98%
921
2 minutes
20
This study aimed to validate the 2022 European LeukemiaNet (ELN) risk stratification for acute myeloid leukemia (AML). A total of 624 newly diagnosed AML patients from 1998 to 2014 were included in the analysis. Genetic profiling was conducted using targeted deep sequencing of 45 genes based on recurrent driver mutations. In total, 134 (21.5%) patients had their risk classification reassessed according to the 2022 ELN risk stratification. Among those initially classified as having a favorable risk in 2017 (n = 218), 31 and 3 patients were reclassified as having intermediate risk or adverse risk, respectively. Among the three subgroups, the 2022 ELN favorable-risk group showed significantly longer survival outcomes than the other groups. Within the 2017 ELN intermediate-risk group (n = 298), 21 and 46 patients were reclassified as having favorable risk or adverse risk, respectively, and each group showed significant stratifications in survival outcomes. Some patients initially classified as having adverse risk in 2017 were reclassified into the intermediate-risk group (33 of 108 patients), but no prognostic improvements were observed in this group. A multivariable analysis identified the 2022 ELN risk stratification, age, and receiving allogeneic hematopoietic cell transplantation as significant prognostic factors for survival. The 2022 ELN risk stratification enables more precise decisions for proceeding with allogeneic hematopoietic cell transplantation for AML patients.
Download full-text PDF |
Source |
---|---|
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11014905 | PMC |
http://dx.doi.org/10.1038/s41598-024-57295-5 | DOI Listing |
Purpose Clear cell renal cell carcinoma (ccRCC), the dominant subtype of renal malignancy, has a rising global incidence and mortality. While surgery is the standard of care for localized cases, adjuvant therapy aims to improve outcomes in high-risk postoperative patients. To quantify the clinical value of adjuvant pharmacotherapy, this systematic review and meta-analysis assesses its effect on overall survival (OS), disease-free survival (DFS), and progression-free survival (PFS) in patients with ccRCC.
View Article and Find Full Text PDFJ Electrocardiol
August 2025
Department of Cardiology, Kırşehir Ahi Evran Training and Research Hospital, Kırşehir, Turkey. Electronic address:
Background: Ischemia with non-obstructive coronary arteries (INOCA) represents a diagnostic and therapeutic challenge, often related to coronary microvascular dysfunction (CMD). Identifying non-invasive electrocardiographic markers that predict ischemia in this population remains a clinical priority. P-wave peak time (PWPT), reflecting atrial conduction delay, has been linked to ischemic pathophysiology.
View Article and Find Full Text PDFExp Cell Res
September 2025
Key Laboratory of Carcinogenesis and Translational Research (Ministry of Education/Beijing), Gastrointestinal Cancer Center, Peking University Cancer Hospital and Institute, Beijing, China. Electronic address:
Background: Enteric glial cells (EGCs) have been implicated in colorectal cancer (CRC) progression. This study aimed to develop and validate a prognostic model integrating EGC- and CRC-associated gene expression to predict patient survival, recurrence, metastasis, and therapy response.
Methods: Bulk and single-cell RNA sequencing data were analyzed, and a machine learning-based model was constructed using the RSF random forest algorithm.
Mod Pathol
September 2025
Department of Pathology, Northwestern University Feinberg School of Medicine, Chicago, IL, USA. Electronic address:
Uterine leiomyosarcoma (uLMS) is a rare and deadly gynecologic malignancy. uLMS is histologically heterogeneous and presents with a wide spectrum of tumor differentiation, with a broad range of genomic DNA instability, which can make the diagnosis and prognosis of uLMS challenging. Methylation has emerged as a useful molecular tool in tumor classification and diagnosis in certain neoplasms.
View Article and Find Full Text PDFJ Cardiol
September 2025
Catholic Research Institute for Intractable Cardiovascular Disease, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea; Department of Cardiology, Daejeon St. Mary's Hospital, College of Medicine, The Catholic University of Korea, Seoul, Republic of Korea. Electronic addr
Heart failure with preserved ejection fraction (HFpEF) accounts for more than half of all HF cases and its incidence and prevalence continue to increase, with a substantial burden of morbidity and mortality. Despite advances in our understanding of heterogeneous pathophysiology underlying HFpEF, the diagnosis, risk assessment, and management of this disease entity remain challenging in everyday practice. Artificial intelligence (AI) algorithm can handle large amounts of complex data and machine learning (ML), a subfield of AI, allows for the identification of relevant patterns by learning from big data.
View Article and Find Full Text PDF