Department of Hematology and Medical Oncology, Cleveland Clinic, Taussig Cancer Center, Desk R35, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
Department of Hematology and Medical Oncology, Cleveland Clinic, Center for Clinical Artificial Intelligence, Lerner College of Medicine, Case Western Reserve University, Taussig Cancer Institute, Desk R35, 9500 Euclid Avenue, Cleveland, OH 44195, USA.
Hematol Oncol Clin North Am. 2020 Apr;34(2):369-378. doi: 10.1016/j.hoc.2019.10.001. Epub 2019 Dec 5.
Myelodysplastic syndromes are disorders of clonal myelopoiesis having a range of clinical manifestations, from benign and indolent to aggressive with very poor prognosis. Classifying the likely trajectory of disease within a patient largely guides therapeutic decision making and therefore survival. Traditional methods of risk-stratification systems rely on clinical features: simple blood tests, peripheral smears, bone marrow biopsies, and cytogenetics, but do not adequately predict disease severity for a substantial proportion of patients. This article reviews the state of stratification at use in the clinic, describes emerging systems that leverage large-scale genomic data, and summarizes efforts toward truly personalized prediction models.
骨髓增生异常综合征是一种克隆性髓系疾病,具有多种临床表现,从良性和惰性到侵袭性,预后非常差。在患者中对疾病的可能轨迹进行分类在很大程度上指导治疗决策和生存。传统的风险分层系统方法依赖于临床特征:简单的血液检查、外周涂片、骨髓活检和细胞遗传学,但不能充分预测相当一部分患者的疾病严重程度。本文综述了临床应用中的分层状态,描述了利用大规模基因组数据的新兴系统,并总结了真正实现个性化预测模型的努力。