EBMT data: Data from the European Society for Blood and Marrow Transplantation (EBMT)
Description
Data from the European Society for Blood and Marrow Transplantation (EBMT)
Format
A data frame of 2279 patients transplanted at the EBMT between 1985 and
1998. These data were used in Fiocco, Putter & van Houwelingen (2008) and
van Houwelingen & Putter (2008). The included variables are
- id
- Patient identification number
- rec
- Time in days from
transplantation to recovery or last follow-up
- rec.s
- Recovery status;
1 = recovery, 0 = censored
- ae
- Time in days from transplantation to
adverse event (AE) or last follow-up
- ae.s
- Adverse event status; 1 =
adverse event, 0 = censored
- recae
- Time in days from transplantation
to both recovery and AE or last follow-up
- plag.s
- Recovery and AE
status; 1 = both recovery and AE, 0 = no recovery or no AE or censored
- rel
- Time in days from transplantation to relapse or last follow-up
- rel.s
- Relapse status; 1 = relapse, 0 = censored
- srv
- Time in
days from transplantation to death or last follow-up
- srv.s
- Relapse
status; 1 = dead, 0 = censored
- year
- Year of transplantation; factor
with levels "1985-1989", "1990-1994", "1995-1998"
- agecl
- Patient age
at transplant; factor with levels "<=20", "20-40",="" "="">40"=20",>
- proph
- Prophylaxis; factor with levels "no", "yes"
- match
- Donor-recipient gender match; factor with levels "no gender
mismatch", "gender mismatch"
Source
We gratefully acknowledge the European Society for Blood and Marrow
Transplantation (EBMT) for making available these data. Disclaimer: these
data were simplified for the purpose of illustration of the analysis of
competing risks and multi-state models and do not reflect any real life
situation. No clinical conclusions should be drawn from these data.References
Fiocco M, Putter H, van Houwelingen HC (2008). Reduced-rank
proportional hazards regression and simulation-based prediction for
multi-state models. Statistics in Medicine 27, 4340--4358.van Houwelingen HC, Putter H (2008). Dynamic predicting by landmarking as an
alternative for multi-state modeling: an application to acute lymphoid
leukemia data. Lifetime Data Anal 14, 447--463.