Table 1.

Multivariable logistic regression analysis for predictors of receiving No Treatment (N = 446,383)

Odds Ratio Estimates
Effect	Point Estimate	95% Wald Confidence Limits		p-value
Age	1.053	1.052	1.054	< 0.0001
Sex				0.0038
Male vs. Female	0.976	0.961	0.992
Race				< 0.0001
Black vs. White	1.245	1.214	1.277
Other vs. White	1.337	1.184	1.509
Unknown vs. White	1.538	1.415	1.671
Insurance Status				< 0.0001
Unknown vs. Not Insured	0.674	0.627	0.723
Medicaid vs. Not Insured	0.784	0.746	0.825
Medicare vs. Not Insured	0.504	0.482	0.526
Other Government vs. Not Insured	0.466	0.428	0.508
Private Insurance vs. Not Insured	0.453	0.433	0.473
Income				< 0.0001
High vs. Low	0.907	0.884	0.930
Middle vs. Low	0.919	0.897	0.941
Education				< 0.0001
High vs. Low	0.827	0.807	0.847
Middle vs. Low	0.885	0.866	0.904
Charlson-Deyo Score				< 0.0001
1 vs. 0	1.176	1.155	1.198
2 vs. 0	1.582	1.546	1.620
Year of Diagnosis	0.991	0.988	0.994	< 0.0001
Stage				< 0.0001
II vs. I	1.302	1.252	1.354
IIIA vs. I	1.727	1.666	1.790
IIIB vs. I	2.207	2.133	2.283
IV vs. I	3.069	2.985	3.155
Histology				< 0.0001
Other vs. Adenocarcinoma	1.052	1.033	1.073
Squamous vs. Adenocarcinoma	1.008	0.987	1.029
Facility Type				< 0.0001
Academic/Research Program vs. Community Cancer Program	0.772	0.752	0.793
Comprehensive Community Cancer Program vs. Community Cancer Program	0.862	0.842	0.883
Other specified types of cancer programs vs. Community Cancer Program	1.088	0.903	1.311
Tumor Size (mm)	1.000	1.000	1.001	< 0.0001
Clinical N Status				< 0.0001
cN1 vs. cN0	0.915	0.887	0.944
cN2 vs.CN0	0.934	0.912	0.957
cN3 vs. CN0	0.789	0.766	0.813