title: Improving Prognostic Modeling in Myelodysplastic Syndromes.
abstract: Myelodysplastic syndromes (MDSs) are a heterogeneous group of disorders characterized by the accumulation of complex genetic alterations that drive disease pathogenesis and outcome. Several prognostic models have been developed over the last two decades to risk stratify patients with MDS. These models mainly used clinical variables including blast percentage, cytopenias, cytogenetics, transfusion dependency, and age. Recently, somatic mutations in specific genes have been shown to impact overall survival in MDS and can be incorporated into established prognostic models to improve their predictive abilities. Here, we review the advantages and disadvantages of established prognostic models in MDS and the impact of emerging data regarding the incorporation of somatic mutations in risk stratification.
authors: Leukemia Program, Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Desk R35 9500 Euclid Ave, Cleveland, OH, 44195, USA. nazhaa@ccf.org.
authors: Aziz
authors: A
authors: Nazha
authors: Leukemia Program, Department of Hematology and Medical Oncology, Taussig Cancer Institute, Cleveland Clinic, Desk R35 9500 Euclid Ave, Cleveland, OH, 44195, USA.
authors: Mikkael A
authors: MA
authors: Sekeres
mesh_terms: D003582:Cytogenetics; D019175:DNA Methylation; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D009154:Mutation; D009190:Myelodysplastic Syndromes / Q000145:classification / Q000175:diagnosis* / Q000473:pathology; D011379:Prognosis; D012326:RNA Splicing; D014157:Transcription Factors / Q000235:genetics / Q000378:metabolism
chemical_list: D014157:Transcription Factors
keywords: Cytogenetics; Cytopenias; Myelodysplastic syndromes; Transfusion dependency