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Predicting outcome in higher-risk myelodysplastic syndrome patients treated with azacitidine.

Anthi BouchlaThomas P ThomopoulosSotirios G PapageorgiouChristina ApostolopoulouConstantinos LoucariEfthimia MpazaniVassiliki Pappa
Published in: Epigenomics (2021)
5-Azacitidine (5-AZA) is widely used for the treatment of higher-risk myelodysplastic syndromes. However, response and survival rates vary considerably, while indicated treatment duration remains undefined. For these reasons, factors determining response and survival are of major importance. Clinical, morphological, flow cytometry, cytogenetic and molecular factors are discussed in this review. Biomarkers predictive of response and prognosis, as well as their link to the mode of action of 5-AZA are also addressed, shifting the focus from clinical practice to investigational research. Their use could further improve prognostic classification of 5-AZA treated higher-risk myelodysplastic syndromes in the near future.
Keyphrases
  • flow cytometry
  • acute myeloid leukemia
  • machine learning
  • deep learning
  • free survival
  • single molecule