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Original Article|Free Preview

Molecular International Prognostic Scoring System for Myelodysplastic Syndromes

  • Elsa Bernard, Ph.D.1,
  • Heinz Tuechler,
  • Peter L. Greenberg, M.D.2,
  • Robert P. Hasserjian, M.D.3,
  • Juan E. Arango Ossa, M.S.1,
  • Yasuhito Nannya, M.D., Ph.D.4,5,
  • Sean M. Devlin, Ph.D.1,
  • Maria Creignou, M.D.6,
  • Philippe Pinel, M.S.1,
  • Lily Monnier, M.S.1,
  • Gunes Gundem, Ph.D.1,
  • Juan S. Medina-Martinez, M.S.1,
  • Dylan Domenico, B.S.1,
  • Martin Jädersten, M.D., Ph.D.6,
  • Ulrich Germing, M.D.7,
  • Guillermo Sanz, M.D., Ph.D.8,9,10,
  • Arjan A. van de Loosdrecht, M.D., Ph.D.11,
  • Olivier Kosmider, M.D., Ph.D.12,
  • Matilde Y. Follo, Ph.D.13,
  • Felicitas Thol, M.D.14,
  • Lurdes Zamora, Ph.D.15,
  • Ronald F. Pinheiro, Ph.D.16,
  • Andrea Pellagatti, Ph.D.17,
  • Harold K. Elias, M.D.18,
  • Detlef Haase, M.D., Ph.D.19,
  • Christina Ganster, Ph.D.19,
  • Lionel Ades, M.D., Ph.D.20,
  • Magnus Tobiasson, M.D., Ph.D.6,
  • Laura Palomo, Ph.D.21,
  • Matteo Giovanni Della Porta, M.D.22,
  • Akifumi Takaori-Kondo, M.D., Ph.D.23,
  • Takayuki Ishikawa, M.D., Ph.D.24,
  • Shigeru Chiba, M.D., Ph.D.25,
  • Senji Kasahara, M.D., Ph.D.26,
  • Yasushi Miyazaki, M.D., Ph.D.27,
  • Agnes Viale, Ph.D.28,
  • Kety Huberman, B.S.28,
  • Pierre Fenaux, M.D., Ph.D.20,
  • Monika Belickova, Ph.D.29,
  • Michael R. Savona, M.D.30,
  • Virginia M. Klimek, M.D.18,
  • Fabio P. S. Santos, M.D., Ph.D.31,
  • Jacqueline Boultwood, Ph.D.17,
  • Ioannis Kotsianidis, M.D., Ph.D.32,
  • Valeria Santini, M.D.33,
  • Francesc Solé, Ph.D.21,
  • Uwe Platzbecker, M.D.34,
  • Michael Heuser, M.D.14,
  • Peter Valent, M.D.35,36,
  • Kazuma Ohyashiki, M.D., Ph.D.37,
  • Carlo Finelli, M.D.38,
  • Maria Teresa Voso, M.D.39,
  • Lee-Yung Shih, M.S.40,
  • Michaela Fontenay, M.D., Ph.D.12,
  • Joop H. Jansen, Ph.D.41,
  • José Cervera, M.D., Ph.D.42,
  • Norbert Gattermann, M.D.7,
  • Benjamin L. Ebert, M.D., Ph.D.43,
  • Rafael Bejar, M.D., Ph.D.44,
  • Luca Malcovati, M.D.45,
  • Mario Cazzola, M.D.45,
  • Seishi Ogawa, M.D., Ph.D.4,46,47,
  • Eva Hellström-Lindberg, M.D., Ph.D.6, and
  • Elli Papaemmanuil, Ph.D.1
Published June 12, 2022
NEJM Evid 2022; 1 (7)
DOI:https://doi.org/10.1056/EVIDoa2200008
Issue

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.)

Clinical decisions are best made based on evidence.


This work was supported in part by grants from Celgene Corporation through the MDS Foundation. E.B. was supported by the Edward P. Evans Foundation. L.M., M.T.V., and M.C. were supported by the Associazione Italiana per la Ricerca sul Cancro (AIRC; Investigator Grant 20125 and AIRC 5x1000 Project 21267) and Cancer Research UK and AIRC under the Accelerator Award Program (CRUK C355/A26819, AIRC 22796). M.Y.F. was supported by the Projects of National Relevance of the Italian Ministry of University and Research (Grants 2015CFS5RY and 2017RKWNJT). A.P. and J.B. were supported by Blood Cancer UK (Grants 13042 and 19004). P.V. was supported by the Austrian Science Fund (grant F4704-B20). L.-Y.S. was supported by the Taiwan Department of Health (Grant DOH102-TD-C-111-006). Finally, this work was supported by the Japan Agency for Medical Research and Development (Grants JP21cm0106501h0006, P20cm0106501h0005, JP19cm0106501h0004), JSPS (Japan Society for the Promotion of Science) program KAKENHI (Grants JP19H05656 and JP26221308 to S.O. and JP18H02836 to Y.N.), and the MEXT (Japanese Ministry of Education, Culture, Sports, Science and Technology) Program for Promoting Research on the Supercomputer Fugaku (hp200138). E.P. was supported by the Josie Robertson Investigators Program.

Disclosure forms provided by the authors are available with the full text of this article.

A data sharing statement provided by the authors is available with the full text of this article.

We are deeply thankful for the support of the MDS Foundation given to the study and thank Tracey Iraca and Lea Harrison. We thank the broader International Working Group MDS community for providing feedback and engaging in fruitful discussions on the study at the annual meetings.

Dr. Bernard can be contacted at [email protected] or at Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065; or Dr. Papaemmanuil can be contacted at [email protected] or at Department of Epidemiology and Biostatistics, Memorial Sloan Kettering Cancer Center, New York, NY 10065.

Figures/Media

  • Figure 1. International Working Group for Prognosis in Myelodysplastic Syndromes Cohort Molecular Characteristics.
    Figure 1

    In Panel A, the frequency of mutated genes and cytogenetic alterations in the 2957 myelodysplastic syndrome samples is shown. Lesions observed in more than five patients are shown. Colors represent the type of lesions. In Panel B, a histogram of the total number of oncogenic alterations (gene mutations and cytogenetic abnormalities) per patient (top) and violin plots representing the associated distribution of percentage of bone marrow blasts (bottom) are shown. P-value is from the Kruskal–Wallis test. In Panel C, Kaplan–Meier probability estimates of leukemia-free survival (LFS) across numbers of oncogenic alterations per patient (gene mutations and cytogenetic abnormalities) are shown. Isolated SF3B1 mutations are shown separately in purple. P-value is from the log-rank test.

  • Figure 2. International Prognostic Scoring System–Molecular Risk Score and Risk Categories.
    Figure 2

    In Panel A, the density plot shows the International Prognostic Scoring System–Molecular (IPSS-M) risk score calculated for 2701 patients from the International Working Group for Prognosis in Myelodysplastic Syndromes cohort with available data for hemoglobin, platelets, marrow blasts, cytogenetic, and gene mutations. The bottom x-axis shows the IPSS-M score and the top x-axis shows the corresponding hazard ratio from the hypothetical average patient. Vertical dashed lines represent cutoffs that are applied to the score to define the six IPSS-M risk categories. In Panel B, hazard ratios are provided for the risk of death or transformation of the IPSS-M risk categories, in which the low category corresponds to the reference. In Panels C and D, Kaplan–Meier probability estimates of leukemia-free survival (LFS) and overall survival (OS) are presented across IPSS-M risk categories, respectively. Dashed lines highlight the median values. P-values are from the log-rank test. In Panel E, cause-specific cumulative incidences are shown for the rate of acute myeloid leukemia (AML) transformation (long-dashed line), death with AML (dot-dashed lines), death without AML (dotted line), overall death (solid line), and death or transformation (short-dashed line). In the latter two cases, the curves are equivalent to 1 − Kaplan–Meier estimates for OS and LFS. CI denotes confidence interval, H high, L low, MH moderate high, ML moderate low, VH very high, and VL very low.

  • Figure 3. Comparison of the International Prognostic Scoring System–Revised and the International Prognostic Scoring System–Molecular.
    Figure 3

    In Panel A, model discrimination as measured by the C-index obtained with the International Prognostic Scoring System–Revised (IPSS-R) or the International Prognostic Scoring System–Molecular (IPSS-M) across the three end points (i.e., leukemia-free survival, overall survival, and acute myeloid leukemia [AML] transformation) is shown. In red, the risk was encoded as categories (using five categories for both IPSS-R and IPSS-M by merging the moderate low and moderate high categories), while in blue it was encoded as a score. In Panel B, stacked bar plots show the restratification of IPSS-R to IPSS-M for 2678 patients where both scores could be calculated. Each row corresponds to one IPSS-R category, and colors represent the IPSS-M categories. The gray bar plots represent the percentage of restratified patients in each IPSS-R stratum, counting either any shift (left) or cases with more than one shifts (right). In Panel C, the association between the number of mutated IPSS-M main effect adverse genes and patient restratification is shown. Simplified risk categories were obtained by merging the very low/low categories into (very) low, and very high/high categories into (very) high for both IPSS-R and IPSS-M. The simplified IPSS-R and IPSS-M categories are separated by facet and y-axis, respectively. CI denotes confidence interval.

  • Figure 4. International Prognostic Scoring System–Molecular in Secondary/Therapy-Related Myelodysplastic Syndromes.
    Figure 4

    Kaplan–Meier probability estimates of leukemia-free survival (LFS) for primary myelodysplastic syndromes (MDS) (red) or secondary/therapy-related MDS (s/t-MDS, blue), when patients are not stratified (top left) or with International Prognostic Scoring System–Molecular (IPSS-M) risk stratification (all other facets). The numbers at risk are indicated below the x-axis. Dashed lines highlight the median values. P-values are from the log-rank test. CI denotes confidence interval, and HR hazard ratio.

  • Table 1. IPSS-M Risk Score Construction from an Adjusted Cox Multivariable Regression for Leukemia-Free Survival.
  • Table 2. Summary of Clinical Outcomes for 2701 Patients by IPSS-M Risk Category.

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