BackgroundTriglyceride and glucose (TyG) index and nonalcoholic fatty liver disease (NAFLD) both bave been related to insulin resistance (IR). The study aimed to investigate the longitudinal relationship between TyG index and NAFLD and to evaluate the ability of TyG, through comparing with the predictive value of other indexes, to identify individuals at risk for NAFLD.MethodsFour thousand and five hundred thirty nine subjects without NAFLD initially were followed up for 9 years. Cox regression models were used to analyze the risk factors of NAFLD.ResultsCox regression analyses indicated the TyG index was independently and positively associated with the risk of incident NAFLD. In receiver operating characteristic (ROC) curve analysis, the optimal cut-off level for TyG to predict incident NAFLD was 8.52 and the area under the ROC curve (AUC) was 0.76 (95% CI 0.74–0.77), which was larger than that of TG, ALT and FPG.ConclusionThis study demonstrated that the elevation of the TyG index might predict increase risk for incident NAFLD and it may be suitable as a diagnostic criterion for NAFLD.

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Patients with stage IV non-small cell lung cancer (NSCLC) comprise a heterogeneous group, and the optimal treatment for this group of patients is complex and debatable. We aimed to assess the effect of local thoracic therapy combined with chemotherapy on cancer specific survival (CSS). To evaluate the CSS of four subgroups of patients with stage IV NSCLC according to four different treatment modalities: combined modality of Chemotherapy, Surgery, and Radiation (Chem+Sur+RT), Chemotherapy and Radiation (Chem+RT), Chemotherapy and Surgery (Chem+Sur), and Chemotherapy only (Chem Only) by analyzing the Surveillance, Epidemiology, and End Results (SEER)-registered database. Kaplan-Meier methods were adopted and multivariable Cox regression models were built for the analysis of survival outcomes and risk factors. The 3-year CSS was 33.5% in “Chem+Sur+RT” group, 9.3% in “Chem+RT” group, 42.7% in “Chem+Sur” group and 11.8% in “Chem Only” group, which had significant difference in univariate log-rank test (P<0.001) and multivariate Cox regression (P<0.001). Moreover, we observed significant survival benefits in “Chem+Sur” group in all stage of T/N categories, including stage I, stage II, stage IIIa and stage IIIb (all P<0.001). Multimodality therapy, especially combined thoracic surgery and chemotherapy is associated with dramatically improved prognosis for patients with stage IV NSCLC.

Purpose The purpose of this study was to conduct a matched-pair analysis to assess the impact of radiotherapy (RT) on patients with malignant tracheal tumors using the surveillance, epidemiology, and end results database. Additionally, a predictive nomogram was developed for patients with malignant tracheal tumors. Methods Propensity score matching (PSM) was used to minimize bias between the RT and no-RT groups. We utilized both univariate and multivariate Cox proportional hazards regression analyses to identify independent prognostic factors for patients and subgroups. We developed a novel nomogram and evaluated its results using the C-index. Results A total of 648 patients between 1975 and 2019 were included, and 160 patients in RT were 1:1 propensity score-matched with no-RT. The independent prognostic factors for patients with tracheal malignant tumors were surgery, marital status, disease extension, pathology, and age. The independent risk factors for patients without surgery included RT and disease extension. The C-index confirmed that the nomogram accurately predicted the prognosis of patients with tracheal malignant tumors. Conclusions Our findings suggest that RT may provide a survival benefit for tracheal cancer patients who did not undergo surgery. The nomogram can be a useful tool for predicting prognosis in patients with tracheal malignant tumors.

Lung adenocarcinoma (LACA) is the leading cause of cancer-associated death worldwide. The present study intended to identify DNA methylation patterns that may serve as diagnostic and prognostic biomarkers for LACA. Data on DNA methylation and the survival data of the patients of LACA were obtained from The Cancer Genome Atlas. Kaplan-Meier curves and receiver operating characteristic curve analysis were utilized to build diagnostic and prognostic models. A total of 13 CpG sites were identified and validated as the optimal diagnostic and prognostic signature for overall survival. It was concluded that the CpG-based signature is a reliable predictor for the diagnosis and prognosis of patients with LACA.