Case Report and Literature Review of Multi-drugs Synergy and Targeted Comprehensive Treatment in Advanced Hepatocellular Carcinoma.

BACKGROUND: A 43-year-old female patient was found to have an abnormal liver function, abnormally elevated alpha-fetoprotein and space-occupying lesions in the liver on routine screening. The patient came to our hospital for further diagnosis and treatment. CASE PRESENTATION: Investigations: Laboratory investigations, digital subtraction angiography (DSA) of the hepatic artery, abdominal ultrasound examination, and magnetic resonance imaging (MRI) scan were conducted using pathological staining and immunohistochemistry. DIAGNOSIS: Clinical diagnosis: cT3NxM0. Barcelona clinic liver cancer (BCLC) staging: BCLC stage C. China liver cancer (CNLC) staging: CNLC IIIa. DISCUSSION: The patient was hospitalized for the first time for transcatheter arterial chemoembolization (TACE) and FOLFOX-based hepatic arterial infusion chemotherapy (HAIC). Then, the second and third hospital admissions were given HAIC based on FOLFOX. Camrelizumab and oncolytic virus were also injected into the liver cancer through the microcatheter in the first three treatments. On the fourth admission, the patient's indicators were improved, and the tumor shrank. Furthermore, as the patient suffered adverse reactions the first few times, we suspended the treatment of FOLFOX and the oncolytic virus. Before surgical treatment, lenvatinib was used throughout the treatment. On the fifth admission, the patient underwent liver cancer resection. CONCLUSION: It proves the value of multiple combination therapy, which can provide guidance for patients with advanced hepatocellular carcinoma that cannot be surgically removed.

Laboratory blood test profiling reveals distinct biochemical and hemocyte features of KRAS mutated non-small cell lung cancer.

Background: The testing for capability of some routine blood test parameters to reflect the biology of non-small cell lung carcinoma with different driver mutations is of great interest and practice significance. We aim to screen these variables and, if allowed, develop a novel predictive model based on results of these routine blood tests commonly performed in clinical practice to inform which can help doctors assess the patient's genetic mutation status as early as possible before surgery. Methods: For the exploration cohort, we included 1,595 patients who were diagnosed with non-small cell lung cancer (NSCLC) and genetically profiled by a next-generation sequencing panel in the First Affiliated Hospital of Guangzhou Medical University. The external validation cohort, which consists of 197 NSCLC cancer patients from Sun Yat-sen University Cancer Hospital, was subsequently established. Results: We analyzed the association between 46 frequently tested laboratory variables and different genetic mutation types. KRAS mutation was found to be a unique subtype that exclusively correlated with several blood parameters in our study. Least absolute shrinkage and selection operator (LASSO) regression was performed, and the following parameters were found to be significantly associated with KRAS mutation: triglycerides [odds ratio (OR) =1.63], arterial oxygen partial pressure (OR =0.97), uric acid (OR =1.01), basophil count (OR =1.41), eosinophil count (OR =1.146), fibrinogen (OR =1.42), standard bicarbonate (OR =0.85), high-density lipoprotein cholesterol (OR =0.18), alpha-L-fucosidase (OR =1.07). The areas under the receiver-operator characteristic curve in the training set and the external validation set were 0.85 [95% confidence interval (CI): 0.81-0.88] and 0.81 (95% CI: 0.71-0.91), respectively. Conclusions: We developed a non-invasive, more cost-effective predictive model of NSCLC based on routinely available variables, with practical predictive power. This model can be used as a practical screening tool to guide the use of more specialized and expensive molecular assays for KRAS mutation in NSCLC. However, further studies are warranted to investigate the mechanism underlying such association between KRAS mutations and the related parameters of blood tests.

Lung metastases after liver cancer resection cured by immunotherapy: case report and literature review.

The lung is the most common metastatic organ of primary liver cancer, accounting for 39.5-53.8% of extrahepatic metastasis, which seriously affects the prognosis of patients. In clinical treatment, it is difficult for one therapeutic schedule to achieve the desired effect sometimes, requiring two or even several combined methods for liver cancer lung metastasis. In this study, we report a liver cancer patient with lung metastases who received various combined therapies. However, the comprehensive treatment did not improve the patient's pulmonary metastasis symptoms until after the application of immunotherapy, and the lung metastases were gradually cured.

Development and validation of a clinical risk model to predict the hospital mortality in ventilated patients with acute respiratory distress syndrome: a population-based study.

BACKGROUND: Large variability in mortality exists in patients of acute respiratory distress syndrome (ARDS), especially those with invasive ventilation. The aim of this study was to develop a model to predict risk of in-hospital death in ventilated ARDS patients. METHODS: Ventilated patients with ARDS from two public databases (MIMIC-III and eICU-CRD) were randomly divided as training cohort and internal validation cohort. Least absolute shrinkage and selection operator (LASSO) and then Logistic regression was used to construct a predictive model with demographic, clinical, laboratory, comorbidities and ventilation variables ascertained at first 24 h of ICU admission and invasive ventilation. Our model was externally validated using data from another database (MIMIC-IV). RESULTS: A total of 1075 adult patients from MIMIC-III and eICU were randomly divided into training cohort (70%, n = 752) and internal validation cohort (30%, n = 323). 521 patients were included from MIMIC-IV. From 176 potential predictors, 9 independent predictive factors were included in the final model. Five variables were ascertained within the first 24 h of ICU admission, including age (OR, 1.02; 95% CI: 1.01-1.03), mean of respiratory rate (OR, 1.04; 95% CI: 1.01-1.08), the maximum of INR (OR, 1.14; 95% CI: 1.03-1.31) and alveolo-arterial oxygen difference (OR, 1.002; 95% CI: 1.001-1.003) and the minimum of RDW (OR, 1.17; 95% CI: 1.09-1.27). And four variables were collected within the first 24 h of invasive ventilation: mean of temperature (OR, 0.70; 95% CI: 0.57-0.86), the maximum of lactate (OR, 1.15; 95% CI: 1.09-1.22), the minimum of blood urea nitrogen (OR, 1.02; 95% CI: 1.01-1.03) and white blood cell counts (OR, 1.03; 95% CI: 1.01-1.06). Our model achieved good discrimination (AUC: 0.77, 95% CI: 0.73-0.80) in training cohort but the performance declined in internal (AUC: 0.75, 95% CI: 0.69-0.80) and external validation cohort (0.70, 95% CI: 0.65-0.74) and showed modest calibration. CONCLUSIONS: A risk score based on routinely collected variables at the start of admission to ICU and invasive ventilation can predict mortality of ventilated ARDS patients, with a moderate performance.

Dynamic monitoring serum tumor markers to predict molecular features of EGFR-mutated lung cancer during targeted therapy.

To reveal the correlation of dynamic serum tumor markers (STMs) and molecular features of epidermal growth factor receptor-mutated (EGFR-mutated) lung cancer during targeted therapy, we retrospectively reviewed 303 lung cancer patients who underwent dynamic STM tests [neuron-specific enolase (NSE), carcinoembryonic antigen (CEA), carbohydrate antigen 125 (CA125), carbohydrate antigen 153 (CA153), the soluble fragment of cytokeratin 19 (CYFRA21-1), and squamous cell carcinoma antigen (SCC)] and circulating tumor DNA (ctDNA) testing with a panel covering 168 genes. At baseline, patients with EGFR mutation trended to have abnormal CEA, abnormal CA153, and normal SCC levels. Additionally, patients with Thr790Met (T790M) mutation were more likely to have abnormal CEA levels than patients without T790M mutation. Among patients with secondary resistance to EGFR tyrosine kinase inhibitors (TKI), the dynamic STMs showed a descending trend in the responsive stage and a rising trend in the resistant stage. However, the changing slopes differed between T790M subgroup and the non-T790M subgroup in individual STMs. Our study demonstrated that the combination of baseline levels and variations of STMs (including the responsive stage and resistant stage) can be suggestive of secondary EGFR-T790M mutation [area under the curve (AUC) = 0.897] and that changing trends of STMs (within 8 weeks after initiating the TKI therapy) can be potential predictors for the clearance of EGFR ctDNA [AUC = 0.871]. In conclusion, dynamic monitoring STMs can help to predict the molecular features of EGFR-mutated lung cancer during targeted therapy.

Multi-Role Surface Modification of Single-Crystalline Nickel-Rich Lithium Nickel Cobalt Manganese Oxides Cathodes with WO3 to Improve Performance for Lithium-Ion Batteries.

Compared with the polycrystalline system, the single-crystalline ternary cathode material has better cycle stability because the only primary particles without grain boundaries effectively alleviate the formation of micro/nanocracks and retain better structural integrity. Therefore, it has received extensive research attention. There is no consistent result whether tungsten oxide acts as doping and/or coating from the surface modification of the polycrystalline system. Meanwhile, there is no report on the surface modification of the single-crystalline system by tungsten oxide. In this paper, multirole surface modification of single-crystalline nickel-rich ternary cathode material LiNi0.6Co0.2Mn0.2O2 by WO3 is studied by a simple method of adding WO3 followed by calcination. The results show that with the change in the amount of WO3 added, single-crystalline nickel-rich ternary cathode material can be separately doped, separately coated, and both doped and coated. Either doping or coating effectively enhances the structural stability, reduces the polarization of the material, and improves the lithium-ion diffusion kinetics, thus improving the cycle stability and rate performance of the battery. Interestingly, both doping and coating (for SC-NCM622-0.5%WO3) do not show a more excellent synergistic effect, while the single coating (for SC-NCM622-1.0%WO3) after eliminating the rock-salt phase layer performs the most excellent modification effect.

Comparison of first-generation EGFR-TKIs (gefitinib, erlotinib, and icotinib) as adjuvant therapy in resected NSCLC patients with sensitive EGFR mutations.

BACKGROUND: Several randomized controlled trials have suggested that adjuvant epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) were associated with prolonged disease-free survival (DFS) in EGFR-mutated NSCLC patients after radical resection, comparing with chemotherapy or placebo. We aimed to compare the effectiveness of different first-generation EGFR-TKIs as adjuvant treatment in real-world setting. METHODS: Early-stage EGFR mutated NSCLC patients who underwent radical resection and treated with first-generation EGFR-TKIs (gefitinib, erlotinib, icotinib) as adjuvant therapy between Feb 2010 and Jan 2019 were retrieved from a prospectively-maintained database in our center. The primary endpoint was DFS in stage II/III (TNM 8th) patients with exploratory endpoint regarding DFS in stage I patients. Sensitivity analyses were based on propensity score matched (PSM) cohorts. Treatment failure patterns among different TKIs were also compared. RESULTS: Of 588 eligible patients, 198 patients (33.7%) received gefitinib, 106 patients (17.9%) received erlotinib, and 284 patients (48.2%) received icotinib. The median DFS of stage II/III patients in the gefitinib, erlotinib and icotinib group were 36.1 months (95% CI, 23.9-49.4), 42.8 months (95% CI, 29.6-97.8), and 32.5 months (95% CI, 23.9-49.4), respectively, with no significant difference (log-rank test P=0.22). There was also no significant difference in DFS among stage I patients receiving different TKIs (P=0.12). PSM adjustments and multivariate analyses adjusting for other confounders revealed similar results. In addition, there were no significant differences in treatment failure pattens in different EGFR-TKI arms, especially in terms of brain metastases (6.1% in gefitinb, 7.5% in erlotinib, 3.9% in icotinib) and bone metastases (8.6% in gefitinb, 9.4% in erlotinib, 7.0% in icotinib). CONCLUSIONS: This first and largest real-world study showed that gefitinib, erlotinib, and icotinib demonstrated comparable clinical effectiveness as adjuvant therapy for patients with early-stage EGFR mutated NSCLC.

Early triage of critically ill COVID-19 patients using deep learning.

The sudden deterioration of patients with novel coronavirus disease 2019 (COVID-19) into critical illness is of major concern. It is imperative to identify these patients early. We show that a deep learning-based survival model can predict the risk of COVID-19 patients developing critical illness based on clinical characteristics at admission. We develop this model using a cohort of 1590 patients from 575 medical centers, with internal validation performance of concordance index 0.894 We further validate the model on three separate cohorts from Wuhan, Hubei and Guangdong provinces consisting of 1393 patients with concordance indexes of 0.890, 0.852 and 0.967 respectively. This model is used to create an online calculation tool designed for patient triage at admission to identify patients at risk of severe illness, ensuring that patients at greatest risk of severe illness receive appropriate care as early as possible and allow for effective allocation of health resources.

Development and Validation of a Clinical Risk Score to Predict the Occurrence of Critical Illness in Hospitalized Patients With COVID-19.

Importance: Early identification of patients with novel coronavirus disease 2019 (COVID-19) who may develop critical illness is of great importance and may aid in delivering proper treatment and optimizing use of resources. Objective: To develop and validate a clinical score at hospital admission for predicting which patients with COVID-19 will develop critical illness based on a nationwide cohort in China. Design, Setting, and Participants: Collaborating with the National Health Commission of China, we established a retrospective cohort of patients with COVID-19 from 575 hospitals in 31 provincial administrative regions as of January 31, 2020. Epidemiological, clinical, laboratory, and imaging variables ascertained at hospital admission were screened using Least Absolute Shrinkage and Selection Operator (LASSO) and logistic regression to construct a predictive risk score (COVID-GRAM). The score provides an estimate of the risk that a hospitalized patient with COVID-19 will develop critical illness. Accuracy of the score was measured by the area under the receiver operating characteristic curve (AUC). Data from 4 additional cohorts in China hospitalized with COVID-19 were used to validate the score. Data were analyzed between February 20, 2020 and March 17, 2020. Main Outcomes and Measures: Among patients with COVID-19 admitted to the hospital, critical illness was defined as the composite measure of admission to the intensive care unit, invasive ventilation, or death. Results: The development cohort included 1590 patients. the mean (SD) age of patients in the cohort was 48.9 (15.7) years; 904 (57.3%) were men. The validation cohort included 710 patients with a mean (SD) age of 48.2 (15.2) years, and 382 (53.8%) were men and 172 (24.2%). From 72 potential predictors, 10 variables were independent predictive factors and were included in the risk score: chest radiographic abnormality (OR, 3.39; 95% CI, 2.14-5.38), age (OR, 1.03; 95% CI, 1.01-1.05), hemoptysis (OR, 4.53; 95% CI, 1.36-15.15), dyspnea (OR, 1.88; 95% CI, 1.18-3.01), unconsciousness (OR, 4.71; 95% CI, 1.39-15.98), number of comorbidities (OR, 1.60; 95% CI, 1.27-2.00), cancer history (OR, 4.07; 95% CI, 1.23-13.43), neutrophil-to-lymphocyte ratio (OR, 1.06; 95% CI, 1.02-1.10), lactate dehydrogenase (OR, 1.002; 95% CI, 1.001-1.004) and direct bilirubin (OR, 1.15; 95% CI, 1.06-1.24). The mean AUC in the development cohort was 0.88 (95% CI, 0.85-0.91) and the AUC in the validation cohort was 0.88 (95% CI, 0.84-0.93). The score has been translated into an online risk calculator that is freely available to the public (http://118.126.104.170/). Conclusions and Relevance: In this study, a risk score based on characteristics of COVID-19 patients at the time of admission to the hospital was developed that may help predict a patient's risk of developing critical illness.

DNA methylation markers that correlate with occult lymph node metastases of non-small cell lung cancer and a preliminary prediction model.

BACKGROUND: Lymph node (LN) metastasis status is the most important prognostic factor and determines treatment strategy. Methylation alteration is an optimal candidate to trace the signal from early stage tumors due to its early existence, multiple loci and stability in blood. We built a diagnostic tool to screen and identify a set of plasma methylation markers in early stage occult LN metastasis. METHODS: High-throughput targeted methylation sequencing was performed on tissue and matched plasma samples from a cohort of 119 non-small cell lung cancer (NSCLC) patients with a primary lesion of less than 3.0 cm in diameter. The methylation profiles were compared between patients with and without occult LN metastases. We carried out a set of machine-learning analyses on our discovery cohort to evaluate the utility of cell free DNA methylation profiles in early detection of LN metastasis. Two preliminary prognostic models predictive of LN metastasis were built by random forest with differentially methylated markers shared by plasma and tissue samples and markers present either in plasma or tissue samples respectively. The performance of these models was then evaluated using receiver operating characteristic (ROC) statistics derived from ten-fold cross validation repeated ten times. RESULTS: Within this cohort, 27 cases (27/119, 22.7%) were found to have occult LN metastases found by pathological examination. Compared with those without metastases, 878 and 52 genes were differentially methylated in terms of tissue (MTA3, MIR548H4, HIST3H2A, etc.) and plasma (CIRBP, CHGB, FCHO1, etc.) respectively. 19 of these genes (ICAM1, EPH4, COCH, etc.) were overlapped. We selected 22 pairs of cases with or without occult LN metastasis by matching gender, age, smoking history and tumor histology to build and test the plasma model. The AUC of the preliminary prediction model using markers shared by plasma and tissue samples and markers present either in plasma or tissue samples is 88.6% (95% CI, 87.8-89.4%) and 74.9% (95% CI, 72.2-77.6%) respectively. CONCLUSIONS: We identified a set of specific plasma methylation markers for early occult LN metastasis of NSCLC and established a preliminary non-invasive blood diagnostic tool.

An annual review of the remarkable advances in lung cancer clinical research in 2019.

In recent years, lung cancer has become the most common cancer and the leading cause of deaths attributed to cancer. In China, lung cancer is the third leading cause of death after strokes and ischemic heart disease. This review aimed to provide an up-to-date summary of studies in regard to lung cancer in 2019 and to present the remarkable progress seen in lung cancer clinical research. A systematic search of PubMed and Web of Science for research published in 2019 was conducted using the search terms "lung cancer", "early stage", "advanced", "diagnosis", "treatment", or any combination of these terms. We selected 56 studies that we considered to be significant and have presented their major findings. In summary, survival among lung cancer patients was significantly improved compared with historical controls, turning lung cancer from an incurable disease into a chronic disease. In addition, treating lung cancer has become increasingly comprehensive, diversified, and individualized. Exploring the accurate biomarkers in immunotherapy and the mechanism of drug resistance in targeted therapy constitutes the greatest challenge at this stage.

Clinical characteristics and outcomes of hospitalised patients with COVID-19 treated in Hubei (epicentre) and outside Hubei (non-epicentre): a nationwide analysis of China.

BACKGROUND: During the outbreak of coronavirus disease 2019 (COVID-19), consistent and considerable differences in disease severity and mortality rate of patients treated in Hubei province compared to those in other parts of China have been observed. We sought to compare the clinical characteristics and outcomes of patients being treated inside and outside Hubei province, and explore the factors underlying these differences. METHODS: Collaborating with the National Health Commission, we established a retrospective cohort to study hospitalised COVID-19 cases in China. Clinical characteristics, the rate of severe events and deaths, and the time to critical illness (invasive ventilation or intensive care unit admission or death) were compared between patients within and outside Hubei. The impact of Wuhan-related exposure (a presumed key factor that drove the severe situation in Hubei, as Wuhan is the epicentre as well the administrative centre of Hubei province) and the duration between symptom onset and admission on prognosis were also determined. RESULTS: At the data cut-off (31 January 2020), 1590 cases from 575 hospitals in 31 provincial administrative regions were collected (core cohort). The overall rate of severe cases and mortality was 16.0% and 3.2%, respectively. Patients in Hubei (predominantly with Wuhan-related exposure, 597 (92.3%) out of 647) were older (mean age 49.7 versus 44.9 years), had more cases with comorbidity (32.9% versus 19.7%), higher symptomatic burden, abnormal radiologic manifestations and, especially, a longer waiting time between symptom onset and admission (5.7 versus 4.5 days) compared with patients outside Hubei. Patients in Hubei (severe event rate 23.0% versus 11.1%, death rate 7.3% versus 0.3%, HR (95% CI) for critical illness 1.59 (1.05-2.41)) have a poorer prognosis compared with patients outside Hubei after adjusting for age and comorbidity. However, among patients outside Hubei, the duration from symptom onset to hospitalisation (mean 4.4 versus 4.7 days) and prognosis (HR (95%) 0.84 (0.40-1.80)) were similar between patients with or without Wuhan-related exposure. In the overall population, the waiting time, but neither treated in Hubei nor Wuhan-related exposure, remained an independent prognostic factor (HR (95%) 1.05 (1.01-1.08)). CONCLUSION: There were more severe cases and poorer outcomes for COVID-19 patients treated in Hubei, which might be attributed to the prolonged duration of symptom onset to hospitalisation in the epicentre. Future studies to determine the reason for delaying hospitalisation are warranted.

Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis.

BACKGROUND: The coronavirus disease 2019 (COVID-19) outbreak is evolving rapidly worldwide. OBJECTIVE: To evaluate the risk of serious adverse outcomes in patients with COVID-19 by stratifying the comorbidity status. METHODS: We analysed data from 1590 laboratory confirmed hospitalised patients from 575 hospitals in 31 provinces/autonomous regions/provincial municipalities across mainland China between 11 December 2019 and 31 January 2020. We analysed the composite end-points, which consisted of admission to an intensive care unit, invasive ventilation or death. The risk of reaching the composite end-points was compared according to the presence and number of comorbidities. RESULTS: The mean age was 48.9 years and 686 (42.7%) patients were female. Severe cases accounted for 16.0% of the study population. 131 (8.2%) patients reached the composite end-points. 399 (25.1%) reported having at least one comorbidity. The most prevalent comorbidity was hypertension (16.9%), followed by diabetes (8.2%). 130 (8.2%) patients reported having two or more comorbidities. After adjusting for age and smoking status, COPD (HR (95% CI) 2.681 (1.424-5.048)), diabetes (1.59 (1.03-2.45)), hypertension (1.58 (1.07-2.32)) and malignancy (3.50 (1.60-7.64)) were risk factors of reaching the composite end-points. The hazard ratio (95% CI) was 1.79 (1.16-2.77) among patients with at least one comorbidity and 2.59 (1.61-4.17) among patients with two or more comorbidities. CONCLUSION: Among laboratory confirmed cases of COVID-19, patients with any comorbidity yielded poorer clinical outcomes than those without. A greater number of comorbidities also correlated with poorer clinical outcomes.

PD-L1 expression with respect to driver mutations in non-small cell lung cancer in an Asian population: a large study of 1370 cases in China.

BACKGROUND: Programmed cell death ligand 1 (PD-L1) expression with respect to genetic alternations has not been well established in non-small cell lung cancer (NSCLC), especially in the Asian population. METHODS: We reviewed 1370 NSCLC patients from a prospectively maintained database. Immunohistochemistry was performed on tumor cells and tumor-infiltrating lymphocytes (TILs) using the VENTANA (SP142) anti-PD-L1 antibody. The tumor proportion score (TPS) cutoff values were set at ⩾1% and ⩾50%, and the immune proportion score (IPS) cutoff values were set at ⩾1% and ⩾10%. RESULTS: In tumor cells, PD-L1 positivity was observed in 405 (29.6%), 122 (8.9%), and 27 (2.0%) patients with TPS cutoff values at ⩾1% and ⩾50%. Contrastingly, TILs of 1154 (84.2%) and 346 (25.3%) patients stained positive at IPS cutoff values of ⩾1% and ⩾50%, respectively. PD-L1 expression was more common in patients who were mutation-negative irrespective of the TPS cutoff values and tumor size. PD-L1 expression in tumor cells was less frequent in patients harboring EGFR mutations (18.8% TPS ⩾ 1% and 4.6% TPS ⩾ 50%). Conversely, PD-L1 expression was high in the presence of KRAS mutations (47.3% TPS ⩾ 1% and 22.5% TPS ⩾ 50%). Overall, KRAS, BRAF, PICK3A, MET mutations and ROS1 and RET translocations were more frequent, while EGFR and HER2 mutations and ALK translocations were less frequent compared with the overall PD-L1 expression levels. Although the difference between TILs among the PD-L1-positive cases was comparatively small, PD-L1 positivity was less prevalent in EGFR-mutated tumors and more common in those with KRAS mutations, ROS1 translocations, BRAF mutations, or MET mutations. CONCLUSION: Our study showed the heterogeneity in PD-L1 expression with respect to nine major oncogenic drivers in China. Future studies are warranted to further clarify the association between PD-L1 expression and driver mutations in NSCLC.

Impact of examined lymph node counts on survival of patients with stage IA non-small cell lung cancer undergoing sublobar resection.

BACKGROUND: The correlation between the number of examined lymph nodes (ELNs) and lung cancer-specific survival (LCSS) of stage IA non-small cell lung cancer (NSCLC) patients, who underwent sublobar resection in which lymph node (LN) sampling was relatively restricted as compared with standard lobectomy remains unclear. METHODS: Patients from the Surveillance, Epidemiology, and End Results database with stage IA NSCLC who underwent sublobar resection were categorized based on ELN count (1-6 vs. ≥7; the cut point 7 was identified by Cox model). RESULTS: Collectively, 3,219 patients with a median follow-up time of 37 months were included in this study (G1: 1-6 ELN, n=2,410; G2: ≥7 ELN, n=809). The 5-year LCSS rate of the G1 and G2 cohorts were 75% and 83%, respectively. Cox analysis suggested that the LCSS of G1 cohort patients was lower as compared with the G2 cohort [hazard ratio (HR) =1.530; 95% confidence interval (CI): 1.240-1.988, P<0.001). Propensity score analysis also showed decreased survival of the matched G1 cohort (HR =1.499; 95% CI: 1.176-1.911; P=0.001). CONCLUSIONS: The data suggested the ELNs ≤6 were associated with poor prognoses. Adequate LN sampling is essential even for stage IA NSCLC patients undergoing sublobar resection.

Risk Factors Associated with Peer Victimization and Bystander Behaviors among Adolescent Students.

Despite the prevalence of the phenomena of peer victimization and bystander behaviors, little data has generated to describe their relationships and risk factors. In this paper, a self-administered survey using a cross-sectional cluster-random sampling method in a sample of 5450 participants (2734 girls and 2716 boys) between 4th and 11th grades was conducted at six schools (two primary schools and four middle schools) located in Shantou, China. Self-reported peer victimization, bystander behaviors and information regarding parents' risky behaviors and individual behavioral factors were collected. Multinomial logistic regression analysis was applied to evaluate risk factors affecting peer victimization and bystander behaviors. The results indicated that urban participants were more likely to become bullying victims but less likely to become passive bystanders. Contrarily, bullying victimization was related to the increasing of passive bystander behaviors. Father drinking and mother smoking as independent factors were risk factors for peer victimization. Participants who were smoking or drinking had a tendency to be involved in both peer victimization and passive bystander behaviors. This study suggested that bystander behaviors, victims' and parents' educations play a more important role in peer victimization than previously thought.

The application of the grey disaster model to forecast epidemic peaks of typhoid and paratyphoid fever in China.

OBJECTIVE: The objectives of this study were to forecast epidemic peaks of typhoid and paratyphoid fever in China using the grey disaster model, to evaluate its feasibility of predicting the epidemic tendency of notifiable diseases. METHODS: According to epidemiological features, the GM(1,1) model and DGM model were used to build the grey disaster model based on the incidence data of typhoid and paratyphoid fever collected from the China Health Statistical Yearbook. Model fitting accuracy test was used to evaluate the performance of these two models. Then, the next catastrophe date was predicted by the better model. RESULTS: The simulation results showed that DGM model was better than GM(1,1) model in our data set. Using the DGM model, we predicted the next epidemic peak time will occur between 2023 to 2025. CONCLUSION: The grey disaster model can predict the typhoid and paratyphoid fever epidemic time precisely, which may provide valuable information for disease prevention and control.