{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,26]],"date-time":"2026-04-26T17:36:53Z","timestamp":1777225013620,"version":"3.51.4"},"reference-count":32,"publisher":"Wiley","issue":"2","license":[{"start":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:00:00Z","timestamp":1773187200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T00:00:00Z","timestamp":1773187200000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["eJHaem"],"published-print":{"date-parts":[[2026,4]]},"abstract":"<jats:title>ABSTRACT<\/jats:title>\n                  <jats:sec>\n                    <jats:title>Background<\/jats:title>\n                    <jats:p>Older adults with acute myeloid leukemia (AML) have inferior outcomes, yet current genetic risk models do not explicitly account for how age modifies the prognostic impact of molecular features. We hypothesized that integrating apoptosis and p53\u2010related gene expression with recurrent mutations would improve prediction of complete remission (CR) and 2\u2010year overall survival (OS), particularly across age groups.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Methods<\/jats:title>\n                    <jats:p>Using the BeatAML2 dataset (805 patients; 942 specimens), we built two cohorts: a clinical cohort of 916 adults with full data and an expression\u2010linked cohort of 852 with matched RNA\u2010seq. Patients were divided into four age groups 18\u201330, 30\u201345, 45\u201360, and 60+ years. We tested whether adding expression of 12 apoptosis and p53\u2010related genes to five well\u2010known mutations, that is TP53, NPM1, FLT3, RUNX1, and ASXL1, could improve the prediction of CR and 2\u2010year OS.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Results<\/jats:title>\n                    <jats:p>Adding gene expression improved predictive performance across models. For 2\u2010year OS, AUCs rose from 0.765 to 0.772 in XGBoost, 0.703 to 0.843 in Random Forest, and 0.697 to 0.721 in Logistic Regression. For CR, performance improved from 0.770 to 0.851 in XGBoost, 0.811 to 0.861 in Random Forest, and 0.731 to 0.696 in Logistic Regression. Calibration was strongest for tree\u2010based models, and reclassification improved most with XGBoost. Multivariable regression confirmed TP53 as the most adverse marker for OS (HR: 3.07), with added risk from ASXL1 (HR: 1.53) and FLT3 (HR: 1.39). NPM1 increased the chance of remission (OR: 2.47) but did not extend survival. SHAP analysis showed that age remained the leading predictor of OS. Among genes, CHEK2 expression was most important for survival, especially in patients 60 years and older, while CCNG1 expression best predicted remission, along with BAX and MCL1.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Conclusions<\/jats:title>\n                    <jats:p>These results demonstrate that combining gene expression with recurrent mutations makes risk prediction more accurate, especially in older patients who formed the largest group and had the poorest outcomes. Although treatment variables were not included and analysis focused on selected genes, these findings support incorporation of expression\u2010based features into genetic risk models and warrant prospective validation.<\/jats:p>\n                  <\/jats:sec>\n                  <jats:sec>\n                    <jats:title>Trial Registration<\/jats:title>\n                    <jats:p>The authors have confirmed clinical trial registration is not needed for this submission<\/jats:p>\n                  <\/jats:sec>","DOI":"10.1002\/jha2.70261","type":"journal-article","created":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T08:44:09Z","timestamp":1773218649000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["Integrating Gene Expression With Recurrent Mutations Improves Age\u2010Stratified Risk Prediction in Acute Myeloid Leukemia"],"prefix":"10.1002","volume":"7","author":[{"given":"Mobina","family":"Shrestha","sequence":"first","affiliation":[{"name":"USACS Sentara Albemarle Medical Center  Elizabeth City North Carolina USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Salina","family":"Dahal","sequence":"additional","affiliation":[{"name":"The Ohio State University  Columbus Ohio USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Asis","family":"Shrestha","sequence":"additional","affiliation":[{"name":"University of Arkansas for Medical Sciences  Little Rock Arkansas USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Patricia","family":"McNally","sequence":"additional","affiliation":[{"name":"Trinity Health Ann Arbor  Ypsilanti Michigan USA"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Amir Babu","family":"Shrestha","sequence":"additional","affiliation":[{"name":"Manipal College of Medical Sciences  Pokhara Nepal"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Niklas","family":"Mackler","sequence":"additional","affiliation":[{"name":"Trinity Health Ann Arbor  Ypsilanti Michigan USA"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2026,3,11]]},"reference":[{"key":"e_1_2_11_2_1","doi-asserted-by":"publisher","DOI":"10.1182\/blood\u20102005\u201009\u20103724"},{"issue":"18","key":"e_1_2_11_3_1","first-page":"4179","article-title":"Age and Acute Myeloid Leukemia: Real World Data on Decision to Treat and Outcomes From the Swedish Acute Leukemia Registry","volume":"113","author":"Juliusson G.","year":"2009","journal-title":"Blood, the Journal of the American Society of Hematology"},{"key":"e_1_2_11_4_1","doi-asserted-by":"publisher","DOI":"10.1200\/JCO.2012.42.2964"},{"key":"e_1_2_11_5_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa1516192"},{"issue":"12","key":"e_1_2_11_6_1","first-page":"1345","article-title":"Diagnosis and Management of AML in Adults: 2022 Recommendations From an International Expert Panel on Behalf of the ELN","volume":"140","author":"D\u00f6hner H.","year":"2022","journal-title":"Blood, the Journal of the American Society of Hematology"},{"issue":"3","key":"e_1_2_11_7_1","first-page":"354","article-title":"Refinement of Cytogenetic Classification in Acute Myeloid Leukemia: Determination of Prognostic Significance of Rare Recurring Chromosomal Abnormalities Among 5876 Younger Adult Patients Treated in the United Kingdom Medical Research Council Trials","volume":"116","author":"Grimwade D.","year":"2010","journal-title":"Blood, the Journal of the American Society of Hematology"},{"key":"e_1_2_11_8_1","doi-asserted-by":"publisher","DOI":"10.1038\/nrc2297"},{"key":"e_1_2_11_9_1","doi-asserted-by":"publisher","DOI":"10.1172\/JCI28281"},{"key":"e_1_2_11_10_1","doi-asserted-by":"publisher","DOI":"10.1158\/2159\u20108290.CD\u201013\u20100609"},{"key":"e_1_2_11_11_1","doi-asserted-by":"publisher","DOI":"10.1056\/NEJMoa2012971"},{"issue":"24","key":"e_1_2_11_12_1","first-page":"2137","article-title":"Venetoclax Plus LDAC for Newly Diagnosed AML Ineligible for Intensive Chemotherapy: A Phase 3 Randomized Placebo\u2010Controlled Trial","volume":"135","author":"Wei A. 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