Assessment of influencing factors of hospitalization expenses for Crohn's disease patients: Based on LASSO and linear mixed model.

Aims: Crohn's disease (CD) is a global disease that is dramatically increasing. This study aimed to identify the primary drivers of hospitalization expenses for CD patients to provide guidance on the allocation and control of health care costs.

Methods: This study retrospectively collected the homepage data of the electronic medical records of CD patients in two tertiary hospitals in Zhejiang Province, China, from January 2016 to December 2021.

Association of Evaluated Glomerular Filtration Rate and Incident Diabetes Mellitus: A Secondary Retrospective Analysis Based on a Chinese Cohort Study.

Background: Previous studies have revealed that chronic kidney disease (CKD) is a significant risk factor for insulin resistance and diabetes. However, few studies are on the association between estimated glomerular filtration rate (eGFR) and incident diabetes, especially in the Chinese population with eGFR>60 mL/min·1.73 m.

Epigenome-wide gene-age interaction analysis reveals reversed effects of DNA methylation on survival between young and elderly early-stage NSCLC patients.

DNA methylation changes during aging, but it remains unclear whether the effect of DNA methylation on lung cancer survival varies with age. Such an effect could decrease prediction accuracy and treatment efficacy. We performed a methylation-age interaction analysis using 1,230 early-stage lung adenocarcinoma patients from five cohorts.

Independent Validation of Early-Stage Non-Small Cell Lung Cancer Prognostic Scores Incorporating Epigenetic and Transcriptional Biomarkers With Gene-Gene Interactions and Main Effects.

Background: DNA methylation and gene expression are promising biomarkers of various cancers, including non-small cell lung cancer (NSCLC). Besides the main effects of biomarkers, the progression of complex diseases is also influenced by gene-gene (G×G) interactions.

Research Question: Would screening the functional capacity of biomarkers on the basis of main effects or interactions, using multiomics data, improve the accuracy of cancer prognosis?

Study Design And Methods: Biomarker screening and model validation were used to construct and validate a prognostic prediction model.

Trans-omics biomarker model improves prognostic prediction accuracy for early-stage lung adenocarcinoma.

Limited studies have focused on developing prognostic models with trans-omics biomarkers for early-stage lung adenocarcinoma (LUAD). We performed integrative analysis of clinical information, DNA methylation, and gene expression data using 825 early-stage LUAD patients from 5 cohorts. Ranger algorithm was used to screen prognosis-associated biomarkers, which were confirmed with a validation phase.

SIPA1L3 methylation modifies the benefit of smoking cessation on lung adenocarcinoma survival: an epigenomic-smoking interaction analysis.

Smoking cessation prolongs survival and decreases mortality of patients with non-small-cell lung cancer (NSCLC). In addition, epigenetic alterations of some genes are associated with survival. However, potential interactions between smoking cessation and epigenetics have not been assessed.

EGLN2 DNA methylation and expression interact with HIF1A to affect survival of early-stage NSCLC.

Hypoxia occurs frequently in human cancers and promotes stabilization and activation of hypoxia inducible factor (HIF). HIF-1α is specific for the hypoxia response, and its degradation mediated by three enzymes EGLN1, EGLN2 and EGLN3. Although EGLNs expression has been found to be related to prognosis of many cancers, few studies examined DNA methylation in EGLNs and its relationship to prognosis of early-stage non-small cell lung cancer (NSCLC).