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The elevation of red blood cell distribution width is an independent prognostic factor for juvenile myelomonocytic leukemia. 2024

Weiru Liang, and Chenmeng Liu, and Jingliao Zhang, and Meihui Yi, and Yuli Cai, and Aoli Zhang, and Lipeng Liu, and Li Zhang, and Xiaojuan Chen, and Yao Zou, and Yumei Chen, and Ye Guo, and Yingchi Zhang, and Xiaofan Zhu, and Wenyu Yang
State Key Laboratory of Experimental Hematology, National Clinical Research Center for Blood Diseases, Institute of Hematology & Blood Diseases Hospital, Chinese Academy of Medical Sciences & Peking Union Medical College, Tianjin 300020, China.

Juvenile myelomonocytic leukemia (JMML) is a disorder characterized by the simultaneous presence of myeloproliferative and myelodysplastic features, primarily affecting infants and young children. Due to the heterogeneous genetic background among patients, the current clinical and laboratory prognostic features are insufficient for accurately predicting outcomes. Thus, there is a pressing need to identify novel prognostic indicators. Red cell distribution width (RDW) is a critical parameter reflecting the variability in erythrocyte size. Recent studies have emphasized that elevated RDW serves as a valuable predictive marker for unfavorable outcomes across various diseases. However, the prognostic role of RDW in JMML remains unclear. Patients with JMML from our single-center cohort between January 2008 and December 2019 were included. Overall, 77 patients were eligible. Multivariate Cox proportional hazard models showed that patients with red cell distribution width coefficient of variation (RDW-CV) >17.35% at diagnosis were susceptible to much worse overall survival rate (hazard ratio [HR] = 5.22, confidence interval [CI] = 1.50-18.21, P = .010). Besides, the combination of RDW elevation and protein phosphatase non-receptor type 11 (PTPN11) mutation was likely to predict a subgroup with the worst outcomes in our cohort. RDW is an independent prognostic variable in JMML subjects. RDW may be regarded as an inexpensive biomarker to predict the clinical outcome in patients with JMML.

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