A Novel Tool for the Risk Assessment and Personalized Chemo-/Immunotherapy Response Prediction of Adenocarcinoma and Squamous Cell Carcinoma Lung Cancer.

BACKGROUND: The prevalence and cancer-specific death rate of lung cancer (LC) have risen in recent decades. A universally applicable prognostic signature for both adenocarcinoma LC (LUAD) and squamous cell carcinoma LC (LUSC) is still lacking. METHODS: A total of 453 patients from The Cancer Genome Atlas (TCGA)-LUAD cohort and 452 patients from TCGA-LUSC cohort were enrolled, and a prognostic model was constructed using least absolute shrinkage and selection operator (LASSO) regression analysis based on the consensus prognostic genes in both cohorts. The newly defined pan-lung cancer risk count (PLCRC) of each patient was calculated via the summation formula. RESULTS: A total of 23 genes were selected for the calculation of the PLCRC. The PLCRC showed a moderate prognostic value in the entire (p < 0.001, HR: 2.75, AUC: 0.643), LUAD (p < 0.001, HR: 2.51, AUC: 0.636) and LUSC (p < 0.001, HR: 2.89, AUC: 0.656) cohorts. The PLCRC was an independent prognostic factor after adjusting the clinical features. The PLCRC was also effective in nine external validation cohorts and in patients with different clinical features. Activation of extracellular matrix pathways and infiltration of immunocytes promoted the tumorigenesis and development of both LUAD and LUSC. We generated a universally applicable prognostic signature, the PLCRC, which could dichotomize patients with significantly different clinical outcomes and guide the clinical treatment of LC patients. Chemotherapy is more suitable for patients with a low PLCRC, while anti-cytotoxic T-lymphocyte-associated protein 4 immunotherapy is more suitable for patients with a high PLCRC. CONCLUSION: We established and validated a newly defined prognostic signature, the PLCRC, for both LUAD and LUSC patients and provided clinical strategies for patients from different risk subgroups.

Development and validation of prognostic nomogram for lung cancer patients below the age of 45 years.

This study aimed to establish a nomogram for the prognostic prediction of patients with early-onset lung cancer (EOLC) in both overall survival (OS) and cancer-specific survival (CSS). EOLC patients diagnosed between 2004 and 2015 were retrieved from the Surveillance, Epidemiology, and End Results (SEER) database and further divided into training and validation sets randomly. The prognostic nomogram for predicting 3-, 5- and 10-years OS and CSS was established based on the relative clinical variables determined by the multivariate Cox analysis results. Furthermore, the predictive performance of nomogram was assessed by concordance index (C-index), calibration curve, receiver operating characteristic (ROC) curve and decision curve analysis (DCA) curve. A total of 1,822 EOLC patients were selected and randomized into a training cohort (1,275, 70%) and a validation cohort (547, 30%). The nomograms were established based on the statistical results of Cox analysis. In training set, the C-indexes for OS and CSS prediction were 0.797 (95% confidence interval [CI]: 0.773-0.818) and 0.794 (95%CI:0.771-0.816). Significant agreement in the calibration curves was noticed in the nomogram models. The results of ROC and DCA indicated nomograms possessed better predict performance compared with TNM-stage and SEER-stage. And the area under the curve (AUC) of the nomogram for OS and CSS prediction in ROC analysis were 0.766 (95%CI:0.745-0.787) and 0.782 (95%CI:0.760-0.804) respectively. The prognostic nomogram provided an accurate prediction of 3-, 5-, and 10-year OS and CSS of EOLC patients which contributed clinicians to optimize individualized treatment plans.

The butterfly fragment in comminuted femoral shaft fracture may be movable following intramedullary nail treatment.

The gap among fracture fragments is an important factor which influences the healing of bone fracture, and it may be changeable during the early phase of bone healing. In this letter, we pointed out our view that the gap between the butterfly fragment, and the shaft in femoral shaft fractures can easily be changed, so it is hard to study the potential correlation between the size of the gap and fracture healing.