Cuplov Vesna, André Nicolas
SMARTc, Marseille Cancer Research Center (CRCM), UMR Inserm 1068, CNRS UMR 7258, Aix Marseille Université U105, Institut Paoli Calmettes & APHM, 13385 Marseille, France.
Paediatric Haematology and Oncology Department, La Timone Children's Hospital, AP-HM, 13385 Marseille, France.
Cancers (Basel). 2020 Jul 17;12(7):1944. doi: 10.3390/cancers12071944.
Developing precision medicine is a major trend in clinical oncology. The main adverse effects of ifosfamide, actinomycin D and vincristine (IVA) treatment for rhabdomyosarcoma are haematological toxicities such as neutropenia or thrombocytopenia. The severity of these effects vary among patients but their dynamic profiles are similar. A non-empirical adjustment of the chemotherapy dose to avoid severe toxicities could help secure the treatment administration. Twenty-four patients with rhabdomyosarcoma treated with IVA chemotherapy courses were selected. Before and during each cycle, routine multiple blood cell counts were performed allowing for a dynamic study of the haematological toxicities. We developed a machine learning analysis using a gradient boosting regression technique to forecast the ifosfamide induced haematological toxicities as a function of neutrophils and platelets initial levels and the initial ifosfamide dose. To validate models' accuracy, predicted and observed neutrophils and platelets levels were compared. The model was able to reproduce the dynamic profiles of the haematological toxicities. Among all cycles, the mean absolute errors between predicted and observed neutrophils and platelets levels were 1.0 and 72.8 G/L, respectively. Adjusting a patient's ifosfamide dose based upon the predicted haematological toxicity levels at the end of a treatment cycle could enable tailored treatment.
发展精准医学是临床肿瘤学的一个主要趋势。异环磷酰胺、放线菌素D和长春新碱（IVA）治疗横纹肌肉瘤的主要不良反应是血液学毒性，如中性粒细胞减少或血小板减少。这些影响的严重程度在患者之间有所不同，但其动态变化模式相似。对化疗剂量进行非经验性调整以避免严重毒性有助于确保治疗的实施。选择了24例接受IVA化疗疗程的横纹肌肉瘤患者。在每个周期之前和期间，进行常规多次血细胞计数，以便对血液学毒性进行动态研究。我们使用梯度提升回归技术进行了机器学习分析，以预测异环磷酰胺诱导的血液学毒性，该毒性是中性粒细胞和血小板初始水平以及初始异环磷酰胺剂量的函数。为了验证模型的准确性，比较了预测和观察到的中性粒细胞和血小板水平。该模型能够重现血液学毒性的动态变化模式。在所有周期中，预测和观察到的中性粒细胞和血小板水平之间的平均绝对误差分别为1.0和72.8 G/L。根据治疗周期结束时预测的血液学毒性水平调整患者的异环磷酰胺剂量可以实现个性化治疗。
