The impact of CD34+ cell dose on engraftment after SCTs: personalized estimates based on mathematical modeling

Abstract

It is known that the number of transplanted cells has a significant impact on the outcome after SCT. We identify issues that cannot be addressed by conventional analysis of clinical trials and ask whether it is possible to develop a refined analysis to conclude about the outcome of individual patients given clinical trial results. To accomplish this, we propose an interdisciplinary approach based on mathematical modeling. We devise and calibrate a mathematical model of short-term reconstitution and simulate treatment of large patient groups with random interindividual variation. Relating model simulations to clinical data allows quantifying the effect of transplant size on reconstitution time in the terms of patient populations and individual patients. The model confirms the existence of lower bounds on cell dose necessary for secure and efficient reconstitution but suggests that for some patient subpopulations higher thresholds might be appropriate. Simulations demonstrate that relative time gain because of increased cell dose is an 'interpersonally stable' parameter, in other words that slowly engrafting patients profit more from transplant enlargements than average cases. We propose a simple mathematical formula to approximate the effect of changes of transplant size on reconstitution time.

Cell Division Patterns in Acute Myeloid Leukemia Stem-like Cells Determine Clinical Course: A Model to Predict Patient Survival

“…This finding is new and cannot be directly deduced from existing experimental data. Importantly, our model allows self-renewal of progenitor cells, as it is crucial after bone marrow transplantation (5,46,47).…”

“…The model is an extension of a model of hematopoiesis (6,34), which has been validated on the basis of patient data and applied to clinical questions (5,35).…”

“…[28][29][30][31][32][33]. They offer the possibility to comprehend processes not yet accessible by experimental measurements (5).…”

“…In this work, we have applied a combination of mathematical models established by our group (5,27). In conjunction with clinical parameters, we have studied the impact of LSC proliferation and self-renewal rates, compared with proliferation and self-renewal of less primitive leukemia blast cells or leukemia progenitor cells (LPC), on clinical outcome.…”

Mathematical modeling reveals differential effects of erythropoietin on proliferation and lineage commitment of human hematopoietic progenitors in early erythroid culture

“…Mathematical models have been developed as tools to assist in the analysis of population dynamics during hematopoiesis, [16][17][18][19] and to determine the transcription factor regulatory interactions that control hematopoietic differentiation pathways. 20 To understand how proliferation integrates with lineage commitment and impacts on the overall population dynamics, a number of mathematical approaches for cell division have also been proposed, taking advantage of CFSE division-tracking.…”