Table 1 without transplant

table1(~ ., data=final_cohort_1)
Overall
(N=435261)
HISPANIC
1 59315 (13.6%)
2 375946 (86.4%)
RACE
1 295314 (67.8%)
2 114642 (26.3%)
3 4031 (0.9%)
4 15297 (3.5%)
5 4828 (1.1%)
6 1149 (0.3%)
RACE_cate
1 295314 (67.8%)
2 114642 (26.3%)
3 25305 (5.8%)
race_cat_4
Asian 15297 (3.5%)
Black 114642 (26.3%)
Other 10008 (2.3%)
White 295314 (67.8%)
SEX
1 250210 (57.5%)
2 185051 (42.5%)
state_cat
FIPSMW 86558 (19.9%)
FIPSNE 70108 (16.1%)
FIPSS 188037 (43.2%)
FIPSW 84619 (19.4%)
Missing 5939 (1.4%)
age
Mean (SD) 66.9 (13.3)
Median [Min, Max] 68.0 [18.0, 165]
sex_cat
Female 185051 (42.5%)
Male 250210 (57.5%)
COMO_CHF
N 290593 (66.8%)
Y 144668 (33.2%)
COMO_COPD
N 387096 (88.9%)
Y 48165 (11.1%)
COMO_TOBAC
N 407527 (93.6%)
Y 27734 (6.4%)
COMO_CANC
N 400857 (92.1%)
Y 34404 (7.9%)
COMO_ASHD
N 366833 (84.3%)
Y 68428 (15.7%)
COMO_OTHCARD
N 336380 (77.3%)
Y 98881 (22.7%)
COMO_CVATIA
N 393160 (90.3%)
Y 42101 (9.7%)
COMO_PVD
N 385404 (88.5%)
Y 49857 (11.5%)
COMO_HTN
N 51151 (11.8%)
Y 384110 (88.2%)
COMO_AMP
N 419403 (96.4%)
Y 15858 (3.6%)
COMO_DM_INS
N 241192 (55.4%)
Y 194069 (44.6%)
COMO_DM_ORAL
N 382837 (88.0%)
Y 52424 (12.0%)
COMO_DM_NOMEDS
N 403381 (92.7%)
Y 31880 (7.3%)
COMO_ALCHO
N 428882 (98.5%)
Y 6379 (1.5%)
COMO_DRUG
N 430756 (99.0%)
Y 4505 (1.0%)
COMO_INAMB
N 398780 (91.6%)
Y 36481 (8.4%)
COMO_INTRANS
N 415437 (95.4%)
Y 19824 (4.6%)
COMO_NEEDASST
N 366720 (84.3%)
Y 68541 (15.7%)
COMO_INST_OTH
N 432040 (99.3%)
Y 3221 (0.7%)
COMO_INST
N 391483 (89.9%)
Y 43778 (10.1%)
COMO_INST_AL
N 431506 (99.1%)
Y 3755 (0.9%)
COMO_INST_NURS
N 398045 (91.4%)
Y 37216 (8.6%)
PATTXOP_UNSUTAGE
N 417839 (96.0%)
Y 17422 (4.0%)
PATTXOP_PHYSUNFIT
N 433287 (99.5%)
Y 1974 (0.5%)
PATTXOP_MEDUNFIT
N 411632 (94.6%)
Y 23629 (5.4%)
FERRITIN
Mean (SD) 578 (445)
Median [Min, Max] 478 [0, 16500]
Missing 35743 (8.2%)
HGB
Mean (SD) 10.5 (1.22)
Median [Min, Max] 10.6 [0, 310]
Missing 23989 (5.5%)
IRON_SAT_PERCENT
Mean (SD) 26.9 (9.62)
Median [Min, Max] 26.0 [0, 844]
Missing 31951 (7.3%)
ALBUMIN
Mean (SD) 3.51 (0.467)
Median [Min, Max] 3.58 [0, 70.2]
Missing 27382 (6.3%)
CALCIUM_CORRECTED
Mean (SD) 9.23 (0.653)
Median [Min, Max] 9.22 [0.100, 75.7]
Missing 44331 (10.2%)
CALCIUM_UNCORRECTED
Mean (SD) 8.82 (0.601)
Median [Min, Max] 8.83 [0.100, 55.6]
Missing 26224 (6.0%)
PHOSPHORUS
Mean (SD) 4.93 (1.18)
Median [Min, Max] 4.82 [0.300, 126]
Missing 25671 (5.9%)
HEMOSESSIONS_1year
0 424715 (97.6%)
1 31 (0.0%)
2 259 (0.1%)
3 10172 (2.3%)
4 40 (0.0%)
5 38 (0.0%)
6 6 (0.0%)
HEMOSESSIONS_3year
0 422050 (97.0%)
1 48 (0.0%)
1.5 1 (0.0%)
2 351 (0.1%)
2.5 9 (0.0%)
3 12689 (2.9%)
4 56 (0.0%)
5 50 (0.0%)
6 6 (0.0%)
7 1 (0.0%)
HD_KTV
Mean (SD) 1.70 (16.0)
Median [Min, Max] 1.52 [0, 5000]
Missing 31134 (7.2%)
CLM_FROM_1year_num
Mean (SD) 1.26 (2.00)
Median [Min, Max] 0 [0, 38.0]
CLM_FROM_3year_num
Mean (SD) 2.85 (4.06)
Median [Min, Max] 1.00 [0, 136]
ICU_DAYS_1year_num
Mean (SD) 0.885 (2.69)
Median [Min, Max] 0 [0, 149]
ICU_DAYS_3year_num
Mean (SD) 1.25 (2.89)
Median [Min, Max] 0 [0, 161]
time_to_death_1year
Mean (SD) 321 (98.0)
Median [Min, Max] 365 [1.00, 365]
time_to_death_3year
Mean (SD) 802 (388)
Median [Min, Max] 1100 [1.00, 1100]
time_to_death_1year_status
0 342426 (78.7%)
1 92835 (21.3%)
time_to_death_3year_status
0 235089 (54.0%)
1 200172 (46.0%)

feature selection cohort without transplant

1 year

## Warning in train.default(x, y, weights = w, ...): The metric "Accuracy" was not
## in the result set. ROC will be used instead.
##    alpha       lambda
## 80     1 0.0003829714
## Warning in train.default(x, y, weights = w, ...): The metric "Accuracy" was not
## in the result set. ROC will be used instead.
## glmnet variable importance
## 
##   only 20 most important variables shown (out of 44)
## 
##                     Overall
## ALBUMIN              100.00
## age                   75.64
## HEMOSESSIONS_1year6   59.08
## HISPANIC2             57.54
## race_cat_4White       56.18
## HGB                   41.70
## COMO_CHFY             41.60
## ICU_DAYS_1year_num    40.76
## COMO_CANCY            33.18
## COMO_COPDY            32.30
## COMO_HTNY             30.81
## HEMOSESSIONS_1year2   23.81
## IRON_SAT_PERCENT      22.92
## SEX2                  22.70
## COMO_OTHCARDY         22.30
## CLM_FROM_1year_num    20.73
## HEMOSESSIONS_1year3   16.33
## COMO_TOBACY           16.10
## COMO_INSTY            14.73
## COMO_INST_NURSY       13.60

3 year

## Warning in model.frame.default(Terms, newdata, na.action = na.action, xlev =
## object$lvls): variable 'time_to_death_3year_status' is not a factor
## Warning in model.frame.default(Terms, newdata, na.action = na.action, xlev =
## object$lvls): variable 'time_to_death_3year_status' is not a factor
## Warning in train.default(x, y, weights = w, ...): The metric "Accuracy" was not
## in the result set. ROC will be used instead.
##    alpha       lambda
## 86     1 0.0005051342
## Warning in train.default(x, y, weights = w, ...): The metric "Accuracy" was not
## in the result set. ROC will be used instead.
## glmnet variable importance
## 
##   only 20 most important variables shown (out of 47)
## 
##                       Overall
## HEMOSESSIONS_3year1.5  100.00
## HEMOSESSIONS_3year2.5   50.79
## ALBUMIN                 45.21
## age                     44.93
## race_cat_4White         37.84
## HISPANIC2               37.60
## ICU_DAYS_3year_num      33.66
## COMO_CHFY               23.98
## COMO_COPDY              23.13
## COMO_TOBACY             20.60
## COMO_CANCY              17.09
## HGB                     16.97
## COMO_INSTY              15.40
## COMO_HTNY               14.97
## COMO_OTHCARDY           14.93
## SEX2                    13.49
## COMO_CVATIAY            10.21
## IRON_SAT_PERCENT         9.50
## COMO_NEEDASSTY           8.91
## COMO_PVDY                8.19