Individual outcome prediction for myelodysplastic syndrome (MDS) and secondary acute myeloid leukemia from MDS after allogeneic hematopoietic cell transplantation

Ann Hematol. 2017 Aug;96(8):1361-1372. doi: 10.1007/s00277-017-3027-5. Epub 2017 Jun 13.

Abstract

We integrated molecular data with available prognostic factors in patients undergoing allogeneic hematopoietic cell transplantation (alloHCT) for myelodysplastic syndrome (MDS) or secondary acute myeloid leukemia (sAML) from MDS to evaluate their impact on prognosis. Three hundred four patients were sequenced for mutations in 54 genes. We used a Cox multivariate model and competing risk analysis with internal and cross validation to identify factors prognostic of overall survival (OS), cumulative incidence of relapse (CIR), and non-relapse mortality (NRM). In multivariate analysis, mutated NRAS, U2AF1, IDH2, and TP53 and/or a complex karyotype were significant prognostic markers for OS besides age above 60 years, remission status, IPSS-R cytogenetic risk, HCT-CI > 2 and female donor sex. Mutated NRAS, IDH1, EZH2, and TP53 and/or a complex karyotype were genetic aberrations with prognostic impact on CIR. No molecular markers were associated with the risk of NRM. The inclusion of molecular information results in better risk prediction models for OS and CIR when assessed by the Akaike information criterion. Internal cross validation confirmed the robustness of our comprehensive risk model. In summary, we propose to combine molecular, cytogenetic, and patient- and transplantation-associated risk factors into a comprehensive risk model to provide personalized predictions of outcome after alloHCT.

Keywords: AML; Allogeneic HCT; Calculator; MDS; Mutations; Personalized predictions; Prognosis.

Publication types

  • Multicenter Study

MeSH terms

  • Acute Disease
  • Adult
  • Aged
  • Algorithms
  • Female
  • Hematopoietic Stem Cell Transplantation / methods*
  • Humans
  • Leukemia, Myeloid / genetics*
  • Leukemia, Myeloid / therapy
  • Male
  • Middle Aged
  • Multivariate Analysis
  • Mutation*
  • Myelodysplastic Syndromes / genetics*
  • Myelodysplastic Syndromes / therapy
  • Neoplasms, Second Primary / genetics*
  • Neoplasms, Second Primary / therapy
  • Outcome Assessment, Health Care / methods
  • Outcome Assessment, Health Care / statistics & numerical data
  • Precision Medicine
  • Prognosis
  • Proportional Hazards Models
  • Risk Assessment / methods
  • Risk Assessment / statistics & numerical data
  • Risk Factors
  • Sequence Analysis, DNA
  • Survival Analysis
  • Transplantation, Homologous
  • Young Adult