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INDIVIDUAL OUTCOME PREDICTION FOR MDS AND SECONDARY AML AFTER ALLOGENEIC HEMATOPOIETIC CELL TRANSPLANTATION BASED ON GENETIC, PATIENT- AND TRANSPLANTATION-ASSOCIATED RISK FACTORS
Author(s):
Michael Heuser
,
Michael Heuser
Affiliations:
Hannover Medical School,Hannover,Germany
Razif Gabdoulline
,
Razif Gabdoulline
Affiliations:
Hannover Medical School,Hannover,Germany
Patrick Loeffeld
,
Patrick Loeffeld
Affiliations:
Hannover Medical School,Hannover,Germany
Vera Dobbernack
,
Vera Dobbernack
Affiliations:
Hannover Medical School,Hannover,Germany
Henriette Kreimeyer
,
Henriette Kreimeyer
Affiliations:
Hannover Medical School,Hannover,Germany
Mira Pankratz
,
Mira Pankratz
Affiliations:
Hannover Medical School,Hannover,Germany
Madita Flintrop
,
Madita Flintrop
Affiliations:
Hannover Medical School,Hannover,Germany
Viktoria Panagiota
,
Viktoria Panagiota
Affiliations:
Hannover Medical School,Hannover,Germany
Michael Stadler
,
Michael Stadler
Affiliations:
Hannover Medical School,Hannover,Germany
Martin Wichmann
,
Martin Wichmann
Affiliations:
Hannover Medical School,Hannover,Germany
Rabia Shaswar
,
Rabia Shaswar
Affiliations:
Hannover Medical School,Hannover,Germany
Uwe Platzbecker
,
Uwe Platzbecker
Affiliations:
Universtitätsklinikum Carl Gustav Carus,Dresden,Germany
Christian Thiede
,
Christian Thiede
Affiliations:
Universtitätsklinikum Carl Gustav Carus,Dresden,Germany
Thomas Schroeder
,
Thomas Schroeder
Affiliations:
Heinrich Heine University,Duesseldorf,Germany
Guido Kobbe
,
Guido Kobbe
Affiliations:
Heinrich Heine University,Duesseldorf,Germany
Robert Geffers
,
Robert Geffers
Affiliations:
Helmholtz Centre for Infection Research,Braunschweig,Germany
Brigitte Schlegelberger
,
Brigitte Schlegelberger
Affiliations:
Hannover Medical School,Hannover,Germany
Gudrun Göhring
,
Gudrun Göhring
Affiliations:
Hannover Medical School,Hannover,Germany
Hans-Heinrich Kreipe
,
Hans-Heinrich Kreipe
Affiliations:
Hannover Medical School,Hannover,Germany
Ulrich Germing
,
Ulrich Germing
Affiliations:
Heinrich Heine University,Duesseldorf,Germany
Arnold Ganser
,
Arnold Ganser
Affiliations:
Hannover Medical School,Hannover,Germany
Nicolaus Kroeger
,
Nicolaus Kroeger
Affiliations:
University Medical Center Hamburg-Eppendorf,Hamburg,Germany
Christian Koenecke
,
Christian Koenecke
Affiliations:
Hannover Medical School,Hannover,Germany
Felicitas Thol
Felicitas Thol
Affiliations:
Hannover Medical School,Hannover,Germany
(Abstract release date: 05/18/17) EHA Library. Heuser M. 06/24/17; 181781; S494
Michael Heuser
Michael Heuser
Contributions
PDF Abstract
Abstract

Abstract: S494

Type: Oral Presentation

Presentation during EHA22: On Saturday, June 24, 2017 from 16:45 - 17:00

Location: Room N103

Background

Prediction of individual outcomes after allogeneic hematopoietic cell transplantation (alloHCT) is difficult, as it is influenced by a multitude of risk factors.

Aims

To develop a tool that predicts individual outcomes of patients with myelodysplastic syndrome (MDS) or secondary acute myeloid leukemia from MDS (sAML) after alloHCT.

Methods
We integrated molecular data with available prognostic factors in patients undergoing alloHCT for MDS and sAML to evaluate their impact on prognosis. 304 patients with MDS or sAML who underwent alloHCT 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).

Results

In multivariate analysis, mutated NRAS, U2AF1, IDH2, TP53 and/or a complex karyotype were significant prognostic markers for OS besides age above 60 years, remission status treated but not in CR, 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 addition of molecular information significantly improved the risk prediction for OS and CIR as assessed by the Akaike information criterion. Internal and cross validation confirmed the robustness of our comprehensive risk model. We developed an interactive risk prediction tool to provide personalized predictions for OS, CIR and NRM outcome after alloHCT. An individualized prediction for a 53-year-old male with sAML with trisomy 11, mutated NRAS, IDH2 and DNMT3A and complete remission after double induction is shown in Figure 1. The probability of CIR at 2 years was 45% and the patient relapsed after 0.61 years. The probability of OS at 2 years was 41% and the patient died after 0.88 years.

Conclusion

We combine molecular, cytogenetic, patient- and transplantation associated risk factors into a comprehensive risk score to provide personalized predictions for outcome after alloHCT. Upon validation in larger patient cohorts, this will improve patient information before alloHCT and provide a platform to improve treatment strategies for patients with high risk of CIR or NRM.

Session topic: 22. Stem cell transplantation - Clinical

Keyword(s): AML, Transplant, prognosis, MDS

Abstract: S494

Type: Oral Presentation

Presentation during EHA22: On Saturday, June 24, 2017 from 16:45 - 17:00

Location: Room N103

Background

Prediction of individual outcomes after allogeneic hematopoietic cell transplantation (alloHCT) is difficult, as it is influenced by a multitude of risk factors.

Aims

To develop a tool that predicts individual outcomes of patients with myelodysplastic syndrome (MDS) or secondary acute myeloid leukemia from MDS (sAML) after alloHCT.

Methods
We integrated molecular data with available prognostic factors in patients undergoing alloHCT for MDS and sAML to evaluate their impact on prognosis. 304 patients with MDS or sAML who underwent alloHCT 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).

Results

In multivariate analysis, mutated NRAS, U2AF1, IDH2, TP53 and/or a complex karyotype were significant prognostic markers for OS besides age above 60 years, remission status treated but not in CR, 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 addition of molecular information significantly improved the risk prediction for OS and CIR as assessed by the Akaike information criterion. Internal and cross validation confirmed the robustness of our comprehensive risk model. We developed an interactive risk prediction tool to provide personalized predictions for OS, CIR and NRM outcome after alloHCT. An individualized prediction for a 53-year-old male with sAML with trisomy 11, mutated NRAS, IDH2 and DNMT3A and complete remission after double induction is shown in Figure 1. The probability of CIR at 2 years was 45% and the patient relapsed after 0.61 years. The probability of OS at 2 years was 41% and the patient died after 0.88 years.

Conclusion

We combine molecular, cytogenetic, patient- and transplantation associated risk factors into a comprehensive risk score to provide personalized predictions for outcome after alloHCT. Upon validation in larger patient cohorts, this will improve patient information before alloHCT and provide a platform to improve treatment strategies for patients with high risk of CIR or NRM.

Session topic: 22. Stem cell transplantation - Clinical

Keyword(s): AML, Transplant, prognosis, MDS

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