Prognostic impact of lymphocyte to monocyte ratio in patients with myelodysplastic neoplasms/syndromes
Wan-Hsuan Lee1,2,3,4, Chien-Chin Lin1,5, Xavier Cheng-Hong Tsai1
1Divisions of Hematology, Department of Internal Medicine, National Taiwan University Hospital, Taipei, Taiwan.
Purpose:
Myelodysplastic syndromes/neoplasms (MDS) represent a heterogeneous group of clonal hematopoietic disorders with variable prognosis. While several risk models exist, the prognostic role of immune-related biomarkers remains unclear. This study aimed to determine whether the lymphocyte-to-monocyte (L/M) ratio at diagnosis serves as an independent prognostic factor in MDS and to explore its biological correlates.
Methods:
A retrospective analysis of 554 patients with primary MDS diagnosed at the National Taiwan University Hospital was conducted. Patients were stratified by an L/M ratio cutoff of 1.5, determined by maximally selected rank statistics. Clinical, cytogenetic, and mutational profiles were assessed. Survival outcomes were analyzed using Kaplan-Meier methods and multivariable Cox regression incorporating IPSS-R, IPSS-M, and WHO-2022/ICC classifications. RNA sequencing was performed on diagnostic bone marrow samples to evaluate transcriptomic differences between groups.
Results:
Patients with L/M ratio > 1.5 were younger, had lower platelet counts, more advanced subtypes, and higher frequencies of STAG2 and U2AF1 mutations. Elevated L/M ratio was significantly associated with inferior leukemia-free and overall survival, independent of established prognostic models. Adverse prognostic effects were mitigated by allogeneic hematopoietic stem cell transplantation but not by hypomethylating agents. Transcriptomic analysis revealed downregulation of inflammatory pathways (IL-2-STAT5, IL6-JAK-STAT3, interferon responses) and the p53 pathway, along with enrichment of MYC targets in the high L/M group.
Conclusion:
An elevated L/M ratio is an independent and readily available biomarker that predicts poor outcomes in MDS. Integration of this parameter into existing risk models may refine prognostication and guide treatment intensity. Transcriptomic findings suggest immune suppression and p53 deregulation underlie its adverse impact, highlighting potential therapeutic avenues.
