Peng YJ, Liu X, Liu Y, Tang X, Zhao QP, Du Y. Computed tomography-based multi-organ radiomics nomogram model for predicting the risk of esophagogastric variceal bleeding in cirrhosis. World J Gastroenterol 2024; 30(36): 4044-4056 [PMID: 39351251 DOI: 10.3748/wjg.v30.i36.4044]
Corresponding Author of This Article
Yong Du, MD, Professor, Department of Radiology, The Affiliated Hospital of North Sichuan Medical College, No. 1 Maoyuannan Road, Nanchong 637000, Sichuan Province, China. duyong@nsmc.edu.cn
Research Domain of This Article
Gastroenterology & Hepatology
Article-Type of This Article
Retrospective Study
Open-Access Policy of This Article
This article is an open-access article which was selected by an in-house editor and fully peer-reviewed by external reviewers. It is distributed in accordance with the Creative Commons Attribution Non Commercial (CC BY-NC 4.0) license, which permits others to distribute, remix, adapt, build upon this work non-commercially, and license their derivative works on different terms, provided the original work is properly cited and the use is non-commercial. See: http://creativecommons.org/licenses/by-nc/4.0/
World J Gastroenterol. Sep 28, 2024; 30(36): 4044-4056 Published online Sep 28, 2024. doi: 10.3748/wjg.v30.i36.4044
Table 1 Clinical characteristics of the patients, n (%)
Characteristics
Training cohort (n = 145)
Validation cohort (n = 63)
P value
Age (years)
54.6 ± 11.6
54.3 ± 13.8
0.869
Sex
0.250
Male
82 (56.6)
41 (65.1)
Female
63 (43.4)
22 (34.9)
Etiology
0.112
HBV
95 (65.5)
44 (69.8)
Alcohol
18 (12.4)
1 (1.6)
PBC
9 (6.2)
4 (6.3)
AIH
5 (3.4)
1 (1.6)
HCV
2 (1.4)
2 (3.2)
HLD
2 (1.4)
1 (1.6)
Other
14 (9.7)
10 (15.9)
Ascites
0.624
Absent
66 (45.5)
31 (49.2)
Present
79 (54.5)
32 (50.8)
Hypertension
0.149
Absent
129 (89.0)
60 (95.2)
Present
16 (11.0)
3 (4.8)
PVT
0.175
Absent
118 (81.4)
46 (73)
Present
27 (18.6)
17 (27)
Child-Pugh
0.629
Class A
55 (37.9)
27 (42.9)
Class B
68 (46.9)
25 (39.7)
Class C
22 (15.2)
11 (17.5)
AFP (μg/L)
0.772
< 20
122 (84.1)
54 (85.7)
≥ 20
23 (15.9)
9 (14.3)
ALB (g/L), mean ± SD
34.5 ± 6.0
33.5 ± 6.0
0.271
PT (second), median (range)
16.1 (14.9-17.5)
15.8 (14.7-17.4)
0.480
PLT (109/L), median (range)
54.0 (41.0-73.5)
57.0 (43.0-84.0)
0.395
ALT (U/L), median (range)
28.0 (19.5-50.0)
31.0 (21.0-57.0)
0.362
AST (U/L), median (range)
42.0 (29.5-69.0)
45.0 (29.0-73.0)
0.754
GGT (U/L), median (range)
44.0 (24.0-97.5)
44.0 (24.0-97.0)
0.953
TBIL (μmol/L), median (range)
28.0 (20.4-44.1)
23.1 (18.3-43.9)
0.226
DBIL (μmol/L), median (range)
10.0 (6.9-16.4)
9.1 (6.4-16.8)
0.712
IBIL (μmol/L), median (range)
17.8 (11.7-27.3)
14.9 (10.3-22.5)
0.076
Table 2 Univariate and multivariable analysis of clinical variables
Variables
Univariate logistic regression
Multivariable logistic regression
OR (95%CI)
P value
OR (95%CI)
P value
Age
1.000 (0.978-1.022)
0.973
Sex
1.677 (0.959-2.932)
0.070
Etiology
1.008 (0.880-1.154)
0.905
Ascites
2.826 (1.597-5.001)
< 0.001
2.625 (1.367-5.039)
0.004
Hypertension
0.690 (0.268-1.775)
0.441
PVT
4.622 (2.215-9.645)
< 0.001
3.500 (1.547-7.916)
0.003
Child-Pugh
1.352 (0.916-2.007)
0.130
AFP
0.977 (0.457-2.088)
0.953
ALB
0.965 (0.921-1.011)
0.135
PT
1.158 (1.032-1.299)
0.013
1.199 (1.033-1.390)
0.017
PLT
0.999 (0.992-1.007)
0.832
ALT
0.978 (0.966-0.991)
0.001
AST
0.982 (0.973-0.992)
0.001
GGT
0.998 (0.995-1.001)
0.136
TBIL
0.996 (0.988-1.005)
0.405
DBIL
0.994 (0.981-1.008)
0.427
IBIL
0.995 (0.977-1.012)
0.546
Table 3 Area under the receiver operating characteristic curve values of different models in training and validation cohorts
Models
Training cohort
Validation cohort
AUC (95%CI)
P value
AUC (95%CI)
P value
Rad-score (liver)
0.801 (0.727-0.875)
< 0.001
0.763 (0.646-0.880)
0.002
Rad-score (spleen)
0.831 (0.766-0.897)
< 0.001
0.792 (0.677-0.906)
0.016
Rad-score (esophagus)
0.864 (0.807-0.922)
< 0.001
0.857 (0.762-0.952)
0.109
Rad-score (liver+ spleen + esophagus)
0.930 (0.891-0.970)
0.049
0.886 (0.808-0.964)
0.139
Clinical model
0.727 (0.644-0.811)
< 0.001
0.692 (0.556-0.828)
< 0.001
RC model
0.951 (0.919-0.983)
0.93 (0.872-0.987)
Table 4 Evaluation of predictive performance in training and validation cohorts
Models
Cohort
Sensitivity
Specificity
Accuracy
PPV
NPV
Rad-score (liver)
Training
0.656
0.815
0.745
0.737
0.750
Validation
0.643
0.686
0.667
0.621
0.706
Rad-score (spleen)
Training
0.750
0.765
0.759
0.716
0.795
Validation
0.714
0.829
0.778
0.769
0.784
Rad-score (esophagus)
Training
0.734
0.802
0.772
0.746
0.793
Validation
0.786
0.857
0.825
0.815
0.833
Rad-score (liver + spleen + esophagus)
Training
0.844
0.852
0.848
0.818
0.873
Validation
0.779
0.886
0.794
0.826
0.775
Clinical model
Training
0.531
0.790
0.676
0.667
0.687
Validation
0.571
0.686
0.635
0.600
0.667
RC model
Training
0.875
0.877
0.876
0.848
0.899
Validation
0.821
0.857
0.841
0.821
0.857
Citation: Peng YJ, Liu X, Liu Y, Tang X, Zhao QP, Du Y. Computed tomography-based multi-organ radiomics nomogram model for predicting the risk of esophagogastric variceal bleeding in cirrhosis. World J Gastroenterol 2024; 30(36): 4044-4056