scholarly journals Nomograms Predict Overall Survival and Cancer-Specific Survival in Patients with Fibrosarcoma: A SEER-Based Study

2020 ◽  
Vol 2020 ◽  
pp. 1-9
Author(s):  
Guang-Heng Xiang ◽  
Juan-Juan Zhu ◽  
Chen-Rong Ke ◽  
Yi-Min Weng ◽  
Ming-Qiao Fang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Tumor Size ◽  
Multivariate Analyses ◽  
Discrimination Performance ◽  
Tumor Stage ◽  
Good Discrimination ◽  
Cancer Specific Survival ◽  
Internal Validation ◽  
Clinical Benefits

Purpose. Due to the rarity, it is difficult to predict the survival of patients with fibrosarcoma. This study aimed to apply a nomogram to predict survival outcomes in patients with fibrosarcoma. Methods. A total of 2235 patients with diagnoses of fibrosarcoma were registered in the Surveillance, Epidemiology, and End Results database, of whom 663 patients were eventually enrolled. Univariate and multivariate Cox analyses were used to identify independent prognostic factors. Nomograms were constructed to predict 3-year and 5‐year overall survival and cancer‐specific survival of patients with fibrosarcoma. Results. In univariate and multivariate analyses of OS, age, sex, race, tumor stage, pathologic grade, use of surgery, and tumor size were identified as independent prognostic factors. Age, sex, tumor stage, pathologic grade, use of surgery, and tumor size were significantly associated with CSS. These characteristics were further included to establish the nomogram for predicting 3-year and 5-year OS and CSS. For the internal validation of the nomogram predictions of OS and CSS, the C-indices were 0.784 and 0.801. Conclusion. We developed the nomograms that estimated 3-year and 5-year OS and CSS. These nomograms not only have good discrimination performance and calibration but also provide patients with better clinical benefits.

scholarly journals Nomograms Predict Overall Survival And Cancer-Specific Survival In Patients With Fibrosarcoma: A SEER-Based Study

2020 ◽  
Author(s):  
Guangheng Xiang ◽  
Juan-Juan Zhu ◽  
Chen-Rong Ke ◽  
Yi-Min Weng ◽  
Ming-Qiao Fang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Tumor Size ◽  
Multivariate Analyses ◽  
Discrimination Performance ◽  
Tumor Stage ◽  
Good Discrimination ◽  
Cancer Specific Survival ◽  
Internal Validation ◽  
Clinical Benefits

Abstract Background Due to the rarity, it is difficult to predict the survival of patients with fibrosarcoma. This study aimed to apply a nomogram to predict survival outcomes in patients with fibrosarcoma. Methods A total of 2235 patients with diagnoses of fibrosarcoma were registered in the Surveillance, Epidemiology, and End Results database, of whom 663 patients were eventually enrolled. Univariate and multivariate Cox analyses were used to identify independent prognostic factors. Nomograms were constructed to predict 3‐ and 5‐year overall survival and cancer‐specific survival of patients with fibrosarcoma. Results In univariate and multivariate analyses of OS, age, sex, race, tumor stage, pathologic grade, use of surgery and tumor size identified as independent prognostic factors. Age, sex, tumor stage, pathologic grade, use of surgery and tumor size were significantly associated with CSS. These characteristics were further included to establish the nomogram for predicting 3- and 5- year OS and CSS. For the internal validation of the nomogram predictions of OS and CSS, the C-indices were 0.784 and 0.801. Conclusion We developed and validated the nomograms that estimated 3- and 5-year OS and CSS. These nomograms not only have good discrimination performance and calibration, but also provide patients with better clinical benefits.

scholarly journals Prognostic Nomograms for Predicting Overall Survival and Cancer‐Specific Survival of Patients With Malignant Pheochromocytoma and Paraganglioma

2021 ◽  
Vol 12 ◽  
Author(s):  
Lei Zheng ◽  
Yalong Gu ◽  
Jiangcun Silang ◽  
Jinlong Wang ◽  
Feng Luo ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Univariate Analysis ◽  
Roc Curves ◽  
Tumor Stage ◽  
Malignant Pheochromocytoma ◽  
Tumor Type ◽  
Lasso Regression ◽  
Cancer Specific Survival ◽  
Calibration Curves

BackgroundMalignant pheochromocytoma and paraganglioma (PPGL) are rare tumors with few prognostic tools. This study aimed to construct nomograms for predicting 3- and 5-year survival for patients with malignant PPGL.MethodsThe patient data was retrieved from the Surveillance, Epidemiology, and End Results (SEER) database. A total of 764 patients diagnosed with malignant PPGL from 1975 to 2016 were included in this study. The patients were randomly divided into two cohorts; the training cohort (n = 536) and the validation cohort (n = 228). Univariate analysis, Lasso regression, and multivariate Cox analysis were used to identify independent prognostic factors, which were then utilized to construct survival nomograms. The nomograms were used to predict 3- and 5-year overall survival (OS) and cancer-specific survival (CSS) for patients with malignant PPGL. The prediction accuracy of the nomogram was assessed using the concordance index (C-index), receiver operating characteristic (ROC) curves and calibration curves. Decision curve analysis (DCAs) was used to evaluate the performance of survival models.ResultsAge, gender, tumor type, tumor stage, or surgery were independent prognostic factors for OS in patients with malignant PPGL, while age, tumor stage, or surgery were independent prognostic factors for CSS (P <.05). Based on these factors, we successfully constructed the OS and CSS nomograms. The C-indexes were 0.747 and 0.742 for the OS and CSS nomograms, respectively. In addition, both the calibration curves and ROC curves for the model exhibited reliable performance.ConclusionWe successfully constructed nomograms for predicting the OS and CSS of patients with malignant PPGL. The nomograms could inform personalized clinical management of the patients.

scholarly journals Development and validation of nomograms for prediction of overall survival and cancer-specific survival of patients of colorectal cancer

2019 ◽  
Vol 50 (3) ◽  
pp. 261-269
Author(s):  
Jieyun Zhang ◽  
Yue Yang ◽  
Xiaojian Fu ◽  
Weijian Guo
Keyword(s):  
Colorectal Cancer ◽  
Overall Survival ◽  
Prognostic Factors ◽  
Prognostic Model ◽  
Cox Regression ◽  
External Validation ◽  
Cancer Prognosis ◽  
Cancer Specific Survival ◽  
Internal Validation ◽  
Development And Validation

Abstract Purpose Nomograms are intuitive tools for individualized cancer prognosis. We sought to develop a clinical nomogram for prediction of overall survival and cancer-specific survival for patients with colorectal cancer. Methods Patients with colorectal cancer diagnosed between 1988 and 2006 and those who underwent surgery were retrieved from the Surveillance, Epidemiology, and End Results database and randomly divided into the training (n = 119 797) and validation (n = 119 797) cohorts. Log-rank and multivariate Cox regression analyses were used in our analysis. To find out death from other cancer causes and non-cancer causes, a competing-risks model was used, based on which we integrated these significant prognostic factors into nomograms and subjected the nomograms to bootstrap internal validation and to external validation. Results The 1-, 3-, 5- and 10-year probabilities of overall survival in patients of colorectal cancer after surgery intervention were 83.04, 65.54, 54.79 and 38.62%, respectively. The 1-, 3-, 5- and 10-year cancer-specific survival was 87.36, 73.44, 66.22 and 59.11%, respectively. Nine independent prognostic factors for overall survival and nine independent prognostic factors for cancer specific survival were included to build the nomograms. Internal and external validation CI indexes of overall survival were 0.722 and 0.721, and those of cancer-specific survival were 0.765 and 0.766, which was satisfactory. Conclusions Nomograms for prediction of overall survival and cancer-specific survival of patients with colorectal cancer. Performance of the model was excellent. This practical prognostic model may help clinicians in decision-making and design of clinical studies.

A nomogram for predicting overall survival in patients with uterine leiomyosarcoma: a SEER population-based study

2020 ◽  
Vol 16 (10) ◽  
pp. 573-584
Author(s):  
Yu-Jie Lu ◽  
Han Wang ◽  
Lin-Yan Fang ◽  
Wen-Jie Wang ◽  
Wei Song ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Marital Status ◽  
Tumor Size ◽  
Multivariate Analyses ◽  
Predictive Accuracy ◽  
Population Based ◽  
Uterine Leiomyosarcoma ◽  
Population Based Study ◽  
End Results

Aim: To establish and validate a nomogram for the estimation of overall survival of patients with uterine leiomyosarcoma (uLMS). Methods: Information on patients diagnosed as uLMS was retrospectively retrieved from the Surveillance, Epidemiology, and End Results database. The patients were randomly assigned into the training and the validation cohorts. Univariate and multivariate analyses were used to determine the independent prognostic factors for building a nomogram for predicting overall survival. The predictive accuracy was evaluated based on the concordance indices and the calibration plots. Results: A nomogram that combined age, marital status, tumor size, Surveillance, Epidemiology, and End Result stage, surgery and radiation was established. The internal and external concordance indices were 0.748 and 0.745, respectively. The calibration plots approached 45 degrees. Conclusion: The nomogram might be an effective tool for predicting the survival of patients with uLMS.

scholarly journals Characteristics and prognosis of pelvic Ewing sarcoma: a SEER population-based study

PeerJ ◽  
2019 ◽  
Vol 7 ◽  
pp. e7710
Author(s):  
Li Chen ◽  
Cheng Long ◽  
Jiaxin Liu ◽  
Fei Xing ◽  
Xin Duan
Keyword(s):  
Prognostic Factors ◽  
Ewing Sarcoma ◽  
Tumor Size ◽  
Proportional Hazards ◽  
Multivariate Analyses ◽  
Survival Rates ◽  
Tumor Stage ◽  
Population Based ◽  
Cox Proportional Hazards ◽  
Survival Prediction

Background The pelvis is one of the primary sites of Ewing sarcoma (ES) and is associated with poorer prognoses than the extremities. Due to the rarity of this disease and limited data available, the prognostic factors of pelvic ES remain controversial. Thus, this study aimed to identify independent prognostic factors, and develop a nomogram for predicting survival rates in patients with pelvic ES. Methods Using data provided by the Surveillance, Epidemiology, and End Results (SEER) database, variables including age, sex, race, tumor size, tumor stage, surgery, and radiotherapy were analyzed using the Kaplan–Meier method and Cox proportional hazards regression. Based on the results of multivariate analyses, a nomogram was built to predict the overall survival (OS) of patients with pelvic ES. The performance of the nomogram was evaluated by the concordance index (C-index). Results A total of 267 cases diagnosed between 2004 and 2016 were included in the study. Univariate and multivariate analyses showed that patients who were younger, white, had a localized tumor stage, or underwent surgery were associated with improved prognoses, while no significant differences were observed in OS based on sex, tumor size, or radiotherapy. A nomogram was developed and the C-index was 0.728, indicating adequate performance for survival prediction. Conclusions Age, race, tumor stage, and surgery were identified as independent prognostic factors for the OS of pelvic ES. The nomogram developed in this study can individually predict 3- and 5-year OS in patients with pelvic ES.

Prognostic features and outcomes in primary liver sarcoma.

2013 ◽  
Vol 31 (4_suppl) ◽  
pp. 150-150
Author(s):  
Mary L. Guye ◽  
Leanne Streja ◽  
Steven L. Chen ◽  
Lori A. Uyeno ◽  
Joseph Kim ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Tumor Size ◽  
Cox Proportional Hazards ◽  
Advanced Stage ◽  
Hepatic Malignancy ◽  
Related Factors ◽  
Cancer Specific Survival ◽  
Prognostic Features ◽  
Treatment Type

150 Background: Primary liver sarcoma (PLS) is a rare and aggressive hepatic malignancy. Due to the low incidence of PLS, prognostic factors have not been well characterized. The purpose of our study was to evaluate survival outcomes in primary hepatic sarcomas and determine which factors predict survival. Methods: The Surveillance Epidemiology and End Results registry was used to identify patients with PLS from 1988-2009. Patients were evaluated by standard clinical and pathological indices including: age, gender, race, tumor size, tumor grade, histology, and extent of disease. Treatment related factors included surgery and radiation. Overall survival was assessed by Kaplan-Meier method. Univariate and stepwise multivariate Cox proportional hazards analyses were performed to identify prognostic factors. Results: 541 patients with PLS were identified. The mean age was 52 and most patients were male (55%) and white (75%). The most common histology type was blood vessel tumors (50.1%) followed by soft tissue neoplasms (17.7%) and complex mixed-stromal neoplasms (14.6%). Only 33% of patients underwent surgery and most (93%) did not receive radiation. When assessing outcomes, we observed median overall survival (OS) and cancer specific survival (CSS) of 6 months for the entire cohort. When stratified by treatment type, those who received surgery + radiation had the best survival (MS=97mos, p<.001) compared to those who received either radiation alone (MS=5mos) or no treatment (MS=2mos). Stepwise multivariate analysis showed that age, male gender, tumor size, advanced stage, and no surgery were independent predictors of worse survival, all p-values < .005. Conclusions: Primary liver sarcoma is an aggressive hepatic malignancy with low median OS of 6 months. Patients treated with surgery + radiation had the best outcome with a median survival of 97 months. Independent predictors for decreased survival included age, gender, tumor size, advanced stage, and no surgery.

scholarly journals Chemotherapy Plus Radiotherapy Versus Radiotherapy in Patients With Small Cell Carcinoma of the Esophagus: A SEER Database Analysis

2021 ◽  
Vol 28 ◽  
pp. 107327482198932
Author(s):  
Tao Li ◽  
Sijia Chen ◽  
Zongkai Zhang ◽  
Limei Lin ◽  
Qian Wu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Prognostic Factors ◽  
Cell Carcinoma ◽  
Small Cell Carcinoma ◽  
Tumor Size ◽  
Small Cell ◽  
Prognosis Factors ◽  
Cancer Specific Survival ◽  
Carcinoma Of The Esophagus ◽  
Factors Affecting

Background: Small cell carcinoma of the esophagus is a rare malignant tumor. We aimed to explore the chemotherapeutic efficacy on the prognosis of patients with small cell carcinoma of the esophagus who received radiotherapy. Methods: To identify the population of interest, Surveillance, Epidemiology, and End Results data from 1996 to 2016 were chosen. Univariate and multivariate analyses were used to probe into prognosis factors. Multivariate Cox regression analysis was conducted to identify factors related to overall survival and cancer-specific survival. Results: Overall, data from 162 patients were analyzed in this study. Tumor size (P = 0.014), T staging (P = 0.028), and chemotherapy (P < 0.001) were independent prognostic factors affecting overall survival. Patients with regional disease (hazard ratio = 5.435, P < 0.001) and distant metastasis (hazard ratio = 2.183, P < 0.001) who received radiotherapy alone had worse survival than those receiving chemoradiotherapy. Tumor size (P = 0.004) and chemotherapy (P < 0.001) were independent prognostic factors affecting cancer-specific survival. Tumor size was an independent factor affecting cancer-specific survival for patients receiving chemoradiation. Conclusions: Age, T staging, tumor size, primary site, and chemotherapy are independent prognosis factors affecting overall survival and cancer-specific survival in patients with small cell carcinoma of the esophagus who receive radiotherapy. Chemotherapy might further improve cancer-specific survival in patients with small cell carcinoma of the esophagus receiving radiotherapy at all stages.

scholarly journals Clinicopathological characteristics and prognostic factors of cervical adenocarcinoma

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Min Wang ◽  
Bo Yuan ◽  
Zhen-huan Zhou ◽  
Wei-wei Han
Keyword(s):  
Prognostic Factors ◽  
Tumor Size ◽  
Survival Rates ◽  
Tumor Grade ◽  
Figo Stage ◽  
Cervical Adenocarcinoma ◽  
Stage Ii ◽  
Prognostic Indicators ◽  
Rank Test ◽  
Cancer Specific Survival

AbstractWe aimed to assess the clinicopathological features and to determine the prognostic factors of cervical adenocarcinoma (AC). Relevant data were extracted from surveillance, epidemiology and end results database from 2004 to 2015. The log-rank test and Cox proportional hazard analysis were subsequently utilized to identify independent prognostic factors. A total of 3102 patients were identified. The enrolled patients were characterized by higher proportion of early FIGO stage (stage I: 65.9%; stage II: 14.1%), low pathological grade (grade I/II: 49.1%) and tumor size ≤ 4 cm (46.8%). The 5- and 10-year cancer-specific survival rates of these patients were 74.47% and 70.00%, respectively. Meanwhile, the 5- and 10-year overall survival (OS) rates were 71.52% and 65.17%, respectively. Multivariate analysis revealed that married status, surgery as well as chemotherapy were independent favorable prognostic indicators. Additionally, aged > 45, tumor grade III/IV, tumor size > 4 cm, advanced FIGO stage and pelvic lymph node metastasis (LNM) were unfavorable prognostic factors (all P < 0.01). Stratified analysis found that patients without surgery could significantly benefit from chemotherapy and radiotherapy. In addition, chemotherapy could significantly improve the survival in stage II–IV patients and radiotherapy could only improve the survival in stage III patients (all P < 0.01). Marital status, age, grade, tumor size, FIGO stage, surgery, pelvic LNM and chemotherapy were significantly associated with the prognosis of cervical AC.

scholarly journals New nomograms based on treatment outcome and prognostic factors for patients with spinal diffuse large B-cell lymphoma: A population‐based study

2020 ◽  
Author(s):  
Ben Wang ◽  
Lijie Chen ◽  
Boda Chen ◽  
Chenglong Xie ◽  
Zhenxuan Shao ◽  
...  
Keyword(s):  
Prognostic Factors ◽  
B Cell ◽  
Cell Lymphoma ◽  
B Cell Lymphoma ◽  
Treatment Method ◽  
Population Based ◽  
Cancer Specific Survival ◽  
Internal Validation ◽  
Large B Cell Lymphoma ◽  
Large B Cell

Abstract Background: Spinal diffuse large B-cell lymphoma (DLBCL) was a rare and malignant tumor, while few studies researched the prognostic factors. The prognostic factors which might have impacts on spinal DLBCL was not clear. Although chemotherapy was recognized as an optimal treatment method, but the curative effect of radiotherapy and surgery were controversial. Methods: The records of patients with spinal DLBCL were selected from the SEER database from 1991 to 2016. The incidence obtained by database was analyzed by Joinpoint Regression Program. The optimal cut-off values of age and year of diagnosis were identified by X-tail program. Univariate and multivariate survival analysis were calculated to identify independent prognostic factors. Prognostic factors were included to predict the survival possibility compared with 5 years of overall (OS) and cancer-specific survival (CSS) via the new nomograms. Results: A total of 917 patients were enrolled. Age, year of diagnosis and chemotherapy were demonstrated as independent prognostic factors for CSS and OS, and primary site was another independent prognostic factor for CSS. However, radiotherapy and surgery might be ineffective in survival. All factors were included to generate the nomograms for CSS and OS. The concordance indices (C-index) for internal validation of OS and CSS prediction were 0.697 (95%CI: 0.662-0.732) and 0.709 (95%CI: 0.692- 0.727) respectively. Conclusions: Age and year of diagnosis are closely associated with the prognosis of spinal DLBCL, and chemotherapy is an ideal treatment modality. The new nomogram is a favourable tool to evaluate the survival possibility, and is benefit for the oncologist to make clinical decisions.

scholarly journals Nomogram to predict overall survival for patients with pseudomyxoma peritonei of appendiceal origin: A retrospective cohort study

2020 ◽  
Author(s):  
Mingjian Bai ◽  
Shilong Wang ◽  
Ruiqing Ma ◽  
Ying Cai ◽  
Yiyan Lu ◽  
...  
Keyword(s):  
Overall Survival ◽  
Pseudomyxoma Peritonei ◽  
Roc Analysis ◽  
Prediction Models ◽  
Radical Surgery ◽  
Individual Risk ◽  
Good Discrimination ◽  
Internal Validation ◽  
Discrimination Ability ◽  
First Time

Abstract Background Pseudomyxoma peritonei (PMP) is a rare disease, the prognosis of overall survival (OS) is affected by many factors, present study aim to define independent prediction indicators and establish a nomogram for PMP patients.Methods 119 PMP patients received cytoreductive surgery (CRS) combined with hyperthermic intraperitoneal chemotherapy (HIPEC) in our center for the first time were included between 01/06/2013 and 22/11/2019 . The log-rank test was used to compare the OS rate among groups, subsequently, variables with P<0.10 were subjected to multivariate Cox model for defining independent prediction indicators. Finally, the nomogram prediction models will be established and for internal validation.Results Multivariate analysis showed Sex, D-Dimer, CA125, CA19-9, PCI, and degree of radical surgery were independently associated with OS in PMP patients. A nomogram was plotted based on the independent predictive factors and undergone internal validation, ROC analysis was performed to calculate discrimination ability of the nomogram, the C-index was 0.880 (95%CI: 0.806- 0.933) and calibration plots showed good performance. Conclusions Six independent prognostic factor for predicting survival in PMP patients were difined, the nomogram has a good discrimination ability for individual risk predition, more researches are needed to verify and improve the prediction model.

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