{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,2]],"date-time":"2026-09-02T12:13:38Z","timestamp":1788351218747,"version":"build-2803163510"},"reference-count":34,"publisher":"Wiley","issue":"11","license":[{"start":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T00:00:00Z","timestamp":1762128000000},"content-version":"vor","delay-in-days":2,"URL":"http:\/\/creativecommons.org\/licenses\/by-nc-nd\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["HemaSphere"],"published-print":{"date-parts":[[2025,11]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Infant acute myeloid leukemia (AML), particularly in those under 3 years of age, presents poor prognostic outcomes and distinct biological characteristics that require age\u2010specific risk assessment. This study, utilizing data from four pediatric AML (pAML) trials conducted by the Children's Oncology Group, aimed to develop a simple RNA expression\u2010based prognostic model to refine risk stratification for infant AML. Expression data from 213 infant AML patients were analyzed using machine\u2010learning algorithms to develop the infant\u2010prognostic\u2010score (IPSscore), or IPSgroup when categorized. To validate the stability of the model, internal validation was conducted on a set of 127 cases, and external validation was performed using a separate set of 63 patients from a different ethnic background. Furthermore, we compared its prognostic prediction capability with that of other AML models and explored its potential clinical decision\u2010making value for infant AML patients. The IPSgroup independently and specifically predicted outcomes in infant AML, outperforming several previously published RNA expression\u2010based models. Infant patients categorized into the high\u2010risk group based on IPSgroup may benefit from hematopoietic stem cell transplantation (HSCT), while those in the low\u2010risk group are not suitable for HSCT. Additionally, when combined with the current pAML stratification system used in clinical trials, the IPSgroup enabled re\u2010stratification of 43% of infant AML patients into more accurate risk groups, highlighting the advantage of incorporating gene expression analysis into clinical decision\u2010making. Infant AML demonstrates significant heterogeneity at clinical, molecular, and prognostic levels. The newly proposed model surpasses existing AML stratifications, offering a valuable tool for clinical decision\u2010making and treatment strategies.<\/jats:p>","DOI":"10.1002\/hem3.70251","type":"journal-article","created":{"date-parts":[[2025,11,3]],"date-time":"2025-11-03T20:28:58Z","timestamp":1762201738000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":3,"title":["Integrating transcriptomic profiling and machine learning: A clinically actionable prognostic model for infant acute myeloid leukemia"],"prefix":"10.1002","volume":"9","author":[{"given":"Yu","family":"Tao","sequence":"first","affiliation":[{"name":"Precision Oncology and Intelligent Theranostics Laboratory, Department of Pediatric Hematology and Oncology, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Diseases, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders Children's Hospital of Chongqing Medical University Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Yali","family":"Shen","sequence":"additional","affiliation":[{"name":"Precision Oncology and Intelligent Theranostics Laboratory, Department of Pediatric Hematology and Oncology, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Diseases, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders Children's Hospital of Chongqing Medical University Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"YanLai","family":"Tang","sequence":"additional","affiliation":[{"name":"Department of Pediatrics The First Affiliated Hospital Sun Yat\u2010sen University Guangzhou China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Hui","family":"Shi","sequence":"additional","affiliation":[{"name":"Precision Oncology and Intelligent Theranostics Laboratory, Department of Pediatric Hematology and Oncology, Chongqing Key Laboratory of Pediatric Metabolism and Inflammatory Diseases, Ministry of Education Key Laboratory of Child Development and Disorders, National Clinical Research Center for Child Health and Disorders Children's Hospital of Chongqing Medical University Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Li","family":"Wei","sequence":"additional","affiliation":[{"name":"Chongqing Health Center for Women and Children, Women and Children's Hospital of Chongqing Medical University, NHC Key Laboratory of Birth Defects and Reproductive Health Chongqing China"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9630-5284","authenticated-orcid":false,"given":"Hua","family":"You","sequence":"additional","affiliation":[{"name":"Precision Oncology and Intelligent Theranostics Laboratory, Department of Pediatric Hematology and 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