<HashMap><database>biostudies-literature</database><scores/><additional><submitter>Archer KJ</submitter><funding>US National Cancer Institute</funding><funding>U.S. National Library of Medicine</funding><funding>Coleman Leukemia Research Foundation</funding><funding>NCI NIH HHS</funding><funding>American Society of Hematology</funding><funding>NLM NIH HHS</funding><funding>D. Warren Brown Family Foundation</funding><funding>Leukemia Research Foundation</funding><funding>Leukemia and Lymphoma Society</funding><pagination>28</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11068580</full_dataset_link><repository>biostudies-literature</repository><omics_type>Unknown</omics_type><volume>17(1)</volume><pubmed_abstract>Patients with cytogenetically normal acute myeloid leukemia (CN-AML) may harbor prognostically relevant gene mutations and thus be categorized into one of the three 2022 European LeukemiaNet (ELN) genetic-risk groups. Nevertheless, there remains heterogeneity with respect to relapse-free survival (RFS) within these genetic-risk groups. Our training set included 306 adults on Alliance for Clinical Trials in Oncology studies with de novo CN-AML aged &lt; 60 years who achieved a complete remission and for whom centrally reviewed cytogenetics, RNA-sequencing, and gene mutation data from diagnostic samples were available (Alliance trial A152010). To overcome deficiencies of the Cox proportional hazards model when long-term survivors are present, we developed a penalized semi-parametric mixture cur</pubmed_abstract><journal>Journal of hematology &amp; oncology</journal><pubmed_title>Identifying long-term survivors and those at higher or lower risk of relapse among patients with cytogenetically normal acute myeloid leukemia using a high-dimensional mixture cure model.</pubmed_title><pmcid>PMC11068580</pmcid><funding_grant_id>UG1CA233327</funding_grant_id><funding_grant_id>UG1CA233338</funding_grant_id><funding_grant_id>UG1 CA233339</funding_grant_id><funding_grant_id>U10CA180882</funding_grant_id><funding_grant_id>R35 CA197734</funding_grant_id><funding_grant_id>UG1 CA233327</funding_grant_id><funding_grant_id>R01 LM013879</funding_grant_id><funding_grant_id>UG1 CA233338</funding_grant_id><funding_grant_id>P30CA016058</funding_grant_id><funding_grant_id>R01LM013879</funding_grant_id><funding_grant_id>U10 CA180882</funding_grant_id><funding_grant_id>P30 CA016058</funding_grant_id><funding_grant_id>R01 CA283574</funding_grant_id><funding_grant_id>U24 CA196171</funding_grant_id><funding_grant_id>U24CA196171</funding_grant_id><funding_grant_id>U10 CA180821</funding_grant_id><funding_grant_id>UG1 CA233331</funding_grant_id><pubmed_authors>Braess J</pubmed_authors><pubmed_authors>Spiekermann K</pubmed_authors><pubmed_authors>Uy GL</pubmed_authors><pubmed_authors>Herold T</pubmed_authors><pubmed_authors>Hiddemann W</pubmed_authors><pubmed_authors>Stock W</pubmed_authors><pubmed_authors>Mrozek K</pubmed_authors><pubmed_authors>Nicolet D</pubmed_authors><pubmed_authors>Mims AS</pubmed_authors><pubmed_authors>Metzeler KH</pubmed_authors><pubmed_authors>Archer KJ</pubmed_authors><pubmed_authors>Fu H</pubmed_authors><pubmed_authors>Byrd JC</pubmed_authors><pubmed_authors>Eisfeld AK</pubmed_authors></additional><is_claimable>false</is_claimable><name>Identifying long-term survivors and those at higher or lower risk of relapse among patients with cytogenetically normal acute myeloid leukemia using a high-dimensional mixture cure model.</name><description>Patients with cytogenetically normal acute myeloid leukemia (CN-AML) may harbor prognostically relevant gene mutations and thus be categorized into one of the three 2022 European LeukemiaNet (ELN) genetic-risk groups. Nevertheless, there remains heterogeneity with respect to relapse-free survival (RFS) within these genetic-risk groups. Our training set included 306 adults on Alliance for Clinical Trials in Oncology studies with de novo CN-AML aged &lt; 60 years who achieved a complete remission and for whom centrally reviewed cytogenetics, RNA-sequencing, and gene mutation data from diagnostic samples were available (Alliance trial A152010). To overcome deficiencies of the Cox proportional hazards model when long-term survivors are present, we developed a penalized semi-parametric mixture cur</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024 May</publication><modification>2026-06-01T05:37:42.676Z</modification><creation>2026-04-08T09:41:11.373Z</creation></dates><accession>S-EPMC11068580</accession><cross_references><pubmed>38702786</pubmed><doi>10.1186/s13045-024-01553-6</doi></cross_references></HashMap>