Lai RM, Wang MM, Lin XY, Zheng Q, Chen J. Clinical value of predictive models based on liver stiffness measurement in predicting liver reserve function of compensated chronic liver disease. World J Gastroenterol 2022; 28(42): 6045-6055 [PMID: 36405384 DOI: 10.3748/wjg.v28.i42.6045]
Corresponding Author of This Article
Jing Chen, MD, Chief Physician, Professor, Department of Hepatology, Hepatology Research Institute, The First Affiliated Hospital, Fujian Medical University, No. 20 Chazhong Road, Taijiang District, Fuzhou 350005, Fujian Province, China. mykelchen@sina.com
Research Domain of This Article
Infectious Diseases
Article-Type of This Article
Retrospective Cohort 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. Nov 14, 2022; 28(42): 6045-6055 Published online Nov 14, 2022. doi: 10.3748/wjg.v28.i42.6045
Table 1 Comparison of demographic and clinical characteristics of chronic liver disease patients in the training cohort and validation cohort
Validation cohort, n = 132
Training cohort, n = 360
P value
Gender (male/female, n)
90/42
260/100
0.381
Age (yr)
54.84 ± 27.70
48.71 ± 13.34
0.001
Etiology
0.097
HBV
111
278
Others
21
82
HCC (n)
42
63
0.001
HB (g/dL)
14.28 ± 10.86
13.71 ± 2.16
0.346
PLT (× 109/L)
174.96 ± 83.93
170.95 ± 74.69
0.610
PT (s)
13.21 ± 1.66
12.84 ± 1.67
0.030
APTT (s)
33.28 ± 7.73
32.54 ± 6.14
0.273
INR
1.16 ± 0.16
1.09 ± 0.16
0.000
AST (U/L)
72.14 ± 78.19
86.16 ± 135.81
0.264
ALT (U/L)
106.35 ± 166.60
136.73 ± 247.37
0.192
ALB (g/L)
38.03 ± 5.22
40.03 ± 5.08
0.000
TBIL (μmol/L)
28.29 ± 31.05
19.94 ± 16.99
0.000
CHE (U/L)
6163.11 ± 2647.19
6748.44 ± 2127.44
0.015
ALP (U/L)
118.60 ± 95.93
179.64 ± 721.94
0.334
GGT (U/L)
128.91 ± 201.79
116.89 ± 188.75
0.539
GLO (g/L)
28.70 ± 4.81
29.02 ± 5.19
0.534
Cr (μmol/L)
65.36 ± 23.23
65.68 ± 15.38
0.860
MELD
8.14 ± 3.46
7.80 ± 2.56
0.241
ALBI
-2.36 ± 0.54
-2.60 ± 0.48
0.000
PTAR
0.31 ± 0.07
0.28 ± 0.07
0.000
ICGR15 (%)
11.55 ± 11.82
8.16 ± 8.56
0.000
LSM (kPa)
19.54 ± 18.28
16.34 ± 16.62
0.066
Table 2 Multivariate logistic stepwise regression analysis of indocyanine green retention rate at 15 min ≥ 10% in the training cohort
Variable
B
SE
Wald
P value
OR (95%CI)
LSM (kPa)
1.472
0.338
19.008
< 0.001
4.357 (2.248-8.445)
PTAR
1.265
0.335
14.260
< 0.001
3.544 (1.838-6.835)
Age (yr)
0.047
0.012
15.329
< 0.001
1.048 (1.024-1.073)
MELD
0.291
0.078
13.844
< 0.001
1.337 (1.147-1.558)
Constant
-7.600
1.022
55.302
< 0.001
0.007
Table 3 Multivariate logistic stepwise regression analysis of indocyanine green retention rate at 15 min ≥ 20% in the training cohort
Variable
B
SE
Wald
P value
OR (95%CI)
LSM (kPa)
1.138
0.520
4.778
0.029
3.120 (1.125-8.656)
PTAR
1.260
0.521
5.825
0.016
3.524 (1.267-9.801)
Age (yr)
0.058
0.017
11.226
0.001
1.059 (1.024-1.096)
MELD
0.320
0.094
11.652
0.001
1.377 (1.146-1.655)
Constant
-9.750
-1.454
44.963
< 0.001
0.001
Table 4 Comparison of the predictive performance of the new constructed models (mLPaM and sLPaM) and other models in the assessment of impaired liver reserve function in the training cohort
AUC (95%CI)
Optimal cut-off
Sensitivity (%)
Specificity (%)
PPV (%)
NPV (%)
Accuracy (%)
mLPaM
0.855 (0.809-0.901)
0.135
91.3
66.4
36.09
97.35
70.68
MELD
0.752 (0.688-0.817)
7.662
80.0
61.4
31.25
93.33
54.75
ALBI
0.776 (0.717-0.835)
-2.557
76.3
67.9
37.67
91.85
69.90
PTAR
0.728 (0.664-0.791)
0.150
73.8
71.8
42.11
90.79
72.24
LSM (kPa)
0.733 (0.672-0.794)
1.50
78.8
67.9
37.67
92.86
70.05
sLPaM
0.872 (0.823-0.921)
0.046
96.8
64.6
14.83
99.69
66.53
MELD
0.786 (0.687-0.886)
9.380
71.0
85.2
35.45
96.25
83.74
ALBI
0.798 (0.706-0.890)
-2.220
64.5
87.4
39.81
95.01
84.78
PTAR
0.731 (0.644-0.818)
0.150
80.6
65.5
15.33
97.76
66.59
LSM (kPa)
0.706 (0.618-0.795)
1.50
80.6
60.6
12.79
97.76
61.94
Table 5 Comparison of the predictive performance of the new constructed models (mLPaM and sLPaM) and other models in the assessment of impaired liver reserve function in the prospective validation cohort
AUC (95%CI)
Optimal cut-off
Sensitivity (%)
Specificity (%)
PPV (%)
NPV (%)
Accuracy (%)
mLPaM
0.869 (0.810-0.929)
0.240
89.1
74.4
60.85
93.86
78.94
MELD
0.729 (0.633-0.824)
9.743
43.5
96.5
93.65
59.01
67.74
ALBI
0.824 (0.749-0.900)
-2.315
78.3
76.7
63.78
87.09
77.25
PTAR
0.672 (0.580-0.765)
1.500
89.1
45.3
30.70
93.86
54.66
LSM (kPa)
0.782 (0.702-0.862)
1.500
91.3
65.1
49.93
95.15
72.33
sLPaM
0.876 (0.812-0.940)
0.073
92.9
68.3
49.94
95.15
72.33
MELD
0.803 (0.701-0.904)
9.187
64.3
85.6
61.54
87.00
79.98
ALBI
0.836 (0.743-0.929)
-1.897
71.4
88.5
67.44
90.27
84.22
PTAR
0.666 (0.566-0.767)
1.500
92.9
59.6
28.43
97.98
64.50
LSM (kPa)
0.743 (0.653-0.833)
1.500
92.9
55.8
25.37
97.98
60.96
Citation: Lai RM, Wang MM, Lin XY, Zheng Q, Chen J. Clinical value of predictive models based on liver stiffness measurement in predicting liver reserve function of compensated chronic liver disease. World J Gastroenterol 2022; 28(42): 6045-6055