Statistical Analysis
Population demographics were compared across exposure groups using the independent-samples t-test and χ2 test, as appropriate. Univariable logistic regression analysis was conducted to assess the relationship between insurance status and treatment type.10 A multivariate logistic regression model was also used to determine this association. The model was adjusted for age, sex, year of diagnosis, marital status, race, and primary site. Given a low level of missingness for all covariates, missing data was handled using the complete case method. Sensitivity analyses were performed to assess the effect of cancer stage (T4a or T4b) and oral cavity subsite. Sensitivity analyses were also performed to assess the effect of ACA adoption (year of diagnosis 2007-2013 versus 2014-2016). Outcome measures were reported as odds ratios (ORs) and associated 95% confidence intervals (95% CIs). A p-value of <0.05 was set as the cut-off for statistical significance. All statistical analyses were performed using Stata software, v 15.1 (Stata Corp, College Station, Texas).