Statistical Methods for Time-Dependent Variables in Hematopoietic Cell Transplantation Studies

The interaction of clinically important yet time-dependent events such as infection and acute graft-versus-host disease (GVHD) on hematopoietic cell transplant outcomes is of particular interest to transplant physicians. Clinically, the development of these events is unknown at the time of transplant, but both events place the patient at risk of morbidity and mortality. Furthermore, the occurrence of one may affect the risk for the development of the other (ie, GVHD results in increased immunosuppression, resulting in infection). While these risks can be determined using traditional Cox modeling, due to their time-varying effects on the outcome, it is challenging to graphically display the patient's expected clinical status over time. Landmark analysis is one of the commonly used methods to present time-dependent variables graphically. It can be a useful tool for describing an outcome of interest with time-dependent variables. In this article, we review the basic concepts of time-dependent variables and describe a landmark study with a single-landmark time point and a dynamic landmark study with multiple landmark time points. We illustrate these methods with a hematopoietic cell transplantation data set with infections.