Time-dependent effects of clinical predictors in unrelated hematopoietic stem cell transplantation

Hematopoietic stem cell transplantation is a multifactorial process. Some of the predictors exhibit time-dependent effects. We present a systematic analysis and description of selected clinical predictors influencing outcome in a time-dependent manner based on an analysis of registry data from the German Registry for Stem Cell Transplantation. A total of 14,951 patients with acute myeloid leukemia, acute lymphocytic leukemia, myelodysplastic syndrome and non-Hodgkin lymphoma transplanted with peripheral blood stem cells or bone marrow grafts were included. Multivariate Cox regression models were tested for time-dependent effects within each diagnosis group. Predictors not satisfying the proportional hazards assumption were modeled in a time-dependent manner, extending the Cox regression models. Similar patterns occurred in all diagnosis groups. Patients with a poor Karnofsky performance score (<80) had a high risk for early mortality until day 139 following transplantation (HR 2.42, CI: 2.19-2.68; P<0.001) compared to patients with a good Karnofsky performance score (80-100). Afterwards the risk reduced to HR 1.43, CI: 1.25-1.63; P<0.001. A lower mortality risk was found for patients after conditioning treatment with reduced intensity until day 120 post transplant (HR: 0.81 CI: 0.75-0.88; P<0.001). After this, a slightly higher risk could be shown for these patients. Similarly, patients who had received a PBSC graft exhibited a significantly lower mortality risk until day 388 post transplantation (HR 0.79, CI: 0.73-0.85; P<0.001), reversing to a significantly higher risk afterwards (HR 1.23, CI: 1.08-1.40; P=0.002). Integrating time dependency in regression models allows a more accurate description and quantification of clinical predictors to be made, which may help in risk assessment and patient counseling.