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Machine Learning Improves Risk Stratification in Myelodysplastic Neoplasms: An Analysis of the Spanish Group of Myelodysplastic Syndromes

Authors :
Adrian Mosquera Orgueira
Manuel Mateo Perez Encinas
Nicolas A Diaz Varela
Elvira Mora
Marina Díaz-Beyá
María Julia Montoro
Helena Pomares
Fernando Ramos
Mar Tormo
Andres Jerez
Josep F Nomdedeu
Carlos De Miguel Sanchez
Arenillas Leonor
Paula Cárcel
Maria Teresa Cedena Romero
Blanca Xicoy
Eugenia Rivero
Rafael Andres del Orbe Barreto
Maria Diez-Campelo
Luis E. Benlloch
Davide Crucitti
David Valcárcel
Source :
HemaSphere, Vol 7, Iss 10, p e961 (2023)
Publication Year :
2023
Publisher :
Wiley, 2023.

Abstract

Myelodysplastic neoplasms (MDS) are a heterogeneous group of hematological stem cell disorders characterized by dysplasia, cytopenias, and increased risk of acute leukemia. As prognosis differs widely between patients, and treatment options vary from observation to allogeneic stem cell transplantation, accurate and precise disease risk prognostication is critical for decision making. With this aim, we retrieved registry data from MDS patients from 90 Spanish institutions. A total of 7202 patients were included, which were divided into a training (80%) and a test (20%) set. A machine learning technique (random survival forests) was used to model overall survival (OS) and leukemia-free survival (LFS). The optimal model was based on 8 variables (age, gender, hemoglobin, leukocyte count, platelet count, neutrophil percentage, bone marrow blast, and cytogenetic risk group). This model achieved high accuracy in predicting OS (c-indexes; 0.759 and 0.776) and LFS (c-indexes; 0.812 and 0.845). Importantly, the model was superior to the revised International Prognostic Scoring System (IPSS-R) and the age-adjusted IPSS-R. This difference persisted in different age ranges and in all evaluated disease subgroups. Finally, we validated our results in an external cohort, confirming the superiority of the Artificial Intelligence Prognostic Scoring System for MDS (AIPSS-MDS) over the IPSS-R, and achieving a similar performance as the molecular IPSS. In conclusion, the AIPSS-MDS score is a new prognostic model based exclusively on traditional clinical, hematological, and cytogenetic variables. AIPSS-MDS has a high prognostic accuracy in predicting survival in MDS patients, outperforming other well-established risk-scoring systems.

Details

Language :
English
ISSN :
25729241 and 00000000
Volume :
7
Issue :
10
Database :
Directory of Open Access Journals
Journal :
HemaSphere
Publication Type :
Academic Journal
Accession number :
edsdoj.8be230579faa4438bea41bbeeacb89de
Document Type :
article
Full Text :
https://doi.org/10.1097/HS9.0000000000000961