He L, Ji WS, Jin HL, Lu WJ, Zhang YY, Wang HG, Liu YY, Qiu S, Xu M, Lei ZP, Zheng Q, Yang XL, Zhang Q. Development of a nomogram for predicting liver transplantation prognosis in hepatocellular carcinoma. World J Gastroenterol 2024; 30(21): 2763-2776 [PMID: 38899335 DOI: 10.3748/wjg.v30.i21.2763]
Corresponding Author of This Article
Qing Zhang, MD, Chief Physician, Department of Organ Transplantation, The Third Medical Centre of Chinese PLA General Hospital, No. 69 Yongding Road, Haidian District, Beijing 100039, China. zqy6920@sina.com
Research Domain of This Article
Transplantation
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. Jun 7, 2024; 30(21): 2763-2776 Published online Jun 7, 2024. doi: 10.3748/wjg.v30.i21.2763
Table 1 Characteristics of hepatocellular carcinoma patients, n (%)
Variables
Value
Gender (male/female)
147 (91.9)/13 (8.1)
Age, yr (≤ 50/> 50)
69 (43.1)/91 (56.9)
OS status (survive/dead)
105 (65.5)/55 (34.5)
RFS status (survive/relapsed)
104 (65.0)/56 (35.0)
ALT, U/L (≤ 40/> 40)
91 (56.9)/69 (43.1)
AST, U/L (≤ 40/> 40)
61 (38.1)/99 (61.9)
ALP, U/L (≤ 125/> 125)
108 (67.5)/52 (32.5)
GGT, U/L (≤ 60/> 60)
55 (34.4)/105 (65.6)
AFP, ng/mL (≤ 200/200-1000/> 1000)
107 (66.9)/19 (11.8)/34 (21.3)
GP73, ng/mL (≤ 150/> 150)
84 (52.5)/76 (47.5)
DCP, ng/mL (≤ 40/> 40)
96 (60.0)/64 (40.0)
CK18-M65, U/L (≤ 500/> 500)
48 (30.0)/112 (70.0)
CK18-M30, U/L (≤ 500/> 500)
91 (56.9)/69 (43.1)
Pathological diferentiation (well/moderate/poor)
9 (5.6)/127 (79.4)/24 (15.0)
Number of tumours (solitary/multiple)
79 (49.4)/81 (50.6)
Maximum tumor diameter, cm (≤ 5/> 5)
112 (70.0)/48 (30.0)
Total tumor diameter, cm (≤ 8/> 8)
114 (71.3)/46 (28.7)
Vascular invasion (yes/no)
42 (26.2)/118 (73.8)
Lymph node metastasis (yes/no)
20 (12.5)/140 (87.5)
Membrane invasion (yes/no)
51 (31.9)/109 (68.1)
Microsatellite lesions (yes/no)
79 (49.4)/81 (50.6)
Child-Pugh score (≤ 8/> 8)
116 (71.5)/44 (27.5)
MELD score (≤ 20/> 20)
147 (91.9)/13 (8.1)
Milan (yes/no)
64 (40.0)/96 (60.0)
UCSF (yes/no)
77 (48.1)/83 (51.9)
Hangzhou (yes/no)
109 (68.1)/51 (31.9)
Table 2 The efficacy analysis of biomarkers
Variable
Cut-off
Specificity
Sensitivity
Positive rate
AUC
P value
AFP
400 ng/m L
87%
56%
28%
0.72
< 0.001
DCP
26 ng/m L
71%
69%
42%
0.71
< 0.001
GP73
222 ng/m L
87%
38%
21%
0.62
0.009
CK18-M65
1066 U/L
73%
67%
41%
0.72
< 0.001
CK18-M30
530 U/L
75%
71%
41%
0.73
< 0.001
Table 3 Univariate analysis for overall survival and recurrence-free survival
Variable
n
Overall survival (%)
P value
Recurrence-free survival (%)
P value
1 yr
3 yr
5 yr
1 yr
3 yr
5 yr
Number of tumour
0.054
0.006
Single tumor
79
0.87
0.78
0.75
0.78
0.77
0.75
Multiple tumors
81
0.88
0.64
0.57
0.69
0.55
0.54
Maximum tumor diameter (cm)
< 0.001
< 0.001
> 5
48
0.79
0.50
0.43
0.58
0.45
-
≤ 5
112
0.92
0.80
0.73
0.80
0.75
0.73
Total tumor diameter (cm)
< 0.001
< 0.001
> 8
46
0.74
0.43
0.38
0.43
0.37
0.34
≤ 8
114
0.93
0.82
0.76
0.86
0.78
-
Vascular invasion
< 0.001
< 0.001
Yes
42
0.69
0.50
0.37
0.50
0.33
0.31
No
118
0.90
0.79
0.74
0.82
0.78
-
Lymph node metastasis
0.098
0.129
Yes
20
0.75
0.60
0.49
0.60
0.50
-
No
140
0.92
0.72
0.68
0.75
0.68
0.67
Membrane invasion
0.001
< 0.001
Yes
59
0.78
0.54
0.50
0.76
0.52
0.46
No
101
0.92
0.78
0.72
0.95
0.82
0.76
Microsatellite lesions
0.002
0.001
Yes
79
0.83
0.60
0.52
0.65
0.53
0.51
No
81
0.92
0.81
0.77
0.81
0.79
0.77
AFP
< 0.001
< 0.001
≤ 400
115
0.90
0.82
0.78
0.86
0.79
-
> 400
45
0.82
0.42
0.33
0.42
0.31
0.28
GP73
0.001
< 0.001
≤ 222
126
0.91
0.76
0.73
0.78
0.73
0.72
> 222
34
0.76
0.52
0.34
0.55
0.38
-
DCP
< 0.001
< 0.001
≤ 26
92
0.91
0.82
0.81
0.85
0.82
0.81
> 26
68
0.83
0.55
0.44
0.57
0.42
0.41
CK18-M65 (U/L)
< 0.001
< 0.001
≤ 1066
95
0.93
0.84
0.81
0.85
0.80
0.80
> 1066
65
0.80
0.52
0.41
0.56
0.43
0.41
CK18-M30 (U/L)
< 0.001
<0.001
≤ 530
95
0.94
0.86
0.83
0.86
0.83
0.82
> 530
65
0.78
0.49
0.39
0.54
0.40
0.39
MC
< 0.001
< 0.001
Yes
64
0.97
0.86
0.82
0.88
0.83
0.81
No
96
0.82
0.61
0.55
0.63
0.54
0.53
UCSF
< 0.001
< 0.001
Yes
77
0.97
0.89
0.85
0.90
0.87
0.85
No
83
0.79
0.54
0.46
0.57
0.47
0.45
Hangzhou
< 0.001
< 0.001
Yes
109
0.95
0.83
0.78
0.86
0.81
0.80
No
51
0.80
0.45
0.37
0.47
0.33
0.31
Table 4 Multivariate Cox hazards analysis for overall survival
Variable
B
SE
HR
95%CI
P value
AFP > 400 ng/mL
1.22
0.28
3.38
1.95-5.88
< 0.001
CK18-M30 > 530 U/L
1.14
0.31
3.15
1.69-5.87
< 0.001
TTD > 8 cm
0.92
0.28
2.52
1.45-4.40
0.001
Table 5 Multivariate Cox hazards analysis for recurrence-free survival
Variable
B
SE
HR
95%CI
P value
AFP > 400 ng/mL
1.45
0.28
4.28
2.47-7.40
< 0.001
CK18-M30 > 530 U/L
0.97
0.31
2.66
1.44-4.91
0.002
TTD > 8 cm
1.10
0.28
3.03
1.73-5.29
< 0.001
Table 6 The area under the curve comparison of the nomogram with the other standards
Overall survival
Recurrence-free survival
Nomogram
Milan
UCSF
Hangzhou
Nomogram
Milan
UCSF
Hangzhou
t = 1-yr
0.78
0.66
0.70
0.72
0.86
0.65
0.72
0.73
t = 3-yr
0.85
0.65
0.71
0.71
0.88
0.66
0.73
0.73
t = 5-yr
0.87
0.67
0.72
0.73
0.91
0.68
0.74
0.76
Table 7 Division of the risk classification and 5-year survival rate
Low risk
Middle risk
High risk
OS
Total points
0-98
100-198
215-315
5-yr survival rate
≥ 90%
70%-89%
≤ 30%
RFS
Total points
0-100
108-208
208-280
5-yr survival rate
≥ 90%
45%-89%
≤ 45%
Citation: He L, Ji WS, Jin HL, Lu WJ, Zhang YY, Wang HG, Liu YY, Qiu S, Xu M, Lei ZP, Zheng Q, Yang XL, Zhang Q. Development of a nomogram for predicting liver transplantation prognosis in hepatocellular carcinoma. World J Gastroenterol 2024; 30(21): 2763-2776