mduration {PBIR}

Estimate mean duration of response

Description

Estimate mean duration of response

Usage

mduration(
  t2PROGRESSION,
  STATUS_PROGRESSION,
  t2RESPONSE,
  STATUS_RESPONSE,
  time.max = -1
)

Arguments

t2PROGRESSION

time to progression/death or censoring

STATUS_PROGRESSION

binary indicator for progression/death status: 1 for progression/death; 0 for censoring

t2RESPONSE

time to response or censoring

STATUS_RESPONSE

binary indicator for response status: 1 for response; 0 for censoring

time.max

maximum time point, up to which the mean DOR is to be estimated; the default value corresponds to the maximum time window in which the mean DOR is estimable

Details

The mean duration of response restricted within a time window is also the area under the PBIR curve over the same time window. The estimated mean duration can be viewed as a global summary of the PBIR curve. One may compare the mean duration of response between two groups, which is also a global comparison between two PBIR curves.

Value

A list with following elements

• meandor.est: the restricted mean DOR estimate

• meandor.se: the standard error of the esimated DOR

• time.truncation: the truncation time point used in DOR.

References

Huang, B., Tian, L., Talukder, E., Rothenberg, M., Kim, DY., and Wei, LJ. (2018) Evaluating Treatment Effect Based on Duration of Response for a Comparative Oncology Study. JAMA Oncol, doi: 10.1001/jamaoncol.2018.0275

Huang, B., Tian, L., McCaw, Z., Luo, Talukder, E., X., Rothenberg, M., Xie, W., Choueiri, T., Kim, DY., & Wei, LJ. (2020). Analysis of Response Data for Assessing Treatment Effects in Comparative Clinical Studies. Ann Intern Med, doi: 10.7326/M20-0104.

Examples

library(survival)
n=100
set.seed(10)

# Generate the data

error=rnorm(n)
tr=exp(rnorm(n)+error+0.5)
tp=exp(rnorm(n)+error)
tr[tp<tr]=Inf
tc=runif(n, 3, 8.5)
t2response=pmin(tr, tc)
delta_response=1*(tr<tc)
t2progression=pmin(tp, tc)
delta_progression=1*(tp<tc)

# Estimate the mean duration of response (point estimator and its standard error)

fit=mduration(t2PROGRESSION=t2progression,
              STATUS_PROGRESSION=delta_progression,
              t2RESPONSE=t2response,
              STATUS_RESPONSE=delta_response,
              time.max=8)

fit