scholarly journals Construction and Validation of a Novel Ferroptosis-Related Prognostic Model for Acute Myeloid Leukemia

2022 ◽  
Vol 12 ◽  
Author(s):  
Ying Song ◽  
Shufang Tian ◽  
Ping Zhang ◽  
Nan Zhang ◽  
Yan Shen ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Prognostic Model ◽  
Risk Groups ◽  
Low Risk ◽  
Functional Enrichment ◽  
Great Promise ◽  
Cox Regression Analysis ◽  
Blood Disorder ◽  
Acute Myeloid

Acute myeloid leukemia (AML) is a clonal malignant proliferative blood disorder with a poor prognosis. Ferroptosis, a novel form of programmed cell death, holds great promise for oncology treatment, and has been demonstrated to interfere with the development of various diseases. A range of genes are involved in regulating ferroptosis and can serve as markers of it. Nevertheless, the prognostic significance of these genes in AML remains poorly understood. Transcriptomic and clinical data for AML patients were acquired from The Cancer Genome Atlas (TCGA) and the Gene Expression Omnibus (GEO). Univariate Cox analysis was performed to identify ferroptosis-related genes with prognostic value, and the least absolute shrinkage and selection operator (LASSO) algorithm and stepwise multivariate Cox regression analysis were utilized to optimize gene selection from the TCGA cohort (132 samples) for model construction. Tumor samples from the GEO database (136 samples and 104 samples) were used as validation groups to estimate the predictive performance of the risk model. Finally, an eight-gene prognostic signature (including CHAC1, CISD1, DPP4, GPX4, AIFM2, SQLE, PGD, and ACSF2) was identified for the prediction of survival probability and was used to stratify AML patients into high- and low-risk groups. Survival analysis illustrated significantly prolonged overall survival and lower mortality in the low-risk group. The area under the receiver operating characteristic curve demonstrated good results for the training set (1-year: 0.846, 2-years: 0.826, and 3-years: 0.837), which verified the accuracy of the model for predicting patient survival. Independent prognostic analysis indicated that the model could be used as a prognostic factor (p ≤ 0.001). Functional enrichment analyses revealed underlying mechanisms and notable differences in the immune status of the two risk groups. In brief, we conducted and validated a novel ferroptosis-related prognostic model for outcome prediction and risk stratification in AML, with great potential to guide individualized treatment strategies in the future.

scholarly journals Construction of a novel ferroptosis-related gene signature for predicting prognosis and immune microenvironment in acute myeloid leukemia

2021 ◽  
Author(s):  
Xianbo Huang ◽  
De Zhou ◽  
Xiujin Ye ◽  
Jie Jin
Keyword(s):  
Overall Survival ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Risk Model ◽  
Cox Regression ◽  
Prognostic Significance ◽  
Risk Groups ◽  
Low Risk ◽  
Cox Regression Analysis ◽  
Acute Myeloid

Acute myeloid leukemia (AML) is a highly heterogeneous hematopoietic malignancy that strongly correlates with poor clinical outcomes. Ferroptosis is an iron-dependent, non-apoptotic form of regulated cell death which plays an important role in various human cancers. Nevertheless, the prognostic significance and functions of ferroptosis-related genes (FRGs) in AML have not received sufficient attention. The aim of this article was to evaluate the association between FRGs levels and AML prognosis using publicly available RNA-sequencing datasets. The univariate Cox regression analysis identified 20 FRGs that correlate with patient overall survival. The LASSO Cox regression model was used to construct a prognostic 12-gene risk model using a TCGA cohort, and internal and external validation proved the signature efficient. The 12-FRGs signature was then used to assign patients into high- and low-risk groups, with the former exhibiting markedly reduced overall survival, compared to the low-risk group. ROC curve analysis verified the predictive ability of the risk model. Functional analysis showed that immune status and drug sensitivity differed between the 2 risk groups. In summary, FRGs is a promising candidate biomarker and therapeutic target for AML.

scholarly journals Loss of H3K27 Methylation Identifies Poor Outcome in Adult-Onset Acute Myeloid Leukemia

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 24-24
Author(s):  
Anneke D. van Dijk ◽  
Fieke W Hoff ◽  
Yihua Qiu ◽  
Eveline S. de Bont ◽  
Sophia W.M. Bruggeman ◽  
...  
Keyword(s):  
Dna Methylation ◽  
Overall Survival ◽  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Molecular Genetic ◽  
Functional Enrichment ◽  
Prognostic Impact ◽  
Cox Regression Analysis ◽  
H3k27 Methylation ◽  
Acute Myeloid

Background: Acute myeloid leukemia (AML) is an epigenetically heterogeneous disease. The intensity of treatment is currently guided by cytogenetic and molecular genetic risk classifications; however these incompletely predict outcomes, requiring additional information for more accurate predictions. We aimed to identify potential prognostic implications of epigenetic modification of histone proteins, with a focus of H3K27 methylation in relation to mutations in chromatin, splicing and transcriptional regulators. Material and methods: Histone methylation mark expressions were evaluated in a cohort of 241 AML bone marrow (BM) and peripheral blood (PB) samples from patients admitted at the MD Anderson Cancer Center relative to their expression in CD34+ BM derived samples from healthy donors. Simultaneous analysis of 230 proteins was performed using the reverse phase protein array - a high-throughput, quantitative proteomic platform that enables identification of aberrant expressed proteins and the pathways they act in. Additional mutational analysis was performed on 65 BM samples. Results:H3K27Me3 was significantly lower in both BM and PB leukemic-derived samples compared to their expression in normal BM (figure 1A). A greater loss of H3K27Me3 associated with increased proliferative potential and shorter overall survival (OS) in the whole patient population (n=241, HR=0.64, 95% CI=0.47-0.87, p<0.01), as well as in subsets, e.g. cytogenetically normal AML (n=110, HR=0.62, 95% CI=0.40-0.97, p=0.03). To study the prognostic impact of H3K27Me3 in the context of cytogenetic aberrations and mutations, multivariate cox regression analysis was performed which identified H3K27Me3 level as an independent favorable prognostic factor in all (HR=0.74, 95%CI=0.57-0.95, p=0.02) as well as in P53 mutated AML (n=54, HR=0.48, 95%CI=0.26-0.87, p=0.02). A total of 78 AML patients had molecular data available for the major methylation affecting genes, i.e. IDH1, IDH2, DNMT3A and TET2. The level of H3K27Me3 was not prognostic in patients without any DNA methylation affecting mutation present, but patients with at least one mutation in any of these had better outcome when H3K27Me3 levels were high (highest tertile, figure 1A) compared to those with lower levels (median OS 7.1 vs. 24.1 months, HR=0.42, 95% CI=0.21-0.83, p=0.01, figure 1B). Mutations in U2AF1 and SRSF2 affect the spliceosome and are frequently found in antecedent hematological disorders (AHD), as well as are mutations in chromatin regulating genes ASXL1 and BCOR. We observed significant decreased H3K27Me3 in patients with these mutations corresponding with observed lower levels of H3K27Me3 in patients with AHD than those without (p=0.035). BCOR, SRSF2, U2AF1 and ASXL1 mutations confer poor prognosis in myeloid malignancies, however, in our cohort of 65 sequenced AML patients; not individual or a combination of these mutations were independent prognostic factors, but the degree of H3K27Me3 in these patients (HR= 0.49, 95% CI=0.25-0.95, p=0.03). To recognize dysregulated pathways in AML patients with the identified loss of H3K27Me3, we examined correlations of H3K27Me3 with the other 229 proteins on the array. H3K27Me3 is catalyzed by the polycomb group protein EZH2 and is linked to transcriptional repression via the formation of heterochromatin regions. To identify upregulated proteins and pathways upon the loss of H3K27Me3, we focused on significant negatively correlated proteins with H3K27Me3 leading us to the identification of 20 total and 6 phospho-proteins that showed increased expression upon decreased H3K27Me3. Functional enrichment analysis of this protein set revealed an upregulated anti-apoptotic phenotype. Conclusion:This study shows that proteomic profiling of epigenetic modifications on the histone level have clinical implications in AML and support the idea that epigenetic patterns contribute to a more accurate picture of the leukemic state complementing cytogenetic and molecular genetic subgrouping. Figure 1. A) Lower H3K27Me3 in BM and PB derived AML samples compared to normal CD34+. **** represents p<0.0001, ns = not significant. B) Overall survival probability in AML patients with any DNA methylation affecting mutation (i.e. IDH1/2, DNMT3A, TET2, n=53) according to H3K27Me3 low (blue) and high (orange) status. Figure 1 Disclosures No relevant conflicts of interest to declare.

Impact of allogeneic hematopoietic stem cell transplantation on pediatric acute myeloid leukemia of FAB subtypes M4 and M5

2020 ◽  
Author(s):  
Yu-juan Xue ◽  
Pan Suo ◽  
Yi-fei Cheng ◽  
Ai-dong Lu ◽  
Yu Wang ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Stem Cell ◽  
High Risk ◽  
Myeloid Leukemia ◽  
Risk Groups ◽  
Low Risk ◽  
Intermediate Risk ◽  
Hematopoietic Stem ◽  
Pediatric Acute Myeloid Leukemia ◽  
Acute Myeloid

Abstract Background: FAB-M4 and M5 are unique subgroups of pediatric acute myeloid leukemia. However, for these patients, few studies have demonstrated the clinical and biological characteristics and efficacy of hematopoietic stem cell transplantation (HSCT), and especially haplo-HSCT. Procedure: We retrospectively evaluated the outcomes of 70 children with FAB-M4/M5 enrolled in our center from January 2013 to December 2017. Results: Of the patients, 32, 23, and 15 were in low-risk, intermediate-risk, and high-risk groups, respectively. T(16;16), inv16/CBFB-MYH11 was the most frequent cytogenetic abnormality. Among detected genetic alterations, WT1 was mutated at the highest frequency, followed by FLT3-ITD, NPM1, and CEBPA. Thirty-three patients received HSCT (haplo-HSCT = 30), of which four, 18, and 11 were in low-risk, intermediate-risk, and high-risk groups, respectively. For all patients, the 3-year overall survival (OS), event-free survival (EFS), and cumulative incidence of relapse (CIR) were 85.3 ± 4.3%, 69.0 ± 5.7%, and 27.9 ± 5.2%, respectively. By multivariate analysis, low-risk stratification predicted superior OS, EFS, and PLT ≤ 50 × 109/L at diagnosis, with FLT3-ITD mutations predicting higher CIR and poorer EFS. In intermediate- and high-risk groups, HSCT was independently associated with higher EFS and lower CIR. With a median post-transplant observation time of 30.0 months, the 3-year OS, EFS, CIR, and non-relapse mortality in the haplo-HSCT group were 74.2 ± 8.6%, 68.3 ± 8.9, 24.6 ± 7.6%, and 6.6 ± 4.1%, respectively. Conclusions: Risk-oriented treatment is important for pediatric FAB-M4/M5. For intermediate- and high-risk groups, HSCT significantly improved survival and haplo-HSCT might be a viable alternative approach.

scholarly journals Identification of m6A-Related lncRNAs Associated With Prognoses and Immune Responses in Acute Myeloid Leukemia

2021 ◽  
Vol 9 ◽  
Author(s):  
Ding Li ◽  
Jiaming Liang ◽  
Cheng Cheng ◽  
Wenbin Guo ◽  
Shuolei Li ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Cox Regression ◽  
Pearson Correlation ◽  
The Cancer Genome Atlas ◽  
Functional Enrichment ◽  
Risk Scores ◽  
Hematopoietic Malignancy ◽  
Cox Regression Analysis ◽  
Acute Myeloid

Background: Acute myeloid leukemia (AML) remains the most common type of hematopoietic malignancy in adults and has an unfavorable outcome. Herein, we aimed to construct an N6-methylandenosine (m6A)-related long noncoding RNAs (lncRNAs) signature to accurately predict the prognosis of patients with AML using the data downloaded from The Cancer Genome Atlas (TCGA) database.Methods: The RNA-seq and clinical data were obtained from the TCGA AML cohort. First, Pearson correlation analysis was performed to identify the m6A-related lncRNAs. Next, univariate Cox regression analysis was used to determine the candidate lncRNAs with prognostic value. Then, feature selection was carried out by Least absolute shrinkage and selection operator (LASSO) analysis, and seven eligible m6A-related lncRNAs were included to construct the prognostic risk signature. Kaplan–Meier and receiver operating characteristic (ROC) curve analyses were performed to evaluate the predictive capacity of the risk signature both in the training and testing datasets. A nomogram was used to predict 1-year, 2-year, and 3-year overall survival (OS) of AML patients. Next, the expression levels of lncRNAs in the signature were validated in AML samples by qRT-PCR. Functional enrichment analyses were carried out to identify probable biological processes and cellular pathways. The ceRNA network was developed to explore the downstream targets and mechanisms of m6A-related lncRNAs in AML.Results: Seven m6A-related lncRNAs were identified as a prognostic signature. The low-risk group hold significantly prolonged OS. The nomogram showed excellent accuracy of the signature for predicting 1-year, 2-year and 3-year OS (AUC = 0.769, 0.820, and 0.800, respectively). Moreover, the risk scores were significantly correlated with enrichment in cancer hallmark- and malignancy-related pathways and immunotherapy response in AML patients.Conclusion: We developed and validated a novel risk signature with m6A-related lncRNAs which could predict prognosis accurately and reflect the immunotherapy response in AML patients.

scholarly journals A Simple-to-Use Nomogram for Predicting Survival in Children with Acute Myeloid Leukemia

2021 ◽  
Vol 2021 ◽  
pp. 1-8
Author(s):  
Feng Jiang ◽  
Xiang Yu ◽  
Chuyan Wu ◽  
Ming Wang ◽  
Ke Wei ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Prognostic Model ◽  
Cox Regression ◽  
Chromosomal Abnormalities ◽  
Web Based ◽  
Cox Regression Analysis ◽  
Predictive Variables ◽  
Target Database ◽  
Acute Myeloid

Background. The research analyzed a group of patients to develop a statistical nomogram and a web-based survival rate predictor for the comprehensive estimate of the overall survival (OS) of children with acute myeloid leukemia. Methods. Between 1999 to 2015, we used the Therapeutically Applicable Research to Generate Effective Treatments (TARGET) database to evaluate and randomly divide 440 children diagnosed with AML into the population of training ( n = 309 ) and validation ( n = 131 ). The analysis of Lasso Cox was used to identify separate predictive variables. We have used essential forecasting considerations to construct a nomogram and a web-based calculator focused on Cox regression analysis. Nomogram validation was tested through discrimination and calibration. Results. Compared to the multivariate training cohort models, a nomogram integrating gender, age of diagnose, WBC at diagnosis, bone marrow leukemic blast percentage, and chromosomal abnormalities [ t (8; 21), inv(16)] were designed for the prediction of OS. We also developed a predictive survival nomogram and a web-based calculator. C-indexes validated internally and checked externally were 0.747 and 0.716. The calibration curves have shown that the nomogram might accurately forecast 3-year and 5-year OS. Conclusions. A nomogram effectively predicts survival in children with AML. This prognostic model can be used in clinical practice.

scholarly journals Mutant DNMT3A: a marker of poor prognosis in acute myeloid leukemia

Blood ◽  
2012 ◽  
Vol 119 (24) ◽  
pp. 5824-5831 ◽  
Author(s):  
Ana Flávia Tibúrcio Ribeiro ◽  
Marta Pratcorona ◽  
Claudia Erpelinck-Verschueren ◽  
Veronika Rockova ◽  
Mathijs Sanders ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Myeloid Leukemia ◽  
Cox Regression ◽  
Multivariable Analysis ◽  
Gene Expression Signature ◽  
Mutation Status ◽  
Cox Regression Analysis ◽  
Prognostic Effect ◽  
Or Gene ◽  
Acute Myeloid

Abstract The prevalence, the prognostic effect, and interaction with other molecular markers of DNMT3A mutations was studied in 415 patients with acute myeloid leukemia (AML) younger than 60 years. We show mutations in DNMT3A in 96 of 415 patients with newly diagnosed AML (23.1%). Univariate Cox regression analysis showed that patients with DNMT3Amutant AML show significantly worse overall survival (OS; P = .022; hazard ratio [HR], 1.38; 95% confidence interval [CI], 1.04-1.81), and relapse-free survival (RFS; P = .005; HR, 1.52; 95% CI, 1.13-2.05) than DNMT3Awild-type AMLs. In a multivariable analysis, DNMT3A mutations express independent unfavorable prognostic value for OS (P = .003; HR, 1.82; 95% CI, 1.2-2.7) and RFS (P < .001; HR, 2.2; 95% CI, 1.4-3.3). In a composite genotypic subset of cytogenetic intermediate-risk AML without FLT3-ITD and NPM1 mutations, this association is particularly evident (OS: P = .013; HR, 2.09; 95% CI, 1.16-3.77; RFS: P = .001; HR, 2.65; 95% CI, 1.48-4.89). The effect of DNMT3A mutations in human AML remains elusive, because DNMT3Amutant AMLs did not express a methylation or gene expression signature that discriminates them from patients with DNMT3Awild-type AML. We conclude that DNMT3A mutation status is an important factor to consider for risk stratification of patients with AML.

scholarly journals Prospective Identification of Acute Myeloid Leukemia Patients Who Benefit from Gene-Expression Based Risk Stratification

Blood ◽  
2019 ◽  
Vol 134 (Supplement_1) ◽  
pp. 1397-1397
Author(s):  
Diego Chacon ◽  
Ali Braytee ◽  
Yizhou Huang ◽  
Julie Thoms ◽  
Shruthi Subramanian ◽  
...  
Keyword(s):  
Gene Expression ◽  
Acute Myeloid Leukemia ◽  
Risk Stratification ◽  
Genetic Risk ◽  
Myeloid Leukemia ◽  
Research Funding ◽  
Risk Groups ◽  
High Fidelity ◽  
Improve Outcome ◽  
Acute Myeloid

Background: Acute myeloid leukemia (AML) is a highly heterogeneous malignancy and risk stratification based on genetic and clinical variables is standard practice. However, current models incorporating these factors accurately predict clinical outcomes for only 64-80% of patients and fail to provide clear treatment guidelines for patients with intermediate genetic risk. A plethora of prognostic gene expression signatures (PGES) have been proposed to improve outcome predictions but none of these have entered routine clinical practice and their role remains uncertain. Methods: To clarify clinical utility, we performed a systematic evaluation of eight highly-cited PGES i.e. Marcucci-7, Ng-17, Li-24, Herold-29, Eppert-LSCR-48, Metzeler-86, Eppert-HSCR-105, and Bullinger-133. We investigated their constituent genes, methodological frameworks and prognostic performance in four cohorts of non-FAB M3 AML patients (n= 1175). All patients received intensive anthracycline and cytarabine based chemotherapy and were part of studies conducted in the United States of America (TCGA), the Netherlands (HOVON) and Germany (AMLCG). Results: There was a minimal overlap of individual genes and component pathways between different PGES and their performance was inconsistent when applied across different patient cohorts. Concerningly, different PGES often assigned the same patient into opposing adverse- or favorable- risk groups (Figure 1A: Rand index analysis; RI=1 if all patients were assigned to equal risk groups and RI =0 if all patients were assigned to different risk groups). Differences in the underlying methodological framework of different PGES and the molecular heterogeneity between AMLs contributed to these low-fidelity risk assignments. However, all PGES consistently assigned a significant subset of patients into the same adverse- or favorable-risk groups (40%-70%; Figure 1B: Principal component analysis of the gene components from the eight tested PGES). These patients shared intrinsic and measurable transcriptome characteristics (Figure 1C: Hierarchical cluster analysis of the differentially expressed genes) and could be prospectively identified using a high-fidelity prediction algorithm (FPA). In the training set (i.e. from the HOVON), the FPA achieved an accuracy of ~80% (10-fold cross-validation) and an AUC of 0.79 (receiver-operating characteristics). High-fidelity patients were dichotomized into adverse- or favorable- risk groups with significant differences in overall survival (OS) by all eight PGES (Figure 1D) and low-fidelity patients by two of the eight PGES (Figure 1E). In the three independent test sets (i.e. form the TCGA and AMLCG), patients with predicted high-fidelity were consistently dichotomized into the same adverse- or favorable- risk groups with significant differences in OS by all eight PGES. However, in-line with our previous analysis, patients with predicted low-fidelity were dichotomized into opposing adverse- or favorable- risk groups by the eight tested PGES. Conclusion: With appropriate patient selection, existing PGES improve outcome predictions and could guide treatment recommendations for patients without accurate genetic risk predictions (~18-25%) and for those with intermediate genetic risk (~32-35%). Figure 1 Disclosures Hiddemann: Celgene: Consultancy, Honoraria; Roche: Consultancy, Honoraria, Research Funding; Bayer: Research Funding; Vector Therapeutics: Consultancy, Honoraria; Gilead: Consultancy, Honoraria; Janssen: Consultancy, Honoraria, Research Funding. Metzeler:Celgene: Honoraria, Research Funding; Otsuka: Honoraria; Daiichi Sankyo: Honoraria. Pimanda:Celgene: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding. Beck:Gilead: Research Funding.

scholarly journals Survival and Prognostic Factors in Adults Acute Myeloid Leukemia: A Retrospective Analysis of 119 Cases

2013 ◽  
Vol 1 (2) ◽  
pp. 70-73
Author(s):  
Alina M Gridjac ◽  
Cristian Daniel Pirlog ◽  
Anca Simona Bojan
Keyword(s):  
Acute Myeloid Leukemia ◽  
Prognostic Factors ◽  
Myeloid Leukemia ◽  
De Novo ◽  
Risk Groups ◽  
Developed Countries ◽  
Risk Level ◽  
Secondary Aml ◽  
Cytogenetic Testing ◽  
Acute Myeloid

Background: Acute myeloid leukemia (AML) is a malignant disease with significant identified prognostic factors. Therefore our aim was to develop an Assessment Scheme of Prognosis in AML based on prognostic factors. In some counties, such as Romania or other less-highly developed countries, this scheme would be beneficial particularly when cytogenetic testing is unavailable or time-intensive. Methods: We analyzed 119 adult patients with AML during a five year-period from a single-center in Romania. We retrospectively collected and analyzed data with Epi Info and Excel using patient medical records. Results: According to age, the group A1 (<60 years) had a 40 months survival, in contrast with the group B1 (≥60 years) with a survival of 19 months (p=0,0063). The group A2 (secondary AML) survived 15 months, whereas the group B2 (AML de novo) survived 40 months (p=0.0021). Additionally, the group A3 (mild comorbidities) achieved a 40 months survival, the group B3 (moderate comorbidities) survived 19 months, whereas the group C3 (severe comorbidities) survived 7 months (p=0,0059). According to WBC and blast number, the group A4 (high levels) had a 25 months survival, whereas the group B4 (low levels) survived 40 months (p=0,0057). Conclusion: The prognostic factors studied are useful to identify the risk level of AML disease for each patient at diagnosis. We developed an assessment scheme of prognosis with three risk groups according to age, secondary AML, comorbidity, WBC and blasts and cytogenetic examination.

scholarly journals Pretreatment platelet count predicts survival outcome of patients with de novo non-M3 acute myeloid leukemia

PeerJ ◽  
2017 ◽  
Vol 5 ◽  
pp. e4139 ◽  
Author(s):  
Qianying Zhang ◽  
Kanchun Dai ◽  
Laixi Bi ◽  
Songfu Jiang ◽  
Yixiang Han ◽  
...  
Keyword(s):  
Acute Myeloid Leukemia ◽  
Platelet Count ◽  
Predictive Value ◽  
Myeloid Leukemia ◽  
De Novo ◽  
Univariate Analysis ◽  
Survival Outcome ◽  
Cox Regression Analysis ◽  
High Platelet Count ◽  
Acute Myeloid

Background Pretreatment platelet count has been reported as a potential tool to predict survival outcome in several solid tumors. However, the predictive value of pretreatment platelet count remains obscure in de novo acute myeloid leukemia (AML) excluding acute promyelocytic leukemia (M3). Methods We conducted a retrospective review of 209 patients with de novo non-M3 AML in our institute over a period of 8 years (2007–2015). Receiver operating characteristic (ROC) curve analysis was used to determine the optimal platelet (PLT) cutoff in patients. We analyzed the overall survival (OS) and disease free survival (DFS) using the log-rank test and Cox regression analysis. Results By defining the platelet count 50 × 109/L and 120 × 109/L as two cut-off points, we categorized the patients into three groups: low (<50 × 109/L), medium (50–120 × 109/L) and high (>120 × 109/L). On univariate analysis, patients with medium platelet count had longer OS and DFS than those with low or high platelet count. However, the multivariate analysis showed that only longer DFS was observed in patients with medium platelet count than those with low or high platelet count. Conclusion Our findings indicate that pretreatment platelet count has a predictive value for the prognosis of patients with non-M3 AML.

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