. 2025 Aug 21;15:30778. doi: 10.1038/s41598-025-05025-w

Table 2.

Multivariate logistic regression analyses of oral squamous cell carcinoma patients.

Gene	Estimate	Standard error	Odds ratio	95% CI Lower	95% CI upper	P-value
Genes associated with radiotherapy (RT) response
CLTCL1	2.860	1.000	17.461	2.830	161.915	0.004^a
ENPP7	2.412	1.068	11.152	1.504	115.082	0.024^a
TJP3	2.529	1.127	12.535	1.577	150.578	0.025^a
ARHGEF19	1.657	1.000	5.242	0.717	41.088	0.098
H3C12	1.404	0.659	4.069	1.168	16.174	0.033^a
MROH9	1.204	0.643	3.332	0.977	12.626	0.061
CES5A	−1.523	1.051	0.218	0.019	1.361	0.147
Genes associated with concurrent chemoradiotherapy (CCRT) response
EVPL	−4.824	1.766	0.008	0.0001	0.143	0.006^a
SLC35G5	2.257	0.870	9.555	1.947	64.274	0.010^a
ANO8	−2.966	1.180	0.0515	0.004	0.390	0.012^a
TJP3	3.810	1.563	45.161	3.157	2099.978	0.015^a
GARS1	3.339	1.883	28.201	1.285	2797.726	0.076
MAP3K2	2.924	1.846	18.620	0.650	1422.276	0.113
RAB2A	18.295	2475.443	88200000.0	< 0.0001		0.994
EMID1	−4.732	2.178	0.009	< 0.0001	0.246	0.030^a
CAPN8	1.466	0.896	4.332	0.805	30.214	0.102

Multivariate logistic regression models were developed to predict 24-month overall survival in patients treated with radiotherapy (RT) or concurrent chemoradiotherapy (CCRT), based on genes significantly associated with prognosis in each treatment group. Gene selection was performed using Stepwise inclusion and exclusion guided by the Akaike information criterion (AIC). The final models demonstrated strong predictive performance, with an area under the curve (AUC) of 0.89 for the RT group and 0.94 for the CCRT group.

CI Confidence interval.

^a p < 0.05, multivariate logistic regression analyses.