scholarly journals Nomograms for predicting the overall survival of patients with cerebellar glioma: an analysis of the surveillance epidemiology and end results (SEER) database

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Jie Li ◽  
Wobin Huang ◽  
Jiajing Chen ◽  
Zhuhui Li ◽  
Bocong Liu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Survival Probability ◽  
Training Group ◽  
Histological Type ◽  
Seer Database ◽  
Validation Group ◽  
Clinical Value ◽  
Who Grade ◽  
Group Data ◽  
End Results

AbstractAt present, our understanding of cerebellar glioma is still insufficient. This study collected information on patients in the SEER database to identify the predictive factors for patients with cerebellar glioma. Data from patients with cerebellar glioma diagnosed from 1975 to 2018 were retrieved from the Surveillance Epidemiology and End Results Database. We randomly divided the patients into a training group and a validation group, established a nomogram based on the training group, and used the validation group data to verify the clinical value of the model. A total of 508 patients were included in this study. Multivariate analysis was performed based on the data before randomization, and the results showed that the patient's age, WHO grade, histological type, and extent were significantly correlated with the survival rate. The C-index of the OS nomograms of the training cohort was 0.909 (95% CI, (0.880–0.938)) and 0.932 (95% CI, (0.889–0.975)) in the validation group. The calibration curve of OS for 3 and 5 years showed that there was good consistency between the actual survival probability and the predicted survival probability. For patients with cerebellar glioma, the age at diagnosis, WHO grade of the glioma, histological type, and extension are the four factors that most strongly affect the overall survival outcomes. Furthermore, our model may be a useful tool for predicting OS in these patients.

scholarly journals Nomograms for predicting the overall survival of patients with cerebellar glioma: An analysis of the SEER (Surveillance Epidemiology and End Results) database

2021 ◽  
Author(s):  
Jie Li ◽  
Wobin Huang ◽  
Jiajing Chen ◽  
Zhuhui Li ◽  
Bocong Liu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Training Group ◽  
Histological Type ◽  
Validation Group ◽  
Clinical Value ◽  
Who Grade ◽  
Group Data ◽  
Good Consistency ◽  
Actual Survival ◽  
End Results

Abstract Purpose: At present, our understanding of cerebellar glioma is still not enough. This study collected information on patients in the seer database to determine the predictive factors patients with cerebellar glioma. Patients and Methods: The data of patients with cerebellar glioma diagnosed from 1975 to 2018 were retrieved from the Surveillance Epidemiology and End Results Database. We randomly divide the data into a training group and a validation group, establish a nomogram based on the training group, and use the validation group data to verify the clinical value of the model. Results: A total of 508 patients were included in this study. Multivariate analysis was performed based on the data before randomization, and the results showed that the patient's age, the tumor's WHO grade, histological type, and extension are significantly correlated with the survival rate. The c index of OS nomograms of the training cohort was 0.909 (95% CI,(0.880-0.938）) and 0.932(95% CI, (0.889-0.975)) in validation group. The calibration curve of OS for 3 and 5 years show that there was a good consistency between the actual survival probability and the predicted survival probability.Conclusion: For patients with cerebellar glioma, the age of the patient at the time of diagnosis, WHO grade of the glioma, histological type, and extension are the four most prominent factors that affect the overall survival outcomes. Furthermore, our model may be a useful tool for predicting OS in these patients.

P10.03 Establishment and validation of clinical prediction model in WHO grade II glioma

2021 ◽  
Vol 23 (Supplement_2) ◽  
pp. ii28-ii28
Author(s):  
X Xue ◽  
Q Gao
Keyword(s):  
Prediction Model ◽  
Training Group ◽  
Clinical Prediction ◽  
Validation Group ◽  
Who Grade ◽  
Clinical Prediction Model ◽  
Cox Regression Analysis ◽  
Who Grade Ii Glioma ◽  
Grade Ii ◽  
Grade Ii Glioma

Abstract OBJECTIVE WHO grade II glioma has the characteristics of heterogeneity, and this disease progresses rapidly in some patients, in whom the malignant degree is equivalent to that of high-grade glioma. In order to accurately predict the prognosis of patients, an effective clinical prediction model based on relevant risk factors is needed which could provide a theoretical basis for optimization of clinical individualized treatment. METHODS According to the inclusion and exclusion criteria, eligible patients from January 2010 to December 2018 in our hospital were selected, and those who met the criteria were randomly assigned 4:1 to the training group and the validation group, respectively. The predictors were screened by univariate and multivariate Cox regression analysis, the prediction model was established, and the model was verified and evaluated. RESULTS A total of 258 patients with WHO grade II glioma were recruited, including 208 patients as the training group and 50 patients as the validation group. Six independent risk factors, including patient age, preoperative Karnofsky performance status (KPS) score, preoperative seizure symptoms, surgical resection range, tumor size and IDH status, were selected and included into the prediction model by univariate and multivariate Cox regression analysis, and were visualized in the form of Nomogram. The concordance index (C index) was used to evaluate the predictive ability of the model. Results showed that the C-index was 0.832 in the training group and 0.853 in the validation group, respectively, indicating good performance for the prediction model. The calibration charts were drawn in both groups respectively, which showed that the calibration lines were in good agreement with the standard lines, indicating good consistency between the two groups. CONCLUSIONS In this study, a clinical prediction model for WHO grade II glioma was established, and it was verified that the model has good predictive ability, which may be beneficial for clinical work.

scholarly journals Risk Analysis for Pulmonary Metastasis of Chondrosarcoma and Establishment and Validation of Novel Clinical Prediction Models: a Clinical Study Based on the SEER Database

2020 ◽  
Author(s):  
Wenle LI ◽  
WANG Hao-sheng ◽  
NING Li-Jun ◽  
GAO Sen ◽  
ZHANG Wen-shi ◽  
...  
Keyword(s):  
Lung Metastasis ◽  
Prediction Models ◽  
Lung Metastases ◽  
Training Group ◽  
Clinical Impact ◽  
Individual Risk ◽  
Seer Database ◽  
Validation Group ◽  
Decision Curve Analysis ◽  
The Individual

Abstract Objective: Lung metastasis of chondrosarcoma is associated with poor prognosis. The purpose of this study was to develop and validate the nomogram to predict the risk of lung metastasis in patients with chondrosarcoma, thus contributing to clinical diagnosis and treatment.Methods: Data on chondrosarcoma patients from the Surveillance, Epidemiology, and End Results (SEER) database from 2010 to 2016 were then screened by univariate and multivariate Logistic regression to construct a Nomogram predicting lung metastasis risk. Nomogram model discrimination was assessed by calibration charts, while prediction accuracy and clinical values were measured by decision curve analysis (DCA) and clinical impact charts. In addition, the predicted Nomogram were validated in the internal test set. Results: A total of 944 patients were enrolled and randomly divided into the training group (n=664) and the validation group (n=280) in a ratio of 7 to 3.After logistics regression analysis, significant variables were gender, age, marital status, tumor volume and lymphatic metastasis. Calibration curves show consistency between Nomogram predictions and actual observations, while DCA and clinical impact diagrams show the clinical utility of Nomogram. In addition, ROC also showed good discrimination and calibration in the training group (AUC = 0.789, 95%CI 0.789 -- 0.808) and the validation group (AUC = 0.796, 95%CI 0.744 -- 0.841).Conclusions: Nomogram for lung metastases in chondrosarcoma can effectively predict the individual risk of lung metastases and provide clinicians with enlightening information to optimize treatment.

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 Nomograms Predicting Long-Term Overall Survival and Cancer-Specific Survival in Metastatic Hepatocellular Carcinoma Patients

2020 ◽  
Author(s):  
Chi Cui ◽  
Yaru Duan ◽  
Rui Li ◽  
Hua Ye ◽  
Peng Wang ◽  
...  
Keyword(s):  
Hepatocellular Carcinoma ◽  
Overall Survival ◽  
Cox Regression ◽  
Training Group ◽  
Clinicopathological Characteristics ◽  
Validation Group ◽  
Cancer Specific Survival ◽  
Term Survival ◽  
Metastatic Hepatocellular Carcinoma

Abstract Background This study aims to evaluate the clinicopathological characteristics of metastatic hepatocellular carcinoma (HCC) patients and develop nomograms to predict their long-term overall survival (OS) and cancer-specific survival (CSS). Methods Information on metastatic HCC from 2010 to 2015 was retrieved from the Surveillance, Epidemiology and End Results (SEER) program of the National Cancer Institute. The metastatic HCC patients were divided into a long-term survival (LTS) group and a short-term survival (STS) group with 1 year selected as the cut-off value. Then, we compared the demographic and clinicopathological features between the two groups. Next, all patients were randomly divided into a training group and validation group at a 7:3 ratio. Univariate and multivariate Cox regression analyses were used to identify potential predictors for OS and CSS in the training group, and nomograms of OS and CSS were established. These predictive models were further validated in the validation group. Results A total of 2163 patients were included in the current study according to the inclusion and exclusion criteria. Patients with characteristics including lower T stage and N stage; treatment with surgery, radiation or chemotherapy; no lung metastasis; and AFP negative status showed better survival. The concordance index (C-index) of the OS nomogram was 0.72 based on 9 variables. The C-index of the CSS nomogram was 0.71 based on 8 variables. Conclusions These nomograms may help clinicians make better treatment recommendations for metastatic HCC patients.

scholarly journals Nomogram predicts the overall survival of patients with Glioma

2021 ◽  
Author(s):  
Junming Xu ◽  
Honglin Li ◽  
Yuanyuan Zou ◽  
Chunjiao Yu
Keyword(s):  
Overall Survival ◽  
Logistic Regression Model ◽  
Training Group ◽  
Curve Analysis ◽  
Clinical Use ◽  
Seer Database ◽  
Discriminative Ability ◽  
Decision Curve Analysis ◽  
Training Cohort ◽  
Discrimination Ability

Abstract Aim Our study aimed to establish a nomogram to predict the cancer-specific surviva (CSS) of patients with Glioma. Patients and methods Patients diagnosed with glioma between 2004 and 2016 were collected from the SEER database. On the basis of the logistic regression model, the nomogram was established, the C-index was used to evaluate the accuracy of the nomogram, and the Decision Curve Analysis was used to evaluate the clinical use of the nomogram. Results 2626 eligible patients were randomly divided into training group (n=1864) and verification group (n=762). Nomogram had better discrimination ability, the C index of the training cohort was 0.74, and the C index of the verification cohort was 0.736. This new predictive model has shown better discriminative ability and greater benefits in both training and validation cohorts to predict CSS in patients with Glioma.Conclusion A nomogram was constructed to predict the CSS of Glioma patients at 1, 3, and 5 years. The verification showed that the nomogram had better discrimination and calibration ability, indicating that the nomogram can be used to predict the CSS of Glioma patients and guide the treatment of Glioma patients.

scholarly journals Construction and Validation of a Novel Nomogram to Predict the Overall Survival of Patients With Combined Small Cell Lung Cancer: A Surveillance, Epidemiology, and End Results Population-Based Study

2021 ◽  
Vol 28 ◽  
pp. 107327482110512
Author(s):  
Aimin Jiang ◽  
Na Liu ◽  
Rui Zhao ◽  
Shihan Liu ◽  
Huan Gao ◽  
...  
Keyword(s):  
Lung Cancer ◽  
Overall Survival ◽  
Small Cell Lung Cancer ◽  
Cell Lung Cancer ◽  
Survival Probability ◽  
Tnm Staging ◽  
Small Cell ◽  
Small Cell Lung ◽  
Calibration Curves ◽  
End Results

Introduction Combined small cell lung cancer (C-SCLC) represents a rare subtype of all small cell lung cancer cases, with limited studies investigated its prognostic factors. The aim of this study was to construct a novel nomogram to predict the overall survival (OS) of patients with C-SCLC. Methods In this retrospective study, a total of 588 C-SCLC patients were selected from the Surveillance, Epidemiology, and End Results database. The univariate and multivariate Cox analyses were performed to identify optimal prognostic variables and construct the nomogram, with concordance index (C-index), receiver operating characteristic curves, and calibration curves being used to evaluate its discrimination and calibration abilities. Furthermore, decision curve analysis (DCA), integrated discrimination improvement (IDI), and net reclassification index (NRI) were also adopted to assess its clinical utility and predictive ability compared with the classic TNM staging system. Results Seven independent predictive factors were identified to construct the nomogram, including T stage, N stage, M stage, brain metastasis, liver metastasis, surgery, and chemotherapy. We observed a higher C-index in both the training (.751) and validation cohorts (.736). The nomogram has higher area under the curve in predicting 6-, 12-, 18-, 24-, and 36-month survival probability of patients with C-SCLC. Meanwhile, the calibration curves also revealed high consistencies between the actual and predicted OS. DCA revealed that the nomogram could provide greater clinical net benefits to these patients. We found that the NRI for 6- and 12-month OS were .196 and .225, and the IDI for 6- and 12-month OS were .217 and .156 in the training group, suggesting that the nomogram can predict a more accurate survival probability. Similar results were also observed in the validation cohort. Conclusion We developed and verified a novel nomogram that can help clinicians recognize high-risk patients with C-SCLC and predict their OS.

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.

scholarly journals Oligodendroglioma resection: a Surveillance, Epidemiology, and End Results (SEER) analysis

2018 ◽  
Vol 128 (4) ◽  
pp. 1076-1083 ◽  
Author(s):  
Ali A. Alattar ◽  
Michael G. Brandel ◽  
Brian R. Hirshman ◽  
Xuezhi Dong ◽  
Kate T. Carroll ◽  
...  
Keyword(s):  
Overall Survival ◽  
Cox Regression ◽  
Primary Cns Lymphoma ◽  
Extent Of Resection ◽  
Subtotal Resection ◽  
Cns Lymphoma ◽  
Who Grade ◽  
Kaplan Meier ◽  
Clinical Benefits ◽  
End Results

OBJECTIVEThe available evidence suggests that the clinical benefits of extended resection are limited for chemosensitive tumors, such as primary CNS lymphoma. Oligodendroglioma is generally believed to be more sensitive to chemotherapy than astrocytoma of comparable grades. In this study the authors compare the survival benefit of gross-total resection (GTR) in patients with oligodendroglioma relative to patients with astrocytoma.METHODSUsing the Surveillance, Epidemiology, and End Results (SEER) Program (1999–2010) database, the authors identified 2378 patients with WHO Grade II oligodendroglioma (O2 group) and 1028 patients with WHO Grade III oligodendroglioma (O3 group). Resection was defined as GTR, subtotal resection, biopsy only, or no resection. Kaplan-Meier and multivariate Cox regression survival analyses were used to assess survival with respect to extent of resection.RESULTSCox multivariate analysis revealed that the hazard of dying from O2 and O3 was comparable between patients who underwent biopsy only and GTR (O2: hazard ratio [HR] 1.06, 95% confidence interval [CI] 0.73–1.53; O3: HR 1.18, 95% CI 0.80–1.72). A comprehensive search of the published literature identified 8 articles without compelling evidence that GTR is associated with improved overall survival in patients with oligodendroglioma.CONCLUSIONSThis SEER-based analysis and review of the literature suggest that GTR is not associated with improved survival in patients with oligodendroglioma. This finding contrasts with the documented association between GTR and overall survival in anaplastic astrocytoma and glioblastoma. The authors suggest that this difference may reflect the sensitivity of oligodendroglioma to chemotherapy as compared with astrocytomas.

scholarly journals Survival trends of grade I, II, and III astrocytoma patients and associated clinical practice patterns between 1999 and 2010: A SEER-based analysis

2015 ◽  
Vol 3 (1) ◽  
pp. 29-38 ◽  
Author(s):  
Xuezhi Dong ◽  
Abraham Noorbakhsh ◽  
Brian R. Hirshman ◽  
Tianzan Zhou ◽  
Jessica A. Tang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Clinical Practice ◽  
Surgical Resection ◽  
Practice Patterns ◽  
Radiation Treatment ◽  
Tumor Location ◽  
Seer Database ◽  
Who Grade ◽  
Clinical Practice Patterns ◽  
Grade Ii

Abstract Background The survival trends and the patterns of clinical practice pertaining to radiation therapy and surgical resection for WHO grade I, II, and III astrocytoma patients remain poorly characterized. Methods Using the Surveillance, Epidemiology and End Results (SEER) database, we identified 2497 grade I, 4113 grade II, and 2755 grade III astrocytomas during the period of 1999–2010. Time-trend analyses were performed for overall survival, radiation treatment (RT), and the extent of surgical resection (EOR). Results While overall survival of grade I astrocytoma patients remained unchanged during the study period, we observed improved overall survival for grade II and III astrocytoma patients (Tarone-Ware P < .05). The median survival increased from 44 to 57 months and from 15 to 24 months for grade II and III astrocytoma patients, respectively. The differences in survival remained significant after adjusting for pertinent variables including age, ethnicity, marital status, sex, tumor size, tumor location, EOR, and RT status. The pattern of clinical practice in terms of EOR for grade II and III astrocytoma patients did not change significantly during this study period. However, there was decreased RT utilization as treatment for grade II astrocytoma patients after 2005. Conclusion Results from the SEER database indicate that there were improvements in the overall survival of grade II and III astrocytoma patients over the past decade. Analysis of the clinical practice patterns identified potential opportunities for impacting the clinical course of these patients.

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