Multi-Omics Prognostic Model for Chinese Acute Myeloid Leukemia Patients

Fengli Li published a dataset on figshare in 2026 containing data for a prognostic model for acute myeloid leukemia. The data likely includes clinical, genetic, cytogenetic, and immunophenotypic features from 378 Chinese AML patients. The model integrates these multi-omics factors to predict patient outcomes and guide treatment decisions.

Use Cases

• Validating the novel 2023 CN genetic risk classification for AML based on molecular and cytogenetic data.
• Training machine learning models for AML outcome prediction using integrated clinical, genetic, and immunophenotypic features.
• Assessing the prognostic value of CD15 positivity, del(7q), and age in AML patient survival.
• Evaluating the utility of multi-omics models for guiding hematopoietic stem cell transplantation decisions.

Strengths

• Data is derived from a cohort of 378 Chinese AML patients, with 298 used for training and 80 for external validation.
• The model demonstrated a concordance index of 0.729 internally and a 3-year overall survival AUC of 0.752 in external validation.
• The dataset integrates multiple data types, including molecular genetics, cytogenetics, and immunophenotyping.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment.
• Data may reflect geographic bias inherent to the single Chinese cohort.

Provenance

Source

figshare

Collection Method

Retrospective study of patient records.

Freshness

Last updated 2026-05-01 05:24:31; freshness should be verified.

Geography

China