Unknown

Dataset Information

Identification of a metabolic gene panel to predict the prognosis of myelodysplastic syndrome.


ABSTRACT: Myelodysplastic syndrome (MDS) is clonal disease featured by ineffective haematopoiesis and potential progression into acute myeloid leukaemia (AML). At present, the risk stratification and prognosis of MDS need to be further optimized. A prognostic model was constructed by the least absolute shrinkage and selection operator (LASSO) regression analysis for MDS patients based on the identified metabolic gene panel in training cohort, followed by external validation in an independent cohort. The patients with lower risk had better prognosis than patients with higher risk. The constructed model was verified as an independent prognostic factor for MDS patients with hazard ratios of 3.721 (1.814-7.630) and 2.047 (1.013-4.138) in the training cohort and validation cohort, respectively. The AUC o

SUBMITTER: Hu F 

PROVIDER: S-EPMC7294120 | biostudies-literature | 2020 Jun

REPOSITORIES: biostudies-literature

altmetric image

Publications

Sorry, this publication's infomation has not been loaded in the Indexer, please go directly to PUBMED or Altmetric.

Similar Datasets