  Due to the heterogeneity of the randomized controlled trial (RCT) and
external target populations, the estimated treatment effect from the RCT is not
directly applicable to the target population. For example, the patient
characteristics of the ACTG 175 HIV trial are significantly different from that
of the three external target populations of interest: US early-stage HIV
patients, Thailand HIV patients, and southern Ethiopia HIV patients. This paper
considers several methods to transport the treatment effect from the ACTG 175
HIV trial to the target populations beyond the trial population. Most transport
methods focus on continuous and binary outcomes; on the contrary, we derive and
discuss several transport methods for survival outcomes: an outcome regression
method based on a Cox proportional hazard (PH) model, an inverse probability
weighting method based on the models for treatment assignment, sampling score,
and censoring, and a doubly robust method that combines both methods, called
the augmented calibration weighting (ACW) method. However, as the PH assumption
was found to be incorrect for the ACTG 175 trial, the methods that depend on
the PH assumption may lead to the biased quantification of the treatment
effect. To account for the violation of the PH assumption, we extend the ACW
method with the linear spline-based hazard regression model that does not
require the PH assumption. Applying the aforementioned methods for
transportability, we explore the effect of PH assumption, or the violation
thereof, on transporting the survival results from the ACTG 175 trial to
various external populations.
