Clinical and genetic predictors of prognosis in myelodysplastic syndromes

骨髓增生异常综合征预后的临床和遗传预测因素

阅读:1

Abstract

Myelodysplastic syndromes are a collection of clonal hematopoietic disorders with a wide range of clinical manifestations and eventual outcomes. Accurate prediction of a patient's prognosis is useful to define the risk posed by the disease and which treatment options are most appropriate. Several models have been created to help predict the prognosis for patients with myelodysplastic syndromes. The International Prognostic Scoring System (IPSS) has been the standard tool used to risk stratify MDS patients since its publication in 1997. Other models have since been created to improve upon the IPSS, including the recent Revised International Prognostic Scoring System. Most models include the presence or severity of peripheral blood cytopenias, the proportion of bone marrow blasts, and specific karyotype abnormalities. Other factors including age, performance status, co-morbidities, transfusion dependence, and molecular biomarkers can further refine the prediction of prognosis in some models. Novel, disease specific biomarkers with prognostic value in myelodysplastic syndromes including cell surface markers, gene expression profiles, and high resolution copy number analyses have been proposed but not yet adopted clinically. Somatic abnormalities in recurrently mutated genes are the most informative prognostic biomarkers not currently considered by clinical risk models. Mutations in specific genes have independent prognostic significance and, unlike cytogenetic abnormalities, are present in the majority of myelodysplastic syndrome cases. However, mutational information can be complex and there are challenges to its clinical implementation. Despite these limitations, DNA sequencing can refine the prediction of prognosis for myelodysplastic syndrome patients and has become increasingly available in the clinic where it will help improve the care of patients with myelodysplastic syndromes.

特别声明

1、本页面内容包含部分的内容是基于公开信息的合理引用;引用内容仅为补充信息,不代表本站立场。

2、若认为本页面引用内容涉及侵权,请及时与本站联系,我们将第一时间处理。

3、其他媒体/个人如需使用本页面原创内容,需注明“来源:[生知库]”并获得授权;使用引用内容的,需自行联系原作者获得许可。

4、投稿及合作请联系:info@biocloudy.com。