  Outcomes in stem cell transplantation (SCT) are modeled using probability
theory. However the clinical course following SCT appears to demonstrate many
characteristics of dynamical systems, especially when outcomes are considered
in the context of immune reconstitution. Dynamical systems tend to evolve over
time according to mathematically determined rules. Characteristically, the
future states of the system are predicated on the states preceding them, and
there is sensitivity to initial conditions. In SCT, the interaction between
donor T cells and the recipient may be considered as such a system in which,
graft source, conditioning and early immunosuppression profoundly influence
immune reconstitution over time. This eventually determines clinical outcomes,
either the emergence of tolerance or the development of graft versus host
disease. In this paper parallels between SCT and dynamical systems are explored
and a conceptual framework for developing mathematical models to understand
disparate transplant outcomes is proposed.
