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


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-06-13

AUTHORS

Michael Heuser, Razif Gabdoulline, Patrick Löffeld, Vera Dobbernack, Henriette Kreimeyer, Mira Pankratz, Madita Flintrop, Alessandro Liebich, Sabrina Klesse, Victoria Panagiota, Michael Stadler, Martin Wichmann, Rabia Shahswar, Uwe Platzbecker, Christian Thiede, Thomas Schroeder, Guido Kobbe, Robert Geffers, Brigitte Schlegelberger, Gudrun Göhring, Hans-Heinrich Kreipe, Ulrich Germing, Arnold Ganser, Nicolaus Kröger, Christian Koenecke, Felicitas Thol

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. More... »

PAGES

1361-1372

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s00277-017-3027-5

DOI

http://dx.doi.org/10.1007/s00277-017-3027-5

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1085999589

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/28612220


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