Description Usage Format Details Source References Examples
A data frame with 240 DLBCL patients. The time-to-event is the time to patient death. This time can be right-censored.
1 |
A data frame with 240 observations (rows) with the 8 following variables (columns).
ident
This numeric vector represents the key for patient identification
t
This numeric vector represents the follow up times (until death or censoring)
f
This numeric vector represents the failure indicators at the follow-up end (1=death, 0=alive)
Rosenwald et al. (2002) evaluated tumour samples from 240 DLBCL patients treated with anthracycline based therapy. They confirmed the existence of the two DLBCL subgroups described previously, GCB-like and ABC-like. The overall survival was significantly different among the subgroups, with 5-year survivals of 60% for the GCB-like and 35% for ABC-like subgroups. An additional third subtype was described with a 5-year survival of 39%.
The data is published at http://llmpp.nih.gov/lymphoma/data.shtml.
Rosenwald et al. The use of molecular profiling to predict survival after chemotherapy for diffuse large-b-cell lymphoma. New England Journal of Medicine, 346(25):1937-47, 2002.
Alizadeh et al. Distinct types of diffuse large b-cell lymphoma identiffied by gene expression profiling. Nature, 403(6769):503-11, 2000.
1 2 3 4 5 6 | data(DLBCLpatients)
### Kaplan and Meier estimation of the patient survival
plot(survfit(Surv(t, f) ~ 1, data = DLBCLpatients),
xlab="Survival time (in years)", ylab="Patient survival",
mark.time=FALSE)
|
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.