Health Insurance, Income, and Marital Status Contribute to Blood Cancer Disparities

Several factors were identified that contribute to inequities in hematologic cancer outcomes, including not having health insurance, being treated at a non-academic facility, having a low income or education level, and being unmarried, according to findings from a systematic review.

“In terms of health care access, this domain was evaluating insurance status; those with Medicaid, Medicare, and who were uninsured had lower survival rates compared with those with private or military health coverage,” Marisol Miranda-Galvis, DDS, MS, PhD, said. “In terms of facility type where the patients were treated, those who didn’t receive treatment at an academic institution or research institution presented with a [worse] mortality compared with those who received treatment at community, comprehensive, or integrated cancer centers.”

Key takeaways from the review were presented at the 2023 Society of Hematologic Oncology (SOHO) Annual Meeting. The analysis examined survival outcomes in several subgroups of patients with hematologic cancers and compared them with the overall population. Investigators were able to conclude that although survival was improving overall, disparities were only growing.

Results showed that insurance status was significantly associated with survival in the multivariate analysis (76%), subgroup analysis (12%), and unadjusted analysis (3%), and not significant in a small portion (9%). Findings were similar regarding facility type (56%, 17%, 6%, and 22%, respectively). Distance traveled did show some significant association in multivariate (18%) and subgroup analyses (27%), but was primarily found to not be significant (55%). The association of both provider expertise and marital status proved significant in the multivariate analysis (100% each).

When assessing the impact of economic stability and education on outcomes, income had a significant association in the multivariate analysis (63%), as well as in a subgroup (4%) and unadjusted analyses (8%). Similar findings were reported with regard to high school education (44%; 6%; 17%; and 33%, respectively). Employment and nineth grade education were not significantly associated with survival (100%). Poverty was insignificant in the multivariate analysis (26%), and a subgroup (26%), vs not significant in 50% of patients.

“When we compare those [survival] curves with the overall population of the United States, we can see that those improvements have not reached everybody,” Marisol Miranda-Galvis, DDS, MS, PhD, research project manager at Georgia Cancer Center, said during a presentation on the analysis. “There are obvious reasons that could explain those differences, but our interest is to identify what those actions are that clinicians could implement in clinical practice, regardless of limitations, that could help to close that gap.”

Investigators defined social determinants of health (SDH) as a “set of non-biologic factors that shape the environment of daily life that influence health outcomes.” Such factors include education access and quality, health care access and quality, social and community context, economic stability, and neighborhood/built environment. The goal of the analysis was two-fold: identify the SDH that have been assessed with regard to their impact on outcomes and determine which SDH were linked with worse treatment-related outcomes.

To be included in the systematic review, several criteria were required during the literature search:

• Patients must have had a hematologic cancer,
• Any SDH,
• No comparisons,
• Any treatment survival measures,
• Observational studies held in the United States.

The review included a total of 24,353 patients (range, 95-132,402). The most common study setting was national (63.4%), and the most common data source was the National Cancer Database (41.5%). Several types of hematologic malignancies were included in the review, including Hodgkin lymphoma, non-Hodgkin lymphoma, and Burkitt lymphoma (34.1%); multiple myeloma and polymyositis (31.7%); acute myeloid leukemia, acute lymphocytic leukemia, and myelodysplastic syndrome (29.3%); and chronic myeloid leukemia and chronic lymphocytic leukemia (4.9%).

In a population of 57 patients, the outcomes evaluated in the included studies were overall survival (73.2%), early mortality (10.7%), cancer-specific survival (8.9%), progression-free survival (3.6%), and disease-free survival and treatment-related mortality (1.8% each).

SDH that were evaluated were health care access (53.0%), including insurance status (47.1%) and facility type (28.5%); economic stability (25.0%), including income (81.8%) and poverty (12.1%); education access (14.4%), including high school education (94.7%); and social context (7%), including marital status (100%).

When looking specifically at health care access (n = 70) and social context (n = 10), Miranda-Galvis shared several key takeaways.

“In terms of health care access, this domain was evaluating insurance status; those with Medicaid, Medicare, and who were uninsured had lower survival rates compared with those with private or military health coverage,” she said. “In terms of facility type where the patients were treated, those who didn’t receive treatment at an academic institution or research institution presented with a [worse] mortality compared with those who received treatment at community, comprehensive, or integrated cancer centers.”

Several economic stability (n = 33) and education (n = 19) factors were also associated with a survival disadvantage, including having a lower income and education level. The impact of poverty rate appeared inconclusive, while no significant correlations were observed from unemployment rate, and ninth grade education level.

Reference

Miranda-Galvis M, Tjioe K, Balas A, Cortes J. Cancer disparities in survival of patients with hematologic malignancies in the context of social determinants of health: a systematic review. Presented at: 2023 Society of Hematologic Oncology (SOHO) Annual Meeting; September 6-9, 2023; Houston, TX. Abstract MDS-044.