Acute myeloid leukemia

This simulated data set is based on a trial in acute myeloid leukemia.

myeloid
data(cancer, package="survival")

Format

A data frame with 646 observations on the following 9 variables.

id

subject identifier, 1-646

trt

treatment arm A or B

sex

f=female, m=male

flt3

mutations of the FLT3 gene, a factor with levels of A, B, C

futime

time to death or last follow-up

death

1 if futime is a death, 0 for censoring

txtime

time to hematropetic stem cell transplant

crtime

time to complete response

rltime

time to relapse of disease

Details

This data set is used to illustrate multi-state survival curves. It is based on the actual study in the reference below. A subset of subjects was de-identifed, reordered, and then all of the time values randomly perturbed.

Mutations in the FLT3 domain occur in about 1/3 of AML patients, the additional agent in treatment arm B was presumed to target this anomaly. All subjects had a FLT mutation, either internal tandem duplications (ITD) (divided into low vs high) +- mutations in the TKD domain, or TKD mutations only. This was a stratification factor for treatment assignment in the study. The levels of A, B, C correspond to increasing severity of the mutation burden.

References

Le-Rademacher JG, Peterson RA, Therneau TM, Sanford BL, Stone RM, Mandrekar SJ. Application of multi-state models in cancer clinical trials. Clin Trials. 2018 Oct; 15 (5):489-498

Examples

coxph(Surv(futime, death) ~ trt + flt3, data=myeloid)
#> Call:
#> coxph(formula = Surv(futime, death) ~ trt + flt3, data = myeloid)
#> 
#>          coef exp(coef) se(coef)      z        p
#> trtB  -0.3534    0.7023   0.1122 -3.149  0.00164
#> flt3B  0.4114    1.5089   0.1587  2.593  0.00952
#> flt3C  0.7878    2.1985   0.1656  4.758 1.96e-06
#> 
#> Likelihood ratio test=34.04  on 3 df, p=1.94e-07
#> n= 646, number of events= 320 
# See the mstate vignette for a more complete analysis