Association of Demographic and Geospatial Factors With Treatment Selection for Laryngeal Cancer.

Importance Guidelines for many head and neck cancers, especially laryngeal cancers, allow for multiple treatment options. Currently, inequitable provision of surgery may contribute to outcome disparities. However, the role of geospatial factors remains understudied. Objective To assess the association between US geospatial factors and treatment selection for patients with laryngeal cancer. Design, Setting, and Participants In this retrospective cohort study, patients diagnosed with laryngeal squamous cell carcinoma between January 1, 2004, and December 31, 2014, were identified from the Surveillance, Epidemiology, and End Results database. Adjusted odds ratios (aORs) for surgical treatment were generated from multivariable, hierarchical models to assess associations with oncologic, demographic, and county variables. Outlier US counties with the highest and lowest aORs were described. Data analysis was performed from April 29 to September 11, 2020. Exposures County of residence. Main Outcomes and Measures The aORs for surgical treatment were generated from multivariable, hierarchical models. Outlier counties with the highest and lowest aORs are described. Results The cohort includes 21 289 patients (mean [SD] age, 63.6 [11.2] years; 17 214 [80.9%] male) in 598 counties. Most counties had no otolaryngologist (365 [61.0%]) or radiation oncologist (434 [72.6%]). Surgery rates varied from 7.1% to 85.7% among counties with at least 10 cases. After oncologic variables were controlled for, factors independently associated with surgical treatment included patient age (aOR [95% CI], 0.94; 0.91-0.98 per 10 years), marital status (single versus married: aOR [95% CI], 0.87 [0.79-0.97]), and county social deprivation index (aOR [95% CI], 0.98 [0.97-1.00 per 5 points]) but not physician number (≥2 otolaryngologists: aOR [95% CI], 0.91 [0.75-1.11] vs ≥1 radiation oncologist: aOR [95% CI], 0.91; 0.75-1.11). The 5% of counties most likely to provide surgery (aOR, >1.23) were nearly all large metropolitan areas (2593 patients [93.3%]) and treated a disproportionately large number of patients (2778 [13.1%]). The 5% of counties least likely to provide surgery (aOR, <0.79) were also mostly large metropolitan areas (1676 patients [91.2%]) and treated a disproportionately large number of patients (1838 [8.6%]). Patients in counties least likely to provide surgery had inferior survival compared with those most likely to provide surgery (adjusted hazard ratio, 1.16; 95% CI, 1.00-1.35). Conclusions and Relevance These findings suggest that sociodemographic factors contribute to the wide variety in surgical treatment practices by county. The largest metropolitan counties were often outliers regarding their adjusted odds of surgical treatment. This finding is concerning for the counties least likely to provide surgery where survival is inferior.