RESUMO
BACKGROUND: The presence of liver metastasis (LM) is an independent prognostic factor for shorter survival in non-small cell lung cancer (NSCLC) patients. The median overall survival of patients with involvement of the liver is less than 5 mo. At present, identifying prognostic factors and constructing survival prediction nomogram for NSCLC patients with LM (NSCLC-LM) are highly desirable. AIM: To build a forecasting model to predict the survival time of NSCLC-LM patients. METHODS: Data on NSCLC-LM patients were collected from the Surveillance, Epidemiology, and End Results database between 2010 and 2018. Joinpoint analysis was used to estimate the incidence trend of NSCLC-LM. Kaplan-Meier curves were constructed to assess survival time. Cox regression was applied to select the independent prognostic predictors of cancer-specific survival (CSS). A nomogram was established and its prognostic performance was evaluated. RESULTS: The age-adjusted incidence of NSCLC-LM increased from 22.7 per 1000000 in 2010 to 25.2 in 2013, and then declined to 22.1 in 2018. According to the multivariable Cox regression analysis of the training set, age, marital status, sex, race, histological type, T stage, metastatic pattern, and whether the patient received chemotherapy or not were identified as independent prognostic factors for CSS (P < 0.05) and were further used to construct a nomogram. The C-indices of the training and validation sets were 0.726 and 0.722, respectively. The results of decision curve analyses (DCAs) and calibration curves showed that the nomogram was well-discriminated and had great clinical utility. CONCLUSION: We designed a nomogram model and further constructed a novel risk classification system based on easily accessible clinical factors which demonstrated excellent performance to predict the individual CSS of NSCLC-LM patients.
RESUMO
A partially coherent light source called a hollow rectangular multi-Gaussian Schell-model array (HRMGSMA) is introduced. The relations between the spectral density of the far field and the characteristics of the source are discussed in detail. It is shown that the characteristics of the arrays, including the hollow size, shapes of the arrays and lobes, quantities of rings and lobes, and directions of lobes, can be adjusted flexibly by changing the related parameters of the HRMGSMA source.
RESUMO
Ependymomas arise from ependymal cells lining the ventricles and central canal of the spinal cord and can occur throughout the whole neuraxis. The lesion rarely occurs in extracranial or extraspinal regions, particularly in the uterine broad ligament. Thus, for the pathogenesis of nonsacral extra-central nervous system (CNS) ependymomas remains elusive. Here, we describe a rare case of primary uterine broad ligament. ependymoma with cell-cycle-checkpoint kinase 2 (CHEK2) p.H371Y germline mutation. A 45-year-old woman presented with a uterine mass. The transvaginal sonographic examination confirmed a 4.4 cm × 3.7 cm, cystic and solid, mass located on the right side uterine wall near isthmus. First, laparoscopy with the neoplasm resection was carried out. Based on morphological and immunohistochemical characteristics of tumor cells that expressed glial fibrillary acidic protein (GFAP), S-100, and vimentin, the tumor was diagnosed as an ependymoma. After that, she underwent a laparotomic total hysterectomy, bilateral salpingo-oophorectomy, and lymphadenectomy. Furthermore, we performed next-generation sequencing (NGS) of the patient's resected tumor tissue and peripheral blood and identified a novel CHEK2 p.H371Y germline mutation. Following surgery, the patient received oral tamoxifen (10 mg 2/day) and followed by letrozole (2.5 mg/day) for 6 months. The patient remained disease-free after 4 years of follow-up. Conceivably, CHEK2 p.H371Y is a driving gene for the development of extra-CNS ependymoma.
