IM

IM

0.1 Results

Factor	Detalis	Total
N=		185
Gender	F	22 (11.9%)
	M	163 (88.1%)
Age	μ ±DS	68.83 ±8.15
	M (min:max)	70 (45.2:86.1)
Year of diagnosis	μ ±DS	2014.95 ±3.1
	M (min:max)	2015.5 (2008:2019)
Survival	μ ±DS	23.11 ±23.0
	M (min:max)	15 (0:114)
Status	0	62 (34.4%)
	1	110 (61.1%)
	2	8 (4.4%)
MRI_diagnosis		57 (30.8%)
CT_Diagnosis		111 (60.0%)
US_Diagnosis		60 (32.4%)
HCC_Screening_18months_before		60 (32.8%)
US_Screening		41 (27.7%)
MRI_Screening		17 (11.5%)
CT_Screening		27 (18.2%)
ASH		130 (70.3%)
NAFLD		106 (57.3%)
Cirrhosis		156 (84.3%)
HCV	no	185 (100%)
HBc	no	185 (100%)
Diagnosis	NASH	55 (29.7%)
	ASH	79 (42.7%)
	BASH	51 (27.6%)
Diabetes		79 (42.7%)
Hipertension		109 (61.6%)
Hiperlipidemia		41 (23.2%)
Smoking	0	94 (51.1%)
	1	76 (41.3%)
	2	14 (7.6%)
Alcohol_Consume	0	97 (52.7%)
	1	70 (38.0%)
	2	17 (9.2%)
BMI	μ ±DS	28.63 ±5.12
	M (min:max)	28.41 (18.48:48.32)
Encephalopathy (acc. to CP score)	1	170 (93.9%)
	2-3	11 (6.1%)
Ascites (acc. to CP score)	1	143 (79.4%)
	2	21 (11.7%)
	3	16 (8.9%)
Bilirubin total (µmol/L)	μ ±DS	28.10 ±42.3
	M (min:max)	17 (3:413)
INR	μ ±DS	1.18 ±0.195
	M (min:max)	1.14 (0.8:2.07)
Albumin (g/L)	μ ±DS	32.12 ±5.78
	M (min:max)	32 (17:49.8)
CHILD	1	103 (58.9%)
	2	61 (34.9%)
	3	11 (6.3%)
CHILD_A		103 (58.9%)
CHILD_B		61 (34.9%)
CHILD_C		11 (6.3%)
BCLC	0	13 (7.1%)
	1	63 (34.2%)
	2	57 (31.0%)
	3	36 (19.6%)
	4	15 (8.2%)
BCLC_0		13 (7.1%)
BCLC_1		63 (34.2%)
BCLC_2		57 (31.0%)
BCLC_3		36 (19.6%)
BCLC_4		15 (8.2%)
Resection		35 (18.9%)
Transplant		5 (2.7%)
TACE		24 (13.0%)
TAE		15 (8.2%)
RFA		3 (1.6%)
MWA		35 (19.0%)
SIRT		5 (2.7%)
Sistemic_therapy		43 (23.4%)
Curative_treatment		66 (35.9%)
Loco_regional_therapies		41 (22.3%)
No_treatment		29 (15.8%)
Treatment	Curative	66 (35.9%)
	Transplant	5 (2.7%)
	Loco-regional	41 (22.3%)
	Systemic	43 (23.4%)
	No treatment	29 (15.8%)
Performance Status	0	110 (60.1%)
	1	46 (25.1%)
	2	17 (9.3%)
	3	9 (4.9%)
	4	1 (0.5%)
PS_0		110 (60.1%)
PS_1		46 (25.1%)
PS_2		17 (9.3%)
PS_3		9 (4.9%)
PS_4		1 (0.5%)
μ ±DS = Mean (standard deviation); M (min:max) = Median (min:max);

0.1.1 by diagnosis

Factor	Detalis	NASH	ASH	BASH	Total	Statistics
Diagnosis		55 (29.7%)	79 (42.7%)	51 (27.6%)	185
Gender	F	9 (16.4%)	11 (13.9%)	2 (3.9%)	22 (11.9%)	V=0.16 (p=0.108)
	M	46 (83.6%)	68 (86.1%)	49 (96.1%)	163 (88.1%)
Age	μ ±DS	70.83 ±7.01	67.28 ±8.81	69.07 ±7.89	68.83 ±8.15	1-way ANOVA: p=0.044
	M (min:max)	71.1 (50.9:86.1)	67.6 (45.2:86)	69.7 (53.5:83.9)	70 (45.2:86.1)
Year of diagnosis	μ ±DS	2014.87 ±3.23	2015.05 ±3.22	2014.86 ±2.78	2014.95 ±3.1	Kruskal-Wallis: p=0.816
	M (min:max)	2015 (2008:2019)	2016 (2008:2019)	2015 (2009:2019)	2015.5 (2008:2019)
Survival	μ ±DS	21.93 ±23.9	23.50 ±23.6	23.80 ±21.7	23.11 ±23.0	Kruskal-Wallis: p=0.872
	M (min:max)	14 (0:110)	15 (0:114)	19.5 (0:85)	15 (0:114)
Status	0	22 (40.7%)	29 (38.2%)	11 (22.0%)	62 (34.4%)	V=0.13 (p=0.226)
	1	29 (53.7%)	45 (59.2%)	36 (72.0%)	110 (61.1%)
	2	3 (5.6%)	2 (2.6%)	3 (6.0%)	8 (4.4%)
MRI_diagnosis		18 (32.7%)	24 (30.4%)	15 (29.4%)	57 (30.8%)	V=0.03 (p=0.928)
CT_Diagnosis		33 (60.0%)	47 (59.5%)	31 (60.8%)	111 (60.0%)	V=0.01 (p=0.989)
US_Diagnosis		20 (36.4%)	25 (31.6%)	15 (29.4%)	60 (32.4%)	V=0.06 (p=0.733)
HCC_Screening_18months_before		23 (41.8%)	23 (29.1%)	14 (28.6%)	60 (32.8%)	V=0.13 (p=0.233)
US_Screening		17 (30.9%)	14 (17.7%)	10 (71.4%)	41 (27.7%)	V=0.34 (p<0.001)
MRI_Screening		6 (10.9%)	7 (8.9%)	4 (28.6%)	17 (11.5%)	V=0.18 (p=0.102)
CT_Screening		9 (16.4%)	14 (17.7%)	4 (28.6%)	27 (18.2%)	V=0.09 (p=0.564)
ASH		0	79 (100%)	51 (100%)	130 (70.3%)	V=1.00 (p<0.001)
NAFLD		55 (100%)	0	51 (100%)	106 (57.3%)	V=1.00 (p<0.001)
Cirrhosis		42 (76.4%)	70 (88.6%)	44 (86.3%)	156 (84.3%)	V=0.14 (p=0.144)
HCV	no	55 (100%)	79 (100%)	51 (100%)	185 (100%)	V=NaN (p=1.000)
HBc	no	55 (100%)	79 (100%)	51 (100%)	185 (100%)	V=NaN (p=1.000)
Diabetes		35 (63.6%)	18 (22.8%)	26 (51.0%)	79 (42.7%)	V=0.36 (p<0.001)
Hipertension		35 (68.6%)	35 (46.1%)	39 (78.0%)	109 (61.6%)	V=0.29 (p<0.001)
Hiperlipidemia		16 (31.4%)	12 (15.8%)	13 (26.0%)	41 (23.2%)	V=0.16 (p=0.107)
Smoking	0	38 (70.4%)	31 (39.2%)	25 (49.0%)	94 (51.1%)	V=0.39 (p<0.001)
	1	16 (29.6%)	48 (60.8%)	12 (23.5%)	76 (41.3%)
	2	0	0	14 (27.5%)	14 (7.6%)
Alcohol_Consume	0	47 (87.0%)	31 (39.2%)	19 (37.3%)	97 (52.7%)	V=0.47 (p<0.001)
	1	7 (13.0%)	48 (60.8%)	15 (29.4%)	70 (38.0%)
	2	0	0	17 (33.3%)	17 (9.2%)
BMI	μ ±DS	30.61 ±4.98	26.26 ±4.15	30.35 ±5.22	28.63 ±5.12	Kruskal-Wallis: p<0.001
	M (min:max)	30.44 (18.48:42.17)	25.98 (18.63:38.74)	29.68 (20.34:48.32)	28.41 (18.48:48.32)
Encephalopathy (acc. to CP score)	1	51 (96.2%)	73 (92.4%)	46 (93.9%)	170 (93.9%)	V=0.07 (p=0.666)
	2-3	2 (3.8%)	6 (7.6%)	3 (6.1%)	11 (6.1%)
Ascites (acc. to CP score)	1	44 (84.6%)	59 (74.7%)	40 (81.6%)	143 (79.4%)	V=0.12 (p=0.253)
	2	7 (13.5%)	10 (12.7%)	4 (8.2%)	21 (11.7%)
	3	1 (1.9%)	10 (12.7%)	5 (10.2%)	16 (8.9%)
Bilirubin total (µmol/L)	μ ±DS	23.88 ±18.2	27.42 ±37.6	33.12 ±61.2	28.10 ±42.3	Kruskal-Wallis: p=0.753
	M (min:max)	18 (5:104)	16 (3:286)	18 (6:413)	17 (3:413)
INR	μ ±DS	1.16 ±0.162	1.19 ±0.222	1.19 ±0.184	1.18 ±0.195	Kruskal-Wallis: p=0.648
	M (min:max)	1.14 (0.99:1.78)	1.11 (0.8:2.07)	1.15 (0.99:1.96)	1.14 (0.8:2.07)
Albumin (g/L)	μ ±DS	33.01 ±4.59	31.73 ±6.24	31.79 ±6.14	32.12 ±5.78	Kruskal-Wallis: p=0.552
	M (min:max)	33 (24:42)	32.5 (20:42)	32 (17:49.8)	32 (17:49.8)
CHILD	1	31 (64.6%)	44 (55.7%)	28 (58.3%)	103 (58.9%)	V=0.08 (p=0.698)
	2	15 (31.2%)	28 (35.4%)	18 (37.5%)	61 (34.9%)
	3	2 (4.2%)	7 (8.9%)	2 (4.2%)	11 (6.3%)
CHILD_A		31 (64.6%)	44 (55.7%)	28 (58.3%)	103 (58.9%)	V=0.07 (p=0.612)
CHILD_B		15 (31.2%)	28 (35.4%)	18 (37.5%)	61 (34.9%)	V=0.05 (p=0.805)
CHILD_C		2 (4.2%)	7 (8.9%)	2 (4.2%)	11 (6.3%)	V=0.10 (p=0.445)
BCLC	0	2 (3.7%)	9 (11.4%)	2 (3.9%)	13 (7.1%)	V=0.14 (p=0.500)
	1	21 (38.9%)	26 (32.9%)	16 (31.4%)	63 (34.2%)
	2	15 (27.8%)	22 (27.8%)	20 (39.2%)	57 (31.0%)
	3	13 (24.1%)	14 (17.7%)	9 (17.6%)	36 (19.6%)
	4	3 (5.6%)	8 (10.1%)	4 (7.8%)	15 (8.2%)
BCLC_0		2 (3.7%)	9 (11.4%)	2 (3.9%)	13 (7.1%)	V=0.15 (p=0.139)
BCLC_1		21 (38.9%)	26 (32.9%)	16 (31.4%)	63 (34.2%)	V=0.06 (p=0.682)
BCLC_2		15 (27.8%)	22 (27.8%)	20 (39.2%)	57 (31.0%)	V=0.11 (p=0.326)
BCLC_3		13 (24.1%)	14 (17.7%)	9 (17.6%)	36 (19.6%)	V=0.07 (p=0.610)
BCLC_4		3 (5.6%)	8 (10.1%)	4 (7.8%)	15 (8.2%)	V=0.07 (p=0.636)
Resection		12 (21.8%)	17 (21.5%)	6 (11.8%)	35 (18.9%)	V=0.11 (p=0.309)
Transplant		0	3 (3.8%)	2 (3.9%)	5 (2.7%)	V=0.11 (p=0.334)
TACE		7 (12.7%)	9 (11.5%)	8 (15.7%)	24 (13.0%)	V=0.05 (p=0.789)
TAE		5 (9.1%)	5 (6.4%)	5 (10.0%)	15 (8.2%)	V=0.06 (p=0.739)
RFA		2 (3.7%)	1 (1.3%)	0	3 (1.6%)	V=0.11 (p=0.311)
MWA		11 (20.0%)	13 (16.7%)	11 (21.6%)	35 (19.0%)	V=0.05 (p=0.767)
SIRT		1 (1.8%)	2 (2.6%)	2 (3.9%)	5 (2.7%)	V=0.05 (p=0.797)
Sistemic_therapy		12 (21.8%)	16 (20.5%)	15 (29.4%)	43 (23.4%)	V=0.09 (p=0.480)
Curative_treatment		25 (45.5%)	27 (34.6%)	14 (27.5%)	66 (35.9%)	V=0.14 (p=0.148)
Loco_regional_therapies		12 (21.8%)	16 (20.5%)	13 (25.5%)	41 (22.3%)	V=0.05 (p=0.798)
No_treatment		6 (10.9%)	16 (20.5%)	7 (13.7%)	29 (15.8%)	V=0.12 (p=0.292)
Treatment	Curative	25 (45.5%)	27 (34.6%)	14 (27.5%)	66 (35.9%)	V=0.15 (p=0.421)
	Transplant	0	3 (3.8%)	2 (3.9%)	5 (2.7%)
	Loco-regional	12 (21.8%)	16 (20.5%)	13 (25.5%)	41 (22.3%)
	Systemic	12 (21.8%)	16 (20.5%)	15 (29.4%)	43 (23.4%)
	No treatment	6 (10.9%)	16 (20.5%)	7 (13.7%)	29 (15.8%)
Performance Status	0	34 (64.2%)	45 (57.0%)	31 (60.8%)	110 (60.1%)	V=0.08 (p=0.965)
	1	13 (24.5%)	20 (25.3%)	13 (25.5%)	46 (25.1%)
	2	4 (7.5%)	8 (10.1%)	5 (9.8%)	17 (9.3%)
	3	2 (3.8%)	5 (6.3%)	2 (3.9%)	9 (4.9%)
	4	0	1 (1.3%)	0	1 (0.5%)
PS_0		34 (64.2%)	45 (57.0%)	31 (60.8%)	110 (60.1%)	V=0.06 (p=0.706)
PS_1		13 (24.5%)	20 (25.3%)	13 (25.5%)	46 (25.1%)	V=<0.01 (p=0.992)
PS_2		4 (7.5%)	8 (10.1%)	5 (9.8%)	17 (9.3%)	V=0.04 (p=0.873)
PS_3		2 (3.8%)	5 (6.3%)	2 (3.9%)	9 (4.9%)	V=0.06 (p=0.743)
PS_4		0	1 (1.3%)	0	1 (0.5%)	V=0.09 (p=0.516)
μ ±DS = Mean (standard deviation); M (min:max) = Median (min:max); MW = Mann-WhitneyTest; OR/RR = odds-ratio / risc-ratio [95% CI] and p value from Fisher test); V = Cramer V (p value from Chi² test);

0.1.2 by diagnosis: NASH vs others

Factor	Detalis	NASH	Other	Total	Statistics
Diagnosis		55 (29.7%)	130 (70.3%)	185
Gender	F	9 (16.4%)	13 (10.0%)	22 (11.9%)	OR=1.76 [0.70, 4.40] (p=0.224)
	M	46 (83.6%)	117 (90.0%)	163 (88.1%)
Age	μ ±DS	70.83 ±7.01	67.98 ±8.48	68.83 ±8.15	T-test: p=0.030
	M (min:max)	71.1 (50.9:86.1)	68.25 (45.2:86)	70 (45.2:86.1)
Year of diagnosis	μ ±DS	2014.87 ±3.23	2014.98 ±3.05	2014.95 ±3.1	MW: p=0.904
	M (min:max)	2015 (2008:2019)	2016 (2008:2019)	2015.5 (2008:2019)
Survival	μ ±DS	21.93 ±23.9	23.62 ±22.8	23.11 ±23.0	MW: p=0.687
	M (min:max)	14 (0:110)	17 (0:114)	15 (0:114)
Status	0	22 (40.7%)	40 (31.7%)	62 (34.4%)	V=0.10 (p=0.408)
	1	29 (53.7%)	81 (64.3%)	110 (61.1%)
	2	3 (5.6%)	5 (4.0%)	8 (4.4%)
MRI_diagnosis		18 (32.7%)	39 (30.0%)	57 (30.8%)	OR=1.14 [0.58, 2.23] (p=0.730)
CT_Diagnosis		33 (60.0%)	78 (60.0%)	111 (60.0%)	OR=1.00 [0.53, 1.90] (p=1.000)
US_Diagnosis		20 (36.4%)	40 (30.8%)	60 (32.4%)	OR=1.29 [0.66, 2.50] (p=0.494)
HCC_Screening_18months_before		23 (41.8%)	37 (28.9%)	60 (32.8%)	OR=1.77 [0.92, 3.41] (p=0.122)
US_Screening		17 (30.9%)	24 (25.8%)	41 (27.7%)	OR=1.29 [0.62, 2.69] (p=0.570)
MRI_Screening		6 (10.9%)	11 (11.8%)	17 (11.5%)	OR=0.91 [0.32, 2.62] (p=1.000)
CT_Screening		9 (16.4%)	18 (19.4%)	27 (18.2%)	OR=0.82 [0.34, 1.97] (p=0.826)
ASH		0	130 (100%)	130 (70.3%)	OR=0.00 [0.00, 0.00] (p<0.001)
NAFLD		55 (100%)	51 (39.2%)	106 (57.3%)	OR=171.35 [10.35, 2 835.45] (p<0.001)
Cirrhosis		42 (76.4%)	114 (87.7%)	156 (84.3%)	OR=0.45 [0.20, 1.02] (p=0.075)
HCV	no	55 (100%)	130 (100%)	185 (100%)	V=NaN (p=1.000)
HBc	no	55 (100%)	130 (100%)	185 (100%)	V=NaN (p=1.000)
Diabetes		35 (63.6%)	44 (33.8%)	79 (42.7%)	OR=3.42 [1.77, 6.61] (p<0.001)
Hipertension		35 (68.6%)	74 (58.7%)	109 (61.6%)	OR=1.54 [0.77, 3.06] (p=0.237)
Hiperlipidemia		16 (31.4%)	25 (19.8%)	41 (23.2%)	OR=1.85 [0.88, 3.86] (p=0.117)
Smoking	0	38 (70.4%)	56 (43.1%)	94 (51.1%)	V=0.27 (p<0.001)
	1	16 (29.6%)	60 (46.2%)	76 (41.3%)
	2	0	14 (10.8%)	14 (7.6%)
Alcohol_Consume	0	47 (87.0%)	50 (38.5%)	97 (52.7%)	V=0.45 (p<0.001)
	1	7 (13.0%)	63 (48.5%)	70 (38.0%)
	2	0	17 (13.1%)	17 (9.2%)
BMI	μ ±DS	30.61 ±4.98	27.79 ±4.97	28.63 ±5.12	MW: p<0.001
	M (min:max)	30.44 (18.48:42.17)	27.34 (18.63:48.32)	28.41 (18.48:48.32)
Encephalopathy (acc. to CP score)	1	51 (96.2%)	119 (93.0%)	170 (93.9%)	OR=1.93 [0.40, 9.24] (p=0.513)
	2-3	2 (3.8%)	9 (7.0%)	11 (6.1%)
Ascites (acc. to CP score)	1	44 (84.6%)	99 (77.3%)	143 (79.4%)	V=0.16 (p=0.109)
	2	7 (13.5%)	14 (10.9%)	21 (11.7%)
	3	1 (1.9%)	15 (11.7%)	16 (8.9%)
Bilirubin total (µmol/L)	μ ±DS	23.88 ±18.2	29.69 ±48.3	28.10 ±42.3	MW: p=0.701
	M (min:max)	18 (5:104)	17 (3:413)	17 (3:413)
INR	μ ±DS	1.16 ±0.162	1.19 ±0.207	1.18 ±0.195	MW: p=0.461
	M (min:max)	1.14 (0.99:1.78)	1.14 (0.8:2.07)	1.14 (0.8:2.07)
Albumin (g/L)	μ ±DS	33.01 ±4.59	31.75 ±6.18	32.12 ±5.78	MW: p=0.279
	M (min:max)	33 (24:42)	32 (17:49.8)	32 (17:49.8)
CHILD	1	31 (64.6%)	72 (56.7%)	103 (58.9%)	V=0.08 (p=0.580)
	2	15 (31.2%)	46 (36.2%)	61 (34.9%)
	3	2 (4.2%)	9 (7.1%)	11 (6.3%)
CHILD_A		31 (64.6%)	72 (56.7%)	103 (58.9%)	OR=1.39 [0.70, 2.77] (p=0.392)
CHILD_B		15 (31.2%)	46 (36.2%)	61 (34.9%)	OR=0.80 [0.39, 1.63] (p=0.597)
CHILD_C		2 (4.2%)	9 (7.1%)	11 (6.3%)	OR=0.57 [0.12, 2.74] (p=0.729)
BCLC	0	2 (3.7%)	11 (8.5%)	13 (7.1%)	V=0.14 (p=0.496)
	1	21 (38.9%)	42 (32.3%)	63 (34.2%)
	2	15 (27.8%)	42 (32.3%)	57 (31.0%)
	3	13 (24.1%)	23 (17.7%)	36 (19.6%)
	4	3 (5.6%)	12 (9.2%)	15 (8.2%)
BCLC_0		2 (3.7%)	11 (8.5%)	13 (7.1%)	OR=0.42 [0.09, 1.94] (p=0.351)
BCLC_1		21 (38.9%)	42 (32.3%)	63 (34.2%)	OR=1.33 [0.69, 2.58] (p=0.399)
BCLC_2		15 (27.8%)	42 (32.3%)	57 (31.0%)	OR=0.81 [0.40, 1.62] (p=0.602)
BCLC_3		13 (24.1%)	23 (17.7%)	36 (19.6%)	OR=1.48 [0.68, 3.18] (p=0.316)
BCLC_4		3 (5.6%)	12 (9.2%)	15 (8.2%)	OR=0.58 [0.16, 2.14] (p=0.559)
Resection		12 (21.8%)	23 (17.7%)	35 (18.9%)	OR=1.30 [0.59, 2.84] (p=0.541)
Transplant		0	5 (3.9%)	5 (2.7%)	OR=0.20 [0.01, 3.75] (p=0.324)
TACE		7 (12.7%)	17 (13.2%)	24 (13.0%)	OR=0.96 [0.37, 2.47] (p=1.000)
TAE		5 (9.1%)	10 (7.8%)	15 (8.2%)	OR=1.18 [0.38, 3.63] (p=0.774)
RFA		2 (3.7%)	1 (0.8%)	3 (1.6%)	OR=4.92 [0.44, 55.47] (p=0.208)
MWA		11 (20.0%)	24 (18.6%)	35 (19.0%)	OR=1.09 [0.49, 2.42] (p=0.839)
SIRT		1 (1.8%)	4 (3.1%)	5 (2.7%)	OR=0.58 [0.06, 5.30] (p=1.000)
Sistemic_therapy		12 (21.8%)	31 (24.0%)	43 (23.4%)	OR=0.88 [0.41, 1.88] (p=0.850)
Curative_treatment		25 (45.5%)	41 (31.8%)	66 (35.9%)	OR=1.79 [0.94, 3.42] (p=0.093)
Loco_regional_therapies		12 (21.8%)	29 (22.5%)	41 (22.3%)	OR=0.96 [0.45, 2.06] (p=1.000)
No_treatment		6 (10.9%)	23 (17.8%)	29 (15.8%)	OR=0.56 [0.22, 1.47] (p=0.276)
Treatment	Curative	25 (45.5%)	41 (31.8%)	66 (35.9%)	V=0.17 (p=0.249)
	Transplant	0	5 (3.9%)	5 (2.7%)
	Loco-regional	12 (21.8%)	29 (22.5%)	41 (22.3%)
	Systemic	12 (21.8%)	31 (24.0%)	43 (23.4%)
	No treatment	6 (10.9%)	23 (17.8%)	29 (15.8%)
Performance Status	0	34 (64.2%)	76 (58.5%)	110 (60.1%)	V=0.08 (p=0.900)
	1	13 (24.5%)	33 (25.4%)	46 (25.1%)
	2	4 (7.5%)	13 (10.0%)	17 (9.3%)
	3	2 (3.8%)	7 (5.4%)	9 (4.9%)
	4	0	1 (0.8%)	1 (0.5%)
PS_0		34 (64.2%)	76 (58.5%)	110 (60.1%)	OR=1.27 [0.66, 2.46] (p=0.509)
PS_1		13 (24.5%)	33 (25.4%)	46 (25.1%)	OR=0.96 [0.46, 2.00] (p=1.000)
PS_2		4 (7.5%)	13 (10.0%)	17 (9.3%)	OR=0.73 [0.23, 2.37] (p=0.781)
PS_3		2 (3.8%)	7 (5.4%)	9 (4.9%)	OR=0.69 [0.14, 3.43] (p=1.000)
PS_4		0	1 (0.8%)	1 (0.5%)	OR=0.81 [0.03, 20.12] (p=1.000)
μ ±DS = Mean (standard deviation); M (min:max) = Median (min:max); MW = Mann-WhitneyTest; OR/RR = odds-ratio / risc-ratio [95% CI] and p value from Fisher test); V = Cramer V (p value from Chi² test);

0.1.3 by diagnosis: ASH vs others

Factor	Detalis	ASH	Other	Total	Statistics
Diagnosis		55 (29.7%)	130 (70.3%)	185
Gender	F	9 (16.4%)	13 (10.0%)	22 (11.9%)	OR=1.76 [0.70, 4.40] (p=0.224)
	M	46 (83.6%)	117 (90.0%)	163 (88.1%)
Age	μ ±DS	70.83 ±7.01	67.98 ±8.48	68.83 ±8.15	T-test: p=0.030
	M (min:max)	71.1 (50.9:86.1)	68.25 (45.2:86)	70 (45.2:86.1)
Year of diagnosis	μ ±DS	2014.87 ±3.23	2014.98 ±3.05	2014.95 ±3.1	MW: p=0.904
	M (min:max)	2015 (2008:2019)	2016 (2008:2019)	2015.5 (2008:2019)
Survival	μ ±DS	21.93 ±23.9	23.62 ±22.8	23.11 ±23.0	MW: p=0.687
	M (min:max)	14 (0:110)	17 (0:114)	15 (0:114)
Status	0	22 (40.7%)	40 (31.7%)	62 (34.4%)	V=0.10 (p=0.408)
	1	29 (53.7%)	81 (64.3%)	110 (61.1%)
	2	3 (5.6%)	5 (4.0%)	8 (4.4%)
MRI_diagnosis		18 (32.7%)	39 (30.0%)	57 (30.8%)	OR=1.14 [0.58, 2.23] (p=0.730)
CT_Diagnosis		33 (60.0%)	78 (60.0%)	111 (60.0%)	OR=1.00 [0.53, 1.90] (p=1.000)
US_Diagnosis		20 (36.4%)	40 (30.8%)	60 (32.4%)	OR=1.29 [0.66, 2.50] (p=0.494)
HCC_Screening_18months_before		23 (41.8%)	37 (28.9%)	60 (32.8%)	OR=1.77 [0.92, 3.41] (p=0.122)
US_Screening		17 (30.9%)	24 (25.8%)	41 (27.7%)	OR=1.29 [0.62, 2.69] (p=0.570)
MRI_Screening		6 (10.9%)	11 (11.8%)	17 (11.5%)	OR=0.91 [0.32, 2.62] (p=1.000)
CT_Screening		9 (16.4%)	18 (19.4%)	27 (18.2%)	OR=0.82 [0.34, 1.97] (p=0.826)
ASH		0	130 (100%)	130 (70.3%)	OR=0.00 [0.00, 0.00] (p<0.001)
NAFLD		55 (100%)	51 (39.2%)	106 (57.3%)	OR=171.35 [10.35, 2 835.45] (p<0.001)
Cirrhosis		42 (76.4%)	114 (87.7%)	156 (84.3%)	OR=0.45 [0.20, 1.02] (p=0.075)
HCV	no	55 (100%)	130 (100%)	185 (100%)	V=NaN (p=1.000)
HBc	no	55 (100%)	130 (100%)	185 (100%)	V=NaN (p=1.000)
Diabetes		35 (63.6%)	44 (33.8%)	79 (42.7%)	OR=3.42 [1.77, 6.61] (p<0.001)
Hipertension		35 (68.6%)	74 (58.7%)	109 (61.6%)	OR=1.54 [0.77, 3.06] (p=0.237)
Hiperlipidemia		16 (31.4%)	25 (19.8%)	41 (23.2%)	OR=1.85 [0.88, 3.86] (p=0.117)
Smoking	0	38 (70.4%)	56 (43.1%)	94 (51.1%)	V=0.27 (p<0.001)
	1	16 (29.6%)	60 (46.2%)	76 (41.3%)
	2	0	14 (10.8%)	14 (7.6%)
Alcohol_Consume	0	47 (87.0%)	50 (38.5%)	97 (52.7%)	V=0.45 (p<0.001)
	1	7 (13.0%)	63 (48.5%)	70 (38.0%)
	2	0	17 (13.1%)	17 (9.2%)
BMI	μ ±DS	30.61 ±4.98	27.79 ±4.97	28.63 ±5.12	MW: p<0.001
	M (min:max)	30.44 (18.48:42.17)	27.34 (18.63:48.32)	28.41 (18.48:48.32)
Encephalopathy (acc. to CP score)	1	51 (96.2%)	119 (93.0%)	170 (93.9%)	OR=1.93 [0.40, 9.24] (p=0.513)
	2-3	2 (3.8%)	9 (7.0%)	11 (6.1%)
Ascites (acc. to CP score)	1	44 (84.6%)	99 (77.3%)	143 (79.4%)	V=0.16 (p=0.109)
	2	7 (13.5%)	14 (10.9%)	21 (11.7%)
	3	1 (1.9%)	15 (11.7%)	16 (8.9%)
Bilirubin total (µmol/L)	μ ±DS	23.88 ±18.2	29.69 ±48.3	28.10 ±42.3	MW: p=0.701
	M (min:max)	18 (5:104)	17 (3:413)	17 (3:413)
INR	μ ±DS	1.16 ±0.162	1.19 ±0.207	1.18 ±0.195	MW: p=0.461
	M (min:max)	1.14 (0.99:1.78)	1.14 (0.8:2.07)	1.14 (0.8:2.07)
Albumin (g/L)	μ ±DS	33.01 ±4.59	31.75 ±6.18	32.12 ±5.78	MW: p=0.279
	M (min:max)	33 (24:42)	32 (17:49.8)	32 (17:49.8)
CHILD	1	31 (64.6%)	72 (56.7%)	103 (58.9%)	V=0.08 (p=0.580)
	2	15 (31.2%)	46 (36.2%)	61 (34.9%)
	3	2 (4.2%)	9 (7.1%)	11 (6.3%)
CHILD_A		31 (64.6%)	72 (56.7%)	103 (58.9%)	OR=1.39 [0.70, 2.77] (p=0.392)
CHILD_B		15 (31.2%)	46 (36.2%)	61 (34.9%)	OR=0.80 [0.39, 1.63] (p=0.597)
CHILD_C		2 (4.2%)	9 (7.1%)	11 (6.3%)	OR=0.57 [0.12, 2.74] (p=0.729)
BCLC	0	2 (3.7%)	11 (8.5%)	13 (7.1%)	V=0.14 (p=0.496)
	1	21 (38.9%)	42 (32.3%)	63 (34.2%)
	2	15 (27.8%)	42 (32.3%)	57 (31.0%)
	3	13 (24.1%)	23 (17.7%)	36 (19.6%)
	4	3 (5.6%)	12 (9.2%)	15 (8.2%)
BCLC_0		2 (3.7%)	11 (8.5%)	13 (7.1%)	OR=0.42 [0.09, 1.94] (p=0.351)
BCLC_1		21 (38.9%)	42 (32.3%)	63 (34.2%)	OR=1.33 [0.69, 2.58] (p=0.399)
BCLC_2		15 (27.8%)	42 (32.3%)	57 (31.0%)	OR=0.81 [0.40, 1.62] (p=0.602)
BCLC_3		13 (24.1%)	23 (17.7%)	36 (19.6%)	OR=1.48 [0.68, 3.18] (p=0.316)
BCLC_4		3 (5.6%)	12 (9.2%)	15 (8.2%)	OR=0.58 [0.16, 2.14] (p=0.559)
Resection		12 (21.8%)	23 (17.7%)	35 (18.9%)	OR=1.30 [0.59, 2.84] (p=0.541)
Transplant		0	5 (3.9%)	5 (2.7%)	OR=0.20 [0.01, 3.75] (p=0.324)
TACE		7 (12.7%)	17 (13.2%)	24 (13.0%)	OR=0.96 [0.37, 2.47] (p=1.000)
TAE		5 (9.1%)	10 (7.8%)	15 (8.2%)	OR=1.18 [0.38, 3.63] (p=0.774)
RFA		2 (3.7%)	1 (0.8%)	3 (1.6%)	OR=4.92 [0.44, 55.47] (p=0.208)
MWA		11 (20.0%)	24 (18.6%)	35 (19.0%)	OR=1.09 [0.49, 2.42] (p=0.839)
SIRT		1 (1.8%)	4 (3.1%)	5 (2.7%)	OR=0.58 [0.06, 5.30] (p=1.000)
Sistemic_therapy		12 (21.8%)	31 (24.0%)	43 (23.4%)	OR=0.88 [0.41, 1.88] (p=0.850)
Curative_treatment		25 (45.5%)	41 (31.8%)	66 (35.9%)	OR=1.79 [0.94, 3.42] (p=0.093)
Loco_regional_therapies		12 (21.8%)	29 (22.5%)	41 (22.3%)	OR=0.96 [0.45, 2.06] (p=1.000)
No_treatment		6 (10.9%)	23 (17.8%)	29 (15.8%)	OR=0.56 [0.22, 1.47] (p=0.276)
Treatment	Curative	25 (45.5%)	41 (31.8%)	66 (35.9%)	V=0.17 (p=0.249)
	Transplant	0	5 (3.9%)	5 (2.7%)
	Loco-regional	12 (21.8%)	29 (22.5%)	41 (22.3%)
	Systemic	12 (21.8%)	31 (24.0%)	43 (23.4%)
	No treatment	6 (10.9%)	23 (17.8%)	29 (15.8%)
Performance Status	0	34 (64.2%)	76 (58.5%)	110 (60.1%)	V=0.08 (p=0.900)
	1	13 (24.5%)	33 (25.4%)	46 (25.1%)
	2	4 (7.5%)	13 (10.0%)	17 (9.3%)
	3	2 (3.8%)	7 (5.4%)	9 (4.9%)
	4	0	1 (0.8%)	1 (0.5%)
PS_0		34 (64.2%)	76 (58.5%)	110 (60.1%)	OR=1.27 [0.66, 2.46] (p=0.509)
PS_1		13 (24.5%)	33 (25.4%)	46 (25.1%)	OR=0.96 [0.46, 2.00] (p=1.000)
PS_2		4 (7.5%)	13 (10.0%)	17 (9.3%)	OR=0.73 [0.23, 2.37] (p=0.781)
PS_3		2 (3.8%)	7 (5.4%)	9 (4.9%)	OR=0.69 [0.14, 3.43] (p=1.000)
PS_4		0	1 (0.8%)	1 (0.5%)	OR=0.81 [0.03, 20.12] (p=1.000)
μ ±DS = Mean (standard deviation); M (min:max) = Median (min:max); MW = Mann-WhitneyTest; OR/RR = odds-ratio / risc-ratio [95% CI] and p value from Fisher test); V = Cramer V (p value from Chi² test);

0.1.4 by diagnosis: BASH vs others

Factor	Detalis	BASH	Other	Total	Statistics
Diagnosis		55 (29.7%)	130 (70.3%)	185
Gender	F	9 (16.4%)	13 (10.0%)	22 (11.9%)	OR=1.76 [0.70, 4.40] (p=0.224)
	M	46 (83.6%)	117 (90.0%)	163 (88.1%)
Age	μ ±DS	70.83 ±7.01	67.98 ±8.48	68.83 ±8.15	T-test: p=0.030
	M (min:max)	71.1 (50.9:86.1)	68.25 (45.2:86)	70 (45.2:86.1)
Year of diagnosis	μ ±DS	2014.87 ±3.23	2014.98 ±3.05	2014.95 ±3.1	MW: p=0.904
	M (min:max)	2015 (2008:2019)	2016 (2008:2019)	2015.5 (2008:2019)
Survival	μ ±DS	21.93 ±23.9	23.62 ±22.8	23.11 ±23.0	MW: p=0.687
	M (min:max)	14 (0:110)	17 (0:114)	15 (0:114)
Status	0	22 (40.7%)	40 (31.7%)	62 (34.4%)	V=0.10 (p=0.408)
	1	29 (53.7%)	81 (64.3%)	110 (61.1%)
	2	3 (5.6%)	5 (4.0%)	8 (4.4%)
MRI_diagnosis		18 (32.7%)	39 (30.0%)	57 (30.8%)	OR=1.14 [0.58, 2.23] (p=0.730)
CT_Diagnosis		33 (60.0%)	78 (60.0%)	111 (60.0%)	OR=1.00 [0.53, 1.90] (p=1.000)
US_Diagnosis		20 (36.4%)	40 (30.8%)	60 (32.4%)	OR=1.29 [0.66, 2.50] (p=0.494)
HCC_Screening_18months_before		23 (41.8%)	37 (28.9%)	60 (32.8%)	OR=1.77 [0.92, 3.41] (p=0.122)
US_Screening		17 (30.9%)	24 (25.8%)	41 (27.7%)	OR=1.29 [0.62, 2.69] (p=0.570)
MRI_Screening		6 (10.9%)	11 (11.8%)	17 (11.5%)	OR=0.91 [0.32, 2.62] (p=1.000)
CT_Screening		9 (16.4%)	18 (19.4%)	27 (18.2%)	OR=0.82 [0.34, 1.97] (p=0.826)
ASH		0	130 (100%)	130 (70.3%)	OR=0.00 [0.00, 0.00] (p<0.001)
NAFLD		55 (100%)	51 (39.2%)	106 (57.3%)	OR=171.35 [10.35, 2 835.45] (p<0.001)
Cirrhosis		42 (76.4%)	114 (87.7%)	156 (84.3%)	OR=0.45 [0.20, 1.02] (p=0.075)
HCV	no	55 (100%)	130 (100%)	185 (100%)	V=NaN (p=1.000)
HBc	no	55 (100%)	130 (100%)	185 (100%)	V=NaN (p=1.000)
Diabetes		35 (63.6%)	44 (33.8%)	79 (42.7%)	OR=3.42 [1.77, 6.61] (p<0.001)
Hipertension		35 (68.6%)	74 (58.7%)	109 (61.6%)	OR=1.54 [0.77, 3.06] (p=0.237)
Hiperlipidemia		16 (31.4%)	25 (19.8%)	41 (23.2%)	OR=1.85 [0.88, 3.86] (p=0.117)
Smoking	0	38 (70.4%)	56 (43.1%)	94 (51.1%)	V=0.27 (p<0.001)
	1	16 (29.6%)	60 (46.2%)	76 (41.3%)
	2	0	14 (10.8%)	14 (7.6%)
Alcohol_Consume	0	47 (87.0%)	50 (38.5%)	97 (52.7%)	V=0.45 (p<0.001)
	1	7 (13.0%)	63 (48.5%)	70 (38.0%)
	2	0	17 (13.1%)	17 (9.2%)
BMI	μ ±DS	30.61 ±4.98	27.79 ±4.97	28.63 ±5.12	MW: p<0.001
	M (min:max)	30.44 (18.48:42.17)	27.34 (18.63:48.32)	28.41 (18.48:48.32)
Encephalopathy (acc. to CP score)	1	51 (96.2%)	119 (93.0%)	170 (93.9%)	OR=1.93 [0.40, 9.24] (p=0.513)
	2-3	2 (3.8%)	9 (7.0%)	11 (6.1%)
Ascites (acc. to CP score)	1	44 (84.6%)	99 (77.3%)	143 (79.4%)	V=0.16 (p=0.109)
	2	7 (13.5%)	14 (10.9%)	21 (11.7%)
	3	1 (1.9%)	15 (11.7%)	16 (8.9%)
Bilirubin total (µmol/L)	μ ±DS	23.88 ±18.2	29.69 ±48.3	28.10 ±42.3	MW: p=0.701
	M (min:max)	18 (5:104)	17 (3:413)	17 (3:413)
INR	μ ±DS	1.16 ±0.162	1.19 ±0.207	1.18 ±0.195	MW: p=0.461
	M (min:max)	1.14 (0.99:1.78)	1.14 (0.8:2.07)	1.14 (0.8:2.07)
Albumin (g/L)	μ ±DS	33.01 ±4.59	31.75 ±6.18	32.12 ±5.78	MW: p=0.279
	M (min:max)	33 (24:42)	32 (17:49.8)	32 (17:49.8)
CHILD	1	31 (64.6%)	72 (56.7%)	103 (58.9%)	V=0.08 (p=0.580)
	2	15 (31.2%)	46 (36.2%)	61 (34.9%)
	3	2 (4.2%)	9 (7.1%)	11 (6.3%)
CHILD_A		31 (64.6%)	72 (56.7%)	103 (58.9%)	OR=1.39 [0.70, 2.77] (p=0.392)
CHILD_B		15 (31.2%)	46 (36.2%)	61 (34.9%)	OR=0.80 [0.39, 1.63] (p=0.597)
CHILD_C		2 (4.2%)	9 (7.1%)	11 (6.3%)	OR=0.57 [0.12, 2.74] (p=0.729)
BCLC	0	2 (3.7%)	11 (8.5%)	13 (7.1%)	V=0.14 (p=0.496)
	1	21 (38.9%)	42 (32.3%)	63 (34.2%)
	2	15 (27.8%)	42 (32.3%)	57 (31.0%)
	3	13 (24.1%)	23 (17.7%)	36 (19.6%)
	4	3 (5.6%)	12 (9.2%)	15 (8.2%)
BCLC_0		2 (3.7%)	11 (8.5%)	13 (7.1%)	OR=0.42 [0.09, 1.94] (p=0.351)
BCLC_1		21 (38.9%)	42 (32.3%)	63 (34.2%)	OR=1.33 [0.69, 2.58] (p=0.399)
BCLC_2		15 (27.8%)	42 (32.3%)	57 (31.0%)	OR=0.81 [0.40, 1.62] (p=0.602)
BCLC_3		13 (24.1%)	23 (17.7%)	36 (19.6%)	OR=1.48 [0.68, 3.18] (p=0.316)
BCLC_4		3 (5.6%)	12 (9.2%)	15 (8.2%)	OR=0.58 [0.16, 2.14] (p=0.559)
Resection		12 (21.8%)	23 (17.7%)	35 (18.9%)	OR=1.30 [0.59, 2.84] (p=0.541)
Transplant		0	5 (3.9%)	5 (2.7%)	OR=0.20 [0.01, 3.75] (p=0.324)
TACE		7 (12.7%)	17 (13.2%)	24 (13.0%)	OR=0.96 [0.37, 2.47] (p=1.000)
TAE		5 (9.1%)	10 (7.8%)	15 (8.2%)	OR=1.18 [0.38, 3.63] (p=0.774)
RFA		2 (3.7%)	1 (0.8%)	3 (1.6%)	OR=4.92 [0.44, 55.47] (p=0.208)
MWA		11 (20.0%)	24 (18.6%)	35 (19.0%)	OR=1.09 [0.49, 2.42] (p=0.839)
SIRT		1 (1.8%)	4 (3.1%)	5 (2.7%)	OR=0.58 [0.06, 5.30] (p=1.000)
Sistemic_therapy		12 (21.8%)	31 (24.0%)	43 (23.4%)	OR=0.88 [0.41, 1.88] (p=0.850)
Curative_treatment		25 (45.5%)	41 (31.8%)	66 (35.9%)	OR=1.79 [0.94, 3.42] (p=0.093)
Loco_regional_therapies		12 (21.8%)	29 (22.5%)	41 (22.3%)	OR=0.96 [0.45, 2.06] (p=1.000)
No_treatment		6 (10.9%)	23 (17.8%)	29 (15.8%)	OR=0.56 [0.22, 1.47] (p=0.276)
Treatment	Curative	25 (45.5%)	41 (31.8%)	66 (35.9%)	V=0.17 (p=0.249)
	Transplant	0	5 (3.9%)	5 (2.7%)
	Loco-regional	12 (21.8%)	29 (22.5%)	41 (22.3%)
	Systemic	12 (21.8%)	31 (24.0%)	43 (23.4%)
	No treatment	6 (10.9%)	23 (17.8%)	29 (15.8%)
Performance Status	0	34 (64.2%)	76 (58.5%)	110 (60.1%)	V=0.08 (p=0.900)
	1	13 (24.5%)	33 (25.4%)	46 (25.1%)
	2	4 (7.5%)	13 (10.0%)	17 (9.3%)
	3	2 (3.8%)	7 (5.4%)	9 (4.9%)
	4	0	1 (0.8%)	1 (0.5%)
PS_0		34 (64.2%)	76 (58.5%)	110 (60.1%)	OR=1.27 [0.66, 2.46] (p=0.509)
PS_1		13 (24.5%)	33 (25.4%)	46 (25.1%)	OR=0.96 [0.46, 2.00] (p=1.000)
PS_2		4 (7.5%)	13 (10.0%)	17 (9.3%)	OR=0.73 [0.23, 2.37] (p=0.781)
PS_3		2 (3.8%)	7 (5.4%)	9 (4.9%)	OR=0.69 [0.14, 3.43] (p=1.000)
PS_4		0	1 (0.8%)	1 (0.5%)	OR=0.81 [0.03, 20.12] (p=1.000)
μ ±DS = Mean (standard deviation); M (min:max) = Median (min:max); MW = Mann-WhitneyTest; OR/RR = odds-ratio / risc-ratio [95% CI] and p value from Fisher test); V = Cramer V (p value from Chi² test);

0.2 Charts:

0.2.1 Year

vs. Diagnosis
Year of diagnosis	NASH	ASH	BASH	(total)
2008	1 (50.0% / 1.8%)	1 (50.0% / 1.3%)	0	2 (1.1%)
2009	2 (33.3% / 3.6%)	3 (50.0% / 3.8%)	1 (16.7% / 2.0%)	6 (3.3%)
2010	5 (35.7% / 9.1%)	6 (42.9% / 7.6%)	3 (21.4% / 6.0%)	14 (7.6%)
2011	2 (22.2% / 3.6%)	4 (44.4% / 5.1%)	3 (33.3% / 6.0%)	9 (4.9%)
2012	6 (30.0% / 10.9%)	7 (35.0% / 8.9%)	7 (35.0% / 14.0%)	20 (10.9%)
2013	2 (22.2% / 3.6%)	5 (55.6% / 6.3%)	2 (22.2% / 4.0%)	9 (4.9%)
2014	4 (33.3% / 7.3%)	5 (41.7% / 6.3%)	3 (25.0% / 6.0%)	12 (6.5%)
2015	6 (30.0% / 10.9%)	6 (30.0% / 7.6%)	8 (40.0% / 16.0%)	20 (10.9%)
2016	6 (27.3% / 10.9%)	10 (45.5% / 12.7%)	6 (27.3% / 12.0%)	22 (12.0%)
2017	6 (31.6% / 10.9%)	8 (42.1% / 10.1%)	5 (26.3% / 10.0%)	19 (10.3%)
2018	7 (25.0% / 12.7%)	11 (39.3% / 13.9%)	10 (35.7% / 20.0%)	28 (15.2%)
2019	8 (34.8% / 14.5%)	13 (56.5% / 16.5%)	2 (8.7% / 4.0%)	23 (12.5%)
(total)	55 (29.7%)	79 (42.7%)	51 (27.6%)	184 (100%)
V=0.17 (p=0.982)

vs. Diagnosis
Year of diagnosis	NASH	ASH	BASH	(total)
2008	1 (50.0% / 1.8%)	1 (50.0% / 1.3%)	0	2 (1.1%)
2009	2 (33.3% / 3.6%)	3 (50.0% / 3.8%)	1 (16.7% / 2.0%)	6 (3.3%)
2010	5 (35.7% / 9.1%)	6 (42.9% / 7.6%)	3 (21.4% / 6.0%)	14 (7.6%)
2011	2 (22.2% / 3.6%)	4 (44.4% / 5.1%)	3 (33.3% / 6.0%)	9 (4.9%)
2012	6 (30.0% / 10.9%)	7 (35.0% / 8.9%)	7 (35.0% / 14.0%)	20 (10.9%)
2013	2 (22.2% / 3.6%)	5 (55.6% / 6.3%)	2 (22.2% / 4.0%)	9 (4.9%)
2014	4 (33.3% / 7.3%)	5 (41.7% / 6.3%)	3 (25.0% / 6.0%)	12 (6.5%)
2015	6 (30.0% / 10.9%)	6 (30.0% / 7.6%)	8 (40.0% / 16.0%)	20 (10.9%)
2016	6 (27.3% / 10.9%)	10 (45.5% / 12.7%)	6 (27.3% / 12.0%)	22 (12.0%)
2017	6 (31.6% / 10.9%)	8 (42.1% / 10.1%)	5 (26.3% / 10.0%)	19 (10.3%)
2018	7 (25.0% / 12.7%)	11 (39.3% / 13.9%)	10 (35.7% / 20.0%)	28 (15.2%)
2019	8 (34.8% / 14.5%)	13 (56.5% / 16.5%)	2 (8.7% / 4.0%)	23 (12.5%)
(total)	55 (29.7%)	79 (42.7%)	51 (27.6%)	184 (100%)
V=0.17 (p=0.982)

Chi-squared Test for Trend in Proportions

data: t\(NASH out of t\)total , using scores: 1 2 3 4 5 6 7 8 9 10 X-squared = 0.2, df = 1, p-value = 0.7

Cochran-Armitage test for trend

data: rbind(t\(NASH, t\)not NASH) Z = -0.4, dim = 10, p-value = 0.7 alternative hypothesis: two.sided

Chi-squared Test for Trend in Proportions

data: t\(ASH out of t\)total , using scores: 1 2 3 4 5 6 7 8 9 10 X-squared = 0.08, df = 1, p-value = 0.8

Cochran-Armitage test for trend

data: rbind(t\(ASH, t\)not ASH) Z = -0.3, dim = 10, p-value = 0.8 alternative hypothesis: two.sided

Chi-squared Test for Trend in Proportions

data: t\(BASH out of t\)total , using scores: 1 2 3 4 5 6 7 8 9 10 X-squared = 0.5, df = 1, p-value = 0.5

Cochran-Armitage test for trend

data: rbind(t\(BASH, t\)not BASH) Z = 0.7, dim = 10, p-value = 0.5 alternative hypothesis: two.sided

0.3 Cox

	LR Chisq	Df	Pr(>Chisq)
Treatment	20.808	4	0.000
Diagnosis	1.868	2	0.393
Age	2.194	1	0.139
Gender	0.275	1	0.600
Diabetes	0.324	1	0.569
Hipertension	0.682	1	0.409
Hiperlipidemia	0.209	1	0.648
Smoking	6.419	2	0.040
Alcohol_Consume	1.800	2	0.407
BMI	3.342	1	0.068
Bilirubin.total..µmol.L.	9.904	1	0.002
INR	1.552	1	0.213
Albumin..g.L.	2.486	1	0.115
BCLC	6.099	4	0.192
CHILD	0.078	2	0.962
Encephalopathy..according.to.Child.Pugh.score.	0.275	1	0.600
Ascites..according.to.Child.Pugh.score.	2.120	2	0.346
Performance.Status	4.082	4	0.395

0.4 Univariate:

Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                Treatment=Curative 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     48       7    0.879  0.0429        0.799        0.967
   36     19      16    0.529  0.0733        0.403        0.694
   60      8       5    0.346  0.0836        0.215        0.555

                Treatment=Transplant 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      5       0     1.00   0.000        1.000            1
   36      3       1     0.75   0.217        0.426            1
   60      3       0     0.75   0.217        0.426            1

                Treatment=Loco-regional 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     31       4   0.8885  0.0526        0.791        0.998
   36      9      18   0.2993  0.0838        0.173        0.518
   60      2       6   0.0748  0.0504        0.020        0.280

                Treatment=Systemic 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     18      17    0.563  0.0816        0.424        0.748
   36      8       7    0.313  0.0842        0.185        0.530
   60      3       3    0.179  0.0758        0.078        0.410

                Treatment=No treatment 
        time       n.risk      n.event     survival      std.err 
     12.0000       4.0000      18.0000       0.2376       0.0907 
lower 95% CI upper 95% CI 
      0.1125       0.5019 

    Pairwise comparisons using Log-Rank test 

data:  db and Treatment 

              Curative          Transplant        Loco-regional    
Transplant    0.142             -                 -                
Loco-regional 0.026             0.019             -                
Systemic      0.004             0.015             0.536            
No treatment  0.000000000000006 0.000503418254664 0.000000000340592
              Systemic         
Transplant    -                
Loco-regional -                
Systemic      -                
No treatment  0.000011587640641

P value adjustment method: BH 
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                Diagnosis=NASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     29      11    0.772  0.0609       0.6617        0.901
   36     10      13    0.388  0.0826       0.2560        0.589
   60      4       5    0.175  0.0744       0.0759        0.403

                Diagnosis=ASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     45      21    0.698  0.0555        0.597        0.816
   36     17      15    0.406  0.0667        0.294        0.561
   60      8       7    0.221  0.0635        0.126        0.388

                Diagnosis=BASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     32      15    0.687  0.0672        0.567        0.832
   36     12      18    0.263  0.0672        0.159        0.434
   60      4       2    0.203  0.0642        0.109        0.377

    Pairwise comparisons using Log-Rank test 

data:  db and Diagnosis 

     NASH ASH
ASH  1.0  -  
BASH 0.8  0.8

P value adjustment method: BH 
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                Gender=F 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     14       6    0.707   0.101        0.535        0.936
   36      3       6    0.283   0.117        0.126        0.636
   60      3       0    0.283   0.117        0.126        0.636

                Gender=M 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     92      41    0.718  0.0376        0.648        0.796
   36     36      40    0.362  0.0448        0.284        0.461
   60     13      14    0.190  0.0413        0.124        0.291

    Pairwise comparisons using Log-Rank test 

data:  db and Gender 

  F  
M 0.7

P value adjustment method: BH 
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                Diabetes=yes 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     42      23    0.687  0.0546       0.5875        0.802
   36     13      20    0.300  0.0629       0.1985        0.452
   60      6       5    0.177  0.0564       0.0952        0.331

                Diabetes=no 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     64      24    0.742  0.0458        0.657        0.837
   36     26      26    0.391  0.0561        0.295        0.518
   60     10       9    0.219  0.0540        0.135        0.355

    Pairwise comparisons using Log-Rank test 

data:  db and Diabetes 

   yes
no 0.3

P value adjustment method: BH 
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                Hipertension=yes 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     66      22    0.772  0.0430        0.693        0.861
   36     21      30    0.356  0.0564        0.261        0.485
   60     10       6    0.232  0.0553        0.145        0.370

                Hipertension=no 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     38      24    0.630  0.0603        0.522        0.760
   36     17      15    0.342  0.0642        0.237        0.494
   60      6       7    0.177  0.0563        0.095        0.330

    Pairwise comparisons using Log-Rank test 

data:  db and Hipertension 

   yes
no 0.3

P value adjustment method: BH 
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                Hiperlipidemia=yes 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     21       8    0.783  0.0683       0.6603        0.929
   36      7      11    0.339  0.0950       0.1961        0.588
   60      3       3    0.175  0.0847       0.0674        0.452

                Hiperlipidemia=no 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     83      38    0.697  0.0413        0.621        0.783
   36     31      34    0.354  0.0474        0.273        0.461
   60     13      10    0.217  0.0451        0.144        0.326

    Pairwise comparisons using Log-Rank test 

data:  db and Hiperlipidemia 

   yes
no 0.8

P value adjustment method: BH 
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                Smoking=0 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     63      20    0.771  0.0451        0.688        0.865
   36     31      25    0.443  0.0562        0.346        0.568
   60     14      11    0.260  0.0539        0.174        0.391

                Smoking=1 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     34      22    0.657  0.0608       0.5478        0.787
   36      5      15    0.250  0.0722       0.1420        0.440
   60      2       3    0.100  0.0619       0.0297        0.337

                Smoking=2 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      8       5    0.619   0.134       0.4045        0.947
   36      3       5    0.181   0.114       0.0524        0.622

    Pairwise comparisons using Log-Rank test 

data:  db and Smoking 

  0    1   
1 0.02 -   
2 0.18 0.94

P value adjustment method: BH 
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                Alcohol_Consume=0 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     64      19    0.790  0.0431        0.710        0.879
   36     31      27    0.438  0.0560        0.341        0.563
   60     13      12    0.240  0.0525        0.156        0.368

                Alcohol_Consume=1 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     30      23    0.610  0.0647       0.4955        0.751
   36      6      10    0.297  0.0797       0.1756        0.503
   60      3       2    0.198  0.0781       0.0915        0.429

                Alcohol_Consume=2 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     11       5    0.680  0.1189       0.4824        0.958
   36      2       8    0.136  0.0892       0.0376        0.492

    Pairwise comparisons using Log-Rank test 

data:  db and Alcohol_Consume 

  0    1   
1 0.07 -   
2 0.07 0.84

P value adjustment method: BH 
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                BCLC=0 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     10       1    0.923  0.0739        0.789        1.000
   36      4       3    0.538  0.1766        0.283        1.000
   60      3       1    0.404  0.1765        0.172        0.951

                BCLC=1 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     43       9    0.835  0.0504        0.742        0.940
   36     12      18    0.424  0.0749        0.300        0.599
   60      5       2    0.303  0.0900        0.169        0.542

                BCLC=2 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     36      10    0.792  0.0590        0.684        0.916
   36     18      16    0.408  0.0753        0.284        0.586
   60      6       8    0.196  0.0638        0.104        0.371

                BCLC=3 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     15      15    0.552  0.0874       0.4043        0.752
   36      5       7    0.255  0.0880       0.1300        0.502
   60      2       3    0.102  0.0661       0.0287        0.363

                BCLC=4 
        time       n.risk      n.event     survival      std.err 
     12.0000       1.0000      12.0000       0.2000       0.1033 
lower 95% CI upper 95% CI 
      0.0727       0.5503 

    Pairwise comparisons using Log-Rank test 

data:  db and BCLC 

  0     1           2           3    
1 0.638 -           -           -    
2 0.357 0.678       -           -    
3 0.064 0.016       0.034       -    
4 0.001 0.000000002 0.000000002 0.001

P value adjustment method: BH 
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                CHILD=1 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     71      12    0.868  0.0356        0.801        0.941
   36     30      27    0.483  0.0597        0.379        0.615
   60     14      10    0.293  0.0593        0.197        0.436

                CHILD=2 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     28      24    0.563  0.0683        0.444        0.714
   36      7      15    0.198  0.0611        0.108        0.363
   60      2       3    0.106  0.0515        0.041        0.275

                CHILD=3 
        time       n.risk      n.event     survival      std.err 
      12.000        3.000        8.000        0.273        0.134 
lower 95% CI upper 95% CI 
       0.104        0.716 

    Pairwise comparisons using Log-Rank test 

data:  db and CHILD 

  1           2   
2 0.000009990 -   
3 0.000000001 0.02

P value adjustment method: BH 
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                Encephalopathy..according.to.Child.Pugh.score.=1 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     99      40    0.736  0.0361        0.669        0.811
   36     38      40    0.384  0.0450        0.305        0.483
   60     15      14    0.214  0.0427        0.145        0.316

                Encephalopathy..according.to.Child.Pugh.score.=2-3 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      5       6   0.4545  0.1501        0.238        0.868
   36      1       4   0.0909  0.0867        0.014        0.589
   60      1       0   0.0909  0.0867        0.014        0.589

    Pairwise comparisons using Log-Rank test 

data:  db and Encephalopathy..according.to.Child.Pugh.score. 

    1    
2-3 0.006

P value adjustment method: BH 
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                Ascites..according.to.Child.Pugh.score.=1 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     90      26    0.798  0.0356        0.731        0.871
   36     36      38    0.412  0.0492        0.326        0.521
   60     15      12    0.243  0.0478        0.166        0.358

                Ascites..according.to.Child.Pugh.score.=2 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      7      11    0.368   0.122        0.192        0.706
   36      2       1    0.295   0.118        0.135        0.646

                Ascites..according.to.Child.Pugh.score.=3 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      7       9   0.4375   0.124       0.2510        0.763
   36      1       5   0.0833   0.077       0.0136        0.510
   60      1       0   0.0833   0.077       0.0136        0.510

    Pairwise comparisons using Log-Rank test 

data:  db and Ascites..according.to.Child.Pugh.score. 

  1      2  
2 0.0009 -  
3 0.0009 0.7

P value adjustment method: BH 
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    make.names(by)))

                Performance.Status=0 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     63      20    0.784  0.0431        0.704        0.873
   36     26      20    0.486  0.0600        0.382        0.619
   60      9       9    0.269  0.0642        0.168        0.430

                Performance.Status=1 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     35       9    0.788  0.0628        0.674        0.921
   36     12      20    0.296  0.0715        0.184        0.475
   60      7       4    0.192  0.0626        0.101        0.364

                Performance.Status=2 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      6       9    0.471   0.121        0.284        0.779
   36      1       4    0.118   0.101        0.022        0.630

                Performance.Status=3 
        time       n.risk      n.event     survival      std.err 
     12.0000       1.0000       7.0000       0.2222       0.1386 
lower 95% CI upper 95% CI 
      0.0655       0.7544 

                Performance.Status=4 
     time n.risk n.event survival std.err lower 95% CI upper 95% CI

    Pairwise comparisons using Log-Rank test 

data:  db and Performance.Status 

  0         1         2     3    
1 0.389     -         -     -    
2 0.0002116 0.008     -     -    
3 0.0000001 0.0001380 0.216 -    
4 0.0002116 0.005     0.643 0.820

P value adjustment method: BH 

0.5 Survival: Treatment x Diagnosis

Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    by))

                Treatment=Curative 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     48       7    0.879  0.0429        0.799        0.967
   36     19      16    0.529  0.0733        0.403        0.694
   60      8       5    0.346  0.0836        0.215        0.555

                Treatment=Transplant 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      5       0     1.00   0.000        1.000            1
   36      3       1     0.75   0.217        0.426            1
   60      3       0     0.75   0.217        0.426            1

                Treatment=Loco-regional 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     31       4   0.8885  0.0526        0.791        0.998
   36      9      18   0.2993  0.0838        0.173        0.518
   60      2       6   0.0748  0.0504        0.020        0.280

                Treatment=Systemic 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     18      17    0.563  0.0816        0.424        0.748
   36      8       7    0.313  0.0842        0.185        0.530
   60      3       3    0.179  0.0758        0.078        0.410

                Treatment=No treatment 
        time       n.risk      n.event     survival      std.err 
     12.0000       4.0000      18.0000       0.2376       0.0907 
lower 95% CI upper 95% CI 
      0.1125       0.5019 

	records	n.max	n.start	events	*rmean	*se(rmean)	median	0.95LCL	0.95UCL
Treatment=Curative	66	66	66	29	46.17	4.41	39	26	NA
Treatment=Transplant	5	5	5	1	69.00	11.26	NA	30	NA
Treatment=Loco-regional	39	39	39	28	31.23	3.41	30	20	37
Treatment=Systemic	43	43	43	29	28.94	4.64	22	10	40
Treatment=No treatment	26	26	26	22	6.69	1.72	3	2	14

    Pairwise comparisons using Log-Rank test 

data:  db and Treatment 

              Curative          Transplant        Loco-regional    
Transplant    0.142             -                 -                
Loco-regional 0.026             0.019             -                
Systemic      0.004             0.015             0.536            
No treatment  0.000000000000006 0.000503418254664 0.000000000340592
              Systemic         
Transplant    -                
Loco-regional -                
Systemic      -                
No treatment  0.000011587640641

P value adjustment method: BH 

    Pairwise comparisons using Log-Rank test 

data:  db2 and Treatment 

              Curative          Loco-regional     Systemic         
Loco-regional 0.025             -                 -                
Systemic      0.003             0.536             -                
No treatment  0.000000000000004 0.000000000204355 0.000006952584384

P value adjustment method: BH 

0.5.1 Diagnosis == “ASH”

Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    by))

                Treatment=Curative 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     21       2    0.913  0.0588        0.805        1.000
   36      6       7    0.523  0.1176        0.336        0.812
   60      3       1    0.418  0.1327        0.225        0.779

                Treatment=Transplant 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      3       0        1       0            1            1
   36      2       0        1       0            1            1
   60      2       0        1       0            1            1

                Treatment=Loco-regional 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     13       0    1.000   0.000       1.0000        1.000
   36      4       7    0.417   0.142       0.2133        0.814
   60      1       3    0.104   0.097       0.0168        0.646

                Treatment=Systemic 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      8       7    0.521   0.132       0.3166        0.857
   36      5       1    0.434   0.136       0.2351        0.801
   60      2       3    0.174   0.110       0.0504        0.598

                Treatment=No treatment 
     time n.risk n.event survival std.err lower 95% CI upper 95% CI

	records	n.max	n.start	events	*rmean	*se(rmean)	median	0.95LCL	0.95UCL
Treatment=Curative	27	27	27	11	46.09	6.539	39.0	28	NA
Treatment=Transplant	3	3	3	0	76.00	0.000	NA	NA	NA
Treatment=Loco-regional	16	16	16	10	38.48	4.823	33.0	27	NA
Treatment=Systemic	16	16	16	12	28.49	6.742	13.0	7	NA
Treatment=No treatment	13	13	13	11	3.33	0.584	2.5	2	NA

    Pairwise comparisons using Log-Rank test 

data:  db and Treatment 

              Curative      Transplant Loco-regional Systemic     
Transplant    0.20          -          -             -            
Loco-regional 0.53          0.07       -             -            
Systemic      0.05          0.04       0.48          -            
No treatment  0.00000000005 0.01       0.00000011027 0.00008204834

P value adjustment method: BH 

    Pairwise comparisons using Log-Rank test 

data:  db2 and Treatment 

              Curative      Loco-regional Systemic     
Loco-regional 0.53          -             -            
Systemic      0.04          0.52          -            
No treatment  0.00000000003 0.00000006616 0.00004922900

P value adjustment method: BH 

0.5.2 Diagnosis == “NASH”

Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    by))

                Treatment=Curative 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     18       1    0.955  0.0444        0.871        1.000
   36      9       6    0.607  0.1174        0.415        0.887
   60      4       4    0.308  0.1227        0.141        0.673

                Treatment=Loco-regional 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      8       2    0.818   0.116       0.6192        1.000
   36      1       5    0.184   0.153       0.0359        0.944

                Treatment=Systemic 
        time       n.risk      n.event     survival      std.err 
      12.000        1.000        6.000        0.333        0.175 
lower 95% CI upper 95% CI 
       0.119        0.932 

                Treatment=No treatment 
        time       n.risk      n.event     survival      std.err 
      12.000        2.000        2.000        0.625        0.213 
lower 95% CI upper 95% CI 
       0.320        1.000 

	records	n.max	n.start	events	*rmean	*se(rmean)	median	0.95LCL	0.95UCL
Treatment=Curative	25	25	25	11	29.7	2.32	50.0	23	NA
Treatment=Loco-regional	11	11	11	8	21.2	3.54	17.0	14	NA
Treatment=Systemic	12	12	12	6	17.3	5.04	10.5	8	NA
Treatment=No treatment	6	6	6	4	12.8	4.09	16.0	3	NA

    Pairwise comparisons using Log-Rank test 

data:  db and Treatment 

              Curative Loco-regional Systemic
Loco-regional 0.02     -             -       
Systemic      0.01     0.35          -       
No treatment  0.01     0.35          0.88    

P value adjustment method: BH 

    Pairwise comparisons using Log-Rank test 

data:  db2 and Treatment 

              Curative Loco-regional Systemic
Loco-regional 0.02     -             -       
Systemic      0.01     0.35          -       
No treatment  0.01     0.35          0.88    

P value adjustment method: BH 

0.5.3 Diagnosis == “BASH”

Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    by))

                Treatment=Curative 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      9       4    0.692   0.128        0.482        0.995
   36      4       3    0.404   0.149        0.196        0.831
   60      1       0    0.404   0.149        0.196        0.831

                Treatment=Transplant 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      2       0      1.0   0.000        1.000            1
   36      1       1      0.5   0.354        0.125            1
   60      1       0      0.5   0.354        0.125            1

                Treatment=Loco-regional 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     10       2   0.8182  0.1163        0.619        1.000
   36      4       6   0.2727  0.1343        0.104        0.716
   60      1       2   0.0909  0.0867        0.014        0.589

                Treatment=Systemic 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      9       4    0.733   0.114       0.5405        0.995
   36      3       6    0.244   0.121       0.0924        0.647
   60      1       0    0.244   0.121       0.0924        0.647

                Treatment=No treatment 
        time       n.risk      n.event     survival      std.err 
     12.0000       2.0000       5.0000       0.2857       0.1707 
lower 95% CI upper 95% CI 
      0.0886       0.9218 

	records	n.max	n.start	events	*rmean	*se(rmean)	median	0.95LCL	0.95UCL
Treatment=Curative	14	14	14	7	38.56	8.80	24	11	NA
Treatment=Transplant	2	2	2	1	52.00	15.56	30	30	NA
Treatment=Loco-regional	12	12	12	10	28.82	5.53	27	17	NA
Treatment=Systemic	15	15	15	11	32.58	7.07	25	22	NA
Treatment=No treatment	7	7	7	7	6.57	3.59	2	0	NA

    Pairwise comparisons using Log-Rank test 

data:  db and Treatment 

              Curative Transplant Loco-regional Systemic
Transplant    0.70     -          -             -       
Loco-regional 0.69     0.50       -             -       
Systemic      0.80     0.50       0.81          -       
No treatment  0.01     0.07       0.01          0.01    

P value adjustment method: BH 

    Pairwise comparisons using Log-Rank test 

data:  db2 and Treatment 

              Curative Loco-regional Systemic
Loco-regional 0.723    -             -       
Systemic      0.808    0.808         -       
No treatment  0.008    0.008         0.008   

P value adjustment method: BH 

0.6 Survival: Diagnosis x Treatment

Factor	Detalis	Curative	Transplant	Loco-regional	Systemic	No treatment	Total	Statistics
Treatment		66 (35.9%)	5 (2.7%)	41 (22.3%)	43 (23.4%)	29 (15.8%)	184
Gender	F	11 (16.7%)	1 (20.0%)	3 (7.3%)	2 (4.7%)	5 (17.2%)	22 (12.0%)	V=0.17 (p=0.241)
	M	55 (83.3%)	4 (80.0%)	38 (92.7%)	41 (95.3%)	24 (82.8%)	162 (88.0%)
Age	μ ±DS	68.55 ±8.16	60.32 ±7.03	71.25 ±7.78	69.46 ±8.2	67.02 ±7.51	68.83 ±8.15	1-way ANOVA: p=0.026
	M (min:max)	70.45 (45.2:83.2)	61.7 (53.5:70.5)	71.1 (50.9:86)	70.2 (48.3:86.1)	66.7 (49.2:83.9)	70 (45.2:86.1)
Year of diagnosis	μ ±DS	2015.45 ±2.99	2013.20 ±2.17	2013.55 ±3.34	2015.44 ±2.75	2015.14 ±3.07	2014.95 ±3.1	Kruskal-Wallis: p=0.022
	M (min:max)	2016 (2009:2019)	2012 (2012:2017)	2013 (2008:2019)	2016 (2009:2019)	2016 (2010:2019)	2015.5 (2008:2019)
Survival	μ ±DS	28.82 ±25.8	59.40 ±29.5	25.18 ±16.9	19.53 ±20.7	5.31 ±7.15	23.11 ±23.0	Kruskal-Wallis: p<0.001
	M (min:max)	20.5 (1:114)	74 (25:85)	21 (2:76)	10 (1:82)	2 (0:27)	15 (0:114)
Status	0	33 (50.0%)	4 (80.0%)	9 (23.1%)	13 (30.2%)	3 (11.5%)	62 (34.6%)	V=0.25 (p=0.004)
	1	29 (43.9%)	1 (20.0%)	28 (71.8%)	29 (67.4%)	22 (84.6%)	109 (60.9%)
	2	4 (6.1%)	0	2 (5.1%)	1 (2.3%)	1 (3.8%)	8 (4.5%)
MRI_diagnosis		25 (37.9%)	1 (20.0%)	13 (31.7%)	6 (14.0%)	12 (41.4%)	57 (31.0%)	V=0.22 (p=0.060)
CT_Diagnosis		34 (51.5%)	3 (60.0%)	23 (56.1%)	31 (72.1%)	19 (65.5%)	110 (59.8%)	V=0.17 (p=0.266)
US_Diagnosis		18 (27.3%)	0	19 (46.3%)	15 (34.9%)	8 (27.6%)	60 (32.6%)	V=0.20 (p=0.124)
HCC_Screening_18months_before		33 (50.8%)	2 (40.0%)	13 (32.5%)	5 (11.6%)	7 (24.1%)	60 (33.0%)	V=0.33 (p<0.001)
US_Screening		24 (41.4%)	1 (25.0%)	7 (21.9%)	3 (10.3%)	6 (25.0%)	41 (27.9%)	V=0.27 (p=0.035)
MRI_Screening		9 (15.5%)	1 (25.0%)	5 (15.6%)	0	2 (8.3%)	17 (11.6%)	V=0.20 (p=0.189)
CT_Screening		12 (20.7%)	1 (25.0%)	8 (25.0%)	3 (10.3%)	3 (12.5%)	27 (18.4%)	V=0.14 (p=0.548)
ASH		41 (62.1%)	5 (100%)	29 (70.7%)	31 (72.1%)	23 (79.3%)	129 (70.1%)	V=0.17 (p=0.249)
NAFLD		39 (59.1%)	2 (40.0%)	25 (61.0%)	27 (62.8%)	13 (44.8%)	106 (57.6%)	V=0.13 (p=0.509)
Cirrhosis		54 (81.8%)	5 (100%)	35 (85.4%)	35 (81.4%)	26 (89.7%)	155 (84.2%)	V=0.11 (p=0.705)
HCV	no	66 (100%)	5 (100%)	41 (100%)	43 (100%)	29 (100%)	184 (100%)	V=NaN (p=1.000)
HBc	no	66 (100%)	5 (100%)	41 (100%)	43 (100%)	29 (100%)	184 (100%)	V=NaN (p=1.000)
Diagnosis	NASH	25 (37.9%)	0	12 (29.3%)	12 (27.9%)	6 (20.7%)	55 (29.9%)	V=0.15 (p=0.421)
	ASH	27 (40.9%)	3 (60.0%)	16 (39.0%)	16 (37.2%)	16 (55.2%)	78 (42.4%)
	BASH	14 (21.2%)	2 (40.0%)	13 (31.7%)	15 (34.9%)	7 (24.1%)	51 (27.7%)
Diabetes		28 (42.4%)	1 (20.0%)	15 (36.6%)	19 (44.2%)	16 (55.2%)	79 (42.9%)	V=0.14 (p=0.470)
Hipertension		41 (64.1%)	3 (60.0%)	28 (73.7%)	26 (60.5%)	11 (42.3%)	109 (61.9%)	V=0.19 (p=0.156)
Hiperlipidemia		17 (26.6%)	1 (20.0%)	8 (21.1%)	12 (27.9%)	3 (11.5%)	41 (23.3%)	V=0.13 (p=0.551)
Smoking	0	33 (50.8%)	3 (60.0%)	27 (65.9%)	19 (44.2%)	12 (41.4%)	94 (51.4%)	V=0.13 (p=0.596)
	1	26 (40.0%)	2 (40.0%)	12 (29.3%)	20 (46.5%)	15 (51.7%)	75 (41.0%)
	2	6 (9.2%)	0	2 (4.9%)	4 (9.3%)	2 (6.9%)	14 (7.7%)
Alcohol_Consume	0	32 (49.2%)	3 (60.0%)	28 (68.3%)	23 (53.5%)	11 (37.9%)	97 (53.0%)	V=0.16 (p=0.322)
	1	28 (43.1%)	1 (20.0%)	9 (22.0%)	16 (37.2%)	15 (51.7%)	69 (37.7%)
	2	5 (7.7%)	1 (20.0%)	4 (9.8%)	4 (9.3%)	3 (10.3%)	17 (9.3%)
BMI	μ ±DS	28.57 ±5.0	25.71 ±3.9	28.32 ±6.25	28.92 ±4.29	29.22 ±5.2	28.63 ±5.12	Kruskal-Wallis: p=0.590
	M (min:max)	27.76 (20.9:42.17)	26.59 (19.75:30.37)	28.45 (18.48:48.32)	29.44 (20.34:37.8)	28.72 (19.84:46.65)	28.41 (18.48:48.32)
Encephalopathy (acc. to CP score)	1	63 (96.9%)	4 (80.0%)	38 (95.0%)	41 (100%)	23 (79.3%)	169 (93.9%)	V=0.30 (p=0.003)
	2-3	2 (3.1%)	1 (20.0%)	2 (5.0%)	0	6 (20.7%)	11 (6.1%)
Ascites (acc. to CP score)	1	59 (90.8%)	3 (60.0%)	33 (84.6%)	35 (85.4%)	13 (44.8%)	143 (79.9%)	V=0.35 (p<0.001)
	2	4 (6.2%)	0	6 (15.4%)	4 (9.8%)	6 (20.7%)	20 (11.2%)
	3	2 (3.1%)	2 (40.0%)	0	2 (4.9%)	10 (34.5%)	16 (8.9%)
Bilirubin total (µmol/L)	μ ±DS	20.30 ±15.0	27.20 ±14.5	20.05 ±15.2	28.71 ±62.6	56.21 ±62.0	28.10 ±42.3	Kruskal-Wallis: p<0.001
	M (min:max)	15.5 (5:77)	24 (16:52)	16 (4:67)	15 (3:413)	36 (6:286)	17 (3:413)
INR	μ ±DS	1.15 ±0.174	1.41 ±0.12	1.16 ±0.168	1.14 ±0.176	1.28 ±0.251	1.18 ±0.195	Kruskal-Wallis: p<0.001
	M (min:max)	1.12 (0.8:1.96)	1.43 (1.29:1.56)	1.12 (0.99:1.64)	1.1 (0.8:1.83)	1.26 (1:2.07)	1.14 (0.8:2.07)
Albumin (g/L)	μ ±DS	34.20 ±4.8	29.20 ±5.93	33.46 ±5.49	32.46 ±5.45	26.19 ±4.04	32.12 ±5.78	Kruskal-Wallis: p<0.001
	M (min:max)	34 (21:42)	28 (24:38)	32 (24:49.8)	32 (17:41)	26 (20:34)	32 (17:49.8)
CHILD	1	45 (72.6%)	2 (40.0%)	27 (69.2%)	25 (62.5%)	4 (14.3%)	103 (59.2%)	V=0.34 (p<0.001)
	2	15 (24.2%)	2 (40.0%)	12 (30.8%)	14 (35.0%)	17 (60.7%)	60 (34.5%)
	3	2 (3.2%)	1 (20.0%)	0	1 (2.5%)	7 (25.0%)	11 (6.3%)
CHILD_A		45 (72.6%)	2 (40.0%)	27 (69.2%)	25 (62.5%)	4 (14.3%)	103 (59.2%)	V=0.42 (p<0.001)
CHILD_B		15 (24.2%)	2 (40.0%)	12 (30.8%)	14 (35.0%)	17 (60.7%)	60 (34.5%)	V=0.26 (p=0.019)
CHILD_C		2 (3.2%)	1 (20.0%)	0	1 (2.5%)	7 (25.0%)	11 (6.3%)	V=0.36 (p<0.001)
BCLC	0	11 (16.9%)	1 (20.0%)	0	0	0	12 (6.6%)	V=0.40 (p<0.001)
	1	39 (60.0%)	2 (40.0%)	15 (36.6%)	3 (7.0%)	4 (13.8%)	63 (34.4%)
	2	12 (18.5%)	1 (20.0%)	20 (48.8%)	18 (41.9%)	6 (20.7%)	57 (31.1%)
	3	3 (4.6%)	1 (20.0%)	4 (9.8%)	20 (46.5%)	8 (27.6%)	36 (19.7%)
	4	0	0	2 (4.9%)	2 (4.7%)	11 (37.9%)	15 (8.2%)
BCLC_0		11 (16.9%)	1 (20.0%)	0	0	0	12 (6.6%)	V=0.34 (p<0.001)
BCLC_1		39 (60.0%)	2 (40.0%)	15 (36.6%)	3 (7.0%)	4 (13.8%)	63 (34.4%)	V=0.46 (p<0.001)
BCLC_2		12 (18.5%)	1 (20.0%)	20 (48.8%)	18 (41.9%)	6 (20.7%)	57 (31.1%)	V=0.29 (p=0.005)
BCLC_3		3 (4.6%)	1 (20.0%)	4 (9.8%)	20 (46.5%)	8 (27.6%)	36 (19.7%)	V=0.42 (p<0.001)
BCLC_4		0	0	2 (4.9%)	2 (4.7%)	11 (37.9%)	15 (8.2%)	V=0.48 (p<0.001)
Resection		34 (51.5%)	1 (20.0%)	0	0	0	35 (19.0%)	V=0.62 (p<0.001)
Transplant		0	5 (100%)	0	0	0	5 (2.7%)	V=1.00 (p<0.001)
TACE		1 (1.5%)	1 (20.0%)	22 (53.7%)	0	0	24 (13.0%)	V=0.65 (p<0.001)
TAE		0	0	14 (34.1%)	0	1 (3.4%)	15 (8.2%)	V=0.51 (p<0.001)
RFA		3 (4.5%)	0	0	0	0	3 (1.6%)	V=0.17 (p=0.248)
MWA		35 (53.0%)	0	0	0	0	35 (19.0%)	V=0.65 (p<0.001)
SIRT		0	0	5 (12.2%)	0	0	5 (2.7%)	V=0.31 (p=0.001)
Sistemic_therapy		0	0	0	43 (100%)	0	43 (23.4%)	V=1.00 (p<0.001)
Curative_treatment		66 (100%)	0	0	0	0	66 (35.9%)	V=1.00 (p<0.001)
Loco_regional_therapies		0	0	41 (100%)	0	0	41 (22.3%)	V=1.00 (p<0.001)
No_treatment		0	0	0	0	29 (100%)	29 (15.8%)	V=1.00 (p<0.001)
Performance Status	0	51 (78.5%)	3 (60.0%)	19 (46.3%)	27 (64.3%)	9 (31.0%)	109 (59.9%)	V=0.29 (p<0.001)
	1	13 (20.0%)	1 (20.0%)	18 (43.9%)	10 (23.8%)	4 (13.8%)	46 (25.3%)
	2	1 (1.5%)	1 (20.0%)	2 (4.9%)	4 (9.5%)	9 (31.0%)	17 (9.3%)
	3	0	0	2 (4.9%)	1 (2.4%)	6 (20.7%)	9 (4.9%)
	4	0	0	0	0	1 (3.4%)	1 (0.5%)
PS_0		51 (78.5%)	3 (60.0%)	19 (46.3%)	27 (64.3%)	9 (31.0%)	109 (59.9%)	V=0.35 (p<0.001)
PS_1		13 (20.0%)	1 (20.0%)	18 (43.9%)	10 (23.8%)	4 (13.8%)	46 (25.3%)	V=0.24 (p=0.031)
PS_2		1 (1.5%)	1 (20.0%)	2 (4.9%)	4 (9.5%)	9 (31.0%)	17 (9.3%)	V=0.35 (p<0.001)
PS_3		0	0	2 (4.9%)	1 (2.4%)	6 (20.7%)	9 (4.9%)	V=0.33 (p<0.001)
PS_4		0	0	0	0	1 (3.4%)	1 (0.5%)	V=0.17 (p=0.257)
μ ±DS = Mean (standard deviation); M (min:max) = Median (min:max); MW = Mann-WhitneyTest; OR/RR = odds-ratio / risc-ratio [95% CI] and p value from Fisher test); V = Cramer V (p value from Chi² test);

Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    by))

                Diagnosis=NASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     29      11    0.772  0.0609       0.6617        0.901
   36     10      13    0.388  0.0826       0.2560        0.589
   60      4       5    0.175  0.0744       0.0759        0.403

                Diagnosis=ASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     45      20    0.708  0.0555        0.607        0.825
   36     17      15    0.412  0.0674        0.299        0.568
   60      8       7    0.224  0.0643        0.128        0.393

                Diagnosis=BASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     32      15    0.687  0.0672        0.567        0.832
   36     12      18    0.263  0.0672        0.159        0.434
   60      4       2    0.203  0.0642        0.109        0.377

	records	n.max	n.start	events	*rmean	*se(rmean)	median	0.95LCL	0.95UCL
Diagnosis=NASH	54	54	54	29	38.7	6.43	23	17	50
Diagnosis=ASH	75	75	75	44	41.0	5.32	28	24	40
Diagnosis=BASH	50	50	50	36	33.9	5.49	25	17	32

    Pairwise comparisons using Log-Rank test 

data:  db and Diagnosis 

     NASH ASH
ASH  0.9  -  
BASH 0.8  0.8

P value adjustment method: BH 

[1] " Exclude: Transplant >>> "

    Pairwise comparisons using Log-Rank test 

data:  db2 and Diagnosis 

     NASH ASH
ASH  0.8  -  
BASH 0.6  0.6

P value adjustment method: BH 

[1] " Exclude: No treatment >>> "

    Pairwise comparisons using Log-Rank test 

data:  db3 and Diagnosis 

     NASH ASH
ASH  0.5  -  
BASH 0.8  0.5

P value adjustment method: BH 

0.6.1 Treatment == “Curative”

Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    by))

                Diagnosis=NASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     18       1    0.955  0.0444        0.871        1.000
   36      9       6    0.607  0.1174        0.415        0.887
   60      4       4    0.308  0.1227        0.141        0.673

                Diagnosis=ASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     21       2    0.913  0.0588        0.805        1.000
   36      6       7    0.523  0.1176        0.336        0.812
   60      3       1    0.418  0.1327        0.225        0.779

                Diagnosis=BASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      9       4    0.692   0.128        0.482        0.995
   36      4       3    0.404   0.149        0.196        0.831
   60      1       0    0.404   0.149        0.196        0.831

	records	n.max	n.start	events	*rmean	*se(rmean)	median	0.95LCL	0.95UCL
Diagnosis=NASH	25	25	25	11	56.3	9.72	50	23	NA
Diagnosis=ASH	27	27	27	11	60.3	10.95	39	28	NA
Diagnosis=BASH	14	14	14	7	53.1	14.09	24	11	NA

    Pairwise comparisons using Log-Rank test 

data:  db and Diagnosis 

     NASH ASH
ASH  0.9  -  
BASH 0.7  0.7

P value adjustment method: BH 

0.6.2 Treatment == “Transplant”

Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    by))

                Diagnosis=ASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      3       0        1       0            1            1
   36      2       0        1       0            1            1
   60      2       0        1       0            1            1

                Diagnosis=BASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      2       0      1.0   0.000        1.000            1
   36      1       1      0.5   0.354        0.125            1
   60      1       0      0.5   0.354        0.125            1

	records	n.max	n.start	events	*rmean	*se(rmean)	median	0.95LCL	0.95UCL
Diagnosis=ASH	3	3	3	0	84	0.0	NA	NA	NA
Diagnosis=BASH	2	2	2	1	57	19.1	30	30	NA

    Pairwise comparisons using Log-Rank test 

data:  db and Diagnosis 

     ASH
BASH 0.3

P value adjustment method: BH 

0.6.3 Treatment == “Loco-regional”

Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    by))

                Diagnosis=NASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      8       2    0.818   0.116       0.6192        1.000
   36      1       5    0.184   0.153       0.0359        0.944

                Diagnosis=ASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     13       0    1.000   0.000       1.0000        1.000
   36      4       7    0.417   0.142       0.2133        0.814
   60      1       3    0.104   0.097       0.0168        0.646

                Diagnosis=BASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12     10       2   0.8182  0.1163        0.619        1.000
   36      4       6   0.2727  0.1343        0.104        0.716
   60      1       2   0.0909  0.0867        0.014        0.589

	records	n.max	n.start	events	*rmean	*se(rmean)	median	0.95LCL	0.95UCL
Diagnosis=NASH	11	11	11	8	22.2	4.08	17	14	NA
Diagnosis=ASH	16	16	16	10	37.4	4.09	33	27	NA
Diagnosis=BASH	12	12	12	10	28.1	5.01	27	17	NA

    Pairwise comparisons using Log-Rank test 

data:  db and Diagnosis 

     NASH ASH 
ASH  0.05 -   
BASH 0.43 0.41

P value adjustment method: BH 

0.6.4 Treatment == “Systemic”

Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+% 
    by))

                Diagnosis=NASH 
        time       n.risk      n.event     survival      std.err 
      12.000        1.000        6.000        0.333        0.175 
lower 95% CI upper 95% CI 
       0.119        0.932 

                Diagnosis=ASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      8       7    0.521   0.132       0.3166        0.857
   36      5       1    0.434   0.136       0.2351        0.801
   60      2       3    0.174   0.110       0.0504        0.598

                Diagnosis=BASH 
 time n.risk n.event survival std.err lower 95% CI upper 95% CI
   12      9       4    0.733   0.114       0.5405        0.995
   36      3       6    0.244   0.121       0.0924        0.647
   60      1       0    0.244   0.121       0.0924        0.647

	records	n.max	n.start	events	*rmean	*se(rmean)	median	0.95LCL	0.95UCL
Diagnosis=NASH	12	12	12	6	27.0	10.07	10.5	8	NA
Diagnosis=ASH	16	16	16	12	28.5	6.74	13.0	7	NA
Diagnosis=BASH	15	15	15	11	30.6	6.20	25.0	22	NA

    Pairwise comparisons using Log-Rank test 

data:  db and Diagnosis 

     NASH ASH
ASH  0.7  -  
BASH 0.7  0.7

P value adjustment method: BH 

1 References

1. R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.