Dataset Information

A nomogram for predicting overall survival in patients with Ewing sarcoma: a SEER-based study.

ABSTRACT: BACKGROUND:Ewing sarcoma, the second most frequent bone tumor in children and adolescents, is often presented with localized disease or metastatic-related symptoms. In this study, we aim to construct and validate a nomogram for patients with Ewing sarcoma to predict the 3- and 5-year overall survival (OS) based on the Surveillance, Epidemiology, and End Results (SEER) database. METHODS:Demographic and clinic pathological characteristics of patients with Ewing sarcoma diagnosed between 2010 and 2015 were extracted from SEER database. Univariate and multivariate Cox analyses were carried out to identify the independent characteristics. The independent factors were further included into the construction of a nomogram. Finally, c-index and calibration curves were used to validate the nomogram. RESULTS:A total of 578 patients were enrolled into our analysis. The results of univariate Cox analysis showed that age, 7th AJCC stage, 7th AJCC T stage, 7th AJCC N stage, 7th AJCC M stage, metastatic status to lung, liver and bone were significant factors. Multivariate Cox analysis was performed and it confirmed age, N stage and bone metastasis as independent variables. Next, a nomogram was constructed using these independent variables in prediction to the 3- and 5-year OS. Furthermore, favorable results with c-indexes (0.757 in training set and 0.697 in validation set) and calibration curves closer to ideal curves indicated the accurate predictive ability of this nomogram. CONCLUSIONS:The individualized nomogram demonstrated a good ability in prognostic prediction for patients with Ewing sarcoma.

SUBMITTER: Zhou Z

PROVIDER: S-EPMC7661249 | biostudies-literature | 2020 Nov

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

A nomogram for predicting overall survival in patients with Ewing sarcoma: a SEER-based study.

Zhou Zhenggang Z Wang Jinyu J Fang Liming L Ma Jianlin J Guo Mingbo M

BMC musculoskeletal disorders 20201112 1

<h4>Background</h4>Ewing sarcoma, the second most frequent bone tumor in children and adolescents, is often presented with localized disease or metastatic-related symptoms. In this study, we aim to construct and validate a nomogram for patients with Ewing sarcoma to predict the 3- and 5-year overall survival (OS) based on the Surveillance, Epidemiology, and End Results (SEER) database.<h4>Methods</h4>Demographic and clinic pathological characteristics of patients with Ewing sarcoma diagnosed bet ...[more]

PMID: 33183244

Similar Datasets

Project description:BACKGROUND:Extremity liposarcoma represents 25% of extremity soft tissue sarcoma and has a better prognosis than liposarcoma occurring in other anatomic sites. The purpose of this study was to develop two nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) of patients with extremity liposarcoma. METHODS:A total of 2170 patients diagnosed with primary extremity liposarcoma between 2004 and 2015 were extracted from the Surveillance, Epidemiology, and End Results (SEER) database. Univariate and multivariate Cox analyses were performed to explore the independent prognostic factors and establish two nomograms. The area under the curve (AUC), C-index, calibration curve, decision curve analysis (DCA), Kaplan-Meier analysis, and subgroup analyses were used to evaluate the nomograms. RESULTS:Six variables were identified as independent prognostic factors for both OS and CSS. In the training cohort, the AUCs of the OS nomogram were 0.842, 0.841, and 0.823 for predicting 3-, 5-, and 8-year OS, respectively, while the AUCs of the CSS nomogram were 0.889, 0.884, and 0.859 for predicting 3-, 5-, and 8-year CSS, respectively. Calibration plots and DCA revealed that the nomogram had a satisfactory ability to predict OS and CSS. The above results were also observed in the validation cohort. In addition, the C-indices of both nomograms were significantly higher than those of all independent prognostic factors in both the training and validation cohorts. Stratification of the patients into high- and low-risk groups highlighted the differences in prognosis between the two groups in the training and validation cohorts. CONCLUSION:Age, sex, tumor size, grade, M stage, and surgery status were confirmed as independent prognostic variables for both OS and CSS in extremity liposarcoma patients. Two nomograms based on the above variables were established to provide more accurate individual survival predictions for extremity liposarcoma patients and to help physicians make appropriate clinical decisions.

Project description:Ewing's sarcoma is a high-grade malignancy bone and soft tissue tumor that most commonly occurs in children and adolescents. Although the overall prognosis of Ewing's sarcoma has improved, the 5-year survival rate has not improved significantly. The study aimed to determine the risk factors independently associated with the prognosis of Ewing's sarcoma and to construct a nomogram to predict patient survival. Patients diagnosed with Ewing's sarcoma were collected from the Surveillance, Epidemiology, and End Results program database between 2004 and 2015 and further divided into training and validation cohort. Univariate and multivariate Cox regression analyses were used to identify meaningful independent prognostic factors. The nomogram was used to predict 3- and 5-year overall survival (OS) and cancer-specific survival (CSS). Finally, the nomogram was verified internally and externally through the training and validation cohorts, and the predictive capability was evaluated using the receiver operating characteristic (ROC) curve, C-index, and calibration curve and compared with that of the 7th TNM stage. A total of 1120 patients were divided into training (n = 713) and validation (n = 407) cohorts. Based on the multivariate analysis of the training cohort, a nomogram that integrated age, tumor size, primary site, N stage, and M stage was constructed (P < 0.05). The predicted C-indexes of OS and CSS of the training cohort were 0.744 (95% CI 0.717-0.771) and 0.743 (95% CI 0.715-0.770), respectively. However, the TNM stage had a C-index of 0.695 (95% CI 0.666-0.724) and 0.698 (95% CI 0.669-0.727) for predicting OS and CSS, respectively. The nomogram showed higher C-indexes than those in the TNM stage. Furthermore, the internal and external calibration curves showed good consistency between the predicted and observed values. Age, tumor size, primary site, N stage, and M stage are independent risk factors affecting the OS and CSS in Ewing's sarcoma patients. Compared with the 7th TNM staging, the nomogram consisting of these factors was more accurate for risk assessment and survival prediction in patients with Ewing's sarcoma, thus providing a novel reliable tool for risk assessment and survival prediction in Ewing's sarcoma patients.

Project description:BackgroundAlthough some studies have explored prognostic factors of myxofibrosarcoma (MFS), the sample sizes were small, generally fewer than 100 patients. There is still no effective prognostic model for MFS patients based on a large population and comprehensive factors. The present study was designed to establish and validate a large population-based, clinically relevant prognostic nomogram for predicting 3- and 5-year overall survival (OS) in patients with MFS.MethodsWe identified patients with MFS (ICD-O-3 code: 8811/3) who were diagnosed between 2004 and 2015 from the Surveillance, Epidemiology, and End Results database and separated them into training and validation cohorts (7:3 ratio). Survival was described using the Kaplan-Meier method. Univariate and multivariate Cox regression analyses were used to identify prognostic factors of survival. An individual nomogram was established to predict OS at 3 and 5 years in MFS patients. The discriminative ability and predictive accuracy of the nomogram were compared to those of the traditional American Joint Committee on Cancer (AJCC) staging system in the training and validation cohorts. Finally, MFS patients were divided into two subgroups based on the prognostic index (PI) score of the nomogram, and the survival outcomes of the subgroups were compared.ResultsA total of 1,270 patients were included. Age at diagnosis, total number of in situ or malignant tumors, tumor size, tumor site, tumor extension, AJCC stage, surgical status, chemotherapy, and radiotherapy were the independent predictors of survival and were included in the nomogram. The nomogram had C-indexes of 0.806 in the training cohort and 0.783 in the validation cohort, which were greater than those of the sixth edition of the AJCC staging system (training cohort, 0.669 and validation cohort, 0.674). Decision curve analysis (DCA) revealed that the nomogram was useful with high clinical net benefits. Survival outcomes were significantly different between the different risk subgroups (P<0.001).ConclusionsA novel nomogram based on a large population was constructed to evaluate survival outcomes for MFS. Its predictive efficacy was markedly superior than that of the traditional sixth edition of the AJCC staging system.

Project description:Background:To establish and validate nomograms for predicting the overall survival (OS) and cancer-specific survival (CSS) in patients with papillary renal cell carcinoma (pRCC). Methods:Patients diagnosed with pRCC between 2010 and 2014 in the Surveillance, Epidemiology, and End Results (SEER) database were retrospectively included in this study and divided into training and validation groups randomly. Uni- and multivariate Cox regression analyses were used to identify significant variables related to OS and CSS in the training group. Based on results of multivariate Cox regression analysis, nomograms for 3- and 5-year CSS and OS were established, respectively. Additionally, Kaplan-Meier (KM) survival curves were produced to learn the actual effects of different variables. Finally, the nomograms were evaluated both in the training group and the validation group using the area under the receiver operating characteristic (ROC) curve, the concordance index (C-index) and calibration curves. Results:A total of 4,859 eligible patients were enrolled, with 3,403 categorized into the training group and 1,456 into the validation group. Seven factors [age, T stage, N stage, M stage, use of surgery/lymph node removal (LNR) and insurance status] were significantly related to OS and seven factors (age, T stage, N stage, M stage and use of surgery/chemotherapy/LNR) were significantly associated with CSS. These factors were eventually included in the predictive nomograms. The C-indexes for OS in the training and validation groups were 0.764 and 0.723 respectively, and 0.859 and 0.824 for CSS. The 3- and 5-year AUCs for OS were 0.779 and 0.752 in the training cohort, and 0.749 and 0.722 in the validation cohort. Similarly, 3- and 5-year AUCs for OS were 0.871 and 0.844 in the training cohort, and 0.853 and 0.822 in the validation group. Finally, the calibration curves suggested that the predictive nomograms had a good consistency between the observed and the predicted survival. Conclusions:It was the first time to develop nomograms to predict the survival outcomes of pRCC patients. The prognostic nomograms were reliable with high accuracy, which might have guiding significance for clinical practice.

Dataset Information

A nomogram for predicting overall survival in patients with Ewing sarcoma: a SEER-based study.

Publications

A nomogram for predicting overall survival in patients with Ewing sarcoma: a SEER-based study.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure