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Personalized Prediction Model to Risk Stratify Patients With Myelodysplastic Syndromes.

Publication ,  Journal Article
Nazha, A; Komrokji, R; Meggendorfer, M; Jia, X; Radakovich, N; Shreve, J; Hilton, CB; Nagata, Y; Hamilton, BK; Mukherjee, S; Al Ali, N ...
Published in: J Clin Oncol
November 20, 2021

PURPOSE: Patients with myelodysplastic syndromes (MDS) have a survival that can range from months to decades. Prognostic systems that incorporate advanced analytics of clinical, pathologic, and molecular data have the potential to more accurately and dynamically predict survival in patients receiving various therapies. METHODS: A total of 1,471 MDS patients with comprehensively annotated clinical and molecular data were included in a training cohort and analyzed using machine learning techniques. A random survival algorithm was used to build a prognostic model, which was then validated in external cohorts. The accuracy of the proposed model, compared with other established models, was assessed using a concordance (c)index. RESULTS: The median age for the training cohort was 71 years. Commonly mutated genes included SF3B1, TET2, and ASXL1. The algorithm identified chromosomal karyotype, platelet, hemoglobin levels, bone marrow blast percentage, age, other clinical variables, seven discrete gene mutations, and mutation number as having prognostic impact on overall and leukemia-free survivals. The model was validated in an independent external cohort of 465 patients, a cohort of patients with MDS treated in a prospective clinical trial, a cohort of patients with paired samples at different time points during the disease course, and a cohort of patients who underwent hematopoietic stem-cell transplantation. CONCLUSION: A personalized prediction model on the basis of clinical and genomic data outperformed established prognostic models in MDS. The new model was dynamic, predicting survival and leukemia transformation probabilities at different time points that are unique for a given patient, and can upstage and downstage patients into more appropriate risk categories.

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Published In

J Clin Oncol

DOI

EISSN

1527-7755

Publication Date

November 20, 2021

Volume

39

Issue

33

Start / End Page

3737 / 3746

Location

United States

Related Subject Headings

  • Young Adult
  • Survival Rate
  • Prospective Studies
  • Prognosis
  • Oncology & Carcinogenesis
  • Myelodysplastic Syndromes
  • Mutation
  • Models, Statistical
  • Middle Aged
  • Male
 

Citation

APA
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Nazha, A., Komrokji, R., Meggendorfer, M., Jia, X., Radakovich, N., Shreve, J., … Sekeres, M. A. (2021). Personalized Prediction Model to Risk Stratify Patients With Myelodysplastic Syndromes. J Clin Oncol, 39(33), 3737–3746. https://doi.org/10.1200/JCO.20.02810
Nazha, Aziz, Rami Komrokji, Manja Meggendorfer, Xuefei Jia, Nathan Radakovich, Jacob Shreve, C Beau Hilton, et al. “Personalized Prediction Model to Risk Stratify Patients With Myelodysplastic Syndromes.J Clin Oncol 39, no. 33 (November 20, 2021): 3737–46. https://doi.org/10.1200/JCO.20.02810.
Nazha A, Komrokji R, Meggendorfer M, Jia X, Radakovich N, Shreve J, et al. Personalized Prediction Model to Risk Stratify Patients With Myelodysplastic Syndromes. J Clin Oncol. 2021 Nov 20;39(33):3737–46.
Nazha, Aziz, et al. “Personalized Prediction Model to Risk Stratify Patients With Myelodysplastic Syndromes.J Clin Oncol, vol. 39, no. 33, Nov. 2021, pp. 3737–46. Pubmed, doi:10.1200/JCO.20.02810.
Nazha A, Komrokji R, Meggendorfer M, Jia X, Radakovich N, Shreve J, Hilton CB, Nagata Y, Hamilton BK, Mukherjee S, Al Ali N, Walter W, Hutter S, Padron E, Sallman D, Kuzmanovic T, Kerr C, Adema V, Steensma DP, Dezern A, Roboz G, Garcia-Manero G, Erba H, Haferlach C, Maciejewski JP, Haferlach T, Sekeres MA. Personalized Prediction Model to Risk Stratify Patients With Myelodysplastic Syndromes. J Clin Oncol. 2021 Nov 20;39(33):3737–3746.

Published In

J Clin Oncol

DOI

EISSN

1527-7755

Publication Date

November 20, 2021

Volume

39

Issue

33

Start / End Page

3737 / 3746

Location

United States

Related Subject Headings

  • Young Adult
  • Survival Rate
  • Prospective Studies
  • Prognosis
  • Oncology & Carcinogenesis
  • Myelodysplastic Syndromes
  • Mutation
  • Models, Statistical
  • Middle Aged
  • Male