logistic regression and Cox regression analysis. The models included a standardized socioeconomic status (SES) index along with measures of county-level uninsurance rates and urban-rural stratification. In addition to increased early mortality with rising age, the likelihood of death during the first 30 days was higher in men (OR 1.22, 95% CI 1.01-1.44; p = 0.04). Marital status was not a significant predictor of death at 30 days, but there was a 2% increase in the odds of early death with every 1% increase of county-level uninsurance (p = 0.02). Conversely, gender and census-level uninsurance rates did not predict survival beyond the first 30 days, however, marriage and SES index above the median were associated with improved long-term survival (OR 0.70, 95% CI 0.57-0.81; OR 0.64, 95% CI 0.46 – 0.84 respectively, p ≤ 0.001).

Conclusion:

The impact of marital status, gender, and socioeconomic factors on clinical outcomes of patients with newly diagnosed APML appears to differ between the early acute and late clinical settings. Male sex and uninsurance rates were associated with early APML mortality and may suggest delay in seeking acute medical care. Marital and SES status appear to have greater influence on late survival of patients with APML and may be related to improvements in long-term medical adherence. Overall, our analysis suggests marital status, insurance coverage, and SES factors affect the outcomes of patients with APML, a highly curable malignancy. Future studies investigating the impact of social support on outcomes of other highly curable hematological malignancies may allow identification of important patient factors that affect clinical course.

Table 1: 30-day mortality, multivariable logistic regression Variable Unadjusted OR (95% CI) Adjusted OR (95% CI) p Age at diagnosis (years) 1.03 (1.02-1.04) 1..03 (1.02-1.04) <0.001 Gender (M:F) 1.20 (1.01-1.44) 1.22 (1.01-1.47) 0.04 Marriage (Y:N) 1.08 (0.91-1.31) 0.84 (0.69-1.02) 0.08 Race (white:non-white) 1.24 (0.98-1.57) 1.12 (0.88-1.43) 0.36 SES index (50%+) 0.88 (0.70-1.13) 0.97 (0.74-1.26) 0.80 Rural vs. Urban 1.24 (0.80-1.92) 1.21 (0.76-1.93) 0.43 % uninsured 1.01 (0.99-1.03) 1.02 (1.00-1.04) 0.02

Table 2: Long-term overall survival, Cox regression Variable Unadjusted HR (95% CI) Adjusted HR (95% CI) p Age at diagnosis (years) 1.04 (1.03-1.05) 1.04 (1.03-1.05) <0.001 Gender (M:F) 0.99 (0.82-1.21) 1.04 (0.85-1.27) 0.68 Marriage (Y:N) 0.97 (0.80-1.19) 0.70 (0.57-0.85) <0.001 Race (white:non-white) 0.90 (0.71-1.14) 0.81 (0.63-1.03) 0.09 SES index (50%+) 0.68 (0.53-0.87) 0.64 (0.50-0.84) 0.001 Rural vs. Urban 0.99 (0.58-1.69) 0.82 (0.47-1.41) 0.47 % uninsured 0.99 (0.97-1.01) 0.99 (0.97-1.01) 0.41

Disclosures

No relevant conflicts of interest to declare.