Epidemiology and Nomogram Development for Chronic Eosinophilic Leukemia, Not Otherwise Specified (CEL-NOS): Insights from the SEER Database
Wang, F.
Show abstract
BackgroundChronic Eosinophilic Leukemia, Not Otherwise Specified (CEL-NOS), a rare and intricate hematological disorder characterized by uncontrolled eosinophilic proliferation, presents clinical challenges owing to its infrequency. This study aimed to investigate the epidemiology and develop a prognostic nomogram for CEL-NOS patients. MethodsUtilizing the Surveillance, Epidemiology and End Results (SEER) database, CEL-NOS cases diagnosed between 2001 and 2020 were analyzed for incidence rates, clinical profiles, and survival outcomes. Patients were randomly divided into training and validation cohorts (7:3 ratio). LASSO regression analysis and Cox regression analysis were performed to screen the prognostic factors for overall survival. A nomogram was then constructed and validated to predict the 3- and 5-year overall survival probability of CEL-NOS patients by incorporating these factors. ResultsThe incidence rate of CEL-NOS was very low, with an average of 0.033 per 100,000 person-years from 2001 to 2020. The incidence rate significantly increased with age and was higher in males than females. The mean age at diagnosis was 57 years. Prognostic analysis identified advanced age, specific marital statuses, and secondary CEL-NOS as independent and adverse predictors of overall survival (OS). To facilitate personalized prognostication, a nomogram was developed incorporating these factors, demonstrating good calibration and discrimination. Risk stratification using the nomogram effectively differentiated patients into low- and high-risk groups. ConclusionsThis study enhances our understanding of CEL-NOS, offering novel insights into its epidemiology, demographics, and prognostic determinants, while providing a possible prognostication tool for clinical use. However, further research is warranted to elucidate molecular mechanisms and optimize therapeutic strategies for CEL-NOS.
Matching journals
The top 9 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Multiple Myeloma and SARS-CoV-2 Infection: Clinical Characteristics and Prognostic Factors of Inpatient Mortality 92%
- High WEE1 expression is independently linked to poor survival in multiple myeloma 92%
- Real World Predictors of Response and 24-month survival in high-grade TP53 -mutated Myeloid Neoplasms 92%
Similar papers in this journal
- Risk and Outcome of Second primary malignancy in patients with classical Hodgkin lymphoma 95%
- Combination therapy of Tocilizumab and steroid for management of COVID-19 associated cytokine release syndrome: A single center experience from Pune, Western India 89%
- Upregulation of ARHGAP9 is correlated with poor prognosis and immune infiltration in clear cell renal cell carcinoma 89%
Similar papers in this journal
- Clinicopathologic Correlates and Natural History of Atypical Chronic Myeloid Leukemia 94%
- Patients with CLL have similar high risk of death upon the omicron variant of COVID-19 as previously during the pandemic 92%
- Mutational and transcriptional landscape of pediatric B-cell precursor lymphoblastic lymphoma 91%
Similar papers in this journal
- Impact of blood analysis and immune function on the prognosis of patients with COVID-19 94%
- Investigation of HLA susceptibility alleles and genotypes with hematological disease among Chinese Han population 93%
- Analytical validation and performance characteristics of a 48-gene next-generation sequencing panel for detecting potentially actionable genomic alterations in myeloid neoplasms 93%
Similar papers in this journal
- Exploring the role of Large Language Models (LLMs) in hematology: a systematic review of applications, benefits, and limitations 91%
- Validation of the IMPEDE VTE Score for Prediction of Venous Thromboembolism in Multiple Myeloma: A Retrospective Cohort Study 91%
- COVID symptoms, testing, shielding impact on patient reported outcomes and early vaccine responses in individuals with multiple myeloma 90%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.