Overall Survival Rate Analysis For Risk Factors In Women With Neuroendocrine Carcinoma of The Cervix Using Surveillance, Epidemiology, And End Results (SEER) Database

2021 ◽  
Author(s):  
Ziran Yin ◽  
Xiumin Huang
Keyword(s):  
Overall Survival ◽  
Lymph Nodes ◽  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
Analysis Data ◽  
Seer Database ◽  
Regional Lymph Nodes ◽  
Data Set ◽  
Cox Models ◽  
Cox Regression Analysis

Abstract Background: Neuroendocrine carcinoma of the cervix is rare and aggressive disease, of which prognosis information and the effectiveness of the therapies is unclear.Methods: A retrospective study using data from the SEER database for the first diagnosed Neuroendocrine carcinoma of the cervix patients was conducted. We performed univariate and multivariate Cox models to screen for independent prognostic factors for overall survival. Subgroup analysis and sensitive analysis were performed for further study, then again univariate and multivariate analyses of Cox regression analysis were performed based on the sensitivity analysis data set.Results: A total of 250 Neuroendocrine carcinoma of the cervix cases was included, tumor subtype, age, marriage, race, number of regional lymph nodes, number of positive lymph nodes, radiotherapy, surgery, and FIGO stage were all factors affecting OS, and multivariate analysis identified FIGO staging (HR, 2.4; 95% CI, 1.505-3.828, P < 0.001) and surgery (HR, 0.467; 95% CI, 0.358-0.609, P < 0.001) treatment as independent indicators. With respect to the factors associated with treatments, we found that patients who underwent surgery (yes vs. no vs. unknown) or radiation (yes vs. no) experienced prolonged survival, both P < 0.001Conclusions: Our investigation shows that for patients with NECC surgery seems to be the effective treatment. Chemotherapy cannot improve the prognosis of NECC patients, and the effectiveness of radiation should be further verified.

scholarly journals Construction of a nomogram to predict overall survival for patients with lung large cell neuroendocrine carcinoma: analysis of the SEER database

2020 ◽  
Author(s):  
Dong Han ◽  
Fei Gao ◽  
Nan Li ◽  
Hao Wang ◽  
Qi Fu
Keyword(s):  
Overall Survival ◽  
Survival Rate ◽  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
Risk Group ◽  
Multivariable Analysis ◽  
Large Cell ◽  
Large Cell Neuroendocrine Carcinoma ◽  
Seer Database ◽  
Cox Regression Analysis

Abstract Background Lung large cell neuroendocrine carcinoma (L-LCNEC) has a poor prognosis with lower survival rate than other NSCLC patients. The estimation of an individual survival rate is puzzling. The main purpose of this study was to establish a more accurate model to predict the prognosis of L-LCNEC.Methods Patients aged 18 years or older with L-LCNEC were identified from the Surveillance, Epidemiology and End Results (SEER) database from 2004 to 2015. Cox regression analysis was used to identify factors associated with survival time. The results were used to construct a nomogram to predict 1-year, and 3-year survival probability in L-LCNEC patients. Overall survival (OS) were compared between low risk group and high risk group by the Kaplan–Meier analysis.Results A total of 3216 patients were included in the study. We randomly divided all included patients into 7:3 training and validating groups. In multivariable analysis of training cohort, age at diagnosis, sex, stage of tumor, surgical treatment, radiotherapy and chemotherapy were independent prognostic factors for OS. All these factors were incorporated to construct a nomogram, which was tested in the validating cohort.Conclusions we constructed a visual nomogram prognosis model, which had the potential to predict the 1-year and 3-year survival rate of L-LCNEC patients, and could be used as an assistant prediction tool in clinical practice.

scholarly journals Construction of a Nomogram to Predict Overall Survival for Patients With Lung Large Cell Neuroendocrine Carcinoma: Analysis of the SEER Database

2021 ◽  
Author(s):  
Dong Han ◽  
Fei Gao ◽  
Nan Li ◽  
Hao Wang ◽  
Qi Fu
Keyword(s):  
Overall Survival ◽  
Survival Rate ◽  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
Risk Group ◽  
Multivariable Analysis ◽  
Large Cell ◽  
Large Cell Neuroendocrine Carcinoma ◽  
Seer Database ◽  
Cox Regression Analysis

Abstract Background: Lung large cell neuroendocrine carcinoma (L-LCNEC) has a poor prognosis with lower survival rate than other NSCLC patients. The estimation of an individual survival rate is puzzling. The main purpose of this study was to establish a more accurate model to predict the prognosis of L-LCNEC. Methods: Patients aged 18 years or older with L-LCNEC were identified from the Surveillance, Epidemiology and End Results (SEER) database from 2004 to 2015. Cox regression analysis was used to identify factors associated with survival time. The results were used to construct a nomogram to predict 1-year, and 3-year survival probability in L-LCNEC patients. Overall survival (OS) were compared between low risk group and high risk group by the Kaplan–Meier analysis. Results: A total of 3216 patients were included in the study. We randomly divided all included patients into 7:3 training and validating groups. In multivariable analysis of training cohort, age at diagnosis, sex, stage of tumor, surgical treatment, radiotherapy and chemotherapy were independent prognostic factors for OS. All these factors were incorporated to construct a nomogram, which was tested in the validating cohort.Conclusions: we constructed a visual nomogram prognosis model, which had the potential to predict the 1-year and 3-year survival rate of L-LCNEC patients, and could be used as an assistant prediction tool in clinical practice.

NF-κB in the Vascular Progression of Melanoma

2004 ◽  
Vol 22 (4) ◽  
pp. 617-623 ◽  
Author(s):  
Mohammed Kashani-Sabet ◽  
Ladan Shaikh ◽  
James R. Miller ◽  
Mehdi Nosrati ◽  
Carlos M.M. Ferreira ◽  
...  
Keyword(s):  
Overall Survival ◽  
Cox Regression ◽  
Surrogate Marker ◽  
Tissue Array ◽  
Matched Pair ◽  
Vascular Involvement ◽  
Tumor Vascularity ◽  
Data Set ◽  
Cox Regression Analysis ◽  
The Impact

Purpose To examine a model of melanoma progression based on vascular factors and the role of NF-κB in the vascular progression of melanoma. Patients and Methods A data set of 526 patients from the University of California San Francisco Melanoma Center with 2 years of follow-up or first relapse was studied. The impact of the presence or absence of various prognostic factors on overall survival of melanoma patients was assessed using Cox regression and Kaplan-Meier analysis. A matched-pair analysis of NF-κB expression was performed in cases with vascular involvement and increased tumor vascularity versus matched controls lacking these factors. Results Cox regression analysis of factors evaluated by the American Joint Committee on Cancer Melanoma Staging Committee reproduced the powerful impact of tumor thickness and ulceration in this data set. With the inclusion of vascular factors such as tumor vascularity and vascular involvement, ulceration was no longer significant in predicting overall survival. By multivariate analysis, vascular involvement and tumor vascularity were the strongest predictors of melanoma outcome. Tumor vascularity seems to be a precursor of both vascular involvement and ulceration. A matched-pair tissue array analysis demonstrated the significant correlation between overexpression of NF-κB–p65 and the development of vascular factors. Conclusion Vascular factors play an important role in the progression of malignant melanoma. Ulceration may be a surrogate marker for the interactions between melanoma and the tumor vasculature. NF-κB seems to play an important role in the development of these factors.

scholarly journals Postoperative Nomogram for predicting Cancer-Specific and Overall Survival Among Patients with Medullary Thyroid Cancer

2020 ◽  
Author(s):  
Li Chen ◽  
Yizeng Wang ◽  
Ke Zhao ◽  
Yuyun Wang ◽  
Dongyang Li ◽  
...  
Keyword(s):  
Overall Survival ◽  
Lymph Nodes ◽  
Total Thyroidectomy ◽  
Cox Regression ◽  
Test Group ◽  
Training Group ◽  
Seer Database ◽  
Cancer Specific Survival ◽  
Lymph Nodes Dissection ◽  
Neck Lymph Nodes

Abstract Background Medullary thyroid carcinoma (MTC) accounts for 1% -2% of thyroid cancer in the United States based on the latest Surveillance, Epidemiology, and End Results (SEER) data, this study aimed to construct a comprehensive predictive nomogram based on various clinical variables in MTC patients who undergo total thyroidectomy and neck lymph nodes dissection.Methods Data regarding 1237 MTC patients who undergo total thyroidectomy and neck lymph nodes dissection from 2004 to 2015 were obtained from the SEER database. Univariate and multivariate Cox regression analyses were used to screen for meaningful independent predictors. These independent factors were used to construct a nomogram model, a survival prognostication tool for 3- and 5-year overall survival and cancer-specific survival among these MTC patients.Result A total of 1237 patients enrolled from the SEER database were randomly divided into the training group (n = 867) and the test group (n = 370). Univariate and multivariate Cox regression analyses were used to identify meaningful independent prognostic factors (P <0.05). Tumor size, age, metastasis status, and LNR were selected as independent predictors of overall survival (OS) and cancer-specific survival (CSS). Finally, two nomograms were developed, the predicted C-index of overall survival (OS) and cancer-specific survival (CSS) rate in the training group were 0.828 and 0.904, respectively. The predicted C-index of overall survival (OS) and cancer-specific survival (CSS) rate in the test group were 0.813 and 0.828.Conclusion Nomograms constructed by using various clinical variables can make more comprehensive and accurate predictions for MTC patients who undergo total thyroidectomy and neck lymph nodes. These predictive nomograms help identify postoperative high-risk MTC patients and facilitate patient counseling on clinical prognosis and follow-up.

scholarly journals Identification of IFN-β Associated Genes Signature Predicting Overall Survival for Glioblastoma

2021 ◽  
Author(s):  
Cheng Lijing ◽  
Yuan Meiling ◽  
Li Shu ◽  
Chen Junjing ◽  
Zhong Shupeng ◽  
...  
Keyword(s):  
Overall Survival ◽  
Clinical Decision Making ◽  
Cox Regression ◽  
Risk Group ◽  
Expression Profiles ◽  
Individual Treatment ◽  
Normal Brain ◽  
Data Set ◽  
Cox Regression Analysis ◽  
Prognosis Prediction

Abstract Background: Brain glioblastoma (GBM) is the most common primary malignant tumor of intracranial tumors. The prognosis of this disease is extremely poor. While the introduction of IFN-β regimen in the treatment of gliomas has significantly improved the outcome of patients, the underlying mechanism remains to be elucidated. Materials and methods: mRNA expression profiles and clinicopathological data were downloaded from TCGA-GBM and GSE83300 data set from the GEO. Univariate Cox regression analysis and lasso Cox regression model established a novel four‐gene IFN-β signature (including PRDX1, SEC61B, XRCC5, and BCL2L2) for GBM prognosis prediction. Further, GBM samples (n=50) and normal brain tissues (n=50) were then used for real-time polymerase chain reaction (PCR) experiments. Gene Set Enrichment Analyses (GSEA) was performed to further understand the underlying molecular mechanisms. Pearson correlation was applied to calculate the correlation between the lncRNAs and IFN-β associated genes. A lncRNA with a correlation coefficient |R2| > 0.3 and P < 0.05 was considered to be an IFN-β associated lncRNA.Results: Patients in the high‐risk group shown significantly poorer survival than patients in the low‐risk group. The signature was found to be an independent prognostic factor for GBM survival. Furthermore, GSEA revealed several significantly enriched pathways, which might help explain the underlying mechanisms. Our study identified a novel robust four‐gene IFN-β signature for GBM prognosis prediction. The signature might contain potential biomarkers for metabolic therapy and treatment response prediction in GBM.Conclusions: Our study established a novel IFN-β associated genes signature to predict overall survival of GBM, which may help in clinical decision making for individual treatment.

scholarly journals Development and Validation of Nomograms to Predict Prognosis of Oral and Oropharyngeal Mucoepidermoid Carcinoma: A SEER-Based Study

2020 ◽  
Author(s):  
muyuan liu ◽  
Litian Tong ◽  
Manbin Xu ◽  
Xiang Xu ◽  
Bin Liang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Mucoepidermoid Carcinoma ◽  
Cox Regression ◽  
Seer Database ◽  
Disease Specific Survival ◽  
Cox Regression Analysis ◽  
T Stage ◽  
N Stage ◽  
Disease Specific

Abstract Background: Due to the low incidence of mucoepidermoid carcinoma, there lacks sufficient studies for determining optimal treatment and predicting prognosis. The purpose of this study was to develop prognostic nomograms, to predict overall survival and disease-specific survival (DSS) of oral and oropharyngeal mucoepidermoid carcinoma patients, using the National Cancer Institute’s Surveillance, Epidemiology, and End Results (SEER) database. Methods: Clinicopathological and follow-up data of patients diagnosed with oral and oropharyngeal mucoepidermoid carcinoma between 2004 and 2017 were collected from the SEER database. The Kaplan-Meier method with the log-rank test was employed to identify single prognostic factors. Multivariate Cox regression was utilized to identify independent prognostic factors. C-index, area under the ROC curve (AUC) and calibration curves were used to assess performance of the prognostic nomograms. Results: A total of 1230 patients with oral and oropharyngeal mucoepidermoid carcinoma were enrolled in the present study. After multivariate Cox regression analysis, age, sex, tumor subsite, T stage, N stage, M stage, grade and surgery were identified as independent prognostic factors for overall survival. T stage, N stage, M stage, grade and surgery were identified as independent prognostic factors for disease-specific survival. Nomograms were constructed to predict the overall survival and disease-specific survival based on the independent prognostic factors. The fitted nomograms possessed excellent prediction accuracy, with a C-index of 0.899 for OS prediction and 0.893 for DSS prediction. Internal validation by computing the bootstrap calibration plots, using the validation set, indicated excellent performance by the nomograms. Conclusion: The prognostic nomograms developed, based on individual clinicopathological characteristics, in the present study, accurately predicted the overall survival and disease-specific survival of patients with oral and oropharyngeal mucoepidermoid carcinoma.

scholarly journals Postoperative Nomogram for Predicting Cancer-Specific and Overall Survival among Patients with Medullary Thyroid Cancer

2020 ◽  
Vol 2020 ◽  
pp. 1-13
Author(s):  
Li Chen ◽  
Yizeng Wang ◽  
Ke Zhao ◽  
Yuyun Wang ◽  
Xianghui He
Keyword(s):  
Overall Survival ◽  
Lymph Nodes ◽  
Total Thyroidectomy ◽  
Cox Regression ◽  
Test Group ◽  
Training Group ◽  
Seer Database ◽  
Cancer Specific Survival ◽  
Lymph Nodes Dissection ◽  
Neck Lymph Nodes

Background. Medullary thyroid carcinoma (MTC) accounts for 1%–2% of thyroid cancer in the United States based on the latest Surveillance, Epidemiology, and End Results (SEER) data, and this study aimed to construct a comprehensive predictive nomogram based on various clinical variables in MTC patients who underwent total thyroidectomy and neck lymph nodes dissection. Methods. Data regarding 1,237 MTC patients who underwent total thyroidectomy and neck lymph nodes dissection from 2004 to 2015 were obtained from the SEER database. Univariate and multivariate Cox regression analyses were used to screen for meaningful independent predictors. These independent factors were used to construct a nomogram model, a survival prognostication tool for 3- and 5-year overall survival, and cancer-specific survival among these MTC patients. Result. A total of 1,237 patients enrolled from the SEER database were randomly divided into the training group (n = 867) and the test group (n = 370). Univariate and multivariate Cox regression analyses were used to identify meaningful independent prognostic factors ( P < 0.05 ). Tumor size, age, metastasis status, and LNR were selected as independent predictors of overall survival (OS) and cancer-specific survival (CSS). Finally, two nomograms were developed, and the predicted C-index of overall survival (OS) and cancer-specific survival (CSS) rate in the training group was 0.828 and 0.904, respectively. The predicted C-index of overall survival (OS) and cancer-specific survival (CSS) rate in the test group was 0.813 and 0.828. Conclusion. Nomograms constructed by using various clinical variables can make more comprehensive and accurate predictions for MTC patients who underwent total thyroidectomy and neck lymph nodes. These predictive nomograms help identify postoperative high-risk MTC patients and facilitate patient counseling on clinical prognosis and follow-up.

Nomogram to predict survival of pulmonary large-cell neuroendocrine carcinoma after surgery

2020 ◽  
Author(s):  
Qian Huang ◽  
Jie Liu ◽  
Huifang Cai ◽  
Qi Zhang ◽  
Lina Wang
Keyword(s):  
Overall Survival ◽  
Regression Analysis ◽  
Prognostic Factors ◽  
Neuroendocrine Carcinoma ◽  
Cox Regression ◽  
Predictive Performance ◽  
Large Cell ◽  
Large Cell Neuroendocrine Carcinoma ◽  
Operating Characteristics ◽  
Cox Regression Analysis

Abstract Background Pulmonary large-cell neuroendocrine carcinoma (LCNEC) is a rare primary malignant tumor with a poor prognosis, and surgery is the main treatment. However, there are no effective predictive tools to assess the prognosis of postoperative patients. Our aim is to identify prognostic factors and construct nomogram to accurately assess prognosis. Methods Patients were identified in the Surveillance, Epidemiology, and End Results (SEER) database. Based on the results of Cox regression analysis, construct nomogram for predicting 1-, 3-, and 5-year survival. The predictive performance of nomogram was evaluated using the consistency index (C-index), the area under the receiver operating characteristics curve (AUC), and calibration plots. Results We finally screened 903 patients with pulmonary LCNEC who underwent surgery. The Cox regression analysis showed that age, SEER stage, T stage, N stage, M stage, tumor size, and chemotherapy were independent prognostic factors for overall survival (P<0.05). The C-index of the nomogram is 0.681 on the training cohort and 0.675 on the validation cohort. The AUC and calibration plots show that the nomogram has good performance. Conclusion We constructed and validated nomogram for predicting 1-, 3-, and 5-year survival of patients with pulmonary LCNEC after surgery. Our nomogram provides reference information for assessing the overall survival of these patients.

scholarly journals CD169 Expression on Lymph Node Macrophages Predicts in Patients With Gastric Cancer

2021 ◽  
Vol 11 ◽  
Author(s):  
Keiichiro Kumamoto ◽  
Takashi Tasaki ◽  
Koji Ohnishi ◽  
Michihiko Shibata ◽  
Shohei Shimajiri ◽  
...  
Keyword(s):  
Gastric Cancer ◽  
Lymph Node ◽  
Immune Responses ◽  
Lymph Nodes ◽  
Advanced Gastric Cancer ◽  
Cox Regression ◽  
Regional Lymph Nodes ◽  
Cox Regression Analysis ◽  
Anti Cancer ◽  
Cancer Tissues

The induction of an anti-cancer immune responses is potentially associated with the efficacy of anti-cancer therapy. Recent studies have indicated that sinus macrophages in regional lymph nodes are involved in anti-cancer immune responses in the cancer microenvironment. In the present study, we investigated the correlation between lymphocyte infiltration in cancer tissues and macrophage activation in regional lymph nodes. We retrospectively identified 294 patients with gastric cancer who underwent surgery from 2008 to 2012. Using immunohistochemistry, we evaluated CD169-expression on CD68-positive macrophages, and the density of CD8-postive lymphocytes in tumor microenvironment. We statistically examined the correlation between CD169 and CD8 expression, and performed Cox regression analysis of potential prognostic factors, including CD169 and CD8 expression, for cancer-specific survival (CSS) in patients with total and advanced gastric cancer. CD169 overexpression in lymph node sinus macrophages (LySMs) was positively correlated to the density of CD8-positive lymphocytes in primary cancer tissues (R = 0.367, p &lt; 0.001). A high density of CD8-positive T lymphocytes in the primary site and a high level of CD169 expression in LySMs were independently associated with greater CSS in patients with total and advanced gastric cancer (p &lt; 0.05 for all). The expression on CD169 in LySMs is a predictor of a favorable clinical course in patients with gastric cancer, and might be useful for evaluating anti-cancer immune responses.

scholarly journals Influence of marital status on overall survival in patients with ovarian serous carcinoma: finding from the surveillance epidemiology and end results (SEER) database

2019 ◽  
Vol 12 (1) ◽  
Author(s):  
Pei Luo ◽  
Jian-Guo Zhou ◽  
Su-Han Jin ◽  
Ming-Song Qing ◽  
Hu Ma
Keyword(s):  
Overall Survival ◽  
Regression Analysis ◽  
Marital Status ◽  
Cox Regression ◽  
The United States ◽  
Serous Carcinoma ◽  
Cancer Center ◽  
Seer Database ◽  
Ovarian Serous Carcinoma ◽  
Cox Regression Analysis

Abstract Objective This study is to investigate the relationship between marital status and prognosis of patients with ovarian serous carcinoma. Results We performed data analysis from 19,276 patients identified from the SEER database of the National Cancer Center of the United States. 57.8% of the patients were married, 13.0% unmarried, and 29.2% separated/ divorced/widowed (SDW). The median overall survival time ofthe unmarried group and the married group are 48 months and 52 months respectively. Univariate Cox regression analysis showed that the patients with serous ovarian cancer in the unmarried group resulted in a hazard ratio (HR) of 1.14 (95% CI: 1.08–1.19%; P < 0.001), comparing to SDW group with a HR of 1.02 (95% CI: 0.98–1.19%; P = 0.26). However, the SDW group was not statistically significantly different from the married group. (median 32 vs 52 months). Multivariate Cox regression analysis presented the unmarried group leading to a HR of 1.05 (95% CI: 1.00–1.11%; P = 0.05), and the SDW group was not significant with a HR of 0.99 (95% CI: 0.95–1.03%; P = 0.57). Conclusion Unmarried patients with ovarian serous carcinoma have higherHRof overall survival. After controlling age, race, grade, radiation and year of diagnosis, unmarried patients were found to have a significantly higher risk of OS. Consequently, these patients are suggested to obtain more focused healthcare for the management of ovarian serous carcinoma.

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