DCI analysis v1.2
Dihua Xu
December 14, 2015
Original data
n=450 DCI identified calciphylaxis patients with available onset date and correct death date.
Baseline information
## Variable Treatment Control P.Value
## 1 sex 85 / 251 (33.9 %) 63 / 199 (31.7 %) 0.694
## 2 race 158 / 245 (64.5 %) 117 / 198 (59.1 %) 0.286
## 3 ethnicity 26 / 242 (10.7 %) 7 / 198 (3.5 %) 0.007
## 4 age 58.5 + 12.8 (251) 54.8 + 12.9 (199) 0.002
## 5 diabetes 157 / 251 (62.5 %) 111 / 199 (55.8 %) 0.175
## 6 dm 58 / 251 (23.1 %) 68 / 199 (34.2 %) 0.013
## 7 bmi 32.2 + 8.7 (251) 32.0 + 8.8 (199) 0.826
## 8 calcium 8.8 + 0.8 (235) 8.9 + 1.0 (176) 0.491
## 9 phosphate 6.1 + 1.9 (234) 6.6 + 2.1 (176) 0.022
## 10 pth 517.9 + 484.1 (223) 553.2 + 609.8 (162) 0.528
## 11 alkphos 174.0 + 134.3 (235) 211.9 + 223.6 (175) 0.034
## 12 albumin 3.4 + 0.6 (235) 3.4 + 0.6 (175) 0.701
## 13 warfarin 16 / 251 (6.4 %) 5 / 199 (2.5 %) 0.088
## 14 cinacalcet 110 / 251 (43.8 %) 60 / 199 (30.2 %) 0.004
## 15 vd 135 / 251 (53.8 %) 92 / 199 (46.2 %) 0.134Kaplan Meier Curve
km1 <- survfit(Surv(len_fu2, death)~trt, data=dat)
plot(km1, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km1## Call: survfit(formula = Surv(len_fu2, death) ~ trt, data = dat)
##
## n events median 0.95LCL 0.95UCL
## trt=1 251 137 445 370 786
## trt=0 199 131 684 430 1011Kaplan Meier Curve with 1 yr follow up
dat$death.1y <- (dat$death==1 & dat$len_fu2 < 365.25)
dat$len_fu.1y <- as.numeric(ifelse(dat$len_fu2 > 365.25, 365.25, dat$len_fu2))
km1y <- survfit(Surv(len_fu.1y, death.1y)~trt, data=dat)
plot(km1y, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km1y## Call: survfit(formula = Surv(len_fu.1y, death.1y) ~ trt, data = dat)
##
## n events median 0.95LCL 0.95UCL
## trt=1 251 96 NA NA NA
## trt=0 199 74 NA NA NAKaplan Meier Curve with 2 yrs follow up
dat$death.2y <- (dat$death==1 & dat$len_fu2 < 365.25*2)
dat$len_fu.2y <- as.numeric(ifelse(dat$len_fu2 > 365.25*2, 365.25*2, dat$len_fu2))
km2y <- survfit(Surv(len_fu.2y, death.2y)~trt, data=dat)
plot(km2y, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km2y## Call: survfit(formula = Surv(len_fu.2y, death.2y) ~ trt, data = dat)
##
## n events median 0.95LCL 0.95UCL
## trt=1 251 117 445 370 NA
## trt=0 199 93 684 430 NAPatients with Caliphylaxis diagnostic date only
n=340 DCI identified calciphylaxis patients with available onset diagnostic date.
dat.calci <- subset(dat, CalciDiag==1)Baseline information
## Variable Treatment Control P.Value
## 1 sex 50 / 141 (35.5 %) 63 / 199 (31.7 %) 0.538
## 2 race 91 / 138 (65.9 %) 117 / 198 (59.1 %) 0.247
## 3 ethnicity 7 / 135 (5.2 %) 7 / 198 (3.5 %) 0.647
## 4 age 59.3 + 12.2 (141) 54.8 + 12.9 (199) 0.001
## 5 diabetes 97 / 141 (68.8 %) 111 / 199 (55.8 %) 0.021
## 6 dm 33 / 141 (23.4 %) 68 / 199 (34.2 %) 0.043
## 7 bmi 32.5 + 8.4 (141) 32.0 + 8.8 (199) 0.591
## 8 calcium 8.8 + 0.8 (126) 8.9 + 1.0 (176) 0.517
## 9 phosphate 6.4 + 1.9 (125) 6.6 + 2.1 (176) 0.545
## 10 pth 605.0 + 500.4 (120) 553.2 + 609.8 (162) 0.448
## 11 alkphos 167.6 + 131.7 (126) 211.9 + 223.6 (175) 0.048
## 12 albumin 3.3 + 0.6 (126) 3.4 + 0.6 (175) 0.196
## 13 warfarin 11 / 141 (7.8 %) 5 / 199 (2.5 %) 0.045
## 14 cinacalcet 65 / 141 (46.1 %) 60 / 199 (30.2 %) 0.004
## 15 vd 74 / 141 (52.5 %) 92 / 199 (46.2 %) 0.305Kaplan Meier Curve for Caliphylaxis diagnostic patients
km.calci <- survfit(Surv(len_fu2, death)~trt, data=dat.calci)
plot(km.calci, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
Kaplan Meier Curve with 1 yr follow up for Caliphylaxis diagnostic patients
km1y <- survfit(Surv(len_fu.1y, death.1y)~trt, dat=dat.calci)
plot(km1y, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km1y## Call: survfit(formula = Surv(len_fu.1y, death.1y) ~ trt, data = dat.calci)
##
## n events median 0.95LCL 0.95UCL
## trt=1 141 58 NA 327 NA
## trt=0 199 74 NA NA NAKaplan Meier Curve with 2 yrs follow up for Caliphylaxis diagnostic patients
km2y <- survfit(Surv(len_fu.2y, death.2y)~trt, data=dat.calci)
plot(km2y, col=c("blue", "red"))
legend("topright", c("STS", "non-STS"), lty=1, col=c("red", "blue"))
km2y## Call: survfit(formula = Surv(len_fu.2y, death.2y) ~ trt, data = dat.calci)
##
## n events median 0.95LCL 0.95UCL
## trt=1 141 71 409 327 NA
## trt=0 199 93 684 430 NAdelayed treatment analysis (STS patients only)
n=141 DCI identified calciphylaxis patients with available STS treatment date. Delete 7 out of 141 patients who have STS treatment date before calciphylaxis diagnostic date. Final n=134. 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.calci, trt==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 <= 14Baseline information
## Variable Treatment Control P.Value
## 1 sex 18 / 50 (36.0 %) 30 / 84 (35.7 %) >.999
## 2 race 32 / 50 (64.0 %) 57 / 81 (70.4 %) 0.571
## 3 ethnicity 2 / 48 (4.2 %) 4 / 80 (5.0 %) >.999
## 4 age 56.8 + 10.7 (50) 61.1 + 12.1 (84) 0.044
## 5 diabetes 38 / 50 (76.0 %) 57 / 84 (67.9 %) 0.42
## 6 dm 12 / 50 (24.0 %) 18 / 84 (21.4 %) 0.896
## 7 bmi 34.0 + 9.1 (50) 32.3 + 7.8 (84) 0.234
## 8 calcium 8.8 + 0.9 (41) 8.8 + 0.8 (78) 0.697
## 9 phosphate 6.7 + 2.0 (41) 6.2 + 1.7 (77) 0.186
## 10 pth 660.5 + 643.8 (39) 579.4 + 426.2 (74) 0.425
## 11 alkphos 186.9 + 185.7 (41) 155.4 + 85.3 (78) 0.207
## 12 albumin 3.3 + 0.5 (41) 3.3 + 0.7 (78) 0.788
## 13 warfarin 2 / 50 (4.0 %) 9 / 84 (10.7 %) 0.296
## 14 cinacalcet 23 / 50 (46.0 %) 39 / 84 (46.4 %) >.999
## 15 vd 29 / 50 (58.0 %) 43 / 84 (51.2 %) 0.558Kaplan Meier Curve for STS patients
km.delay <- survfit(Surv(len_fu2, death)~group, dat=dat.sts2)
plot(km.delay, col=c("blue", "red"))
legend("topright", c("> 14 days", "<= 14 days"), lty=1, col=c("red", "blue"))
Kaplan Meier Curve with 1 yr follow up for Caliphylaxis diagnostic patients
km.delay.1y <- survfit(Surv(len_fu.1y, death.1y)~group, dat=dat.sts2)
plot(km.delay.1y, col=c("blue", "red"))
legend("topright", c("> 14 days", "<= 14 days"), lty=1, col=c("red", "blue"))
Kaplan Meier Curve with 2 yrs follow up for Caliphylaxis diagnostic patients
km.delay.2y <- survfit(Surv(len_fu.2y, death.2y)~group, data=dat.sts2)
plot(km.delay.2y, col=c("blue", "red"))
legend("topright", c("> 14 days", "<= 14 days"), lty=1, col=c("red", "blue"))