Predicting secondary myeloid neoplasms in acquired aplastic anemia using machine learning models.

Authors

Ahmet Celal Toprak
Mutlu Mete
Julia J Shi
Daria V Babushok
Carmelo Gurnari
Jaroslaw P Maciejewski
Zoe Bass
Zehra Tombul
Carlos I A Santos
Munevver N Duran
Hussein Awada
Ibrahim Ibrahim
Alper Olcal
Yusuf Ozcan
Leslie Guerrero
Julio Alvarenga Thiebaud
Taha Bat

Publication/Presentation Date

11-1-2025

Abstract

Patients with acquired aplastic anemia (AA) treated with immunosuppressive therapy (IST) face up to a 20% long-term risk of developing secondary myeloid neoplasms (sMNs), including acute myeloid leukemia and myelodysplastic syndromes. Although hematopoietic stem cell transplantation (HSCT) is curative and prevents sMNs, older patients and those lacking suitable donors have historically received IST as first-line therapy. Recent improvements in HSCT outcomes have expanded transplant eligibility, highlighting the need for tools to better identify patients at high risk for sMN. Validated predictive models could help guide early HSCT consideration or tailor surveillance strategies. We developed 2 binary machine learning models to predict sMN development in patients with acquired AA at clinically relevant time points: diagnosis (model 1) and 6 months after IST response (model 2). We analyzed data from 275 adult patients with AA treated at University of Texas Southwestern, Cleveland Clinic, and the Hospital of the University of Pennsylvania between 1975 and 2023. Seventy-nine clinical variables were collected, including demographics, somatic mutations, and treatment response. Neural networks were trained with leave-1-out crossvalidation. Both models achieved strong performance (area under the curve, 0.82; sensitivity, 0.82, specificity, 0.73). Shared key predictors included

Volume

2

Issue

4

First Page

100163

Last Page

100163

ISSN

2950-3280

Published In/Presented At

Toprak, A. C., Mete, M., Shi, J. J., Babushok, D. V., Gurnari, C., Maciejewski, J. P., Bass, Z., Tombul, Z., Santos, C. I. A., Duran, M. N., Awada, H., Ibrahim, I., Olcal, A., Ozcan, Y., Guerrero, L., Thiebaud, J. A., & Bat, T. (2025). Predicting secondary myeloid neoplasms in acquired aplastic anemia using machine learning models. Blood neoplasia, 2(4), 100163. https://doi.org/10.1016/j.bneo.2025.100163

Disciplines

Medicine and Health Sciences

PubMedID

41281613

Department(s)

Fellows and Residents

Document Type

Article