Background: This study aimed to identify risk factors affecting cancer-specific survival (CSS) and overall survival (OS) in patients with lung squamous cell carcinoma (LSCC) and to develop nomograms for prognostic prediction in these patients. Methods: Patients who received an LSCC diagnosis between 2007 and 2013 were selected from the Surveillance, Epidemiology, and End Results (SEER) database. The prognostic effect of each variable on survival was evaluated with Cox regression and Kaplan-Meier analysis, and nomograms were developed to predict 3-, 5-, and 7-year CSS and OS rates. Results: Data from 23,004 patients with LSCC were analyzed. Nomograms were first developed by using variables that were significantly associated with CSS and OS and then validated by using an internal bootstrap resampling approach, which showed that they had a sufficient level of discrimination, according to the C-index. Conclusions: The nomograms satisfactorily predicted 3-, 5-, and 7-year CSS and OS rates for patients with LSCC.

BackgroundEpidermal growth factor receptor (EGFR) mutation testing is restricted to several limitations. In this study, we examined the relationship between EGFR mutation status and clinicoradiological characteristics in a Chinese cohort of patients.Materials and methodsThe data of patients who were diagnosed with lung carcinoma and underwent both EGFR testing and chest computed tomography (CT) at our hospital between January 1, 2011, and November 31, 2015, were retrospectively analyzed. The age, sex, and smoking index of the patients, the size, margin, and density of the tumor, and the presence of specific signs visible on the CT images were assessed.ResultsThe results showed a higher rate of EGFR-tyrosine kinase inhibitor (TKI)-sensitive group than nonsensitive group in female patients and patients with a low smoking index (P<0.001, both). In logistic regression analyses, tumor size (P<0.001), smooth margins (P=0.015), and angular margins (P<0.001) were independent negative predictors of EGFR-TKI-sensitive group. Pleural indentation (P<0.001) and air bronchogram (P=0.025) were independent positive predictors of EGFR-TKI-sensitive group. Patients with squamous cell carcinoma had fewer sensitive mutations than those with either adenocarcinoma (P<0.001) or adenosquamous carcinoma (P<0.001).ConclusionClinical and CT characteristics differed significantly between EGFR-TKI-sensitive and nonsensitive groups. Our findings may be useful in deciding therapeutic strategies for patients in whom EGFR testing is not possible.

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.

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Introduction: The purpose of the present study was to evaluate the potential relationship of lymphocyte-to-monocyte ratio (LMR) with outcomes of septic patients at intensive care unit (ICU) admission. Material and methods: 3087 septic patients were included in the final cohort by using the Medical Information Mart for Intensive Care (MIMIC) database. We evaluated the association of different groups of LMR max with 28-day survival and 1-year survival via Kaplan-Meier (K-M) analysis and Cox regression analysis. Subgroups analysis of LMR max was performed to further explore the effect of LMR max on survival. Results: According to the optimal cutoff value, the cohort was divided into low-LMR max and high-LMR max groups. The 28-day and 1-year survival rates were 47.9% and 19.9%, respectively, in the low-LMR max group, and 60.4% and 25.9%, respectively, in the high-LMR max group. Univariate logistic regression and K-M analyses revealed that the 28-day and 1-year survival rates of the high-LMR max group were higher than those of the low-LMR max group (both p < 0.001). A subgroup analysis of LMR max identified a significant stepwise decrease in the risk of death at 28 days and 1 year from group 1 to group 4 (LMR max increased gradually) after adjustment for multiple variables. Conclusions: We report for the first time that a lower LMR max value is independently predictive of a poor prognosis in septic patients. Therefore, as an inexpensive and readily available indicator, LMR max may facilitate stratification of prognosis in septic patients.