AFFILIATIONS
1 Department of Clinical Medicine and Surgery, Hematology Unit, University of Naples Federico II, Naples, Italy., Naples, Italy
2 Department of Clinical Medicine and Surgery, Hematology Unit, University of Naples Federico II, Naples, Italy., Naples, Italy
3 Department of Clinical Medicine and Surgery, Hematology Unit, University of Naples Federico II, Naples, Italy., Naples, Italy
4 Department of Clinical Medicine and Surgery, Hematology Unit, University of Naples Federico II, Naples, Italy., Naples, Italy
5 Department of Clinical Medicine and Surgery, Hematology Unit, University of Naples Federico II, Naples, Italy., Naples, Italy
6 Department of Clinical Medicine and Surgery, Hematology Unit, University of Naples Federico II, Naples, Italy., Naples, Italy
7 CEINGE Biotecnologie Avanzate Franco Salvatore, Naples, Italy, Naples, Italy
8 CEINGE Biotecnologie Avanzate Franco Salvatore, Naples, Italy, Naples, Italy
9 CEINGE Biotecnologie Avanzate Franco Salvatore, Naples, Italy, Naples, Italy
10 CEINGE Biotecnologie Avanzate Franco Salvatore, Naples, Italy, Naples, Italy
11 Hematology Unit, AORN Cardarelli Hospital, Naples, Italy, Naples, Italy
12 Hematology Unit, AORN Cardarelli Hospital, Naples, Italy, Naples, Italy
13 Hematology Unit, Hospital Andrea Tortora, Pagani, Italy, Pagani, Italy
14 Hematology Unit, Azienda Sanitaria Locale Napoli 1 Centro, Naples, Italy, Naples, Italy
15 Department of Clinical Medicine and Surgery, Hematology Unit, University of Naples Federico II, Naples, Italy., Naples, Italy, Hematology, Hospital 'San Giuliano', Giugliano, Italy, Giugliano, Italy
16 Hematology Unit, Azienda Sanitaria Locale Napoli 1 Centro, 80147 Naples, Italy, Naples, Italy
17 Hematology Unit, Hospital Andrea Tortora, Pagani, Italy, Pagani, Italy
18 Hematology Unit, AORN Cardarelli Hospital, Naples, Italy, Naples, Italy
19 CEINGE Biotecnologie Avanzate Franco Salvatore, Naples, Italy, Naples, Italy, Department of Molecular Medicine and Medical Biotechnology, University of Naples Federico II, Naples, Italy, Naples, Italy
20 Department of Clinical Medicine and Surgery, Hematology Unit, University of Naples Federico II, Naples, Italy., Naples, Italy
ABSTRACT
INTRODUCTION
Acute myeloid leukemia (AML) prognosis is determined by genetic profile according to the ELN 2022 risk stratification. While allogeneic hematopoietic cell transplantation (allo-HCT) in first complete remission (CR) is generally recommended for patients (pts) with adverse- and intermediate-risk AML, pts with favourable-risk AML are not considered for allo-HCT in first CR unless they show inadequate clearance of MRD after initial therapy. However, approximately 5-15% of favourable-risk AML pts have primary refractory disease, and a further 25-40% eventually relapse after achieving CR. Hyperleukocytosis is traditionally considered as an adverse prognostic factor in AML; however it is not included in the ELN 2022 genetic risk stratification. Whether baseline leukocytosis provides additional prognostic information beyond ELN stratification remains unclear.
METHODS
We conducted a retrospective multicenter real-world study including pts with newly diagnosed favorable-risk de novo AML treated at four Italian hematological centers between January 2020 and December 2025 to evaluate the prognostic impact of baseline WBC count. Favourable-risk disease was defined according to the ELN 2022 risk stratification. High WBC count was defined as WBC > 50×109/L. Molecular, flow cytometry and cytogenetics analyses were centralized and performed at the CEINGE Biotecnologie Avanzate Franco Salvatore, University of Naples Federico II. Treatment choice was guided by patient fitness and local physician discretion. The primary endpoint was overall survival (OS) and progression free survival (PFS), while secondary endpoints included response rate, measurable residual disease (MRD) negativity and next-generation sequencing (NGS) mutational profile in hyperleukocytic AML. Statistical analyses were performed using R version 4.3.1.
RESULTS
We identified 102 patients, median age was 58 years (range: 21-84), 58/102 pts (57%) were female. Favourable-risk disease was defined by the presence of mutated NPM1 without FLT3-ITD in 57/102 pts (56%), inv(16)(p13.1q22) in 27/102 pts (26%), t(8;21)(q22;q22.1) in 11/102 pts (11%), and bZIP in-frame mutated CEBPA in 7/102 pts (7%).
At diagnosis, 35/102 pts (34%) had high-WBC count, and 67/102 pts (66%) had low-WBC count. 75/102 pts (74%) were treated with intensive chemotherapy, and the most common regimen was 7+3 plus gemtuzumab ozogamicin in 42/102 pts (41%). CR rates did not differ between pts with high and low-WBC count (74% vs 79%, p=0.62) and, among patients treated with intensive chemotherapy, MRD negativity rates after two courses were similar in the two groups ( 53% vs 51%, p=1). Likewise, early death rates were also comparable (26% vs 15%, p=0.2).
After a median follow-up of 32 months (95% CI, 28-39), median OS was significantly shorter in the high-WBC group (13 months vs not reached, p<0.01), and median PFS was also inferior in the high-WBC group (12 months vs 28 months, p<0.01). In univariable Cox regression analysis, increasing baseline WBC count was associated with inferior OS, with a hazard ratio (HR) of 1.12 (95% CI, 1.057–1.183; p<0.001) for every 10×10?/L increase.This association remained significant after adjustment for age, sex, and treatment intensity in multivariable Cox regression analysis (adjusted HR 1.13 per 10×10?/L increase, 95% CI, 1.07–1.19; p<0.001).
NGS analysis, performed in 96/102 pts (94%), showed that increasing baseline WBC count was significantly associated with the presence of RTK-RAS signaling mutations (NRAS, FLT3-TKD, KRAS, NF1, PTPN11, CBL) with an odds ratio of 1.12 (95% CI 1.03–1.23; p=0.015) for every 10×10?/L increase in WBC count in logistic regression analysis, thus suggesting a biological basis for the adverse prognostic impact of hyperleukocytosis.
CONCLUSIONS
Despite being classified as ELN 2022 favourable-risk, pts in our cohort presenting with high baseline WBC counts had significantly inferior OS and PFS. Baseline WBC count remained an independent predictor of outcome in multivariable analysis, suggesting that leukocyte count provides additional prognostic information beyond current ELN risk stratification. Furthermore, the association between increasing WBC counts and RTK-RAS pathway mutations suggests that hyperleukocytosis may identify a distinct biological subset of favourable-risk AML. These findings warrant prospective validation as integrating baseline WBC count with molecular profiling may further refine AML risk stratification.