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Jeremy Meier

Publications and source records attributed to Jeremy Meier.

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Dynamical System Modeling Of Immune Reconstitution Following Allogeneic Stem Cell Transplantation Identifies Patients At Risk For Adverse Outcomes

Systems that evolve over time and follow mathematical laws as they do so, are called dynamical systems. Lymphocyte recovery and clinical outcomes in 41 allograft recipients conditioned using anti-thymocyte globulin (ATG) and 4.5 Gray total-body-irradiation were studied to determine if immune reconstitution could be described as a dynamical system. Survival, relapse, and graft vs. host disease (GVHD) were not significantly different in two cohorts of patients receiving different doses of ATG. However, donor-derived CD3+ (ddCD3) cell reconstitution was superior in the lower ATG dose cohort, and there were fewer instances of donor lymphocyte infusion (DLI). Lymphoid recovery was plotted in each individual over time and demonstrated one of three sigmoid growth patterns; Pattern A (n=15), had rapid growth with high lymphocyte counts, pattern B (n=14), slower growth with intermediate recovery and pattern C, poor lymphocyte reconstitution (n=10). There was a significant association between lymphocyte recovery patterns and both the rate of change of ddCD3 at day 30 post-SCT and the clinical outcomes. GVHD was observed more frequently with pattern A; relapse and DLI more so with pattern C, with a consequent survival advantage in patients with patterns A and B. We conclude that evaluating immune reconstitution following SCT as a dynamical system may differentiate patients at risk of adverse outcomes and allow early intervention to modulate that risk.

q-bio.QM

Stem Cell Transplantation As A Dynamical System: Are Clinical Outcomes Deterministic?

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.

q-bio.OT