Haematologica (Feb 2024)

A predictive classifier of poor prognosis in transplanted patients with juvenile myelomonocytic leukemia: a study on behalf of the Société Francophone de Greffe de Moelle et de Thérapie Cellulaire

  • Déborah Meyran,
  • Chloé Arfeuille,
  • Sylvie Chevret,
  • Quentin Neven,
  • Aurélie Caye-Eude,
  • Elodie Lainey,
  • Arnaud Petit,
  • Fanny Rialland,
  • Gérard Michel,
  • Dominique Plantaz,
  • Charlotte Jubert,
  • Alexandre Theron,
  • Virginie Gandemer,
  • Marie Ouachée-Chardin,
  • Catherine Paillard,
  • Bénédicte Bruno,
  • Nimrod Buchbinder,
  • Cécile Pochon,
  • Charlotte Calvo,
  • Mony Fahd,
  • André Baruchel,
  • Hélène Cavé,
  • Jean-Hugues Dalle,
  • Marion Strullu

DOI
https://doi.org/10.3324/haematol.2023.284103
Journal volume & issue
Vol. 999, no. 1

Abstract

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Juvenile myelomonocytic leukemia (JMML) is an aggressive pediatric myeloproliferative neoplasm requiring hematopoietic stem cell transplantation (HSCT) in most cases. We retrospectively analyzed 119 JMML patients who underwent first allogeneic HSCT between 2002 and 2021. The majority (97%) carried a RAS-pathway mutation, and 62% exhibited karyotypic alterations or additional mutations in SETBP1, ASXL1, JAK3 and/or the RAS pathway. Relapse was the primary cause of death, with a 5-year cumulative incidence of 24.6% (95%CI: 17.1-32.9). Toxic deaths occurred in 12 patients, resulting in treatmentrelated mortality (TRM) of 9.0% (95%CI: 4.6-15.3). The 5-year overall (OS) and event-free survival were 73.6% (95%CI: 65.7-82.4) and 66.4% (95%CI: 58.2-75.8), respectively. Four independent adverse prognostic factors for OS were identified: age at diagnosis >2 years, time from diagnosis to HSCT >6 months, monocyte count at diagnosis >7.2x109/L, and the presence of additional genetic alterations. Based on these factors, we proposed a predictive classifier. Patients with three or more predictors (21% of the cohort) had a 5-year OS of 34.2%, whereas those with none (7%) had a 5-year OS of 100%. Our study demonstrates improved transplant outcomes compared to prior published data, which can be attributed to the synergistic impacts of a low TRM and a reduced yet still substantial relapse incidence. By integrating genetic information with clinical and hematological features, we have devised a predictive classifier. This classifier effectively identifies a subgroup of patients who are at a heightened risk of unfavorable post-transplant outcomes who would benefit novel therapeutic agents and post-transplant strategies.