DCI analysis v1.3
Dihua Xu
December 18, 2015
PD Patients only
n=126 DCI identified calciphylaxis patients with available onset date, correct death date, and were on PD before onset date.
dat.pd <- subset(dat, dm == "PD")Baseline information
## Variable Treatment Control P.Value
## 1 sex 18 / 58 (31.0 %) 17 / 68 (25.0 %) 0.579
## 2 race 36 / 57 (63.2 %) 42 / 68 (61.8 %) >.999
## 3 ethnicity 6 / 56 (10.7 %) 4 / 68 (5.9 %) 0.514
## 4 age 52.3 + 13.9 (58) 55.0 + 12.9 (68) 0.262
## 5 diabetes 25 / 58 (43.1 %) 34 / 68 (50.0 %) 0.552
## 6 bmi 29.7 + 7.8 (58) 31.5 + 8.8 (68) 0.218
## 7 calcium 8.8 + 1.0 (58) 8.8 + 0.9 (62) 0.944
## 8 phosphate 5.9 + 1.7 (58) 6.5 + 2.2 (62) 0.113
## 9 pth 515.6 + 554.2 (54) 479.0 + 399.3 (57) 0.689
## 10 alkphos 159.9 + 95.7 (58) 175.3 + 122.9 (62) 0.448
## 11 albumin 3.1 + 0.6 (58) 3.2 + 0.7 (62) 0.235
## 12 warfarin 6 / 58 (10.3 %) 2 / 68 (2.9 %) 0.183
## 13 cinacalcet 25 / 58 (43.1 %) 27 / 68 (39.7 %) 0.838
## 14 vd 27 / 58 (46.6 %) 26 / 68 (38.2 %) 0.446Kaplan Meier Curve: all time + PD
km.pd <- survfit(Surv(len_fu2, death)~trt, data=dat.pd)
plot(km.pd, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.pd## Call: survfit(formula = Surv(len_fu2, death) ~ trt, data = dat.pd)
##
## n events median 0.95LCL 0.95UCL
## trt=1 58 31 383 261 NA
## trt=0 68 46 593 184 1418Kaplan Meier Curve: 1 yr follow up + PD
km.pd.1y <- survfit(Surv(len_fu.1y, death.1y)~trt, data=dat.pd)
plot(km.pd.1y, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.pd.1y## Call: survfit(formula = Surv(len_fu.1y, death.1y) ~ trt, data = dat.pd)
##
## n events median 0.95LCL 0.95UCL
## trt=1 58 23 NA 261 NA
## trt=0 68 29 NA 184 NAKaplan Meier Curve: 2 yrs follow up + PD
km.pd.2y <- survfit(Surv(len_fu.2y, death.2y)~trt, data=dat.pd)
plot(km.pd.2y, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.pd.2y## Call: survfit(formula = Surv(len_fu.2y, death.2y) ~ trt, data = dat.pd)
##
## n events median 0.95LCL 0.95UCL
## trt=1 58 27 383 261 NA
## trt=0 68 35 593 184 NAHD patient only
n=324 DCI identified calciphylaxis patients with available onset date, correct death date, and were on PD before onset date.
dat.hd <- subset(dat, dm == "HD")Baseline information
## Variable Treatment Control P.Value
## 1 sex 67 / 193 (34.7 %) 46 / 131 (35.1 %) >.999
## 2 race 122 / 188 (64.9 %) 75 / 130 (57.7 %) 0.237
## 3 ethnicity 20 / 186 (10.8 %) 3 / 130 (2.3 %) 0.009
## 4 age 60.4 + 11.9 (193) 54.7 + 13.0 (131) <.001
## 5 diabetes 132 / 193 (68.4 %) 77 / 131 (58.8 %) 0.098
## 6 bmi 32.9 + 8.8 (193) 32.2 + 8.9 (131) 0.49
## 7 calcium 8.8 + 0.8 (177) 8.9 + 1.1 (114) 0.354
## 8 phosphate 6.2 + 2.0 (176) 6.6 + 2.0 (114) 0.067
## 9 pth 518.7 + 461.3 (169) 593.5 + 696.6 (105) 0.286
## 10 alkphos 178.7 + 144.7 (177) 232.1 + 261.4 (113) 0.026
## 11 albumin 3.4 + 0.6 (177) 3.5 + 0.5 (113) 0.815
## 12 warfarin 10 / 193 (5.2 %) 3 / 131 (2.3 %) 0.311
## 13 cinacalcet 85 / 193 (44.0 %) 33 / 131 (25.2 %) <.001
## 14 vd 108 / 193 (56.0 %) 66 / 131 (50.4 %) 0.382Kaplan Meier Curve: all time + HD
km.hd <- survfit(Surv(len_fu2, death)~trt, data=dat.hd)
plot(km.hd, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.hd## Call: survfit(formula = Surv(len_fu2, death) ~ trt, data = dat.hd)
##
## n events median 0.95LCL 0.95UCL
## trt=1 193 106 512 385 881
## trt=0 131 85 710 446 1163Kaplan Meier Curve: 1 yr follow up + HD
km.hd.1y <- survfit(Surv(len_fu.1y, death.1y)~trt, data=dat.hd)
plot(km.hd.1y, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.hd.1y## Call: survfit(formula = Surv(len_fu.1y, death.1y) ~ trt, data = dat.hd)
##
## n events median 0.95LCL 0.95UCL
## trt=1 193 73 NA NA NA
## trt=0 131 45 NA NA NAKaplan Meier Curve: 2 yrs follow up + HD
km.hd.2y <- survfit(Surv(len_fu.2y, death.2y)~trt, data=dat.hd)
plot(km.hd.2y, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.hd.2y## Call: survfit(formula = Surv(len_fu.2y, death.2y) ~ trt, data = dat.hd)
##
## n events median 0.95LCL 0.95UCL
## trt=1 193 90 512 385 NA
## trt=0 131 58 710 446 NAHD patient only: matched sample
n=268 DCI identified calciphylaxis patients with available onset date, correct death date, and were on PD before onset date; matched by age and ethnicity.
matchit(trt~age+ethnicity, data=na.exclude(dat.hd[,c(1,9,11, 4)]), method="nearest") -> m.out
m.data1 <- match.data(m.out)
dat.hd.m <- subset(dat.hd, patient_id %in% m.data1$patient_id | is.na(ethnicity))Baseline information
## Variable Treatment Control P.Value
## 1 sex 50 / 137 (36.5 %) 46 / 131 (35.1 %) 0.914
## 2 race 82 / 134 (61.2 %) 75 / 130 (57.7 %) 0.650
## 3 ethnicity 0 / 130 (0.0 %) 3 / 130 (2.3 %) 0.245
## 4 age 56.6 + 9.4 (137) 54.7 + 13.0 (131) 0.161
## 5 diabetes 93 / 137 (67.9 %) 77 / 131 (58.8 %) 0.156
## 6 bmi 33.9 + 9.2 (137) 32.2 + 8.9 (131) 0.125
## 7 calcium 8.8 + 0.8 (126) 8.9 + 1.1 (114) 0.239
## 8 phosphate 6.4 + 2.1 (125) 6.6 + 2.0 (114) 0.343
## 9 pth 500.6 + 382.5 (119) 593.5 + 696.6 (105) 0.210
## 10 alkphos 180.3 + 148.2 (126) 232.1 + 261.4 (113) 0.058
## 11 albumin 3.4 + 0.6 (126) 3.5 + 0.5 (113) 0.239
## 12 warfarin 6 / 137 (4.4 %) 3 / 131 (2.3 %) 0.542
## 13 cinacalcet 58 / 137 (42.3 %) 33 / 131 (25.2 %) 0.005
## 14 vd 72 / 137 (52.6 %) 66 / 131 (50.4 %) 0.815Kaplan Meier Curve: all time + HD + matched sample
km.hd.m <- survfit(Surv(len_fu2, death)~trt, data=dat.hd.m)
plot(km.hd.m, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.hd.m## Call: survfit(formula = Surv(len_fu2, death) ~ trt, data = dat.hd.m)
##
## n events median 0.95LCL 0.95UCL
## trt=1 137 74 512 331 1480
## trt=0 131 85 710 446 1163Kaplan Meier Curve: 1 yr follow up + HD + matched sample
km.hd.1y.m <- survfit(Surv(len_fu.1y, death.1y)~trt, data=dat.hd.m)
plot(km.hd.1y.m, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.hd.1y.m## Call: survfit(formula = Surv(len_fu.1y, death.1y) ~ trt, data = dat.hd.m)
##
## n events median 0.95LCL 0.95UCL
## trt=1 137 54 NA 331 NA
## trt=0 131 45 NA NA NAKaplan Meier Curve: 2 yrs follow up + HD + matched sample
km.hd.2y.m <- survfit(Surv(len_fu.2y, death.2y)~trt, data=dat.hd.m)
plot(km.hd.2y.m, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.hd.2y.m## Call: survfit(formula = Surv(len_fu.2y, death.2y) ~ trt, data = dat.hd.m)
##
## n events median 0.95LCL 0.95UCL
## trt=1 137 63 512 331 NA
## trt=0 131 58 710 446 NAPD Patients with Caliphylaxis diagnostic date only
n=101 DCI identified calciphylaxis patients with available onset diagnostic date and were on PD before onset date.
dat.calci.pd <- subset(dat, CalciDiag==1 & dm == "PD")Baseline information
## Variable Treatment Control P.Value
## 1 sex 10 / 33 (30.3 %) 17 / 68 (25.0 %) 0.745
## 2 race 17 / 32 (53.1 %) 42 / 68 (61.8 %) 0.548
## 3 ethnicity 3 / 31 (9.7 %) 4 / 68 (5.9 %) 0.795
## 4 age 53.3 + 14.5 (33) 55.0 + 12.9 (68) 0.57
## 5 diabetes 17 / 33 (51.5 %) 34 / 68 (50.0 %) >.999
## 6 bmi 30.3 + 8.6 (33) 31.5 + 8.8 (68) 0.51
## 7 calcium 8.7 + 1.1 (33) 8.8 + 0.9 (62) 0.54
## 8 phosphate 6.1 + 1.7 (33) 6.5 + 2.2 (62) 0.435
## 9 pth 587.9 + 653.8 (32) 479.0 + 399.3 (57) 0.331
## 10 alkphos 179.5 + 116.1 (33) 175.3 + 122.9 (62) 0.871
## 11 albumin 3.0 + 0.6 (33) 3.2 + 0.7 (62) 0.105
## 12 warfarin 4 / 33 (12.1 %) 2 / 68 (2.9 %) 0.167
## 13 cinacalcet 13 / 33 (39.4 %) 27 / 68 (39.7 %) >.999
## 14 vd 15 / 33 (45.5 %) 26 / 68 (38.2 %) 0.633Kaplan Meier Curve: all time + PD + Caliph diag only
km.calci.pd <- survfit(Surv(len_fu2, death)~trt, data=dat.calci.pd)
plot(km.calci.pd, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
Kaplan Meier Curve: 1 yr follow up + PD + Caliph diag only
km.calci.pd.1y <- survfit(Surv(len_fu.1y, death.1y)~trt, dat=dat.calci.pd)
plot(km.calci.pd.1y, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.calci.pd.1y## Call: survfit(formula = Surv(len_fu.1y, death.1y) ~ trt, data = dat.calci.pd)
##
## n events median 0.95LCL 0.95UCL
## trt=1 33 16 277 130 NA
## trt=0 68 29 NA 184 NAKaplan Meier Curve: 2 yrs follow up + PD + Caliph diag only
km.calci.pd.2y <- survfit(Surv(len_fu.2y, death.2y)~trt, data=dat.calci.pd)
plot(km.calci.pd.2y, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.calci.pd.2y## Call: survfit(formula = Surv(len_fu.2y, death.2y) ~ trt, data = dat.calci.pd)
##
## n events median 0.95LCL 0.95UCL
## trt=1 33 18 277 130 NA
## trt=0 68 35 593 184 NAHD Patients with Caliphylaxis diagnostic date only
n=239 DCI identified calciphylaxis patients with available onset diagnostic date and never on PD before onset date.
dat.calci.hd <- subset(dat, CalciDiag==1 & dm == "HD")Baseline information
## Variable Treatment Control P.Value
## 1 sex 40 / 108 (37.0 %) 46 / 131 (35.1 %) 0.863
## 2 race 74 / 106 (69.8 %) 75 / 130 (57.7 %) 0.074
## 3 ethnicity 4 / 104 (3.8 %) 3 / 130 (2.3 %) 0.764
## 4 age 61.1 + 10.9 (108) 54.7 + 13.0 (131) <.001
## 5 diabetes 80 / 108 (74.1 %) 77 / 131 (58.8 %) 0.019
## 6 bmi 33.2 + 8.2 (108) 32.2 + 8.9 (131) 0.4
## 7 calcium 8.9 + 0.7 (93) 8.9 + 1.1 (114) 0.59
## 8 phosphate 6.5 + 1.9 (92) 6.6 + 2.0 (114) 0.747
## 9 pth 611.2 + 435.9 (88) 593.5 + 696.6 (105) 0.836
## 10 alkphos 163.4 + 137.1 (93) 232.1 + 261.4 (113) 0.023
## 11 albumin 3.4 + 0.6 (93) 3.5 + 0.5 (113) 0.372
## 12 warfarin 7 / 108 (6.5 %) 3 / 131 (2.3 %) 0.198
## 13 cinacalcet 52 / 108 (48.1 %) 33 / 131 (25.2 %) <.001
## 14 vd 59 / 108 (54.6 %) 66 / 131 (50.4 %) 0.6Kaplan Meier Curve: all time + HD + Caliph diag only
km.calci.hd <- survfit(Surv(len_fu2, death)~trt, data=dat.calci.hd)
plot(km.calci.hd, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.calci.hd## Call: survfit(formula = Surv(len_fu2, death) ~ trt, data = dat.calci.hd)
##
## n events median 0.95LCL 0.95UCL
## trt=1 108 60 434 331 1480
## trt=0 131 85 710 446 1163Kaplan Meier Curve: 1 yr follow up + HD + Caliph diag only
km.calci.hd.1y <- survfit(Surv(len_fu.1y, death.1y)~trt, dat=dat.calci.hd)
plot(km.calci.hd.1y, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.calci.hd.1y## Call: survfit(formula = Surv(len_fu.1y, death.1y) ~ trt, data = dat.calci.hd)
##
## n events median 0.95LCL 0.95UCL
## trt=1 108 42 NA 331 NA
## trt=0 131 45 NA NA NAKaplan Meier Curve: 2 yr follow up + HD + Caliph diag only
km.calci.hd.2y <- survfit(Surv(len_fu.2y, death.2y)~trt, data=dat.calci.hd)
plot(km.calci.hd.2y, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.calci.hd.2y## Call: survfit(formula = Surv(len_fu.2y, death.2y) ~ trt, data = dat.calci.hd)
##
## n events median 0.95LCL 0.95UCL
## trt=1 108 53 434 331 NA
## trt=0 131 58 710 446 NAHD Patients with Caliphylaxis diagnostic date only : matched sample
n=205 DCI identified calciphylaxis patients with available onset diagnostic date and never on PD before onset date.
dat.calci.hd.m <- subset(dat.hd.m, CalciDiag==1)Baseline information
## Variable Treatment Control P.Value
## 1 sex 34 / 82 (41.5 %) 46 / 131 (35.1 %) 0.432
## 2 race 56 / 81 (69.1 %) 75 / 130 (57.7 %) 0.128
## 3 ethnicity 0 / 78 (0.0 %) 3 / 130 (2.3 %) 0.453
## 4 age 57.1 + 8.7 (82) 54.7 + 13.0 (131) 0.149
## 5 diabetes 59 / 82 (72.0 %) 77 / 131 (58.8 %) 0.072
## 6 bmi 33.4 + 8.8 (82) 32.2 + 8.9 (131) 0.333
## 7 calcium 8.8 + 0.8 (71) 8.9 + 1.1 (114) 0.367
## 8 phosphate 6.7 + 2.1 (70) 6.6 + 2.0 (114) 0.838
## 9 pth 608.1 + 434.9 (67) 593.5 + 696.6 (105) 0.878
## 10 alkphos 171.4 + 153.0 (71) 232.1 + 261.4 (113) 0.078
## 11 albumin 3.3 + 0.6 (71) 3.5 + 0.5 (113) 0.137
## 12 warfarin 4 / 82 (4.9 %) 3 / 131 (2.3 %) 0.525
## 13 cinacalcet 38 / 82 (46.3 %) 33 / 131 (25.2 %) 0.002
## 14 vd 44 / 82 (53.7 %) 66 / 131 (50.4 %) 0.745Kaplan Meier Curve: all time + HD + Caliph diag only + matched sample
km.calci.hd.m <- survfit(Surv(len_fu2, death)~trt, data=dat.calci.hd.m)
plot(km.calci.hd.m, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.calci.hd.m## Call: survfit(formula = Surv(len_fu2, death) ~ trt, data = dat.calci.hd.m)
##
## n events median 0.95LCL 0.95UCL
## trt=1 82 44 552 332 1518
## trt=0 131 85 710 446 1163Kaplan Meier Curve: 1 yr follow up + HD + Caliph diag only + matched sample
km.calci.hd.1y.m <- survfit(Surv(len_fu.1y, death.1y)~trt, dat=dat.calci.hd.m)
plot(km.calci.hd.1y.m, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.calci.hd.1y.m## Call: survfit(formula = Surv(len_fu.1y, death.1y) ~ trt, data = dat.calci.hd.m)
##
## n events median 0.95LCL 0.95UCL
## trt=1 82 31 NA 332 NA
## trt=0 131 45 NA NA NAKaplan Meier Curve: 2 yr follow up + HD + Caliph diag only + matched sample
km.calci.hd.2y.m <- survfit(Surv(len_fu.2y, death.2y)~trt, data=dat.calci.hd.m)
plot(km.calci.hd.2y.m, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km.calci.hd.2y.m## Call: survfit(formula = Surv(len_fu.2y, death.2y) ~ trt, data = dat.calci.hd.m)
##
## n events median 0.95LCL 0.95UCL
## trt=1 82 37 552 332 NA
## trt=0 131 58 710 446 NAPD Patients with STS date only (group by delayed treatment or not)
n=30 DCI identified patients treated with STS and were on PD before onset date. Choose group cutoff as 14 days, i.e. patients who have there treatment within 14 days of diagnostics as a group.
# delay treatment
dat.sts <- subset(dat, trt==1 & CalciDiag==1)
dat.sts$delay <- as.numeric(difftime(as.Date(dat.sts$STSStartDate, "%m/%d/%Y"), as.Date(dat.sts$CalciDiagDate, "%m/%d/%Y"), units="days"))
dat.sts2 <- subset(dat.sts, delay >= 0)
dat.sts2$group <- dat.sts2$delay <= 14
dat.sts2.pd <- subset(dat.sts2, dm=="PD")Baseline information
## Variable Delayed Within2wks P.Value
## 1 sex 3 / 12 (25.0 %) 7 / 18 (38.9 %) 0.693
## 2 race 7 / 12 (58.3 %) 10 / 17 (58.8 %) >.999
## 3 ethnicity 1 / 11 (9.1 %) 1 / 17 (5.9 %) >.999
## 4 age 54.2 + 11.7 (12) 53.7 + 13.8 (18) 0.832
## 5 diabetes 7 / 12 (58.3 %) 9 / 18 (50.0 %) 0.94
## 6 bmi 31.6 + 9.3 (12) 30.6 + 8.4 (18) 0.866
## 7 calcium 8.3 + 0.8 (12) 8.8 + 1.2 (18) 0.362
## 8 phosphate 6.4 + 1.7 (12) 6.0 + 1.7 (18) 0.458
## 9 pth 774.2 + 984.5 (12) 476.8 + 339.2 (17) 0.352
## 10 alkphos 194.1 + 115.2 (12) 182.0 + 123.8 (18) 0.657
## 11 albumin 3.0 + 0.6 (12) 3.0 + 0.6 (18) 0.832
## 12 warfarin 0 / 12 (0.0 %) 4 / 18 (22.2 %) 0.228
## 13 cinacalcet 7 / 12 (58.3 %) 5 / 18 (27.8 %) 0.196
## 14 vd 7 / 12 (58.3 %) 8 / 18 (44.4 %) 0.709Kaplan Meier Curve: all time + PD + STS patients
km.delay.pd <- survfit(Surv(len_fu2, death)~group, dat=dat.sts2.pd)
plot(km.delay.pd, col=c("blue", "red"))
legend("topright", c("> 14 days", "<= 14 days"), lty=1, col=c("red", "blue"))
km.delay.pd## Call: survfit(formula = Surv(len_fu2, death) ~ group, data = dat.sts2.pd)
##
## n events median 0.95LCL 0.95UCL
## group=FALSE 12 6 277 113 NA
## group=TRUE 18 12 264 130 NAKaplan Meier Curve: 1 yr follow up + PD + STS patients
km.delay.pd.1y <- survfit(Surv(len_fu.1y, death.1y)~group, dat=dat.sts2.pd)
plot(km.delay.pd.1y, col=c("blue", "red"))
legend("topright", c("> 14 days", "<= 14 days"), lty=1, col=c("red", "blue"))
km.delay.pd.1y## Call: survfit(formula = Surv(len_fu.1y, death.1y) ~ group, data = dat.sts2.pd)
##
## n events median 0.95LCL 0.95UCL
## group=FALSE 12 5 277 113 NA
## group=TRUE 18 10 264 130 NAKaplan Meier Curve: 2 yrs follow up + PD + STS patients
km.delay.pd.2y <- survfit(Surv(len_fu.2y, death.2y)~group, data=dat.sts2.pd)
plot(km.delay.pd.2y, col=c("blue", "red"))
legend("topright", c("> 14 days", "<= 14 days"), lty=1, col=c("red", "blue"))
km.delay.pd.2y## Call: survfit(formula = Surv(len_fu.2y, death.2y) ~ group, data = dat.sts2.pd)
##
## n events median 0.95LCL 0.95UCL
## group=FALSE 12 6 277 113 NA
## group=TRUE 18 11 264 130 NAHD Patients with STS date only (group by delayed treatment or not)
n=104 DCI identified patients treated with STS and were on PD before onset date. Choose group cutoff as 14 days, i.e. patients who have there treatment within 14 days of diagnostics as a group.
dat.sts2.hd <- subset(dat.sts2, dm=="HD")Baseline information
## Variable Delayed Within2wks P.Value
## 1 sex 15 / 38 (39.5 %) 23 / 66 (34.8 %) 0.795
## 2 race 25 / 38 (65.8 %) 47 / 64 (73.4 %) 0.552
## 3 ethnicity 1 / 37 (2.7 %) 3 / 63 (4.8 %) >.999
## 4 age 57.7 + 10.4 (38) 63.1 + 10.9 (66) 0.015
## 5 diabetes 31 / 38 (81.6 %) 48 / 66 (72.7 %) 0.436
## 6 bmi 34.8 + 9.0 (38) 32.7 + 7.6 (66) 0.211
## 7 calcium 8.9 + 0.8 (29) 8.8 + 0.7 (60) 0.328
## 8 phosphate 6.8 + 2.1 (29) 6.3 + 1.7 (59) 0.437
## 9 pth 609.9 + 432.5 (27) 610.1 + 446.9 (57) 0.867
## 10 alkphos 184.0 + 209.9 (29) 147.4 + 69.2 (60) 0.847
## 11 albumin 3.4 + 0.4 (29) 3.3 + 0.7 (60) 0.944
## 12 warfarin 2 / 38 (5.3 %) 5 / 66 (7.6 %) 0.963
## 13 cinacalcet 16 / 38 (42.1 %) 34 / 66 (51.5 %) 0.471
## 14 vd 22 / 38 (57.9 %) 35 / 66 (53.0 %) 0.783Kaplan Meier Curve: all time + HD + STS patients
km.delay.hd <- survfit(Surv(len_fu2, death)~group, dat=dat.sts2.hd)
plot(km.delay.hd, col=c("blue", "red"))
legend("topright", c("> 14 days", "<= 14 days"), lty=1, col=c("red", "blue"))
km.delay.hd## Call: survfit(formula = Surv(len_fu2, death) ~ group, data = dat.sts2.hd)
##
## n events median 0.95LCL 0.95UCL
## group=FALSE 38 22 417 321 NA
## group=TRUE 66 36 445 298 NAKaplan Meier Curve: 1 yr follow up + HD + STS patients
km.delay.hd.1y <- survfit(Surv(len_fu.1y, death.1y)~group, dat=dat.sts2.hd)
plot(km.delay.hd.1y, col=c("blue", "red"))
legend("topright", c("> 14 days", "<= 14 days"), lty=1, col=c("red", "blue"))
km.delay.hd.1y## Call: survfit(formula = Surv(len_fu.1y, death.1y) ~ group, data = dat.sts2.hd)
##
## n events median 0.95LCL 0.95UCL
## group=FALSE 38 15 NA 321 NA
## group=TRUE 66 26 NA 298 NAKaplan Meier Curve: 2 yr follow up + HD + STS patients
km.delay.hd.2y <- survfit(Surv(len_fu.2y, death.2y)~group, data=dat.sts2.hd)
plot(km.delay.hd.2y, col=c("blue", "red"))
legend("topright", c("> 14 days", "<= 14 days"), lty=1, col=c("red", "blue"))
km.delay.hd.2y## Call: survfit(formula = Surv(len_fu.2y, death.2y) ~ group, data = dat.sts2.hd)
##
## n events median 0.95LCL 0.95UCL
## group=FALSE 38 18 417 321 NA
## group=TRUE 66 34 445 298 NA