ArticleClinical and experimental medicine2025
Prognostic implications of CD15 antigen expression in patients with acute myeloid leukemia.
Article in Clinical and experimental medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
The prognostic significance of CD15 antigen in acute myeloid leukemia has been evaluated with conflicting results in various studies. However, existing results are limited and further investigation into additional prognostic parameters is necessary. This study aimed to evaluate the impact of CD15 antigen on survival prognosis in patients with de novo AML (dn-AML). We analyzed CD15 antigen expression on diagnostic samples from 676 patients with dn-AML by flow cytometry. Utilizing a 20% positivity threshold, the cohort was stratified into CD15 positivity (56.07%) and CD15 negativity (43.93%) groups. The CD15 negativity group demonstrated a lower complete remission rate (P = 0.006), a higher relapse rate (P = 0.002) and increased mortality (P<0.001) compared to the CD15 positivity group. According to the log-rank test, the CD15 negativity group exhibited significantly shorter overall survival (OS) (P<0.001) and disease-free survival (DFS) (P<0.001). Multivariate analysis identified CD15-positivity, TP53 mutation, European Leukemia Net (ELN) risk category, bone marrow transplant status, white blood cell counts and hemoglobin levels as independent prognostic factors associated with OS. A visualized nomogram was developed to predict OS and demonstrating notable performance with a C-index of 0.778. Compared to the ELN risk model, calibration plots and decision curve analyses indicated superior discrimination, calibration and net benefits. The time-dependent receiver operating characteristic (ROC) curves for 1-, 2-, and 3-year survival also performed robustly (AUC = 0.256, 0.154, and 0.126 respectively). Our study provides a comprehensive perspective on the role of CD15 antigen as an independent prognostic marker in dn-AML patients. To some extent, this prognostic model leverages readily available clinical data to enhance predictive accuracy, identify potential risks and support AML therapeutic decision-making.
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