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Meta-Analysis
. 2013 Mar 20;31(9):1172-81.
doi: 10.1200/JCO.2012.44.3184. Epub 2013 Feb 4.

Identification of a 24-gene prognostic signature that improves the European LeukemiaNet risk classification of acute myeloid leukemia: an international collaborative study

Affiliations
Meta-Analysis

Identification of a 24-gene prognostic signature that improves the European LeukemiaNet risk classification of acute myeloid leukemia: an international collaborative study

Zejuan Li et al. J Clin Oncol. .

Abstract

Purpose: To identify a robust prognostic gene expression signature as an independent predictor of survival of patients with acute myeloid leukemia (AML) and use it to improve established risk classification.

Patients and methods: Four independent sets totaling 499 patients with AML carrying various cytogenetic and molecular abnormalities were used as training sets. Two independent patient sets composed of 825 patients were used as validation sets. Notably, patients from different sets were treated with different protocols, and their gene expression profiles were derived using different microarray platforms. Cox regression and Kaplan-Meier methods were used for survival analyses.

Results: A prognostic signature composed of 24 genes was derived from a meta-analysis of Cox regression values of each gene across the four training sets. In multivariable models, a higher sum value of the 24-gene signature was an independent predictor of shorter overall (OS) and event-free survival (EFS) in both training and validation sets (P < .01). Moreover, this signature could substantially improve the European LeukemiaNet (ELN) risk classification of AML, and patients in three new risk groups classified by the integrated risk classification showed significantly (P < .001) distinct OS and EFS.

Conclusion: Despite different treatment protocols applied to patients and use of different microarray platforms for expression profiling, a common prognostic gene signature was identified as an independent predictor of survival of patients with AML. The integrated risk classification incorporating this gene signature provides a better framework for risk stratification and outcome prediction than the ELN classification.

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Conflict of interest statement

Authors' disclosures of potential conflicts of interest and author contributions are found at the end of this article.

Figures

Fig 1.
Fig 1.
Overview of research design and work flow. (A) Identification and validation of 24-gene signature; (B) development and validation of integrated risk classification scheme. AML, acute myeloid leukemia; APL, acute promyelocytic leukemia; CALGB, Cancer and Leukemia Group B; EFS, event-free survival; ELN, European LeukemiaNet; FDR, false discovery rate; HOVON, Hemato-Oncologie voor Volwassenen Nederland; OS, overall survival.
Fig 2.
Fig 2.
Survival curves of patients with acute myeloid leukemia (AML) in the two validation sets ([A] Netherlands Set 2, n = 277; [B] Germany Set 2, n = 548) predicted by the sum-value signature of 24 genes. Patients in each set were dichotomized into two groups based on median value of the sum-value signature, and Kaplan-Meier curves were generated to depict outcomes. P values were determined by log-rank test. Plus signs indicate censored patients. Patients with AML with higher sum values experienced significantly shorter (P < .005) overall (left panels) and event-free survival (right panel) rates than those with lower sum values in (A) Netherlands Set 2 and (B) Germany Set 2.
Fig 3.
Fig 3.
Distribution and survival of patients with acute myeloid leukemia (AML) in the test set (Netherlands Set 2+, n = 480) according to or predicted by integrated risk categories. (A) Scheme of reclassification of the four European LeukemiaNet (ELN) risk groups into three new integrated risk groups by integrating the 24-gene signature classification (ie, low or high) with ELN risk classification. (B) Distribution of the whole set of patients, those age < 60 years, and those age > 60 years according to integrated risk class criteria. (C, D, E) Overall (left panels) and event-free survival (right panels) rates of (C) the whole set of patients, (D) those age < 60 years, and (E) those age > 60 years predicted by integrated risk categories.
Fig 4.
Fig 4.
Validation and further evaluation of new integrated risk classification. (A) Distribution (upper panels) and overall survival (OS; middle panels) or event-free survival (lower panels) of patients with acute myeloid leukemia in validation set (Germany Set 2′, n = 484) according to or predicted by the European LeukemiaNet (ELN; left panels) or integrated (right panels) risk categories. Additional predictive value displayed by prediction error curves for OS in (B) Netherlands Set 2+ and (C) Germany Set 2′. Lower curve (ie, lower prediction error) indicates better predictive value. Reference line indicates Kaplan-Meier estimation without additional variables; integrated risk class indicates combined prediction model based on ELN and 24-gene signature; 24 gene signature (categorial) indicates model based on 24-gene signature categorized by median (ie, as high or low); ELN indicates model based on ELN risk classification; 24-gene signature (numerical) indicates model based on numerical 24-gene signature.

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