A Six-Gene Signature Predicts Survival of Adenocarcinoma Type of Non-Small-Cell Lung Cancer Patients: A Comprehensive Study Based on Integrated Analysis and Weighted Gene Coexpression Network

Table 4

Multivariate Cox regression analysis of lightcyan module genes and overall survival.

Genes	β	HR	selogHR	z	CI (95% Cl)
RRAGB	−0.2491	0.7795	0.1360	−1.83	0.5971–1.0176	0.06700
RSPH9	−0.0679	0.9344	0.0462	−1.47	0.8535–1.0230	0.14201
RPS6KL1	−0.2317	0.7932	0.0608	−3.81	0.7042–0.8935	0.00014^#
RTL1	0.1104	1.1167	0.0380	2.91	1.0367–1.2030	0.00364^#
RXFP1	−0.1035	0.9016	0.0497	−2.08	0.8180–0.9939	0.03720^#
RRM2	0.1571	1.1701	0.0626	2.51	1.0350–1.3229	0.01209^#

The listed genes were selected by the Akaike information criterion (AIC) model from the significant genes after the univariate Cox regression analysis (Table 3). Multivariate Cox regression analysis of association of the listed genes with survival was performed to reveal the independent predictor for survival and generate a prognostic risk score model. β, regression coefficient; HR, hazard ratio; CI, confidence interval; ^#.