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MYELODYSPLASTIC NEOPLASM

Assessment and validation of the molecular international prognostic scoring system for myelodysplastic syndromes

Leukemia volume 37, pages 1530–1539 (2023)Cite this article

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Abstract

The Molecular International Prognostic Scoring System (IPSS-M) is a novel risk stratification model for myelodysplastic syndromes (MDS) that builds on the IPSS and IPSS-R by incorporating mutational data. The model showed improved prognostic accuracy over the IPSS-R across three endpoints: overall survival (OS), leukemia-free survival (LFS) and leukemic transformation. This study aimed to validate the findings of the original in a large cohort of MDS patients, as well as assess its validity in therapy-related and hypoplastic MDS. We retrospectively reviewed clinical, cytogenetic and molecular data for 2355 MDS patients treated at the Moffitt Cancer Center. Correlative analysis between IPSS-R and mean IPSS-M scores and outcome predictions was performed on LFS, OS and leukemic transformation. Using the IPSS-M, patients were classified as Very Low (4%), Low (24%), Moderate-Low (14%), Moderate-High (11%), High (19%) and Very-High risk (28%). Median OS was 11.7, 7.1, 4.4, 3.1, 2.3, and 1.3 years from VL to VH risk subgroups. Median LFS was 12.3, 6.9, 3.6, 2.2, 1.4, and 0.5 years respectively. For patients with t-MDS and h-MDS the model retained its prognostic accuracy. Generalized use of this tool will likely result in more accurate prognostic assessment and optimize therapeutic decision-making in MDS.

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Fig. 1: IPSS-M model and risk categories.
Fig. 2: IPSS-M model and risk categories.
Fig. 3: Therapy-related Myelodysplastic Syndromes.
Fig. 4: IPSS-M in therapy-related Myelodysplastic Syndromes.
Fig. 5: IPSS-M in therapy-related MDS.
Fig. 6: Hypoplastic Myelodysplastic Syndromes.
Fig. 7: IPSS-M in hypoplastic MDS.
Fig. 8: IPSS-M in hypoplastic MDS as defined by the 5th edition of the WHO classification.

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The authors confirm that the data supporting the findings of this study are available within the paper and/or its supplementary materials.

References

  1. Aguirre LE, Komrokji R, Padron E. It is time to shift the treatment paradigm in myelodysplastic syndromes: A focus on novel developments and current investigational approaches exploring combinatorial therapy in high-risk MDS. Best Pr Res Clin Haematol. 2021;34:101325.

    Article  CAS  Google Scholar 

  2. Ogawa S. Genetics of MDS. Blood. 2019;133:1049–59.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  3. Greenberg P, Cox C, LeBeau MM, Fenaux P, Morel P, Sanz G, et al. International scoring system for evaluating prognosis in myelodysplastic syndromes. Blood. 1997;89:2079–88.

    Article  CAS  PubMed  Google Scholar 

  4. Greenberg PL, Tuechler H, Schanz J, Sanz G, Garcia-Manero G, Solé F, et al. Revised international prognostic scoring system for myelodysplastic syndromes. Blood. 2012;120:2454–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Bejar R. Clinical and genetic predictors of prognosis in myelodysplastic syndromes. Haematologica 2014;99:956–64.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Malcovati L, Karimi M, Papaemmanuil E, Ambaglio I, Jädersten M, Jansson M, et al. SF3B1 mutation identifies a distinct subset of myelodysplastic syndrome with ring sideroblasts. Blood. 2015;126:233–41.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  7. Malcovati L, Stevenson K, Papaemmanuil E, Neuberg D, Bejar R, Boultwood J, et al. SF3B1-mutant MDS as a distinct disease subtype: a proposal from the International Working Group for the Prognosis of MDS. Blood. 2020;136:157–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Papaemmanuil E, Gerstung M, Malcovati L, Tauro S, Gundem G, Van Loo P, et al. Clinical and biological implications of driver mutations in myelodysplastic syndromes. Blood. 2013;122:3616–27.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  9. Haferlach T, Nagata Y, Grossmann V, Okuno Y, Bacher U, Nagae G, et al. Landscape of genetic lesions in 944 patients with myelodysplastic syndromes. Leukemia. 2014;28:241–7.

    Article  CAS  PubMed  Google Scholar 

  10. Nazha A, Al-Issa K, Hamilton BK, Radivoyevitch T, Gerds AT, Mukherjee S, et al. Adding molecular data to prognostic models can improve predictive power in treated patients with myelodysplastic syndromes. Leukemia. 2017;31:2848–50.

    Article  CAS  PubMed  Google Scholar 

  11. Bersanelli M, Travaglino E, Meggendorfer M, Matteuzzi T, Sala C, Mosca E, et al. Classification and personalized prognostic assessment on the basis of clinical and genomic features in myelodysplastic syndromes. J Clin Oncol. 2021;39:1223–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  12. 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;39:3737–46.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Bernard E, Tuechler H, Greenberg PL, Hasserjian RP, Arango JE, Nannya Y, et al. Molecular International Prognostic Scoring System for Myelodysplastic Syndromes. NEJM Evid. 2022;1:1–14.

    Article  Google Scholar 

  14. Kuendgen A, Nomdedeu M, Tuechler H, Garcia-Manero G, Komrokji RS, Sekeres MA, et al. Therapy-related myelodysplastic syndromes deserve specific diagnostic sub-classification and risk-stratification-an approach to classification of patients with t-MDS. Leukemia 2021;35:835–49.

    Article  CAS  PubMed  Google Scholar 

  15. Mishra A, Corrales-Yepez M, Al-Ali N, Kharfan-Dabaja M, Padron E, Zhang L, et al. Validation of the revised International Prognostic Scoring System in treated patients with myelodysplastic syndromes. Am J Hematol. 2013;88:566–70.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  16. Bono E, McLornan D, Travaglino E, Gandhi S, Gallì A, Khan AA, et al. Clinical, histopathological and molecular characterization of hypoplastic myelodysplastic syndrome. Leukemia 2019;33:2495–505.

    Article  CAS  PubMed  Google Scholar 

  17. Fattizzo B, Serpenti F, Barcellini W, Caprioli C. Hypoplastic Myelodysplastic Syndromes: Just an Overlap Syndrome? Cancers (Basel). 2021;13:132.

    Article  CAS  PubMed  Google Scholar 

  18. Khoury JD, Solary E, Abla O, Akkari Y, Alaggio R, Apperley JF, et al. The 5th edition of the World Health Organization Classification of Haematolymphoid Tumours: Myeloid and Histiocytic/Dendritic Neoplasms. Leukemia 2022;36:1703–19.

    Article  PubMed  PubMed Central  Google Scholar 

  19. Platzbecker U. Treatment of MDS. Blood. 2019;133:1096–107.

    Article  CAS  PubMed  Google Scholar 

  20. Arber DA, Orazi A, Hasserjian RP, Borowitz MJ, Calvo KR, Kvasnicka HM, et al. International Consensus Classification of Myeloid Neoplasms and Acute Leukemias: integrating morphologic, clinical, and genomic data. Blood 2022;140:1200–28.

    Article  CAS  PubMed  Google Scholar 

  21. Bernard E, Nannya Y, Hasserjian RP, Devlin SM, Tuechler H, Medina-Martinez JS, et al. Implications of TP53 allelic state for genome stability, clinical presentation and outcomes in myelodysplastic syndromes. Nat Med. 2020;26:1549–56.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Jumniensuk C, Nobori A, Lee T, Senaratne TN, Rao D, Pullarkat S. Concordance of Peripheral Blood and Bone Marrow Next-Generation Sequencing in Hematologic Neoplasms. Adv Hematol. 2022;2022:8091746.

    Article  PubMed  PubMed Central  Google Scholar 

  23. Lucas F, Michaels PD, Wang D, Kim AS. Mutational analysis of hematologic neoplasms in 164 paired peripheral blood and bone marrow samples by next-generation sequencing. Blood Adv. 2020;4:4362–5.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

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Acknowledgements

Parts of this paper will be presented in preliminary form as three separate abstracts at the 2022 64th ASH Annual Meeting and Exposition as an oral presentation and three tow posters. The investigators would like to extend their sincerest gratitude to Dr Elsa Bernard and the Elli Papaemmanuil lab at Memorial Sloan Kettering Cancer Center for providing syntax code and additional support to facilitate batch-calculation analysis.

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Authors and Affiliations

  1. H. Lee Moffitt Cancer Center and Research Institute, Tampa, FL, USA

    Luis E. Aguirre, Najla Al Ali, David A. Sallman, Somedeb Ball, Akriti G. Jain, Onyee Chan, Sara M. Tinsley-Vance, Andrew Kuykendall, Kendra Sweet, Jeffrey E. Lancet, Eric Padron & Rami S. Komrokji

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  1. Luis E. Aguirre
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Contributions

(I) Conception and design: RK, LA. (II) Administrative support: RK, NA. (III) Provision of study materials or patients: RK, LA, DS, JL, KS, EP, NA, AK. (IV) Collection and assembly of data: NA, RK, LA. (V) Data analysis and interpretation: RK, LA, NA, OC. (VI) Paper writing: LA, RK, DS. (VII) Final approval of paper: All authors.

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Correspondence to Luis E. Aguirre or Rami S. Komrokji.

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Competing interests

All authors have completed the ICMJE uniform disclosure form. T-V: Abbvie: Consultancy; Novartis: Consultancy; Jazz: Consultancy, Speakers Bureau; Incyte: Consultancy, Speakers Bureau; CTI: Consultancy, Speakers Bureau; BMS: Consultancy, Speakers Bureau. AK: Protagonist: Other: Research Support; Imago Biosciences: Consultancy, Honoraria, Speakers Bureau; Incyte: Consultancy, Honoraria, Speakers Bureau; Blueprint Medicines Corporation: Consultancy, Honoraria, Research Funding, Speakers Bureau; Novartis: Consultancy, Honoraria, Speakers Bureau; Abbvie: Consultancy, Honoraria, Speakers Bureau; GSK - Sierra Oncology: Consultancy, Honoraria, Other: Research Support, Speakers Bureau; Prelude Pharmaceuticals: Other: Research Support; BMS: Consultancy, Honoraria, Other: Research Support, Speakers Bureau; Morphosys: Other: Research Support; Pharmaessentia: Consultancy, Honoraria, Speakers Bureau; CTI Biopharma: Consultancy, Honoraria, Speakers Bureau. KS: Mablytics: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Pfizer: Consultancy, Membership on an entity’s Board of Directors or advisory committees, Research Funding; Curis: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; berGenBio: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Syntrix Pharmaceuticals: Research Funding; Incyte: Research Funding; AROG: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Gilead Sciences, Inc.: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Novartis: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Astellas: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees; Bristol Myers Squibb: Consultancy, Honoraria, Membership on an entity’s Board of Directors or advisory committees. JEL: Novartis: Consultancy; Jasper Therapeutics: Consultancy; Dedham Group: Consultancy; Boxer Capital: Consultancy; Dava Oncology: Consultancy; Syntrix Pharmaceuticals: Research Funding; Astellas: Consultancy; Agios/Servio: Consultancy; Jazz: Consultancy; BerGenBio: Consultancy; Millenium Pharma/Takeda: Consultancy; ElevateBio Management: Consultancy; Daiichi Sankyo: Consultancy; Celgene/BMS: Research Funding; AbbVie: Consultancy; Servier: Consultancy. EP: Incyte: Research Funding; Kura: Research Funding; Stemline: Honoraria; Taiho: Honoraria; Blueprint: Honoraria; Syntrix Pharmaceuticals: Research Funding; BMS: Research Funding. DAS: Syntrix Pharmaceuticals: Research Funding; Nemucore: Membership on an entity’s Board of Directors or advisory committees; Lixte: Patents & Royalties: LB-100; Magenta: Consultancy; Novartis: Consultancy, Membership on an entity’s Board of Directors or advisory committees; Intellia: Membership on an entity’s Board of Directors or advisory committees; Syndax: Membership on an entity’s Board of Directors or advisory committees; Kite: Membership on an entity’s Board of Directors or advisory committees; Incyte: Speakers Bureau; Shattuck Labs: Membership on an entity’s Board of Directors or advisory committees; BMS: Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; Aprea: Membership on an entity’s Board of Directors or advisory committees, Research Funding; Agios: Membership on an entity’s Board of Directors or advisory committees; AbbVie: Membership on an entity’s Board of Directors or advisory committees; Takeda: Consultancy. RSK: Jazz: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; Servio: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; CTI biopharma: Honoraria, Membership on an entity’s Board of Directors or advisory committees, Speakers Bureau; PharmaEssentia: Honoraria, Other, Speakers Bureau; BMS: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Novartis: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Abbvie: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Geron: Honoraria, Membership on an entity’s Board of Directors or advisory committees; Taiho: Honoraria, Membership on an entity’s Board of Directors or advisory committees. All other authors have no competing interests to declare.

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The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved. The study was conducted in accordance with the Declaration of Helsinki (as revised in 2013). The study was approved by institutional review board and individual consent for this retrospective analysis was waived.

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Aguirre, L.E., Al Ali, N., Sallman, D.A. et al. Assessment and validation of the molecular international prognostic scoring system for myelodysplastic syndromes. Leukemia 37, 1530–1539 (2023). https://doi.org/10.1038/s41375-023-01910-3

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