Hoare R L, Veys P, Klein N, Callard R, Standing J F
Centre for Mathematics and Physics in the Life Sciences and Experimental Biology, University College London, London, United Kingdom.
Great Ormond Street Institute of Child Health, University College London, London, United Kingdom.
Clin Pharmacol Ther. 2017 Aug;102(2):349-357. doi: 10.1002/cpt.621. Epub 2017 May 26.
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.
造血干细胞移植（HSCT）是治疗患有一系列血液系统疾病儿童的一种越来越常见的疗法。细胞毒性化疗和全身照射预处理会使患者严重免疫功能低下。由于胸腺输出恢复延迟，T细胞重建可能需要数年时间。由于正常免疫系统成熟、诊断异质性以及涉及的时间跨度长导致采样稀疏且不均匀，了解儿童的T细胞重建情况变得复杂。我们在此描述了一个儿科移植后CD4 T细胞免疫重建的机制数学模型。纳入相关生物学因素并使用混合效应模型能够确定影响重建的因素。然后，利用移植后早期数据获得了对个体儿童长期重建轨迹的贝叶斯预测。该模型是使用288名儿童的数据开发的；其预测能力在另外75名儿童的数据上得到验证，81%的患者长期重建得到准确预测。
