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).