Education and insurance status: Impact on treatment and survival of sinonasal cancer patients

Abstract

Objectives/Hypothesis To understand the impact of education and insurance as social determinants of health on sinonasal cancer treatment and outcomes. Study Design Retrospective cohort study using the Surveillance, Epidemiology, and End Results (SEER) database. Methods Demographics, tumor characteristics, location, stage at diagnosis, treatment, and survival data for 1,365 patients diagnosed with sinonasal cancers were extracted from the SEER database. All statistical analyses were performed using SAS 9.5. The Fine and Grey method was used to assess covariate impacts. Results Medicaid patients were more likely to live in counties with lower educational levels (8.32% vs. 6.46% below ninth grade education, P < .0001) and lower median household incomes ($56,316 vs. $60,284, P = .0004). Medicaid patients presented with later (T3‐T4) stage disease compared to other insurances (P = .0007) and larger tumor size (P = .011). Medicaid patients were less likely to have surgery recommended (P = .0017) or receive surgery as part of their treatment (P = .0033). Analysis of histology‐specific 5‐year survival rates were lower for Medicaid patients with squamous cell carcinoma (SCCA) (P = .016). Conclusions This is the first and largest study to examine how education and insurance status may impact treatment and outcomes in sinonasal cancers. It is the first using this method of examining other covariates and informing associated risk. Patients with Medicaid and less education present with larger sinonasal cancers. They are less likely to have surgery recommended or receive surgery. For SCCA, the most common histology, Medicaid patients have significantly worse survival. Further emphasis on education and improving health literacy is needed in the at‐risk Medicaid populations. Level of Evidence NA Laryngoscope, 130:649–658, 2020

Predicting salvage laryngectomy in patients treated with primary nonsurgical therapy for laryngeal squamous cell carcinoma using machine learning

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“…Finally, multivariable analysis found education to be an important factor in predicting need for STL; patients living in zip codes where a higher proportion of residents completed high school were less likely to require STL. Understood as a proxy for either health literacy or socioeconomic status, the protective effect of education has been previously described in the literature 55‐59 …”

Sinonasal adenocarcinoma: Population‐based analysis of demographic and socioeconomic disparities

“…In head and neck oncology, HDs have been reported when comparing disparities across race/ethnicity 12–15 and insurance status 16 . Similar findings have been reported for sinonasal malignancies 17–19 . In separate population‐based analyses looking at survival in sinonasal squamous cell carcinoma, Sanghvi et al found that white race had the highest 20 year survival 18 and Turner et al found that black race had the worst survival 19 .…”

“…16 Similar findings have been reported for sinonasal malignancies. [17][18][19] In separate population-based analyses looking at survival in sinonasal squamous cell carcinoma, Sanghvi et al found that white race had the highest 20 year survival 18 and Turner et al found that black race had the worst survival. 19 When stratifying patients by geographic location, Zhou et al found that patients from the southern United States had the worse long-term disease specific survival.…”

Comorbidity burden and nonclinical factors associated with sinonasal cancer all‐cause mortality

“…Second, health insurance status is a known proxy for access to sinonasal cancer care and outcomes in the United States . Modifying this risk factor for sinonasal cancer survival would also mean improved access to care for this population of patients and providing standard quality care irrespective of health insurance status, thereby decreasing cancer‐related health disparities.…”