Prognostic prediction and comparison of three staging programs for patients with advanced (T2-T4) esophageal squamous carcinoma after radical resection.

Purpose: Lymph node-based staging protocols are frequently employed to evaluate the prognosis of esophageal cancer, yet their accuracy remains contentious. The present study was conducted to assess the prognostic significance of three lymph node staging systems, namely N stage, lymph node rate (LNR), and log odds of positive lymph nodes (LODDS), in patients diagnosed with advanced (T2-T4) esophageal squamous cell carcinoma (ESCC). Methods: This cohort comprised 319 eligible patients, with an additional 409 individuals retrieved from the Surveillance, Epidemiology, and End Results (SEER) database, forming the validation cohort. Differences in overall survival (OS) of patients between groups were assessed using the log-rank test. Prognostic independent risk variables were identified, and lymph nodes (LN) prognostic models were built using multivariate Cox regression analysis. Besides, the predictive accuracy of each model was evaluated utilizing the (-2) log-likelihood ratio (-2LLR), the likelihood ratio χ2 score (LRχ2), the Akaike information criterion (AIC), and Harrell's concordance index (C-index). To further evaluate the potential superiority of the model, a nomogram was constructed for comparison with the conventional Tumor Node Metastasis (TNM) staging approach. Results: Independent prognostic factors for advanced ESCC include the N stage, LNR, and LODDS. Herein, LODDS presented higher values for C-index and LRχ2, and lower values for AIC and -2LLR in OS compared to the others. Consequently, a nomogram was constructed based on LODDS. Calibration curves exhibited strong agreement, and assessment through C-index, receiver operating characteristic (ROC) curves, and clinical decision curve analysis (DCA) demonstrated promising clinical applicability. Conclusion: LODDS emerges as a promising future prognostic indicator. After surgery, the proposed model holds the potential to provide valuable treatment recommendations for patients with advanced ESCC.

Identification of Crucial Genes and Signaling Pathways in Alectinib-Resistant Lung Adenocarcinoma Using Bioinformatic Analysis.

Alectinib, a second-generation anaplastic lymphoma kinase (ALK) inhibitor, has been shown to be effective for patients with ALK-positive non-small cell lung cancer (NSCLC). However, alectinib resistance is a serious problem worldwide. To the best of our knowledge, little information is available on its molecular mechanisms using the Gene Expression Omnibus (GEO) database. In this study, the differentially expressed genes (DEGs) were selected from the gene expression profile GSE73167 between parental and alectinib-resistant human lung adenocarcinoma (LUAD) cell samples. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Gene Ontology (GO) annotation enrichment analyses were conducted using Database for Annotation, Visualization and Integrated Discovery (DAVID). The construction of protein-protein interaction (PPI) network was performed to visualize DEGs. The hub genes were extracted based on the analysis of the PPI network using plug-in cytoHubba of Cytoscape software. The functional roles of the key genes were investigated using Gene Expression Profiling Interactive Analysis (GEPIA), University of Alabama at Birmingham Cancer (UALCAN), Gene Set Enrichment Analysis (GSEA), and Tumor Immune Estimation Resource (TIMER) analysis. The networks of kinase, miRNA, and transcription-factor targets of SFTPD were explored using LinkedOmics. The drug sensitivity analysis of SFTPD was analyzed using the RNAactDrug database. Results showed a total of 144 DEGs were identified. Five hub genes were extracted, including mucin 5B (MUC5B), surfactant protein D (SFTPD), deleted in malignant brain tumors 1 (DMBT1), surfactant protein A2 (SFTPA2), and trefoil factor 3 (TFF3). The survival analysis using GEPIA displayed that low expression of SFTPD had a significantly negative effect on the prognosis of patients with LUAD. GSEA revealed that low expression of SFTPD was positively correlated with the pathways associated with drug resistance, such as DNA replication, cell cycle, drug metabolism, and DNA damage repair, including mismatch repair (MMR), base excision repair (BER), homologous recombination (HR), and nucleotide excision repair (NER). The SFTPD expression was negatively correlated with the drug sensitivity of alectinib according to RNAactDrug database. The expression of SFTPD was further validated in parental H3122 cells and alectinib-resistant H3122 cells by quantitative reverse transcription PCR (RT-qPCR). In conclusion, our study found that the five hub genes, especially low expression of SFTPD, are closely related to alectinib resistance in patients with LUAD.

Multi-scale dense selective network based on border modeling for lung nodule segmentation.

PURPOSE: Accurate quantification of pulmonary nodules helps physicians to accurately diagnose and treat lung cancer. We try to improve the segmentation efficiency of irregular nodules while maintaining the segmentation accuracy of simple types of nodules. METHODS: In this paper, we obtain the unique edge part of pulmonary nodules and process it as a single branch stream, i.e., border stream, to explicitly model the nodule edge information. We propose a multi-scale dense selective network based on border modeling (BorDenNet). Its overall framework consists of a dual-branch encoder-decoder, which achieves parallel processing of classical image stream and border stream. We design a dense attention module to facilitate a strongly coupled status of feature images to focus on key regions of pulmonary nodules. Then, during the process of model decoding, the multi-scale selective attention module is proposed to establish long-range correlation relationships between different scale features, which further achieves finer feature discrimination and spatial recovery. We introduce border context enhancement module to mutually fuse and enhance the edge-related voxel features contained in the image stream and border stream and finally achieve the accurate segmentation of pulmonary nodules. RESULTS: We evaluate the BorDenNet rigorously on the lung public dataset LIDC-IDRI. For the segmentation of the target nodules, the average Dice score is 92.78[Formula: see text], the average sensitivity is 91.37[Formula: see text], and the average Hausdorff distance is 3.06 mm. We further test on a private dataset from Shanxi Provincial People's Hospital, which verifies the excellent generalization of BorDenNet. Our BorDenNet relatively improves the segmentation efficiency for multi-type nodules such as adherent pulmonary nodules and ground-glass pulmonary nodules. CONCLUSION: Accurate segmentation of irregular pulmonary nodules can obtain important clinical parameters, which can be used as a guide for clinicians and improve clinical efficiency.

Static-Dynamic coordinated Transformer for Tumor Longitudinal Growth Prediction.

Accurate prediction of the tumor's future imaging features can provide its complete growth evolution and more detailed clinical parameters. The existing longitudinal models tend to lose detailed growth information and make it difficult to model the complete tumor development process. In this paper, we propose the Static-Dynamic coordinated Transformer for Tumor Longitudinal Growth Prediction (SDC-Transformer). To extract the static high-level features of tumors in each period, and to further explore the dynamic growth associations and expansion trend of tumors between different periods. Aiming at the insensitivity to local pixel information of the Transformer, we propose the Local Adaptive Transformer Module to facilitate a strongly coupled status of feature images, which ensures the characterization of tumor complex growth trends. Faced with the dynamic changes brought about by tumor growth, we introduce the Dynamic Growth Estimation Module to predict the future growth trend of the tumor. As a core part of SDC-Transformer, we design the Enhanced Deformable Convolution to enrich the sampling space of tumor growth pixels. And a novel Cascade Self-Attention is performed under multi-growth imaging to obtain dynamic growth relationships between periods and use dual cascade operations to predict the tumor's future expansion trajectories and growth contours. Our SDC-Transformer is rigorously trained and tested on longitudinal tumor data composed of the National Lung Screening Trial (NLST) and collaborative Shanxi Provincial People's Hospital. The RMSE, Dice, Recall, and Specificity of the longitudinal prediction results reach 11.32, 89.31%, 90.57%, and 89.64%, respectively. This result shows that our proposed SDC-Transformer model can achieve accurate longitudinal prediction of tumors, which will help physicians to establish specific treatment plans and accurately diagnose lung cancer. The code will be released soon.

PET and CT Image Fusion of Lung Cancer With Siamese Pyramid Fusion Network.

Background: The fusion of PET metabolic images and CT anatomical images can simultaneously display the metabolic activity and anatomical position, which plays an indispensable role in the staging diagnosis and accurate positioning of lung cancer. Methods: In order to improve the information of PET-CT fusion image, this article proposes a PET-CT fusion method via Siamese Pyramid Fusion Network (SPFN). In this method, feature pyramid transformation is introduced to the siamese convolution neural network to extract multi-scale information of the image. In the design of the objective function, this article considers the nature of image fusion problem, utilizes the image structure similarity as the objective function and introduces L1 regularization to improve the quality of the image. Results: The effectiveness of the proposed method is verified by more than 700 pairs of PET-CT images and elaborate experimental design. The visual fidelity after fusion reaches 0.350, the information entropy reaches 0.076. Conclusion: The quantitative and qualitative results proved that the proposed PET-CT fusion method has some advantages. In addition, the results show that PET-CT fusion image can improve the ability of staging diagnosis compared with single modal image.

Three-Dimensional Computed Tomography Bronchography and Angiography-Guided Thoracoscopic Segmentectomy for Pulmonary Nodules.

BACKGROUND: Three-dimensional computed tomography bronchography and angiography (3D-CTBA) provides detailed imaging information for pulmonary segmentectomy. This study was performed to verify the feasibility of 3D-CTBA-guided thoracoscopic segmentectomy for the treatment of pulmonary nodules. METHODS: A retrospective analysis was performed on all patients who underwent 3D-CTBA-guided uniport thoracoscopic segmentectomies or subsegmentectomies for pulmonary nodules in the period from May 2019 to May 2020. All of the information related to perioperative management and surgical operations was retrieved from the medical records and operating notes for detailed analysis. RESULTS: A total of 104 eligible operations involving the resection of 110 nodules with diameters in the range of 5-20 mm were included. Under 3D-CTBA guidance, the pulmonary nodules were located with an accuracy of 100% (110/110) and the median resection margin was 24.3 mm (17-33 mm). Additionally, the segmental (subsegmental) bronchi, arteries, and veins were identified with accuracy rates of 100% (104/104), 96.2% (100/104), and 94.2% (98/104), respectively. The postoperative complications consisted of 3 cases of pulmonary infection (2.9%), 6 cases of arrhythmia (5.8%), 2 cases of hemoptysis (1.9%), 4 cases of air leak (3.8%), and 2 cases of subcutaneous emphysema (1.9%). No perioperative death occurred. CONCLUSION: 3D-CTBA-guided thoracoscopic segmentectomy is an effective surgical approach for the management of pulmonary nodules.

Best Supportive Care Versus Whole-Brain Irradiation, Chemotherapy Alone, or WBRT Plus Chemotherapy in Patients With Brain Metastases From Small-Cell Lung Cancer: A Case-Controlled Analysis.

BACKGROUND: WBRT and systemic chemotherapy are the mainstay treatments for small-cell lung cancer (SCLC) brain metastases (BM). However, current recommendations are mainly based on evidence from retrospective analyses. A recent randomized trial found no benefits from WBRT compared with best supportive care (BSC) in patients with more than three BM from non-small-cell lung cancer (NSCLC). Herein, we aimed to evaluate the roles of WBRT and chemotherapy further in the management of BM from SCLC. MATERIALS AND METHODS: There were 698 patients with BM from SCLC included. Of these, 580 received anti cancer treatment (Group 1), including 178 who received WBRT only (Group 1a), 129 who received chemotherapy only (Group 1b), and 273 who received WBRT plus chemotherapy (Group 1c). The other 118 received BSC (Group 2). Propensity score matching (PSM) analysis was used to compare Group 2 with each of the other groups. RESULTS: After PSM, compared with Group 2 (n = 118), patients in Group 1 (n = 440) had a prolonged overall survival (OS) in both univariate and multivariate tests, with a median survival time of 10 months (95% CI = 9-11) in Group 1 and 3.5 months (95% CI = 2-7) in Group 2 (p < 0.001). In subgroup analyses, patients who received WBRT plus chemotherapy were more likely to benefit from treatment (p < 0.001). Chemotherapy alone or WBRT alone did not show survival benefits. CONCLUSION: WBRT plus chemotherapy improved OS in patients with BM from SCLC as compared to BSC. Chemotherapy alone and WBRT alone did not show survival benefits. This retrospective study suggests that SCLC patients with BM who receive WBRT combined with chemotherapy have a better outcome than those receiving BSC alone.

Effectiveness and postoperative pain level of single-port versus two-port thoracoscopic lobectomy for lung cancer: a retrospective cohort study.

OBJECTIVES: Single-port thoracoscopic lobectomy is a new therapeutic technique for patients with lung cancer; however, insufficient data are available regarding its clinical outcomes. We therefore compared the clinical outcomes of single-port and two-port thoracoscopic lobectomies for lung cancer. METHODS: We retrospectively analyzed and compared the data of 204 and 368 patients with lung cancer who underwent single-port or two-port thoracoscopic lobectomy, respectively, between October 2014 and October 2017 at our institution. Patients in both groups underwent 1:1 propensity score matching, and 400 patients (200 patients in each group) were included. Perioperative clinical indicators were analyzed, including operation time, lymph node dissection stations and numbers, incidence of postoperative complications, and pain scores at 24 h, 72 h, and 1 week after surgery. RESULTS: No perioperative deaths occurred in either group. The operation time, intraoperative blood loss, chest drainage duration, duration of postoperative hospital stay, lymph node dissection station and number, rate of conversion to open surgery, number of ruptured intraoperative pulmonary vessel, and incidence of postoperative complications were not significantly different between the groups (all P > 0.05). However, analysis of the 24-h (P = 0.005), 72-h (P = 0.011), and 1-week (P = 0.034) visual analog scale score after surgery revealed that the postoperative pain levels were significantly lower in the single-port than in the two-port group. CONCLUSIONS: Single-port and two-port thoracoscopic lobectomies had similar perioperative outcomes, although the postoperative pain was lower after single-port than two-port thoracoscopic lobectomy. Hence, we concluded that single-port thoracoscopic lobectomy is an effective, minimally invasive, and promising surgical procedure.

The Clinical Prognostic Value of the Neutrophil-to-Lymphocyte Ratio in Brain Metastases from Non-Small Cell Lung Cancer-Harboring EGFR Mutations.

PURPOSE: Several studies have explored the correlation between the neutrophil-to-lymphocyte ratio (NLR) and the prognosis of patients with lung cancer. However, little is known about the correlation between the pretreatment NLR and the prognosis of patients with brain metastases from non-small cell lung cancer (NSCLC)-harboring mutations in the epidermal growth factor receptor (EGFR) gene. We sought to evaluate the predictive values in brain metastasis from lung adenocarcinoma with EGFR mutations. METHODS: We retrospectively examined 133 patients with brain metastases (BMs) from lung adenocarcinoma with EGFR mutations. NLR was calculated using N/L, where N and L, respectively, refer to peripheral blood neutrophil (N) and lymphocyte (L) counts. The cut-off value of NLR was assessed by the area under the curve (AUC). The Log rank test and Cox proportional hazard model were used to confirm the impact of NLR and other variables on survival. RESULTS: An NLR value equal to or less than 2.99 was associated with prolonged survival in this cohort of patients in both variable and multivariable analysis. CONCLUSION: We concluded that NLR is an independent prognostic factor in BMs from lung adenocarcinoma with EGFR mutations. This could serve as a useful prognostic biomarker and could be incorporated in the clinical prognostic index specific to patients with BMs.

Ensemble classification for predicting the malignancy level of pulmonary nodules on chest computed tomography images.

Early identification and classification of pulmonary nodules are essential for improving the survival rates of individuals with lung cancer and are considered to be key requirements for computer-assisted diagnosis. To address this topic, the present study proposed a method for predicting the malignant phenotype of pulmonary nodules based on weighted voting rules. This method used the pulmonary nodule regions of interest as the input data and extracted the features of the pulmonary nodules using the Denoising Auto Encoder, ResNet-18. Moreover, the software also modifies texture and shape features to assess the malignant phenotype of the pulmonary nodules. Based on their classification accuracy (Acc), the different classifiers were assigned to different weights. Finally, an integrated classifier was obtained to score the malignant phenotype of the pulmonary nodules. The present study included training and testing experiments conducted by extracting the corresponding lung nodule image data from the Lung Image Database Consortium-Image Database Resource Initiative. The results of the present study indicated a final classification Acc of 93.10±2.4%, demonstrating the feasibility and effectiveness of the proposed method. This method includes the powerful feature extraction ability of deep learning combined with the ability to use traditional features in image representation.

Comparative study of three types of lymphadenectomy along the left recurrent laryngeal nerve by minimally invasive esophagectomy.

BACKGROUND: The objective of this study was to compare three kinds of lymphadenectomy methods along the recurrent laryngeal nerve (RLN) and assess the safety and effectiveness of the new method. METHODS: A total of 194 patients with esophageal cancer who underwent minimally invasive esophagectomy (MIE) at our institution from May 2013 to May 2017 were analyzed retrospectively. According to the method of lymphadenectomy along the left RLN, the patients were divided into three groups: 75 cases underwent the conventional method (A group), 80 cases the skeletonized method (B group) and 39 cases the modified Bascule method (C group). The number of dissected lymph nodes and surgical outcomes were recorded and compared to identify differences among the three groups. RESULTS: The frequency of metastasis to the LRLN lymph node was 18.6% among all patients, and 12%, 20% and 28% in groups A, B and C, respectively. The number of harvested lymph nodes (total/chest/LRLN/LRLN+) in group B and group C were significantly greater than that of group A, but not significant between group B and group C. The hoarseness rate in group C was 15.4%, which was lower than the rate in group B (21.3%) and higher than the rate in group A (13.3%), but there was no statistical significance. CONCLUSIONS: The new method for lymphadenectomy along the left RLN during MIE in the semi-prone position is safe and reliable. It provides sufficient lymph node dissection along the left RLN.

Applicability of graded prognostic assessment of lung cancer using molecular markers to lung adenocarcinoma patients with brain metastases.

Several scoring systems are available to estimate prognosis and assist in selecting treatment methods for non-small cell lung cancer (NSCLC) patients with brain metastasis, including recursive partitioning analysis (RPA), basic score for brain metastases (BS-BM), and diagnosis-specific graded prognostic assessment (DS-GPA). Lung-molGPA is an update of the DS-GPA that incorporates EGFR and/or ALK mutation status. The present study tested the applicability of these four indexes in 361 lung adenocarcinoma patients with brain metastasis. Potential predictive factors in our independent multivariate analysis included patient age, Karnofsky performance status, EGFR and ALK mutation status, and use of targeted therapy. In the log-rank test, all four systems predicted overall survival (OS) (P<0.001). Harrell's C indexes were 0.732, 0.724, 0.729, and 0.747 for RPA, BS-BM, DS-GPA, and Lung-molGPA, respectively. Our results confirmed that the Lung-molGPA index was useful for estimating OS in our patient cohort, and appeared to provide the most accurate predictions. However, the independent prognostic factors identified in our study were not entirely in agreement with the Lung-molGPA factors. In an era of targeted therapy, Lung-molGPA must be further updated to incorporate more specific prognostic factors based on additional patient data.

Prognostic model for brain metastases from lung adenocarcinoma identified with epidermal growth factor receptor mutation status.

BACKGROUND: Several indices have been developed to predict survival of brain metastases (BM) based on prognostic factors. However, such models were designed for general brain metastases from different kinds of cancers, and prognostic factors vary between cancers and histological subtypes. Recently, studies have indicated that epidermal growth factor receptor (EGFR) mutation status may be a potential prognostic biological factor in BM from lung adenocarcinoma. Thus, we sought to define the role of EGFR mutation in prognoses and introduce a prognostic model specific for BM from lung adenocarcinoma. METHODS: Data of 256 patients with BM from lung adenocarcinoma identified with EGFR mutations were collected. Independent prognostic factors were confirmed using a Cox regression model. The new prognostic model was developed based on the results of multivariable analyses. The score of each factor was calculated by six-month survival. Prognostic groups were divided into low, medium, and high risk based on the total scores. The prediction ability of the new model was compared to the three existing models. RESULTS: EGFR mutation and Karnofsky performance status were independent prognostic factors and were thus integrated into the new prognostic model. The new model was superior to the three other scoring systems regarding the prediction of three, six, and 12-month survival by pairwise comparison of the area under the curve. CONCLUSION: Our proposed prognostic model specific for BM from lung adenocarcinoma incorporating EGFR mutation status was valid in predicting patient survival. Further verification is warranted, with prospective testing using large sample sizes.

Assessment of prognostic scores of brain metastases from lung adenocarcinoma with EGFR mutations.

The aim of this study was to analyze prognostic factors and evaluate the value of four prognostic scores including RPA, DS-GPA BS-BM, GGS for the EGFR mutant BM patients from lung adenocarcinoma treated with EGFR-TKI. Data of NSCLC were retrospectively reviewed from August 2010 to June 2015 using the medical database of Shanxi Provincial Cancer Hospital. Patients with BM from lung adenocarcinoma with mutant EGFR treated by EGFR-TKI or a combination of EGFR-TKI and WBRT were included. Potential prognostic factors were statistically examined. The C-index of each prognostic score was calculated. A total of 1063 BM patients with lung adenocarcinoma that had been identified with EGFR mutations were reviewed. A total of 104 patients that had been diagnosed with BM were confirmed to have mutant EGFR in primary tumors. These patients received treatment with EGFR-TKI or EGFR-TKI with WBRT to BM. The potential predictive factors in multivariable analysis included KPS (70 vs.70-80 vs. 90-100) and number of brain metastatic lesions. In the log-rank test, the indexes of RPA, DS-GPA BS-BM, and GGS were all significant predictors of OS. The C-indexes of each prognostic score were 0.79, 0.76, 0.77, and 0.74 in DS-GPA, RPA, GGS, and BS-BM, respectively. The indexes of RPA, DS-GPA BS-BM, GGS were applicable for asessing survival stratification in brain metastases from lung adenocarcinoma with presented EGFR mutations in our independent population. The DS-GPA appears to be the best predictive value. However, all four of the indexes could not evaluate the exact independent prognostic factors in multivariable analysis. A prognostic index specific for this group of patients was needed for targeted lung cancer therapy.

Correlation between status of epidermal growth factor receptor mutation and distant metastases of lung adenocarcinoma upon initial diagnosis based on 1063 patients in China.

The study aimed to explore the correlations between status of epidermal growth factor receptor (EGFR) mutations and distant metastases. A total of 1063 patients with lung adenocarcinoma indentified with status of EGFR mutations from August 2010 to May 2015 at Shanxi Cancer Hospital were enrolled. 456 patients were confirmed with EGFR mutations. The associations among EGFR mutations, clinical factors, and distant metastases at initial diagnosis were evaluated. Patients harboring EGFR mutation were more likely to be female (P < 0.001), with no smoking history (P < 0.001), brain metastases (P = 0.029), and higher ECOG performance scores (P = 0.025). The correlation between EGFR mutation status and distant metastases showed statistical significance both in univariate (P = 0.022) and in multivariate analysis (OR 1.573, 95 % CI 1.202-2.059, P = 0.001) especially in brain metastases (OR 1.675, 95 % CI 1.132-2.479, P = 0.010) and lung metastases (OR 1.571, 59 % CI 1.101-2.243 P = 0.013). Furthermore, the 19del mutations showed associations with brain metastases (OR 1.586, 95 % CI 1.028-2.447, P = 0.037), and lung metastases (OR 1.587, 95 % CI 1.065-2.346, P = 0.023). The exon 21 point mutations showed statistically significant differences in liver metastases (OR 1.987, 95 % CI 1.094-3.067, P = 0.024). In conclusion, the EGFR mutations in lung adenocarcinoma patients were independently correlated with distant metastases. Subgroup analyses showed that patients harboring 19del mutations presented different distant metastases compared with those harboring 21 point mutaions.

Exon 19 deletion of epidermal growth factor receptor is associated with prolonged survival in brain metastases from non-small-cell lung cancer.

Brain metastasis (BM) is a poor prognostic factor for non-small-cell lung cancer (NSCLC). Recent studies have shown that oral epidermal growth factor receptor (EGFR) tyrosine kinase inhibitors (TKIs) were effective for BM from NSCLC with EGFR mutation. However, the relationship between EGFR mutations and prognosis of NSCLC BM patients remains to be determined. In this study, we investigated the impact of EGFR mutation status on the survival of BM patients from NSCLC. One hundred six patients with BM from NSCLC were retrospectively reviewed. Thirty-three subjects (24.3 %) were confirmed to have an exon 19 deletion, while another 33 had an exon 21 point mutation (L858R) (24.3 %). Log-rank test and Cox proportional hazards model were used to analyze the impact of variables on survival. The median survival of NSCLC with BM was 8 months. Log-rank test analysis showed that Eastern Cooperative Oncology Group Performance Status (ECOG-PS) at BM (p < 0.0001), control of primary tumor (p = 0.005), pathology (p = 0.01), EGFR mutations (p = 0.045), and 19 exon deletion (p = 0.007) were associated with a longer survival. In a Cox proportional hazards model, EGFR exon 19 deletion (p = 0.034), control of primary tumor (p = 0.024), and ECOG PS at BM (p = 0.006) were found to be independent prognostic factors. Moreover, there were prognostic differences between groups according to Radiation Therapy Oncology Group (RTOG) recursive partitioning analysis (RPA) classification system (p < 0.0001). Exon 19 deletion is an independent prognostic factor in BM from NSCLC. It should be integrated into the prognostic scoring classification system for NSCLC.

[Effects of adding straw carbon source to root knot nematode diseased soil on soil microbial biomass and protozoa abundance].

A field experiment with successive planting of tomato was conducted to study the effects of adding different amounts of winter wheat straw (2.08 g x kg(-1), 1N; 4.16 g x kg(-1), 2N; and 8.32 g x kg(-1), 4N) to the soil seriously suffered from root knot nematode disease on the soil microbial biomass and protozoa abundance. Adding straw carbon source had significant effects on the contents of soil microbial biomass carbon (MBC) and microbial biomass nitrogen (MBN) and the abundance of soil protozoa, which all decreased in the order of 4N > 2N > 1N > CK. The community structure of soil protozoa also changed significantly under straw addition. In the treatments with straw addition, the average proportion of fagellate, amoeba, and ciliates accounted for 36.0%, 59.5%, and 4.5% of the total protozoa, respectively. Under the same adding amounts of wheat straw, there was an increase in the soil MBC and MBN contents, MBC/MBN ratio, and protozoa abundance with increasing cultivation period.

Survival and bronchial carcinoid tumors: Development of surgical techniques in a 30-year experience of 82 patients in China.

BACKGROUND: We aimed to identify the factors determining long-term survival after surgical management for bronchial typical carcinoid (TC) and atypical carcinoids (AC) and to compare the clinical outcome of the different surgical strategies used in the two periods of 1980-1994 and 1995-2005. METHODS: Records of 82 patients with an initial pathological diagnosis of bronchial carcinoid tumor who underwent surgical management from January 1980 to December 2009 were reviewed. Tumors were classified as TC or AC using the 2004 World Health Organization criteria. RESULTS: There were 60 TC and 22 AC. Surgical procedures included lobectomies, sleeve or bronchoplastic resections, pneumonectomies, wedge resections, and segmental resections. Significantly fewer pneumonectomies and more sleeve and bronchoplastic resections were performed after 1994. The prognosis was more favorable for TC than AC. Comparing lymph node status N0 with N1 + N2, 5- and 10-year survival was 92% and 85% vs. 61% and 41%. No patient with lymph node involvement survived more than 15 years. CONCLUSIONS: Tumor subtype and lymph node status have the greatest impact on long-term survival following surgery. AC and/or regional lymph node metastases have the worst prognosis. Formal anatomic and tissue-saving lung resection plus systematic radical mediastinal lymphadenectomy for TC and AC should be standard.