Molecular International Prognostic Scoring System for Myelodysplastic Syndromes

Elsa Bernard(Memorial Sloan Kettering Cancer Center), Heinz Tuechler, Peter L. Greenberg(Stanford University), Robert P. Hasserjian(Massachusetts General Hospital), Juan Arango Ossa(Memorial Sloan Kettering Cancer Center), Yasuhito Nannya(The University of Tokyo), Sean M. Devlin(Memorial Sloan Kettering Cancer Center), Maria Creignou(Karolinska Institutet), Philippe Pinel(Memorial Sloan Kettering Cancer Center), Lily Monnier(Memorial Sloan Kettering Cancer Center), Gunes Gundem(Memorial Sloan Kettering Cancer Center), Juan S. Medina-Martínez(Memorial Sloan Kettering Cancer Center), Dylan Domenico(Memorial Sloan Kettering Cancer Center), Martin Jädersten(Karolinska University Hospital), Ulrich Germing(Heinrich Heine University Düsseldorf), Guillermo Sanz(Centro de Investigación Biomédica en Red de Cáncer), Arjan A. van de Loosdrecht(University Medical Center), Olivier Kosmider(Université Paris Cité), Matilde Y. Follo(University of Bologna), Felicitas Thol(Medizinische Hochschule Hannover), Lurdes Zamora(Josep Carreras Leukaemia Research Institute), Ronald Feitosa Pinheiro(Universidade Federal do Ceará), Andrea Pellagatti(Oxford BioMedica (United Kingdom)), Harold K. Elias(Memorial Sloan Kettering Cancer Center), Detlef Haase(Universitätsmedizin Göttingen), Christina Ganster(Universitätsmedizin Göttingen), Lionel Adès, Magnus Tobiasson(Karolinska Institutet), Laura Palomo(Fundación Josep Carreras Contra la Leucemia), Matteo Giovanni Della Porta(Humanitas University), Akifumi Takaori‐Kondo(Kyoto University), Takayuki Ishikawa(Kobe City Medical Center General Hospital), Shigeru Chiba(University of Tsukuba), Senji Kasahara(Gifu Municipal Hospital), Yasushi Miyazaki(Nagasaki University), Agnès Viale(Memorial Sloan Kettering Cancer Center), Kety Huberman(Igenbio (United States)), Pierre Fenaux, Monika Beličková(Institute of Haematology and Blood Transfusion), Michael R. Savona(Vanderbilt University), Virginia M. Klimek(Memorial Sloan Kettering Cancer Center), Fábio Pires de Souza Santos(Hospital Israelita Albert Einstein), Jacqueline Boultwood(Oxford BioMedica (United Kingdom)), Ιoannis Kotsianidis(Democritus University of Thrace), Valeria Santini(University of Florence), Françesc Solé(Fundación Josep Carreras Contra la Leucemia), Uwe Platzbecker(University Hospital Leipzig), Michael Heuser(Medizinische Hochschule Hannover), Peter Valent(Medical University of Vienna), Kazuma Ohyashiki(Tokyo Medical University), Carlo Finelli(Istituti di Ricovero e Cura a Carattere Scientifico), Maria Teresa Voso, Lee‐Yung Shih(Chang Gung University), Michaëla Fontenay(Université Paris Cité), Joop H. Jansen(Radboud University Medical Center), José Cervera(Hospital Universitari i Politècnic La Fe), Norbert Gattermann(Heinrich Heine University Düsseldorf), Benjamin L. Ebert(Howard Hughes Medical Institute), Rafael Bejar(University of California, San Diego), Luca Malcovati(University of Pavia), Mario Cazzola(University of Pavia), Seishi Ogawa(Kyoto University), Eva Hellström‐Lindberg(Karolinska Institutet), Elli Papaemmanuil(Memorial Sloan Kettering Cancer Center)
NEJM Evidence
June 12, 2022
Cited by 803Open Access
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Abstract

BACKGROUND: Risk stratification and therapeutic decision-making for myelodysplastic syndromes (MDS) are based on the International Prognostic Scoring System–Revised (IPSS-R), which considers hematologic parameters and cytogenetic abnormalities. Somatic gene mutations are not yet used in the risk stratification of patients with MDS. METHODS: To develop a clinical-molecular prognostic model (IPSS-Molecular [IPSS-M]), pretreatment diagnostic or peridiagnostic samples from 2957 patients with MDS were profiled for mutations in 152 genes. Clinical and molecular variables were evaluated for associations with leukemia-free survival, leukemic transformation, and overall survival. Feature selection was applied to determine the set of independent IPSS-M prognostic variables. The relative weights of the selected variables were estimated using a robust Cox multivariable model adjusted for confounders. The IPSS-M was validated in an external cohort of 754 Japanese patients with MDS. RESULTS: We mapped at least one oncogenic genomic alteration in 94% of patients with MDS. Multivariable analysis identified TP53multihit, FLT3 mutations, and MLLPTD as top genetic predictors of adverse outcomes. Conversely, SF3B1 mutations were associated with favorable outcomes, but this was modulated by patterns of comutation. Using hematologic parameters, cytogenetic abnormalities, and somatic mutations of 31 genes, the IPSS-M resulted in a unique risk score for individual patients. We further derived six IPSS-M risk categories with prognostic differences. Compared with the IPSS-R, the IPSS-M improved prognostic discrimination across all clinical end points and restratified 46% of patients. The IPSS-M was applicable in primary and secondary/therapy-related MDS. To simplify clinical use of the IPSS-M, we developed an open-access Web calculator that accounts for missing values. CONCLUSIONS: Combining genomic profiling with hematologic and cytogenetic parameters, the IPSS-M improves the risk stratification of patients with MDS and represents a valuable tool for clinical decision-making. (Funded by Celgene Corporation through the MDS Foundation, the Josie Robertson Investigators Program, the Edward P. Evans Foundation, the Projects of National Relevance of the Italian Ministry of University and Research, Associazione Italiana per la Ricerca sul Cancro, the Japan Agency for Medical Research and Development, Cancer Research UK, the Austrian Science Fund, the MEXT [Japanese Ministry of Education, Culture, Sports, Science and Technology] Program for Promoting Research on the Supercomputer Fugaku, the Japan Society for the Promotion of Science, the Taiwan Department of Health, and Celgene Corporation through the MDS Foundation.)


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