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Adding molecular data to prognostic models can improve predictive power in treated patients with myelodysplastic syndromes

Leukemia volume 31, pages 2848–2850 (2017)Cite this article

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Myelodysplastic syndromes (MDS) are a collection of clonal disorders characterized by the acquisition of complex genomic alterations that can define disease phenotype, risk of acute myeloid leukemia progression, and overall survival (OS).1 In the past two decades, several prognostic scoring systems were developed to predict outcomes in MDS patients and define preferred treatment strategies, including the International Prognostic Scoring System (IPSS),2 World Health Organization (WHO) classification-based Prognostic Scoring System (WPSS),3 MD Anderson Prognostic Scoring System (MDAPSS),4 and the revised IPSS (IPSS-R).5 Several strengths and weaknesses have been recognized when applying these scoring systems in clinical practice.

Next-generation sequencing technologies have illuminated the genomic landscapes of MDS.6, 7, 8 Although none of the most common recurrent somatic mutations is disease defining, some have an independent impact on OS even after adjusting for clinical variables.9 For example, the addition of the molecular data to the IPSS-R can improve its predictive power in treated patients with MDS, and can make the system dynamics.9 However, the optimal way to incorporate the genomic data into established scoring systems in MDS is not well established.

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Authors and Affiliations

  1. Department of Hematology and Oncology, Leukemia Program, Cleveland Clinic, Taussig Cancer Institute, Cleveland, OH, USA

    A Nazha, K Al-Issa, B K Hamilton, A T Gerds, S Mukherjee, A Zarzour, N Abuhadra, B J Patel, A Advani, H E Carraway & M A Sekeres

  2. Department of Translational Hematology and Oncology Research, Cleveland Clinic, Taussig Cancer Institute, Cleveland, OH, USA

    T Radivoyevitch, V Adema, C M Hirsch, B Przychodzen & J P Maciejewski

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  1. A Nazha
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Correspondence to A Nazha.

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The authors declare no conflict of interest.

Additional information

The study was presented as an oral presentation at the Annual Meeting of the American Society of Hematology, San Diego 2016.

Supplementary Information accompanies this paper on the Leukemia website

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Nazha, A., Al-Issa, K., Hamilton, B. et al. Adding molecular data to prognostic models can improve predictive power in treated patients with myelodysplastic syndromes. Leukemia 31, 2848–2850 (2017). https://doi.org/10.1038/leu.2017.266

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