IM
IM
IM
Factor | Detalis | Total |
N= | 243 | |
Survival | μ ±DS | 29.03 ±27.1 |
M (min:max) | 20.5 (0:114) | |
Status | 0 | 93 (39.7%) |
1 | 131 (56.0%) | |
2 | 10 (4.3%) | |
Treatment | Curative | 91 (37.6%) |
Transplant | 27 (11.2%) | |
Loco-regional | 50 (20.7%) | |
Sistemic | 40 (16.5%) | |
No treatment | 34 (14.0%) | |
DG | ASH | 89 (36.6%) |
NASH | 60 (24.7%) | |
VIRAL | 94 (38.7%) | |
μ ±DS = Mean (standard deviation); M (min:max) = Median (min:max); | ||
0.1 Treatment x DG
Factor | Detalis | Total | ASH | NASH | VIRAL | Statistics |
DG | 243 | 89 (36.6%) | 60 (24.7%) | 94 (38.7%) | ||
Survival | μ ±DS | 29.03 ±27.1 | 29.65 ±29.6 | 25.05 ±26.0 | 31.13 ±25.3 | Kruskal-Wallis: p=0.178 |
M (min:max) | 20.5 (0:114) | 20 (0:114) | 15 (0:110) | 23 (0:112) | ||
Status | 0 | 93 (39.7%) | 36 (41.9%) | 27 (45.8%) | 30 (33.7%) | V=0.08 (p=0.604) |
1 | 131 (56.0%) | 47 (54.7%) | 29 (49.2%) | 55 (61.8%) | ||
2 | 10 (4.3%) | 3 (3.5%) | 3 (5.1%) | 4 (4.5%) | ||
Treatment | Curative | 91 (37.6%) | 28 (31.5%) | 27 (45.0%) | 36 (38.7%) | V=0.14 (p=0.268) |
Transplant | 27 (11.2%) | 9 (10.1%) | 3 (5.0%) | 15 (16.1%) | ||
Loco-regional | 50 (20.7%) | 19 (21.3%) | 12 (20.0%) | 19 (20.4%) | ||
Sistemic | 40 (16.5%) | 16 (18.0%) | 12 (20.0%) | 12 (12.9%) | ||
No treatment | 34 (14.0%) | 17 (19.1%) | 6 (10.0%) | 11 (11.8%) | ||
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))
Treatment=Curative
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 73 11 0.871 0.0364 0.802 0.945
36 32 19 0.573 0.0619 0.463 0.708
60 13 11 0.346 0.0658 0.238 0.502
Treatment=Transplant
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 26 0 1.000 0.0000 1.000 1.000
36 18 4 0.828 0.0787 0.687 0.998
60 12 2 0.713 0.1014 0.540 0.943
Treatment=Loco-regional
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 42 3 0.938 0.0345 0.873 1.000
36 14 5 0.789 0.0707 0.662 0.941
60 6 0 0.789 0.0707 0.662 0.941
Treatment=Sistemic
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 13 8 0.671 0.100 0.501 0.899
36 6 3 0.447 0.125 0.259 0.773
60 3 0 0.447 0.125 0.259 0.773
Treatment=No treatment
time n.risk n.event survival std.err
12.000 3.000 3.000 0.874 0.069
lower 95% CI upper 95% CI
0.748 1.000 records n.max n.start events *rmean *se(rmean)
Treatment=Curative 88 88 88 49 48.1 4.18
Treatment=Transplant 27 27 27 14 74.8 6.92
Treatment=Loco-regional 49 49 49 12 72.2 6.63
Treatment=Sistemic 39 39 39 13 51.3 11.07
Treatment=No treatment 29 29 29 3 96.3 7.49
median 0.95LCL 0.95UCL
Treatment=Curative 39 35 66
Treatment=Transplant 83 62 NA
Treatment=Loco-regional 77 76 NA
Treatment=Sistemic 34 17 NA
Treatment=No treatment NA NA NA
Pairwise comparisons using Log-Rank test
data: db and Treatment
Curative Transplant Loco-regional Sistemic
Transplant 0.07 - - -
Loco-regional 0.07 0.83 - -
Sistemic 0.80 0.21 0.07 -
No treatment 0.80 0.33 0.42 0.86
P value adjustment method: BH
Pairwise comparisons using Log-Rank test
data: db2 and Treatment
Curative Transplant Loco-regional
Transplant 0.04 - -
Loco-regional 0.04 0.75 -
Sistemic 0.69 0.13 0.04
P value adjustment method: BH 
0.1.1 DG == “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 22 3 0.884 0.0634 0.768 1.000
36 7 7 0.495 0.1217 0.306 0.801
60 3 3 0.254 0.1187 0.102 0.635
Treatment=Transplant
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 9 0 1.000 0.000 1.000 1
36 7 2 0.778 0.139 0.549 1
60 6 1 0.667 0.157 0.420 1
Treatment=Loco-regional
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 16 3 0.842 0.0837 0.693 1.00
36 7 2 0.711 0.1127 0.521 0.97
60 4 0 0.711 0.1127 0.521 0.97
Treatment=Sistemic
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 8 3 0.742 0.132 0.524 1
36 5 0 0.742 0.132 0.524 1
60 2 0 0.742 0.132 0.524 1
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)
Treatment=Curative 28 28 28 15 41.4 6.78
Treatment=Transplant 9 9 9 7 73.0 11.39
Treatment=Loco-regional 19 19 19 8 64.2 8.88
Treatment=Sistemic 16 16 16 4 65.2 14.95
Treatment=No treatment 14 14 14 2 88.8 11.28
median 0.95LCL 0.95UCL
Treatment=Curative 31 29 NA
Treatment=Transplant 83 40 NA
Treatment=Loco-regional 77 76 NA
Treatment=Sistemic 64 64 NA
Treatment=No treatment NA NA NA
Pairwise comparisons using Log-Rank test
data: db and Treatment
Curative Transplant Loco-regional Sistemic
Transplant 0.5 - - -
Loco-regional 0.5 0.6 - -
Sistemic 0.5 0.6 0.6 -
No treatment 0.5 0.5 0.5 0.5
P value adjustment method: BH
Pairwise comparisons using Log-Rank test
data: db2 and Treatment
Curative Transplant Loco-regional
Transplant 0.3 - -
Loco-regional 0.3 0.6 -
Sistemic 0.6 0.6 0.6
P value adjustment method: BH 
0.1.2 DG == “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 20 6 0.773 0.0816 0.628 0.951
36 11 3 0.631 0.1008 0.461 0.863
60 5 2 0.505 0.1135 0.325 0.784
Treatment=Transplant
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 3 0 1.000 0.000 1.0 1
36 2 1 0.667 0.272 0.3 1
60 2 0 0.667 0.272 0.3 1
Treatment=Loco-regional
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 8 0 1.000 0.000 1.000 1
36 1 2 0.571 0.249 0.243 1
Treatment=Sistemic
time n.risk n.event survival std.err
12.000 1.000 5.000 0.366 0.188
lower 95% CI upper 95% CI
0.133 1.000
Treatment=No treatment
time n.risk n.event survival std.err
12.000 2.000 1.000 0.800 0.179
lower 95% CI upper 95% CI
0.516 1.000 records n.max n.start events *rmean *se(rmean)
Treatment=Curative 27 27 27 15 31.0 2.98
Treatment=Transplant 3 3 3 3 37.0 4.08
Treatment=Loco-regional 11 11 11 2 32.1 5.57
Treatment=Sistemic 12 12 12 6 17.0 4.36
Treatment=No treatment 6 6 6 1 34.0 7.16
median 0.95LCL 0.95UCL
Treatment=Curative 66 35 NA
Treatment=Transplant 62 27 NA
Treatment=Loco-regional NA 21 NA
Treatment=Sistemic 11 8 NA
Treatment=No treatment NA NA NA
Pairwise comparisons using Log-Rank test
data: db and Treatment
Curative Transplant Loco-regional Sistemic
Transplant 0.9 - - -
Loco-regional 0.9 0.9 - -
Sistemic 0.1 0.3 0.1 -
No treatment 0.9 0.9 0.9 0.9
P value adjustment method: BH
Pairwise comparisons using Log-Rank test
data: db2 and Treatment
Curative Transplant Loco-regional
Transplant 0.93 - -
Loco-regional 0.76 0.76 -
Sistemic 0.07 0.17 0.07
P value adjustment method: BH 
0.1.3 DG == “VIRAL”
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 22 3 0.884 0.0634 0.768 1.000
36 7 7 0.495 0.1217 0.306 0.801
60 3 3 0.254 0.1187 0.102 0.635
Treatment=Transplant
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 9 0 1.000 0.000 1.000 1
36 7 2 0.778 0.139 0.549 1
60 6 1 0.667 0.157 0.420 1
Treatment=Loco-regional
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 16 3 0.842 0.0837 0.693 1.00
36 7 2 0.711 0.1127 0.521 0.97
60 4 0 0.711 0.1127 0.521 0.97
Treatment=Sistemic
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 8 3 0.742 0.132 0.524 1
36 5 0 0.742 0.132 0.524 1
60 2 0 0.742 0.132 0.524 1
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)
Treatment=Curative 28 28 28 15 41.4 6.78
Treatment=Transplant 9 9 9 7 73.0 11.39
Treatment=Loco-regional 19 19 19 8 64.2 8.88
Treatment=Sistemic 16 16 16 4 65.2 14.95
Treatment=No treatment 14 14 14 2 88.8 11.28
median 0.95LCL 0.95UCL
Treatment=Curative 31 29 NA
Treatment=Transplant 83 40 NA
Treatment=Loco-regional 77 76 NA
Treatment=Sistemic 64 64 NA
Treatment=No treatment NA NA NA
Pairwise comparisons using Log-Rank test
data: db and Treatment
Curative Transplant Loco-regional Sistemic
Transplant 0.5 - - -
Loco-regional 0.5 0.6 - -
Sistemic 0.5 0.6 0.6 -
No treatment 0.5 0.5 0.5 0.5
P value adjustment method: BH
Pairwise comparisons using Log-Rank test
data: db2 and Treatment
Curative Transplant Loco-regional
Transplant 0.3 - -
Loco-regional 0.3 0.6 -
Sistemic 0.6 0.6 0.6
P value adjustment method: BH
0.2 DG x Treatment
Factor | Detalis | Total | Curative | Transplant | Loco-regional | Sistemic | No treatment | Statistics |
Treatment | 242 | 91 (37.6%) | 27 (11.2%) | 50 (20.7%) | 40 (16.5%) | 34 (14.0%) | ||
Survival | μ ±DS | 29.03 ±27.1 | 32.95 ±24.8 | 53.85 ±32.3 | 31.80 ±23.6 | 17.18 ±23.5 | 5.31 ±7.27 | Kruskal-Wallis: p<0.001 |
M (min:max) | 20.5 (0:114) | 28 (1:114) | 41 (5:110) | 26 (4:106) | 8 (1:112) | 2 (0:32) | ||
Status | 0 | 93 (39.7%) | 50 (56.2%) | 14 (51.9%) | 12 (24.5%) | 14 (35.0%) | 3 (10.3%) | V=0.27 (p<0.001) |
1 | 131 (56.0%) | 35 (39.3%) | 10 (37.0%) | 35 (71.4%) | 26 (65.0%) | 25 (86.2%) | ||
2 | 10 (4.3%) | 4 (4.5%) | 3 (11.1%) | 2 (4.1%) | 0 | 1 (3.4%) | ||
DG | ASH | 89 (36.8%) | 28 (30.8%) | 9 (33.3%) | 19 (38.0%) | 16 (40.0%) | 17 (50.0%) | V=0.14 (p=0.268) |
NASH | 60 (24.8%) | 27 (29.7%) | 3 (11.1%) | 12 (24.0%) | 12 (30.0%) | 6 (17.6%) | ||
VIRAL | 93 (38.4%) | 36 (39.6%) | 15 (55.6%) | 19 (38.0%) | 12 (30.0%) | 11 (32.4%) | ||
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))
DG=ASH
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 55 11 0.848 0.0426 0.769 0.936
36 26 11 0.638 0.0647 0.523 0.778
60 15 4 0.524 0.0747 0.396 0.693
DG=NASH
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 34 12 0.770 0.0588 0.663 0.894
36 14 7 0.552 0.0836 0.410 0.742
60 7 2 0.467 0.0897 0.320 0.680
DG=VIRAL
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 68 2 0.972 0.0193 0.935 1.000
36 30 13 0.716 0.0645 0.600 0.854
60 12 7 0.489 0.0846 0.348 0.686 records n.max n.start events *rmean *se(rmean) median 0.95LCL
DG=ASH 86 86 86 36 57.5 5.37 64 38
DG=NASH 59 59 59 27 49.0 6.38 39 27
DG=VIRAL 87 87 87 28 62.8 5.40 56 50
0.95UCL
DG=ASH 78
DG=NASH 93
DG=VIRAL NA
Pairwise comparisons using Log-Rank test
data: db and DG
ASH NASH
NASH 0.38 -
VIRAL 0.38 0.09
P value adjustment method: BH [1] " Exclude: No treatment >>> "
Pairwise comparisons using Log-Rank test
data: db2 and DG
ASH NASH
NASH 0.3 -
VIRAL 0.5 0.1
P value adjustment method: BH
0.2.1 Treatment == “Curative”
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+%
by))
DG=ASH
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 22 3 0.884 0.0634 0.768 1.000
36 7 7 0.495 0.1217 0.306 0.801
60 3 3 0.254 0.1187 0.102 0.635
DG=NASH
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 20 6 0.773 0.0816 0.628 0.951
36 11 3 0.631 0.1008 0.461 0.863
60 5 2 0.505 0.1135 0.325 0.784
DG=VIRAL
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 31 2 0.938 0.0422 0.859 1.000
36 14 9 0.580 0.0993 0.415 0.811
60 5 6 0.283 0.0995 0.142 0.564 records n.max n.start events *rmean *se(rmean) median 0.95LCL
DG=ASH 28 28 28 15 41.7 7.02 31 29
DG=NASH 27 27 27 15 52.5 8.41 66 35
DG=VIRAL 33 33 33 19 48.6 6.02 42 32
0.95UCL
DG=ASH NA
DG=NASH NA
DG=VIRAL NA
Pairwise comparisons using Log-Rank test
data: db and DG
ASH NASH
NASH 0.7 -
VIRAL 0.7 0.8
P value adjustment method: BH 
0.2.2 Treatment == “Transplant”
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+%
by))
DG=ASH
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 9 0 1.000 0.000 1.000 1
36 7 2 0.778 0.139 0.549 1
60 6 1 0.667 0.157 0.420 1
DG=NASH
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 3 0 1.000 0.000 1.0 1
36 2 1 0.667 0.272 0.3 1
60 2 0 0.667 0.272 0.3 1
DG=VIRAL
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 14 0 1.000 0.0000 1.000 1
36 9 1 0.923 0.0739 0.789 1
60 4 1 0.738 0.1754 0.464 1 records n.max n.start events *rmean *se(rmean) median 0.95LCL
DG=ASH 9 9 9 7 71.2 10.78 83 40
DG=NASH 3 3 3 3 60.7 15.57 62 27
DG=VIRAL 15 15 15 4 78.5 9.87 70 54
0.95UCL
DG=ASH NA
DG=NASH NA
DG=VIRAL NA
Pairwise comparisons using Log-Rank test
data: db and DG
ASH NASH
NASH 0.6 -
VIRAL 0.9 0.6
P value adjustment method: BH 
0.2.3 Treatment == “Loco-regional”
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+%
by))
DG=ASH
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 16 3 0.842 0.0837 0.693 1.00
36 7 2 0.711 0.1127 0.521 0.97
60 4 0 0.711 0.1127 0.521 0.97
DG=NASH
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 8 0 1.000 0.000 1.000 1
36 1 2 0.571 0.249 0.243 1
DG=VIRAL
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 18 0 1.000 0.0000 1.000 1
36 6 1 0.938 0.0605 0.826 1
60 2 0 0.938 0.0605 0.826 1 records n.max n.start events *rmean *se(rmean) median 0.95LCL
DG=ASH 19 19 19 8 61.9 7.72 77 76
DG=NASH 11 11 11 2 61.3 18.25 NA 21
DG=VIRAL 19 19 19 2 88.2 4.66 93 NA
0.95UCL
DG=ASH NA
DG=NASH NA
DG=VIRAL NA
Pairwise comparisons using Log-Rank test
data: db and DG
ASH NASH
NASH 1.0 -
VIRAL 0.2 0.2
P value adjustment method: BH 
0.2.4 Treatment == “Sistemic”
Call: survfit(formula = as.formula("Surv(time = `Survival`, event = `Dead`) ~ " %+%
by))
DG=ASH
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 8 3 0.742 0.132 0.524 1
36 5 0 0.742 0.132 0.524 1
60 2 0 0.742 0.132 0.524 1
DG=NASH
time n.risk n.event survival std.err
12.000 1.000 5.000 0.366 0.188
lower 95% CI upper 95% CI
0.133 1.000
DG=VIRAL
time n.risk n.event survival std.err lower 95% CI upper 95% CI
12 4 0 1.000 0.000 1.0000 1
36 1 2 0.333 0.272 0.0673 1
60 1 0 0.333 0.272 0.0673 1 records n.max n.start events *rmean *se(rmean) median 0.95LCL
DG=ASH 16 16 16 4 50.3 7.47 64 64
DG=NASH 12 12 12 6 17.0 4.36 11 8
DG=VIRAL 11 11 11 3 39.0 11.73 34 17
0.95UCL
DG=ASH NA
DG=NASH NA
DG=VIRAL NA
Pairwise comparisons using Log-Rank test
data: db and DG
ASH NASH
NASH 0.06 -
VIRAL 0.99 0.06
P value adjustment method: BH 
1 References
- 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/.