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Objectives: To identify factors affecting the development of drug‐resistant epilepsy (DRE), and establish a reliable nomogram to predict DRE development in post‐traumatic epilepsy (PTE) patients. Methods: This study conducted a retrospective clinical analysis in patients with PTE who visited the Epilepsy Center, Beijing Tiantan Hospital from January 2013 to December 2018. All participants were followed up for at least 3 years, and the development of DRE was assessed. Data from January 2013 to December 2017 were used as development dataset for model building. Those independent predictors of DRE were included in the final multivariable logistic regression, and a derived nomogram was built. Data from January 2018 to December 2018 were used as validation dataset for internal validation. Results: Complete clinical information was available for 2830 PTE patients (development dataset: 2023; validation dataset: 807), of which 21.06% (n = 596) developed DRE. Among all parameters of interest including gender, age at PTE, family history, severity of traumatic brain injury (TBI), single or multiple injuries, lesion location, post‐TBI treatments, acute seizures, PTE latency, seizure type, status epilepticus (SE), and electroencephalogram (EEG) findings, four predictors showed independent effect on DRE, they were age at PTE, seizure type, SE, and EEG findings. A model incorporating these four variables was created, and a nomogram to calculate the probability of DRE using the coefficients of the model was developed. The C‐index of the predictive model and the validation was 0.662 and 0.690, respectively. The goodness‐of‐fit test indicated good calibration for model development and validation (p = 0.272, 0.572). Conclusions: The proposed nomogram achieved significant potential for clinical utility in the prediction of DRE among PTE patients. The risk of DRE for individual PTE patients can be estimated by using this nomogram, and identified high‐risk patients might benefit from non‐pharmacological therapies at an early stage. [ABSTRACT FROM AUTHOR]

Background: Colorectal cancer (CRC) has a high worldwide incidence with a tendency to metastasize to the lungs. We aimed to identify clinical factors related to lung metastasis (LM) and analyze the prognosis of patients after LM. Methods: Multivariate logistic regression analysis was used to identify risk factors for LM from CRC. Univariate and multivariate Cox proportional hazard models were performed to identify potentially important prognostic factors for patients with LM. Results: Age (p = 0.010), tumor size (p < 0.001), T stage (p < 0.001), N stage (p < 0.001), race (p < 0.001), tumor site (p < 0.001), liver metastasis (p < 0.001), brain metastasis (p < 0.001), bone metastasis (p < 0.001), serum levels of carcinoembryonic antigen (CEA) (p < 0.001), and circumferential resection margin (CRM) (p < 0.001) were associated with a risk of LM from CRC. All factors (all, p < 0.001) except tumor size (p = 0.095) and race (p = 0.650) were related to the overall survival of patients. Two nomograms were formulated to visually predict lung metastasis risk and 1-, 3-, and 5- year overall survivals for patients with LM. The concordance indices were 0.754 and 0.749, respectively. Conclusions: Age, tumor size, histological grade, serum levels of CEA, tumor site, surgery modalities of CRC, CRM, number of positive lymph nodes, and chemotherapy were independent risk factors for LM from CRC. The nomograms we developed can be effectively used to forecast the risk of LM and predict the survival for LM from CRC. [ABSTRACT FROM AUTHOR]

Abstract: Previous studies have identified potential risk factors for pulmonary carcinoid tumors and evaluated the effect of various treatments; however, the results were not entirely consistent. We conducted a population‐based study to further explore relevant prognostic issues. We extracted cases with pulmonary carcinoid tumors from the Surveillance Epidemiology and End Results database. Cox proportional hazard regression was utilized to identify potential significant risk factors, which helped establish a nomogram for predicting long‐term survival. Survival analysis and a competing risk study were conducted to evaluate the value of different surgical approaches. There were 7057 cases included in the study. Univariate and multivariate analyses showed that age, sex, tumor size, stage, histology, surgical type, chemotherapy, and radiation therapy were all significant prognostic factors. A nomogram with good accuracy for predicting 10‐year survival was formulated. Furthermore, patients who had undergone surgery had a significantly better survival than those who did not undergo surgery. There was no significant prognostic difference between lobectomy and sublobectomy stratified by tumor stage; however, lobectomy was associated with a significantly better survival in atypical tumors, especially those with regional disease. Our research identified possible risk factors in a large cohort and constructed a nomogram to visually predict 10‐year survival of pulmonary carcinoid tumors. We showed that lobectomy and sublobectomy should be considered as the mainstay of treatment, especially lobectomies for atypical tumor. [ABSTRACT FROM AUTHOR]

Background: FBXO11, a member of the F-box protein family, regulates the cell-cycle by promoting the degradation of Bcl-6 and p53. This protein has been implicated in the progression of several cancers, including renal cell carcinoma (RCC). The aim of this study was to determine the prognostic role of FBXO11 in the clinical outcome of RCC patients.Methods: FBXO11 mRNA expression was analysed in normal and RCC tissue microarrays of the Oncomine database. In addition, the in situ expression levels of stromal FBXO11 protein were assessed in primary RCC tissues from 227 patients (training and validation cohorts) using immunohistochemistry (IHC). Kaplan Meier and Cox regression analyses were used to determine the association between FBXO11 expression and cliniopathological factors. A nomogram was established using the significant prognostic factors to predict overall survival (OS) of RCC patients after one, three and 5 years.Results: In the Oncomine database, FBXO11 mRNA levels were lower in normal tissues than in cancer tissues, including clear cell renal cell carcinoma (ccRCC), papillary renal cell carcinoma (pRCC), hereditary ccRCC, non-hereditary ccRCC, VHL mutant ccRCC and VHL wild-type ccRCC. In addition, FBXO11 expression was also significantly higher in metastatic kidney cancer than in primary cancer. Immunohistochemical analysis reported that 57.3% (86 of 150) of the training cohort and 57.1% (44 of 77) of the validation cohort were scored as having high FBXO11 staining density. FBXO11 expression was significantly associated with Fuhrman grade (p = 0.003), UISS score (p = 0.021) and age (p = 0.048) in the training cohort. Furthermore, Kaplan-Meier survival analysis showed that higher FBXO11 levels, T stage, UISS scores and SSIGN score were associated with poor OS in ccRCC patients. Multivariate Cox analysis demonstrated that higher FBXO11 levels and higher UISS score were independent prognostic indicators for OS. Nomogram, calibration plots, AUC values and the C-index showed that the predictive accuracy of conventional prognostic models, including UISS score and SSIGN score, was improved when FBXO11 expression was added.Conclusions: FBXO11 expression was closely related to RCC malignancy and poor prognosis, indicating its potential as a prognostic marker as well as a therapeutic target for RCC. [ABSTRACT FROM AUTHOR]