Deep learning radiomics nomogram based on multi-regional features for predicting lymph node metastasis and prognosis in colorectal cancer

Table 3 Univariate and multivariate logistic regression analysis

Variable	Univariate analysis		Multivariate analysis
	OR (95%CI)	P value	OR (95%CI)	P value
Sex
Male	1 (Ref.)	-	-	-
Female	0.782 (0.387-1.581)	0.494	-	-
Age	0.975 (0.949-1.002)	0.070	0.982 (0.953-1.012)	0.235
Height	1.009 (0.962-1.060)	0.703	-	-
Weight	0.997 (0.961-1.034)	0.865	-	-
BMI	0.972 (0.869-1.008)	0.624	-	-
Location
RCC	1 (Ref.)	-	1 (Ref)	-
LCC	0.495 (0.208-1.175)	0.111	0.552 (0.227-1.342)	0.190
RC	0.452 (0.204-1.004)	0.051	0.583 (0.228-1.492)	0.261
CRP	0.997 (0.988-1.006)	0.520	-	-
LDL	0.697 (0.445-1.094)	0.117	-	-
CEA
≤ 5	1 (Ref.)	-	1 (Ref)	-
> 5	3.348 (1.649-6.797)	< 0.001	2.597 (1.199-5.623)	0.015
CA 19-9
≤ 37	1 (Ref.)	-	1 (Ref)	-
> 37	5.948 (2.467-14.337)	< 0.001	3.704 (1.435-9.563)	0.007

OR: Odds ratios; CI: Confidence interval; BMI: Body mass index; RCC: Right-sided colon cancer; LCC: Left-sided colon cancer; RC: Rectal cancer; CRP: C-reactive protein; LDL: Low-density lipoprotein; CEA: Carcinoembryonic antigen; CA 19-9: Carbohydrate antigen 19-9.