Commentary on “Adverse prognostic factors for testicular cancer-specific survival: A population-based study of 27,948 patients.” Fosså SD, Cvancarova M, Chen L, Allan AL, Oldenburg J, Peterson DR, Travis LB, Oslo University Hospital, University of Oslo, Norway

2012 ◽  
Vol 30 (1) ◽  
pp. 112-113
Author(s):  
Jerome P. Richie
Keyword(s):  
Prognostic Factors ◽  
Testicular Cancer ◽  
Population Based ◽  
University Hospital ◽  
Cancer Specific Survival ◽  
Population Based Study ◽  
University Of Oslo

scholarly journals Conditional Survival After Surgical Resection of Appendiceal Tumors: a Population-based Study

2021 ◽  
Author(s):  
Shutao Zhao ◽  
Chang Lu ◽  
Junan Li ◽  
Chao Zhang ◽  
Xudong Wang
Keyword(s):  
Prognostic Factors ◽  
Cox Regression ◽  
Population Based ◽  
Conditional Survival ◽  
Seer Database ◽  
Cancer Specific Survival ◽  
Population Based Study ◽  
Factors Affecting ◽  
Probability Of Survival ◽  
N Stage

Abstract Background: This study aimed to evaluate the conditional survival (CS) of appendiceal tumors (ATs) after surgery.Methods: A total of 3,031 patients with ATs who underwent surgery were included in the Surveillance Epidemiology and End Results (SEER) database from 2004 to 2016. A multivariate Cox regression model was used to analyze the prognostic factors affecting overall survival (OS) and cancer-specific survival (CSS). CS was used to calculate the probability of survival for another 3 years after the patient had survived x years. The formulas were COS3 = OS (x + 3) /OS (x), and CCS3 = CSS (x + 3)/CSS (x).Results: The 1-year, 3-year, and 5-year OSs for all patients were 95.6%, 83.3%, and 73.9%, respectively, while the 1-year, 3-year, and 5-year CSSs were 97.0%, 87.1%, and 79.9%, respectively. Age, grade, histology, N stage, carcinoembryonic antigen (CEA), and radiation were independent prognostic factors for OS and CSS. For patients that survived for 1 year, 3 years, and 5 years, their COS3s were 81.7%, 83.9%, and 87.0%, respectively. The CCS3s were 85.5%, 88.3%, and 92.0% respectively. In patients with poor clinicopathological factors, COS3 and CCS3 increased significantly, and the survival gap between OS and COS3, CSS and CCS3 was more obvious.Conclusions: CS for appendiceal tumors were dynamic and increased over time, especially in patients with poor prognosis.

Delivery of chemotherapy for testicular cancer in routine practice: A population-based study

2019 ◽  
Vol 37 (3) ◽  
pp. 183.e17-183.e24 ◽  
Author(s):  
Safiya Karim ◽  
Xuejiao Wei ◽  
Michael J. Leveridge ◽  
David Robert Siemens ◽  
Andrew G. Robinson ◽  
...  
Keyword(s):  
Testicular Cancer ◽  
Population Based ◽  
Routine Practice ◽  
Population Based Study

Treatment Outcomes and Prognostic Factors in Male Patients With Stage IV Breast Cancer: A Population-based Study

2018 ◽  
Vol 18 (1) ◽  
pp. e97-e105 ◽  
Author(s):  
Wei Chen ◽  
Ying Huang ◽  
Gary D. Lewis ◽  
Sean S. Szeja ◽  
Sandra S. Hatch ◽  
...  
Keyword(s):  
Breast Cancer ◽  
Prognostic Factors ◽  
Treatment Outcomes ◽  
Stage Iv ◽  
Population Based ◽  
Population Based Study ◽  
Stage Iv Breast Cancer ◽  
Male Patients

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 A Novel Nomogram for Predicting Cancer-Specific Survival in Patients With Spinal Chordoma: A Population-Based Analysis

2021 ◽  
Vol 20 ◽  
pp. 153303382110365
Author(s):  
Zhangheng Huang ◽  
Zhiyi Fan ◽  
Chengliang Zhao ◽  
He Sun
Keyword(s):  
Prognostic Factors ◽  
Area Under The Curve ◽  
Risk Groups ◽  
Population Based ◽  
Disease Stage ◽  
Survival Prediction ◽  
Cancer Specific Survival ◽  
Spinal Chordoma ◽  
Prediction Of Prognosis ◽  
High Degree

Background: Chordoma is a rare malignant bone tumor, and the survival prediction for patients with chordoma is difficult. The objective of this study was to construct and validate a nomogram for predicting cancer-specific survival (CSS) in patients with spinal chordoma. Methods: A total of 316 patients with spinal chordoma were identified from the SEER database between 1998 and 2015. The independent prognostic factors for patients with spinal chordoma were determined by univariate and multivariate Cox analyses. The prognostic nomogram was established for patients with spinal chordoma based on independent prognostic factors. Furthermore, we performed internal and external validations for this nomogram. Results: Primary site, disease stage, histological type, surgery, and age were identified as independent prognostic factors for patients with spinal chordoma. A nomogram for predicting CSS in patients with spinal chordoma was constructed based on the above 5 variables. In the training cohort, the area under the curve for predicting 1-, 3-, and 5-year CSS were 0.821, 0.856, and 0.920, respectively. The corresponding area under the curve in the validation cohort were 0.728, 0.804, and 0.839, respectively. The calibration curves of the nomogram showed a high degree of agreement between the predicted and the actual results, and the decision curve analysis further demonstrated the satisfactory clinical utility of the nomogram. Conclusions: The prognostic nomogram provides a considerably more accurate prediction of prognosis for patients with spinal chordoma. Clinicians can use it to categorize patients into different risk groups and make personalized treatment methods.

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