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

doi:10.4251/wjgo.v18.i4.115635

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World Journal of Gastrointestinal Oncology

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1948-5204

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Baishideng Publishing Group Inc, 7041 Koll Center Parkway, Suite 160, Pleasanton, CA 94566, USA

Retrospective Cohort Study

Copyright: ©Author(s) 2026. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution-NonCommercial (CC BY-NC 4.0) license. No commercial re-use. See permissions. Published by Baishideng Publishing Group Inc.

World J Gastrointest Oncol. Apr 15, 2026; 18(4): 115635
Published online Apr 15, 2026. doi: 10.4251/wjgo.v18.i4.115635

Table 2 Baseline characteristics of the study population, n (%)

Characteristic	Training cohort (n = 154)			Internal validation cohort (n = 66)			External validation cohort (n = 58)			P value
Characteristic	LNM (n = 54)	non-LNM (n = 100)	P value	LNM (n = 29)	non-LNM (n = 37)	P value	LNM (n = 24)	non-LNM (n = 34)	P value	P value
Sex			0.493	-		0.530	-		0.286	0.112
Male	37 (68.5)	63 (63.0)		15 (51.7)	22 (59.5)		14 (58.3)	15 (44.1)
Female	17 (31.5)	37 (37.0)		14 (48.3)	15 (40.5)		10 (41.7)	19 (55.9)
Age (years), median (IQR)	64.50 (57.00, 74.00)	69.50 (61.00,77.00)	0.054	70.00 (58.50, 72.50)	72.00 (62.50, 78.50)	0.047	66.50 (58.25, 71.00)	67.00 (62.75, 72.00)	0.448	0.203
Height (cm), median (IQR)	165.00 (160.00, 170.25)	165.00 (160.00, 170.00)	0.968	165.00 (159.00,171.00)	165.00 (158.00, 172.00)	0.801	161.50 (156.75, 170.00)	164.00 (155.00, 168.00)	0.776	0.245
Weight (kg), median (IQR)	62.00 (54.75, 68.25)	62.00 (55.00, 68.00)	0.847	65.00 (61.00, 70.00)	60.00 (53.00, 67.50)	0.108	60.50 (52.50, 69.50)	60.50 (54.50, 66.50)	0.937	0.424
BMI, median (IQR)	22.98 (20.42, 24.37)	22.63 (20.55, 24.65)	0.913	23.44 (22.22, 24.67)	22.21 (20.13, 25.37)	0.272	23.14 (20.70, 24.93)	22.99 (20.68, 24.93)	0.819	0.616
Location			0.112	-		0.375	-		0.314	0.254
RCC	21 (38.9)	23 (23.0)		6 (20.7)	8 (21.6)		6 (25.0)	6 (17.6)
LCC	14 (25.9)	31 (31.0)		9 (31.0)	17 (45.9)		8 (33.3)	7 (20.6)
RC	19 (35.2)	46 (46.0)		14 (48.3)	12 (3.24)		10 (41.7)	21 (61.8)
CRP (mg/L), median (IQR)	2.06 (0.53, 7.02)	3.19 (0.50, 11.82)	0.740	2.39 (0.63, 8.17)	5.00 (0.67, 8.43)	0.725	5.00 (0.66, 10.99)	0.87 (0.50, 8.39)	0.068	0.595
LDL (mmol/L), median (IQR)	2.13 (1.61, 2.85)	2.21 (1.85, 2.90)	0.153	2.40 (1.91, 2.98)	1.97 (1.55, 2.41)	0.041	2.07 (1.72, 2.70)	2.85 (2.24, 3.62)	0.011	0.058
CEA (ng/mL)			< 0.001	-		0.366	-		0.467	0.678
≤ 5	27 (50.0)	77 (77.0)		19 (65.5)	28 (75.7)		14 (58.3)	23 (67.6)
> 5	27 (50.0)	23 (23.0)		10 (34.5)	9 (24.3)		10 (41.7)	11 (32.4)
CA 19-9 (U/mL)			< 0.001	-		0.035	-		0.651	0.333
≤ 37	34 (63.0)	91 (91.0)		21 (72.4)	34 (91.9)		21 (87.5)	31 (91.2)
> 37	20 (37.0)	9 (9.0)		8 (27.6)	3 (8.1)		3 (12.5)	3 (8.8)

LNM: Lymph node metastasis; IQR: Interquartile range; 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.

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Citation: Lei XD, Qian GX, Sun ZG, Tang ZQ, Liu YC, Du R, Li YH. Deep learning radiomics nomogram based on multi-regional features for predicting lymph node metastasis and prognosis in colorectal cancer. World J Gastrointest Oncol 2026; 18(4): 115635
URL: https://www.wjgnet.com/1948-5204/full/v18/i4/115635.htm
DOI: https://dx.doi.org/10.4251/wjgo.v18.i4.115635

Lei XD, Qian GX, Sun ZG, Tang ZQ, Liu YC, Du R, Li YH. Deep learning radiomics nomogram based on multi-regional features for predicting lymph node metastasis and prognosis in colorectal cancer. World J Gastrointest Oncol 2026; 18(4): 115635 [DOI: 10.4251/wjgo.v18.i4.115635]

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