dataKTFS: A Sample Of The DIVAT cohort (Kidney Transplant Failure...

In ROCt: Time-Dependent ROC Curve Estimators and Expected Utility Functions

Description

A data frame with 2169 French kidney transplant recipients. The time-to-event is the time between the transplantation and the return in dialysis. This time can be right-censored, especially at the time of the patient death with a functioning graft. The KTFS is a score proposed by Foucher et al. (2010) to stratify the recipients according to their risk of return in dialysis.

Usage

data(dataKTFS)

Format

A data frame with 2169 observations (raws) with the 3 following variables (columns).

time

This numeric vector represents the follow up time in years (until return in dialyis or censoring)

failure

This numeric vector represents the graft failure indicator at the follow-up end (1=return, 0=censoring)

score

This numeric vector represents the KTFS values.

Details

The immunology and nephrology department of the Nantes University hospital constituted a data bank with the monitoring of medical records for kidney and/or pancreas transplant recipients. The associated software is called DIVAT. Here is the training sample of 2169 patients used for the construction of the KTFS, a scoring system proposed by Foucher et al. (2010) in order to stratify patients according to their risk of return in dialysis. The KTFS is based on 8 parameters collected during the first year post transplantation. Patients with a KTFS value higher than 4.17 were considered at high-risk.

Source

URL: http://www.divat.fr

References

Foucher Y. al. (2010) A clinical scoring system highly predictive of long-term kidney graft survival. Kidney International, 78, 1288-94. <doi:10.1038/ki.2010.232>

Examples

data(dataKTFS)

### a short summary of the recipient age at the transplantation
summary(dataKTFS$score)

### Kaplan and Meier estimation of the recipient survival
plot(survfit(Surv(time, failure) ~ I(score>4.17), data = dataKTFS),
 xlab="Post transplantation time (in years)", ylab="Patient survival",
 mark.time=FALSE, col=c(2,1), lty=c(2,1))
 
legend("bottomleft", c("Recipients in the high-risk group",
 "Recipients in the low-risk group"), col=1:2, lty=1:2)

ROCt documentation built on May 2, 2019, 3:25 p.m.