Construction and evaluation of a liver cancer risk prediction model based on machine learning

Table 1 Discrepancy analysis of patient study metrics between the training and validation cohorts

Variables	Total (n = 550)	Group		Z/χ2	P value
		Training set (n = 385)	Validation set (n = 165)
Age	53 (47, 59)	53 (47, 59)	53 (48, 58)	Z = -0.42	0.68
WBC (109/L)	4.09 (2.98, 5.70)	4.06 (2.97, 5.65)	4.21 (3.00, 5.76)	Z = -0.71	0.48
RBC (1012/L)	4.43 (3.83, 4.94)	4.46 (3.84, 4.96)	4.36 (3.83, 4.91)	Z = -0.43	0.67
HB (g/L)	141.00 (121.00, 156.00)	142.00 (121.00, 157.00)	137.00 (121.00, 155.00)	Z = -1.00	0.32
PLT (109/L)	88.00 (55.00, 138.00)	85.00 (55.00, 136.00)	92.00 (56.00, 142.00)	Z = -0.88	0.38
AFP (ng/mL)	7.42 (2.96, 110.14)	7.44 (2.95, 88.46)	7.27 (3.07, 167.59)	Z = -0.21	0.84
PIVKA-II (mAU/mL)	32.55 (20.48, 1555.89)	33.85 (20.89, 1839.88)	28.64 (19.52, 1157.19)	Z = -0.85	0.39
CEA (ng/mL)	2.22 (1.42, 3.40)	2.21 (1.35, 3.36)	2.35 (1.54, 3.44)	Z = -1.28	0.20
CA199 (ng/mL)	19.70 (10.43, 38.10)	19.75 (10.60, 38.92)	18.60 (9.37, 34.30)	Z = -0.88	0.38
CA125 (ng/mL)	25.41 (13.18, 123.00)	23.91 (12.77, 103.25)	27.90 (14.70, 148.90)	Z = -1.24	0.22
Sex, n (%)				χ² = 0.91	0.34
Male	406 (74.22)	288 (75.39)	118 (71.52)
Female	141 (25.78)	94 (24.61)	47 (28.48)

WBC: White blood cell; RBC: Red blood cell; HB: Hemoglobin level; PLT: Platelet; AFP: Alpha-fetoprotein; PIVKA-II: Protein induced by vitamin K absence or antagonist II; CEA: Carcinoembryonic antigen; CA: Carbohydrate antigen.