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PB2091 HOST INFLAMMATORY FACTORS MIGHT PREDICT LEUKEMIC TRANSFORMATION AND OVERALL SURVIVAL IN CHRONIC MYELOMONOCYTIC LEUKEMIA
Author(s) -
Davidkova Y. T.,
Yagurinoski M.,
Spassov B.,
Balatzenko G.,
Guenova M.
Publication year - 2019
Publication title -
hemasphere
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.677
H-Index - 11
ISSN - 2572-9241
DOI - 10.1097/01.hs9.0000566848.00638.eb
Subject(s) - chronic myelomonocytic leukemia , medicine , cohort , myeloid leukemia , hematology , cancer , myeloid , leukemia , myelodysplastic syndromes , malignancy , oncology , immunology , gastroenterology , bone marrow
Background: Chronic myelomonocytic leukemia (CMML) is a clonal myeloid malignancy with a variable clinical course and 15‐30% risk of progression to acute myeloid leukemia. Prognosis can vary according to various pretreatment patients’ factors. Scoring systems have been developed based on clinical and cytogenetic parameters 1 . Among patient related factors, host inflammatory anti‐neoplastic factors, e.g. neutrophils, monocytes, platelets, can contribute significantly to disease progression by promoting cancer cell proliferation, evasion of immune‐surveillance, etc., thus playing key roles in patients’ survival. Aims: The aim of the study was to evaluate the clinical and laboratory features at the initial diagnosis and their impact on the survival outcome of the investigated cohort. Methods We retrospectively collected clinical and hematologic data for 75 consecutive patients with CMML diagnosed at the National Hematology Hospital, Sofia in the period 2013‐2018. The diagnosis was defined according to WHO 2016 revised criteria. Demographic, clinical and laboratory data were recorded at the initial presentation. Overall survival (OS) was calculated as the time from diagnosis until death from any cause or last contact. Results: The patients’ cohort comprised of 49 males (65%) and 26 females (35%) at a mean age of 68,6 (ranging 26‐90). According to the FAB criteria the CMML cases with myelodysplastic features (WBC < 13 G/l) were 28% (n = 21) vs CMML with myeloproliferative characteristics (WBC > 13 G/l) 72% (n = 54). Progression to acute myeloid leukemia occurred in 9% of the cases for a 5‐year period of time and was significantly correlated with absolute neutrophil counts (ANC) (33% in pts with ANC < 1,8 × 10 9 /l vs 67% in pts with ANC ≥1,8 × 10 9 /l; log rank p = 0,05), female gender (29% male vs 71% female pts; log rank p = 0,04) and splenomegaly (p = 0,03). No relevant differences were found in regard to hemoglobin levels, blast cell percentage, degree of myelofibrosis, number of dysplastic lineages, lactate dehydrogenase level or the therapeutic approach. We detected JAK2 V617F activated mutation in five (9,6%) of CMML patients, all younger than 70 years (p = 0,02), however JAK2 V617F mutational status did not correlate with clinical and laboratory parameters and also did not impact either leukemia free (LFS), nor overall survival (OS). Further analysis showed that in terms of OS the presence of constitutional symptoms, monocytes ≥3 × 10 9 /l and platelets <100 × 10 9 /l were associated with adverse survival outcome. CMML cases with absolute monocyte count <3 × 10 9 /l had longer OS (82% vs 62,5% OS in pts with ≥3 × 10 9 /l, mean 44 vs 16 months, respectively; log rank p = 0,03). Similarly, platelet count ≥100 × 10 9 /l correlated with better outcome in the overall cohort (94% vs 64% OS in pts with thrombocytopenia, mean 42 vs 29 months, respectively; log rank p = 0,02) (Figure 1). Figure 1. Overall survival curves for patients with CMML according to the platelet count and absolute monocyte count at the initial diagnosis. Summary/Conclusion: Conclusion: In addition to some well established factors, e.g. gender and splenomegaly, our study provided data that pre‐treatment levels of some systemic inflammatory markers such as neutrophils, monocytes and platelets could be used in addition to predict leukemia transformation and shorter overall survival in CMML. Further research is needed to elucidate the underlying pathophysiological background for predictability of combined inflammatory biomarkers.

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