A Novel Nomogram and Risk Classification System Predicting the Cancer-Specific Survival of Patients with Initially Diagnosed Metastatic Esophageal Cancer: A SEER-Based Study

2018 ◽  
Vol 26 (2) ◽  
pp. 321-328 ◽  
Author(s):  
Xin Tang ◽  
Xiaojuan Zhou ◽  
Yanying Li ◽  
Xue Tian ◽  
Yongsheng Wang ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Classification System ◽  
Risk Classification ◽  
Cancer Specific Survival

scholarly journals Identify Prognostic Factors and Establish a Risk Stratification Model to Predict Cancer-Specific Survival for Patients with Pancreatic Cancer Liver Metastasis: A Population-Based Study

2021 ◽  
Author(s):  
Biyang Cao ◽  
Chenchen Wu ◽  
Letian Zhang ◽  
Jing Wang
Keyword(s):  
Pancreatic Cancer ◽  
Prognostic Factors ◽  
Liver Metastasis ◽  
Classification System ◽  
Cox Regression ◽  
Risk Classification ◽  
Prognostic Models ◽  
Cancer Specific Survival ◽  
Discriminative Ability ◽  
Cox Regression Analysis

Abstract Background Pancreatic cancer liver metastasis (PCLM) is a commonly fatal disease, but there are few prognostic models for these entities. The purpose of this study is to investigate prognostic factors based on clinicopathological characteristics and establish a prognostic nomogram predicting the cancer-specific survival (CSS) for PCLM patients. Methods The characteristics of 6015 patients with PCLM between 2010 and 2015 from Surveillance, Epidemiology, and End Results (SEER) database were analyzed. Prognostic factors and nomogram predicting CSS were developed by Cox proportional hazard regression model. The predictive accuracy and discriminative ability of nomogram were assessed by concordance index (C-index), calibration curve, decision curve analyses (DCAs) and receiver operating characteristic (ROC) curve. Moreover, a risk classification system was built according to the cut-off values off the nomogram. Results Based on the univariate and multivariate Cox regression analysis, significant prognostic factors were identified and included to establish the nomogram for CSS. The median survival time (MST) for all patients is 4.0 months (95% confidence interval [CI]:3.8–4.2) and CSS at 6, 12 and 18 months was 34.12%, 15.63% and 7.83%, respectively. The C-index of nomogram was 0.693 (95%CI: 0.689–0.697) and all verification results showed an accurate and discriminative ability in predicting CSS. Significant differences in Kaplan–Meier curves were observed in patients stratified into different risk groups (p < 0.001), with MST of 7.0 months (95% CI: 6.7–7.3), 3.0 months (95% CI: 2.7–3.3), and 2.0 months (95% CI: 1.8–2.2), respectively. Conclusions A prognostic nomogram and corresponding risk classification system were proposed to predict CSS for PCLM.

scholarly journals A neotype nomogram based on accessible clinical indicators to predict the overall survival of esophageal cancer patients underwent radical resection

2020 ◽  
Author(s):  
Xinye Li ◽  
Jinming Xu ◽  
Linhai Zhu ◽  
Sijia Yang ◽  
Li Yu ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Regression Analysis ◽  
Classification System ◽  
Validation Cohort ◽  
Roc Curves ◽  
Tnm Staging ◽  
Risk Classification ◽  
Radical Esophagectomy ◽  
Hazard Regression ◽  
N Stage

Abstract Background: Esophageal cancer (EC) is a malignant tumor with dreadful mortality, nomogram is a prognosis tool of great significance in therapeutic guidance and assessment. We aimed to establish a newly-built nomogram for OS prediction of EC patients with radical esophagectomy.Methods: A total of 311 EC patients underwent radical esophagectomy were retrospectively investigated with their survival and demographic and clinicopathological data. Patients were randomly divided into the primary and validation cohorts. The establishment of nomogram was based on Cox hazard regression analysis in primary cohort, the calibration curves and Harrell’s concordance index were performed to verify the predictive accuracy while ROC curves was adopted to reflect the efficacy of nomogram. Kaplan–Meier curves showed the clinical significance of risk classification system and Pearson correlation test was utilized to show the correlation between risk classification system and TNM staging.Results: The median OS and 5-year survival rate are 44 months and 29.8% in primary cohort. In validation cohort, they are 52 months and 27.1%, respectively. In Cox hazard regression analysis, we extracted six independent prognostic factors—age, gender, AGR, PRL, N stage, PNI—to establish the nomogram. The C-index of nomogram is 0.75 in primary cohort and 0.70 in validation cohort. Calibration curves indicated high consistency between accurate and predicted OS in both primary and validation cohorts. ROC curves showed a better efficacy of nomogram compared with AJCC T and N stage. The area under curve (AUC) of primary cohort is 0.801 and 0.727 in validation cohort. Patients in primary cohort were divided into three risk groups according to the nomogram score, the median OS between each group was significantly different. Analogical results were obtained in validation cohort. Furthermore, the risk classification system was strongly correlated to AJCC TNM staging system in total cohort (r2=0.647, P<0.001), and it also demonstrated a better OS prediction efficacy (AUC=0.742).Conclusions: We established a neotype nomogram and a relevant risk classification system with verified accuracy and efficacy in OS prediction of EC patients after radical esophagectomy. They may provide feasible value in prognosis assessment and treatment guidance prospectively.

scholarly journals Percepção de enfermeiros sobre utilização do protocolo do sistema de classificação de risco manchester/ Nurses’ perception on the use of the manchester risk classification system protocol

2015 ◽  
Vol 14 (2) ◽  
pp. 1004 ◽  
Author(s):  
Marcia Luciane da Silva Bohn ◽  
Maria Alice Dias da Silva Lima ◽  
Carmen Lúcia Mottin Duro ◽  
Kelly Piacheski de Abreu
Keyword(s):  
Classification System ◽  
Risk Classification

Predictive value of the new ESGO-ESTRO-ESP endometrial cancer risk classification on survival and recurrence in the Danish population

2021 ◽  
pp. ijgc-2021-002582
Author(s):  
Gitte Ortoft ◽  
Claus Høgdall ◽  
Estrid Stæhr Hansen ◽  
Margit Dueholm
Keyword(s):  
Endometrial Cancer ◽  
High Risk ◽  
Recurrence Rate ◽  
European Society ◽  
Classification System ◽  
Risk Group ◽  
High Risk Group ◽  
Risk Classification ◽  
Recurrence Rates ◽  
Disease Specific

ObjectiveTo compare the performance of the new ESGO-ESTRO-ESP (European Society of Gynecological Oncology-European Society for Radiotherapy & Oncology-European Society for Pathology) 2020 risk classification system with the previous 2016 risk classification in predicting survival and patterns of recurrence in the Danish endometrial cancer population.MethodsThis Danish national cohort study included 4516 patients with endometrial cancer treated between 2005 and 2012. Five-year Kaplan–Meier adjusted and unadjusted survival estimates and actuarial recurrence rates were calculated for the previous and the new classification systems.ResultsIn the 2020 risk classification system, 81.0% of patients were allocated to low, intermediate, or high-intermediate risk compared with 69.1% in the 2016 risk classification system, mainly due to reclassification of 44.5% of patients previously classified as high risk to either intermediate or especially high-intermediate risk. The survival of the 2020 high-risk group was significantly lower, and the recurrence rate, especially the non-local recurrence rate, was significantly higher than in the 2016 high risk group (2020/2016, overall survival 59%/66%; disease specific 69%/76%; recurrence 40.5%/32.3%, non-local 34.5%/25.8%). Survival and recurrence rates in the other risk groups and the decline in overall and disease-specific survival rates from the low risk to the higher risk groups were similar in patients classified according to the 2016 and 2020 systems.ConclusionThe new ESGO-ESTRO-ESP 2020 risk classification system allocated fewer patients to the high risk group than the previous risk classification system. The main differences were lower overall and disease-specific survival and a higher recurrence rate in the 2020 high risk group. The introduction of the new 2020 risk classification will potentially result in fewer patients at high risk and allocation to the new high risk group will predict lower survival, potentially allowing more specific selection for postoperative adjuvant therapy.

scholarly journals Statistical Framework in Support of a Revised Children's Oncology Group Neuroblastoma Risk Classification System

2018 ◽  
pp. 1-15 ◽  
Author(s):  
Arlene Naranjo ◽  
Meredith S. Irwin ◽  
Michael D. Hogarty ◽  
Susan L. Cohn ◽  
Julie R. Park ◽  
...  
Keyword(s):  
Classification System ◽  
Recursive Partitioning ◽  
Diagnostic Category ◽  
Staging System ◽  
Risk Classification ◽  
Imaging Data ◽  
Oncology Group ◽  
Clinical Validity ◽  
International Consensus ◽  
Str Analysis

Purpose The International Neuroblastoma Risk Group (INRG) Staging System (INRGSS) was developed through international consensus to provide a presurgical staging system that uses clinical and imaging data at diagnosis. A revised Children's Oncology Group (COG) neuroblastoma (NB) risk classification system is needed to incorporate the INRGSS and within the context of modern therapy. Herein, we provide statistical support for the clinical validity of a revised COG risk classification system. Patients and Methods Nine factors were tested for potential statistical and clinical significance in 4,569 patients diagnosed with NB who were enrolled in the COG biology/banking study ANBL00B1 (2006-2016). Recursive partitioning was performed to create a survival-tree regression (STR) analysis of event-free survival (EFS), generating a split by selecting the strongest prognostic factor among those that were statistically significant. The least absolute shrinkage and selection operator (LASSO) was applied to obtain the most parsimonious model for EFS. COG patients were risk classified using STR, LASSO, and per the 2009 INRG classification (generated using an STR analysis of INRG data). Results were descriptively compared among the three classification approaches. Results The 3-year EFS and overall survival (± SE) were 72.9% ± 0.9% and 84.5% ± 0.7%, respectively (N = 4,569). In each approach, the most statistically and clinically significant factors were diagnostic category (eg, NB, ganglioneuroblastoma), INRGSS, MYCN status, International Neuroblastoma Pathology Classification, ploidy, and 1p/11q status. The results of the STR analysis were more concordant with those of the INRG classification system than with LASSO, although both methods showed moderate agreement with the INRG system. Conclusion These analyses provide a framework to develop a new COG risk classification incorporating the INRGSS. There is statistical evidence to support the clinical validity of each of the three classifications: STR, LASSO, and INRG.

Sign in / Sign up

Export Citation Format

Share Document