Journal
CLINICAL PHARMACOLOGY & THERAPEUTICS
Volume 102, Issue 2, Pages 349-357Publisher
WILEY
DOI: 10.1002/cpt.621
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Funding
- Engineering and Physical Sciences Research Council Life Sciences Interface Doctoral Training Centre studentship at the Centre for Mathematics and Physics in the Life Sciences and Experimental Biology (CoMPLEX)
- United Kingdom Medical Research Council Fellowship [G1002305]
- National Institute for Health Research Biomedical Research Centre at Great Ormond Street Hospital for Children NHS Foundation Trust
- University College London
- Medical Research Council [MR/M008665/1] Funding Source: researchfish
- MRC [MR/M008665/1] Funding Source: UKRI
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Hematopoietic stem cell transplantation (HSCT) is an increasingly common treatment for children with a range of hematological disorders. Conditioning with cytotoxic chemotherapy and total body irradiation leaves patients severely immunocompromised. T-cell reconstitution can take several years due to delayed restoration of thymic output. Understanding T-cell reconstitution in children is complicated by normal immune system maturation, heterogeneous diagnoses, and sparse uneven sampling due to the long time spans involved. We describe here a mechanistic mathematical model for CD4 T-cell immune reconstitution following pediatric transplantation. Including relevant biology and using mixed-effects modeling allowed the factors affecting reconstitution to be identified. Bayesian predictions for the long-term reconstitution trajectories of individual children were then obtained using early post-transplant data. The model was developed using data from 288 children; its predictive ability validated on data from a further 75 children, with long-term reconstitution predicted accurately in 81% of the patients.
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