Non-invasive differentiation between aplastic anemia and myelodysplastic syndromes based on an 8-feature…

Cohort studyCurrent research in translational medicine· Jul 2026

Non-invasive differentiation between aplastic anemia and myelodysplastic syndromes based on an 8-feature lightGBM model: A multicenter external validation study.

Sumei Wang, Zihan Cai, Wei Wei … Yurong Zhang

HematologyCohort studyDiagnosisQ2IF 2.7

A new AI model accurately differentiates aplastic anemia from myelodysplastic syndromes.

Non-invasive differentiation between aplastic anemia and myelodysplastic syndromes based on an 8-feature lightGBM model: A multicenter external validation study.

Sumei Wang … Yurong Zhang

Current research in translational medicine · Jul 2026 · Q2 in General Medicine

Background

Given the highly overlapping pancytopenic phenotypes, non-invasive differentiation between aplastic anemia (anemia) and myelodysplastic syndromes (myelodysplastic syndromes) remains a formidable clinical challenge.

Methods

We retrospectively enrolled patients with histopathologically confirmed anemia or myelodysplastic syndromes, partitioning them into a training set (n = 310) and an internal validation set (n = 131).

n = 310

97.30%

Results

97.30%

The AI model correctly identified aplastic anemia or myelodysplastic syndromes 97.30% of the time.

n = 310

More results

Algorithmic intersection distilled the high-dimensional data into a parsimonious 8-feature panel (CHOL, hsCRP, IL-6, SAA, AGE, LDL-C, HRF, and IL-10).

The optimized LightGBM model demonstrated superior discriminative accuracy.

More results

SHAP analysis bridged mathematical predictions with pathophysiology, revealing that advanced age and an "inflammaging" cytokine profile (IL-6, hsCRP, SAA) are the strongest predictive features associated with myelodysplastic syndromes.

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Conclusion · 1 of 2

In conclusion, we established and externally validated a highly accurate, non-invasive 8-feature LightGBM diagnostic model.

Conclusion · 2 of 2

Translated into a practical clinical nomogram, this interpretable artificial-intelligence tool serves as an efficient "triage gatekeeper" to minimize unnecessary invasive biopsies, thereby facilitating precision triage in hematology.

Non-invasive differentiation between aplastic anemia and myelodysplastic syndromes based on an 8-feature lightGBM model: A multicenter external validation study.

Non-invasive differentiation between aplastic anemia and myelodysplastic syndromes based on an 8-feature lightGBM model: A multicenter external validation study.

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