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©The Author(s) 2024.
World J Gastroenterol. Sep 28, 2024; 30(36): 4044-4056
Published online Sep 28, 2024. doi: 10.3748/wjg.v30.i36.4044
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
- URL: https://www.wjgnet.com/1007-9327/full/v30/i36/4044.htm
- DOI: https://dx.doi.org/10.3748/wjg.v30.i36.4044