Prognostic evaluation of ELN-2022 and ELN-2024 risk stratification in newly diagnosed AML patients and development of a novel genetic risk model

Abstract Background: The pathogenesis of acute myeloid leukemia (AML) is complex, with cytogenetic and molecular abnormalities currently regarded as the most critical prognostic factors. The European LeukemiaNet (ELN) guidelines established the ELN-2022 genetic risk stratification based on data from patients receiving intensive chemotherapy, and later proposed the ELN-2024 risk stratification for patients undergoing low-intensity therapy. However, large-scale real-world data are needed for validation. Additionally, certain genetic abnormalities that may influence AML prognosis require further investigation. Objective: To evaluate the prognostic value of ELN-2022 and ELN-2024 risk stratification in newly diagnosed AML patients and to develop an improved risk model incorporating genetic features. Methods: A retrospective analysis was conducted on 428 adult patients with newly diagnosed AML from Qilu Hospital of Shandong University. Patients were divided into two groups based on treatment: intensive chemotherapy (n=258) and venetoclax combined with azacitidine (VA, n=170). The primary endpoints were overall survival (OS) and progression-free survival (PFS). Kaplan-Meier analysis was used to estimate survival rates, and the log-rank test was employed to compare differences between groups. Logistic regression analyzed factors influencing treatment efficacy, while the Cox proportional hazards model identified variables significantly associated with survival. A novel genetic risk model was constructed based on key genetic variants, and its predictive performance was evaluated using time-dependent receiver operating characteristic curves (td-ROC) with the area under the curve (AUC). Results: The median age of the entire cohort was 53.0 years (range: 40.0–61.0 years). High-frequency mutated genes included FLT3 (31.8%), DNMT3A (25.2%), NRAS (25.0%), and NPM1 (23.4%). The ELN-2022 risk stratification significantly distinguished OS and PFS among favorable-, intermediate-, and adverse-risk patients in the intensive chemotherapy group (p=0.004) but showed no statistical significance in the VA group. Multivariate analysis identified CEBPA bZIP, DNMT3A, GATA2, IDH2, KIT, NPM1, TP53, U2AF1, and STAG2 as independent prognostic factors. A novel genetic risk scoring model was developed: ELN-2022 favorable/intermediate/adverse-risk groups were assigned 2/5/7 points, respectively, with 1 point added for each risk factor (DNMT3A, GATA2, KIT, TP53, U2AF1, STAG2) and 1 point subtracted for each protective factor (CEBPA bZIP, IDH2, NPM1). Patients were categorized into favorable-risk (≤3 points), intermediate-risk (4–6 points), and adverse-risk (≥7 points) groups. The new model significantly differentiated OS (p=0.003) and PFS (p=0.014) among risk groups in the intensive chemotherapy group. Combined with ELN-2024 stratification, the VA group still showed no significant differences in OS (p=0.051) or PFS (p=0.154). ROC curve analysis demonstrated superior discriminatory ability for the new model (AUC: 0.620) compared to ELN-2022 (0.606) and ELN-2024 (0.531). Conclusion: The genetic background of AML influences prognosis under different treatment regimens. ELN-2022 is only applicable for risk stratification in the intensive chemotherapy group, with no significant discriminatory power in the VA group or for ELN-2024. The novel genetic risk model integrating nine key gene mutations demonstrated improved prognostic discrimination in both intensive chemotherapy and VA treatment groups, offering a potential foundation for precise AML risk stratification and therapeutic decision-making. Ethics statement: This study was approved, and the written informed consent was waived by The Medical Ethics Committee of Qilu Hospital of Shandong University (KYLL-202502-055) due to the retrospective nature of the review, and confirmed that the data was anonymized and maintained with confidentiality. The study was conducted in accordance with the Declaration of Helsinki.

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Journal
Blood
Published
2025-11-03
DOI
https://doi.org/10.1182/blood-2025-5269
Primary Topic
Acute Myeloid Leukemia Research
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article
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article

Prognostic evaluation of ELN-2022 and ELN-2024 risk stratification in newly diagnosed AML patients and development of a novel genetic risk model

Minran Zhou, Qing H. Meng, Qingli Ji, Guangyue Yao et al.
Blood
Acute Myeloid Leukemia Research
article

Prognostic evaluation of ELN-2022 and ELN-2024 risk stratification in newly diagnosed AML patients and development of a novel genetic risk model

Minran Zhou, Qing H. Meng, Qingli Ji, Guangyue Yao, Xinwen Jiang, Sai Ma, Xinrui Zhang, Xiaohan Liu, Zhenyi Liu, Chunyan Chen, Yueyue Zheng, Dongmei Hu
article en

Abstract

Abstract Background: The pathogenesis of acute myeloid leukemia (AML) is complex, with cytogenetic and molecular abnormalities currently regarded as the most critical prognostic factors. The European LeukemiaNet (ELN) guidelines established the ELN-2022 genetic risk stratification based on data from patients receiving intensive chemotherapy, and later proposed the ELN-2024 risk stratification for patients undergoing low-intensity therapy. However, large-scale real-world data are needed for validation. Additionally, certain genetic abnormalities that may influence AML prognosis require further investigation. Objective: To evaluate the prognostic value of ELN-2022 and ELN-2024 risk stratification in newly diagnosed AML patients and to develop an improved risk model incorporating genetic features. Methods: A retrospective analysis was conducted on 428 adult patients with newly diagnosed AML from Qilu Hospital of Shandong University. Patients were divided into two groups based on treatment: intensive chemotherapy (n=258) and venetoclax combined with azacitidine (VA, n=170). The primary endpoints were overall survival (OS) and progression-free survival (PFS). Kaplan-Meier analysis was used to estimate survival rates, and the log-rank test was employed to compare differences between groups. Logistic regression analyzed factors influencing treatment efficacy, while the Cox proportional hazards model identified variables significantly associated with survival. A novel genetic risk model was constructed based on key genetic variants, and its predictive performance was evaluated using time-dependent receiver operating characteristic curves (td-ROC) with the area under the curve (AUC). Results: The median age of the entire cohort was 53.0 years (range: 40.0–61.0 years). High-frequency mutated genes included FLT3 (31.8%), DNMT3A (25.2%), NRAS (25.0%), and NPM1 (23.4%). The ELN-2022 risk stratification significantly distinguished OS and PFS among favorable-, intermediate-, and adverse-risk patients in the intensive chemotherapy group (p=0.004) but showed no statistical significance in the VA group. Multivariate analysis identified CEBPA bZIP, DNMT3A, GATA2, IDH2, KIT, NPM1, TP53, U2AF1, and STAG2 as independent prognostic factors. A novel genetic risk scoring model was developed: ELN-2022 favorable/intermediate/adverse-risk groups were assigned 2/5/7 points, respectively, with 1 point added for each risk factor (DNMT3A, GATA2, KIT, TP53, U2AF1, STAG2) and 1 point subtracted for each protective factor (CEBPA bZIP, IDH2, NPM1). Patients were categorized into favorable-risk (≤3 points), intermediate-risk (4–6 points), and adverse-risk (≥7 points) groups. The new model significantly differentiated OS (p=0.003) and PFS (p=0.014) among risk groups in the intensive chemotherapy group. Combined with ELN-2024 stratification, the VA group still showed no significant differences in OS (p=0.051) or PFS (p=0.154). ROC curve analysis demonstrated superior discriminatory ability for the new model (AUC: 0.620) compared to ELN-2022 (0.606) and ELN-2024 (0.531). Conclusion: The genetic background of AML influences prognosis under different treatment regimens. ELN-2022 is only applicable for risk stratification in the intensive chemotherapy group, with no significant discriminatory power in the VA group or for ELN-2024. The novel genetic risk model integrating nine key gene mutations demonstrated improved prognostic discrimination in both intensive chemotherapy and VA treatment groups, offering a potential foundation for precise AML risk stratification and therapeutic decision-making. Ethics statement: This study was approved, and the written informed consent was waived by The Medical Ethics Committee of Qilu Hospital of Shandong University (KYLL-202502-055) due to the retrospective nature of the review, and confirmed that the data was anonymized and maintained with confidentiality. The study was conducted in accordance with the Declaration of Helsinki.

BloodVol. 146(Supplement 1)
Qilu Hospital of Shandong University (CN)
Openalex Percentile: Top 49%
Acute Myeloid Leukemia Research
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