September 5, 2025Scientific ReportsOpen Access

Construction of a prognostic risk model for acute myeloid leukemia based on exosomal genes and analysis of immune microenvironment characteristics

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Observational analysis identifies exosome-related biomarkers, predicting survival in AML patients, highlighting immune microenvironment implications.

The prognostic risk model achieved superior predictive accuracy compared to traditional clinical parameters.
Survival predictions for 1-, 2-, and 3-year metrics had area under the curve (AUC) values of 0.819, 0.825, and 0.832.
Immune microenvironment characterization revealed increased regulatory T cell infiltration in high-risk acute myeloid leukemia patients.
Functional enrichment analysis highlighted significant pathways tied to risk stratification and chemotherapy resistance.

Wang et al. (2025) studied this question.

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September 5, 2025Scientific ReportsOpen Access

View Full Paper

Ask AI

Bookmark

Authors

Observational analysis identifies exosome-related biomarkers, predicting survival in AML patients, highlighting immune microenvironment implications.

The prognostic risk model achieved superior predictive accuracy compared to traditional clinical parameters.
Survival predictions for 1-, 2-, and 3-year metrics had area under the curve (AUC) values of 0.819, 0.825, and 0.832.
Immune microenvironment characterization revealed increased regulatory T cell infiltration in high-risk acute myeloid leukemia patients.
Functional enrichment analysis highlighted significant pathways tied to risk stratification and chemotherapy resistance.

Wang et al. (2025) studied this question.

View Full Paper

Ask AI

Bookmark