Le Thuy T T, Jost Felix, Raupach Thomas, Zierk Jakob, Rauh Manfred, Suttorp Meinolf, Stanulla Martin, Metzler Markus, Sager Sebastian
Institute of Mathematical Optimization, Faculty of Mathematics, Otto-von-Guericke University Magdeburg, Germany.
Department of Pediatrics and Adolescent Medicine, University Hospital Erlangen, Erlangen, Germany.
Math Med Biol. 2019 Dec 4;36(4):471-488. doi: 10.1093/imammb/dqy017.
Acute lymphoblastic leukemia is the most common malignancy in childhood and requires prolonged oral maintenance chemotherapy to prevent disease relapse after remission induction with intensive intravenous chemotherapy. In maintenance therapy, drug doses of 6-mercaptopurine (6-MP) and methotrexate (MTX) are adjusted to achieve sustained antileukemic activity without excessive myelosuppression. However, uncertainty exists regarding timing and extent of drug dose responses and optimal dose adaptation strategies. We propose a novel comprehensive mathematical model for 6-MP and MTX pharmacokinetics, pharmacodynamics and myelosuppression in acute lymphoblastic maintenance therapy. We personalize and cross-validate the mathematical model using clinical data and propose a real-time algorithm to predict chemotherapy responses with a clinical decision support system as a potential future application.
急性淋巴细胞白血病是儿童期最常见的恶性肿瘤，在通过强化静脉化疗诱导缓解后，需要长期口服维持化疗以预防疾病复发。在维持治疗中，调整6-巯基嘌呤（6-MP）和甲氨蝶呤（MTX）的药物剂量，以实现持续的抗白血病活性，同时避免过度的骨髓抑制。然而，关于药物剂量反应的时间和程度以及最佳剂量调整策略仍存在不确定性。我们提出了一种针对急性淋巴细胞维持治疗中6-MP和MTX的药代动力学、药效学和骨髓抑制的新型综合数学模型。我们使用临床数据对该数学模型进行个性化和交叉验证，并提出一种实时算法，通过临床决策支持系统预测化疗反应，作为未来潜在的应用。
