Nomogram Based on Platelet–Albumin–Bilirubin for Predicting Tumor Recurrence After Surgery in Alpha-Fetoprotein-Negative Hepatocellular Carcinoma Patients

Figures & data

Figure 1 Flow chart of the study design.

Table 1 Baseline and Clinicopathological Characteristics of Alpha-Fetoprotein-Negative Hepatocellular Carcinoma Patients

Variables	Recurrence-Free Group (N=92)	Recurrence Group (N=102)	X^2	P
Gender			0.000	0.985
Male	82 (89.1%)	91 (89.2%)
Female	10 (12.2%)	11 (10.8%)
Age, years			0.204	0.651
≥50	65 (70.7%)	69 (67.6%)
<50	27 (29.3%)	33 (32.4%)
PT, seconds			0.000	0.996
>13	9 (9.8%)	10 (9.8%)
≤13	83 (90.2%)	92 (90.2%)
WBC, ×10^9/L			0.004	0.951
>10	7 (7.6%)	8 (7.8%)
≤10	85 (92.4%)	94 (92.2%)
HB,g/L			1.829	0.176
≥120	87 (94.6%)	91 (89.2%)
<120	5 (5.4%)	11 (10.8%)
PLT, ×10^9/L			0.830	0.362
≥100	87 (94.6%)	93 (91.2%)
<100	5 (5.4%)	9 (8.8%)
Na, mmol/L			0.250	0.617
≥135	87 (94.6%)	98 (96.1%)
<135	5 (5.4%)	4 (3.9%)
ALT, U/L			0.340	0.560
>50	25 (27.2%)	24 (23.5%)
≤50	67 (72.8%)	78 (76.5%)
AST, U/L			0.891	0.345
>40	31 (33.7%)	28 (27.5%)
≤40	61 (66.3%)	74 (72.5%)
Tbil,U/L			0.006	0.937
>17.1	23 (25%)	26 (25.5%)
≤17.1	69 (75%)	76 (74.4%)
ALB,g/L			3.684	0.055
≥30	92 (100%)	98 (96.1%)
<30	0 (0%)	4 (3.9%)
PALBI Score			0.970	0.325
≥-5.95	36 (39.1%)	33 (32.4%)
<-5.95	56 (60.9%)	69 (67.6%)
HBsAg
Positive	75 (81.5%)	83 (81.4%)	0.001	0.979
Negative	17 (18.5%)	19 (18.6%)
HBV-DNA			0.006	0.941
>500	51 (55.4%)	56 (54.9%)
≤500	41 (44.6%)	46 (45.1%)
Cirrhosis			0.520	0.471
Positive	35 (38.0%)	44 (43.1%)
Negative	57 (62.0%)	58 (56.9%)
Number of tumors			0.197	0.657
Solitary	83 (90.2%)	90 (88.2%)
Multiple	9 (9.8%)	12 (11.8%)
Tumor size, cm			5.269	0.022
≥5	31 (33.7%)	51 (50.0%)
<5	61 (66.3%)	51 (50.0%)
Tumor capsule			0.004	0.953
Positive	42 (45.7%)	47 (46.1%)
Negative	50 (54.3%)	55 (53.9%)
MVI			18.401	0.000
Positive	8 (8.7%)	35 (34.3%)
Negative	84 (91.3%)	67 (65.7%)
AJCC T stage			1.258	0.262
I	48 (52.2%)	45 (44.1%)
II, III	44 (47.8%)	57 (55.9%)
BCLC stage			38.066	0.000
0, A	79 (85.9%)	44 (43.1%)
B, C	13 (14.1%)	58 (56.9%)
Pathological differentiation			0.449	0.503
Poorly	5 (5.4%)	8 (7.8%)
Moderately and well	87 (94.6%)	94 (92.2%)
Procedure time, h			0.590	0.442
≥3	20 (21.7%)	27 (26.5%)
<3	72 (78.3%)	75 (73.5%)
AFP, ng/mL	3.85±1.80	3.70±1.64	-	0.540

Abbreviations: PT, prothrombin time; WBC, white blood cell; HB, hemoglobin; PLT, platelet count, Na, sodium ion; ALT, alanine aminotransferase; AST, aspartate transaminase; Tbil, total bilirubin; ALP, alkaline phosphatase; PALBI, platelet–albumin–bilirubin; HBsAg, hepatitis B surface antigen; HBV, hepatitis B virus; MVI, microvascular invasion; AJCC, American Joint Committee on Cancer; BCLC, Barcelona Clinic of Liver Cancer; AFP, alpha-fetoprotein.

Table 2 Univariate and Multivariate Cox Analyses for Recurrence-Free Survival of Alpha-Fetoprotein-Negative Hepatocellular Carcinoma Patients

Variables	Univariate Analysis		Multivariate Analysis
	P	HR (95% CI)	P	HR (95% CI)
PALBI Score	0.000	2.519 (1.650–3.844)	0.000	2.262 (1.471–3.477)
Tumor size	0.007	1.706 (1.154–2.523)	0.039	1.982 (1.035–3.795)
MVI	0.000	4.025 (2.627–6.168)	0.000	4.560 (2.276–9.136)
BCLC stage	0.000	2.418 (1.566–3.735)
AJCC T stage	0.047	1.492 (1.006–2.212)
Procedure time	0.018	1.242 (1.037–1.488)

Abbreviations: PALBI, platelet–albumin–bilirubin; MVI, microvascular invasion; AJCC, American Joint Committee on Cancer; BCLC, Barcelona Clinic on Liver Cancer.

Figure 2 Relationship of independent risk factors with recurrence-free survival (RFS) in alpha-fetoprotein-negative hepatocellular carcinoma patients. (A) RFS of patients with platelet–albumin-bilirubin (PALBI) scores <-5.95 was longer than that of patients with PALBI scores ≥-5.95. (B) RFS of patients with microvascular invasion (MVI) was longer than that of patients without MVI. (C) RFS of patients with tumor size <5 cm was longer than that of patients with tumor size ≥5 cm.

Figure 3 Development of nomogram prediction model for recurrence-free survival (RFS). (A) Nomogram prediction model. (B) Receiver operating characteristic curve for the nomogram prediction model. (C–E) Calibration curves of the nomogram for predicting 1-, 3-, and 5-year RFS rates.

Figure 4 Prognostic assessment and risk stratification of the nomogram prediction model. (A) Risk stratification for recurrence-free survival (RFS). (B–D) Decision curve analyses of 1-, 3-, and 5-year RFS rates show an increase in net benefit.