scholarly journals ELECTRE methods with interaction between criteria: An extension of the concordance index

2009 ◽  
Vol 199 (2) ◽  
pp. 478-495 ◽  
Author(s):  
José Rui Figueira ◽  
Salvatore Greco ◽  
Bernard Roy
Keyword(s):  
Concordance Index ◽  
Electre Methods

scholarly journals Dynamic nomograms combining N classification with ratio-based nodal classifications to predict long-term survival for patients with lung adenocarcinoma after surgery: a SEER population-based study

BMC Cancer ◽  
2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Suyu Wang ◽  
Yue Yu ◽  
Wenting Xu ◽  
Xin Lv ◽  
Yufeng Zhang ◽  
...  
Keyword(s):  
Overall Survival ◽  
Lung Adenocarcinoma ◽  
External Validation ◽  
Predictive Performance ◽  
Information Criterion ◽  
Curve Analysis ◽  
Tnm Stage ◽  
Concordance Index ◽  
Cancer Specific Survival ◽  
Decision Curve Analysis

Abstract Background The prognostic roles of three lymph node classifications, number of positive lymph nodes (NPLN), log odds of positive lymph nodes (LODDS), and lymph node ratio (LNR) in lung adenocarcinoma are unclear. We aim to find the classification with the strongest predictive power and combine it with the American Joint Committee on Cancer (AJCC) 8th TNM stage to establish an optimal prognostic nomogram. Methods 25,005 patients with T1-4N0–2M0 lung adenocarcinoma after surgery between 2004 to 2016 from the Surveillance, Epidemiology, and End Results database were included. The study cohort was divided into training cohort (13,551 patients) and external validation cohort (11,454 patients) according to different geographic region. Univariate and multivariate Cox regression analyses were performed on the training cohort to evaluate the predictive performance of NPLN (Model 1), LODDS (Model 2), LNR (Model 3) or LODDS+LNR (Model 4) respectively for cancer-specific survival and overall survival. Likelihood-ratio χ2 test, Akaike Information Criterion, Harrell concordance index, integrated discrimination improvement (IDI) and net reclassification improvement (NRI) were used to evaluate the predictive performance of the models. Nomograms were established according to the optimal models. They’re put into internal validation using bootstrapping technique and external validation using calibration curves. Nomograms were compared with AJCC 8th TNM stage using decision curve analysis. Results NPLN, LODDS and LNR were independent prognostic factors for cancer-specific survival and overall survival. LODDS+LNR (Model 4) demonstrated the highest Likelihood-ratio χ2 test, highest Harrell concordance index, and lowest Akaike Information Criterion, and IDI and NRI values suggested Model 4 had better prediction accuracy than other models. Internal and external validations showed that the nomograms combining TNM stage with LODDS+LNR were convincingly precise. Decision curve analysis suggested the nomograms performed better than AJCC 8th TNM stage in clinical practicability. Conclusions We constructed online nomograms for cancer-specific survival and overall survival of lung adenocarcinoma patients after surgery, which may facilitate doctors to provide highly individualized therapy.

scholarly journals U-survival for prognostic prediction of disease progression and mortality of patients with COVID-19

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Janne J. Näppi ◽  
Tomoki Uemura ◽  
Chinatsu Watari ◽  
Toru Hironaka ◽  
Tohru Kamiya ◽  
...  
Keyword(s):  
Risk Groups ◽  
Healthcare Services ◽  
Chest Ct ◽  
Prediction Performance ◽  
Survival Prediction ◽  
Concordance Index ◽  
Survival Curves ◽  
Analysis Methodology ◽  
Kaplan Meier ◽  
Prognostic Prediction

AbstractThe rapid increase of patients with coronavirus disease 2019 (COVID-19) has introduced major challenges to healthcare services worldwide. Therefore, fast and accurate clinical assessment of COVID-19 progression and mortality is vital for the management of COVID-19 patients. We developed an automated image-based survival prediction model, called U-survival, which combines deep learning of chest CT images with the established survival analysis methodology of an elastic-net Cox survival model. In an evaluation of 383 COVID-19 positive patients from two hospitals, the prognostic bootstrap prediction performance of U-survival was significantly higher (P < 0.0001) than those of existing laboratory and image-based reference predictors both for COVID-19 progression (maximum concordance index: 91.6% [95% confidence interval 91.5, 91.7]) and for mortality (88.7% [88.6, 88.9]), and the separation between the Kaplan–Meier survival curves of patients stratified into low- and high-risk groups was largest for U-survival (P < 3 × 10–14). The results indicate that U-survival can be used to provide automated and objective prognostic predictions for the management of COVID-19 patients.

Novel evaluation approach for extracurricular sports lifestyle of college students

2020 ◽  
pp. 002072092092851
Author(s):  
Pingping Zhang ◽  
Jiyun Cai ◽  
Lining Xing
Keyword(s):  
College Students ◽  
Extracurricular Activities ◽  
University Education ◽  
Concordance Index ◽  
Evaluation Approach ◽  
Electre Method ◽  
Classroom Education ◽  
Credibility Index ◽  
Evaluation Matrix

Good extracurricular activities can optimize the quality of education, fetch up with classroom education and teach them what they cannot learn from it, is conducive to improve students’ comprehensive quality, to complete the task and achieve the goal of university education. For this reason, this paper proposes an extracurricular sports lifestyle evaluation to college students via an improved ELECTRE method. In the proposed method, three indexes – concordance index, non-concordance index and credibility index – are defined first. Based on these indexes, the preference evaluation matrix is constructed, and consistent credibility, non-consistent credibility and net credibility are computed second. Third, it was sorted for the quality of all alternatives according to the value of group net credibility. In general, the greater the value of the group net credibility of a project, the better the project is. Simulation experiments suggest that this proposed method is feasible and valid. Extracurricular activities for college students take a very important part of university education, and it models their characters, opens up their minds, adventure spirits, strengthens their social connections, improve their comprehensive quality and their personal positive socialization.

Possibility-Based ELECTRE II Method with Uncertain Linguistic Fuzzy Variables

2017 ◽  
Vol 31 (09) ◽  
pp. 1759016 ◽  
Author(s):  
Lidong Wang ◽  
Binquan Liao ◽  
Xiaodong Liu ◽  
Jingxia Liu
Keyword(s):  
Decision Making ◽  
Multiple Attribute Decision Making ◽  
Economic Systems ◽  
Linguistic Variables ◽  
Concordance Index ◽  
Fuzzy Variables ◽  
Numerical Example ◽  
Deviation Index ◽  
Multiple Attribute

Linguistic variables can better approximate the fuzziness of man’s thinking, which are important tools for multiple attribute decision-making problems. This paper establishes the possibility-based ELECTRE II model under the environment of uncertain linguistic fuzzy variables and uncertain weight information. By introducing the degree of possibility to ELECTRE II model, the concordance set, the discordance set and the indifferent set are obtained, respectively. Furthermore, the concordance index is redefined by considering deviation index under the same attribute, by which the strong and weak relationships are constructed, and then the rank of alternatives is obtained. A numerical example about the evaluation of socio-economic systems is employed to illustrate the convenience and applicability of the proposed method.

scholarly journals Next-generation prostate cancer risk calculator for primary care physicians

2017 ◽  
Vol 12 (2) ◽  
pp. E64-70 ◽  
Author(s):  
Robert K. Nam ◽  
Raj Satkunasivam ◽  
Joseph L. Chin ◽  
Jonathan Izawa ◽  
John Trachtenberg ◽  
...  
Keyword(s):  
Prostate Cancer ◽  
Cancer Risk ◽  
Life Expectancy ◽  
Prostate Biopsy ◽  
Primary Care Physicians ◽  
Prostate Cancer Risk ◽  
Concordance Index ◽  
Risk Calculator ◽  
Next Generation ◽  
Term Survival

Introduction: Current prostate cancer risk calculators are limited in impact because only a probability of having prostate cancer is provided. We developed the next generation of prostate cancer risk calculator that incorporates life expectancy in order to better evaluate prostate cancer risk in context to a patient’s age and comorbidity.Methods: We combined two cohorts to develop the new risk calculator. The first was 5638 subjects who all underwent a prostate biopsy for prostate cancer detection. The second was 979 men diagnosed with prostate cancer with long-term survival data. Two regression models were used to create multivariable nomograms and an online prostate cancer risk calculator was developed.Results: Of the 5638 patients who underwent a prostate biopsy, 629 (11%) were diagnosed with aggressive prostate cancer (Gleason Score 7[4+3] or more). Of the 979 patients who underwent treatment for prostate cancer, the 10-year overall survival (OS) was 49.6% (95% confidence interval [CI] 46.6‒52.9). The first multivariable nomogram for cancer risk had a concordance index of 0.74 (95% CI 0.72, 0.76), and the second nomogram to predict survival had a concordance index of 0.71 (95% CI 0.69‒0.72). The nextgeneration prostate cancer risk calculator was developed online and is available at: http://riskcalc.org/ProstateCA_Screen_Tool.Conclusions: We have developed the next-generation prostate cancer risk calculator that incorporates a patient’s life expectancy based on age and comorbidity. This approach will better evaluate prostate cancer risk. Future studies examining other populations will be needed for validation.

scholarly journals Mapping of summer crops in the State of Paraná, Brazil, through the 10-day spot vegetation NDVI composites

2011 ◽  
Vol 31 (4) ◽  
pp. 760-770 ◽  
Author(s):  
Gleyce K. D. Araújo ◽  
Jansle V. Rocha ◽  
Rubens A. C. Lamparelli ◽  
Agmon M. Rocha
Keyword(s):  
Satellite Images ◽  
Accuracy Assessment ◽  
State Level ◽  
The State ◽  
Yield Prediction ◽  
Concordance Index ◽  
Kappa Index ◽  
Cropping Seasons ◽  
Rgb Image ◽  
Resolution Data

The search for low subjectivity area estimates has increased the use of remote sensing for agricultural monitoring and crop yield prediction, leading to more flexibility in data acquisition and lower costs comparing to traditional methods such as census and surveys. Low spatial resolution satellite images with higher frequency in image acquisition have shown to be adequate for cropland mapping and monitoring in large areas. The main goal of this study was to map the Summer crops in the State of Paraná, Brazil, using 10-day composition of NDVI SPOT Vegetation data for 2005/2006, 2006/2007 and 2007/2008 cropping seasons. For this, a supervised digital classification method with Parallelepiped algorithm in multitemporal RGB image composites was used, in order to generate masks of Summer cultures for each 10-day composition. Accuracy assessment was performed using Kappa index, overall accuracy and Willmott's concordance index, resulting in good levels of accuracy. This methodology allowed the accomplishment, with free and low resolution data, of the mapping of Summer cultures at State level.

scholarly journals Validation of the 2009 TNM Classification for Renal Cell Carcinoma: Comparison with the 2002 TNM Classification by Concordance Index

2011 ◽  
Vol 52 (8) ◽  
pp. 524 ◽  
Author(s):  
Chunwoo Lee ◽  
Dalsan You ◽  
Junsoo Park ◽  
In Gab Jeong ◽  
Cheryn Song ◽  
...  
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Renal Cell ◽  
Tnm Classification ◽  
Concordance Index

scholarly journals Development and validation of nomogram based on SIRI for predicting the clinical outcome in patients with nasopharyngeal carcinomas

2018 ◽  
Vol 67 (3) ◽  
pp. 691-698 ◽  
Author(s):  
Yuan Chen ◽  
Wenjie Jiang ◽  
Dan Xi ◽  
Jun Chen ◽  
Guoping Xu ◽  
...  
Keyword(s):  
Predictive Accuracy ◽  
Peripheral Lymphocyte ◽  
Clinicopathological Parameters ◽  
Concordance Index ◽  
Tumor Node Metastasis ◽  
Discriminative Ability ◽  
Node Metastasis ◽  
Kaplan Meier ◽  
Treatment Plans ◽  
Development And Validation

The Systemic Inflammation Response Index (SIRI), based on peripheral lymphocyte, neutrophil, and monocyte counts, was recently investigated as a prognostic marker for several tumors. However, use of the SIRI has not been reported for nasopharyngeal carcinoma (NPC). We evaluated the prognostic value of the SIRI in primary and validation cohorts. We also established an effective prognostic nomogram for NPC based on clinicopathological parameters and the SIRI. The predictive accuracy and discriminative ability of the nomogram were determined using the concordance index (C-index) and a calibration curve and were compared with tumor-node-metastasis classifications. Our Kaplan-Meier survival analysis results showed that the SIRI was associated with the overall survival of patients with NPC in the primary and validation cohorts. The SIRI was identified to be an independent prognostic factor for NPC. In addition, we developed and validated a new prognostic nomogram that integrated clinicopathological factors and the SIRI. This nomogram can efficiently predict the prognosis of patients with NPC. The SIRI is a novel, simple and inexpensive prognostic predictor for patients with NPC. The SIRI has important value for predicting the prognosis of patients with NPC and developing individualized treatment plans.

scholarly journals Bioinformatics-Based Identification of Tumor Microenvironment-Related Prognostic Genes in Pancreatic Cancer

2021 ◽  
Vol 12 ◽  
Author(s):  
Shaojie Chen ◽  
Feifei Huang ◽  
Shangxiang Chen ◽  
Yinting Chen ◽  
Jiajia Li ◽  
...  
Keyword(s):  
Pancreatic Cancer ◽  
Overall Survival ◽  
Regression Analysis ◽  
Tumor Microenvironment ◽  
Operating Characteristic ◽  
Cox Regression ◽  
Time Dependent ◽  
Concordance Index ◽  
Cox Regression Analysis ◽  
Score Model

ObjectiveGrowing evidence has highlighted that the immune and stromal cells that infiltrate in pancreatic cancer microenvironment significantly influence tumor progression. However, reliable microenvironment-related prognostic gene signatures are yet to be established. The present study aimed to elucidate tumor microenvironment-related prognostic genes in pancreatic cancer.MethodsWe applied the ESTIMATE algorithm to categorize patients with pancreatic cancer from TCGA dataset into high and low immune/stromal score groups and determined their differentially expressed genes. Then, univariate and LASSO Cox regression was performed to identify overall survival-related differentially expressed genes (DEGs). And multivariate Cox regression analysis was used to screen independent prognostic genes and construct a risk score model. Finally, the performance of the risk score model was evaluated by Kaplan-Meier curve, time-dependent receiver operating characteristic and Harrell’s concordance index.ResultsThe overall survival analysis demonstrated that high immune/stromal score groups were closely associated with poor prognosis. The multivariate Cox regression analysis indicated that the signatures of four genes, including TRPC7, CXCL10, CUX2, and COL2A1, were independent prognostic factors. Subsequently, the risk prediction model constructed by those genes was superior to AJCC staging as evaluated by time-dependent receiver operating characteristic and Harrell’s concordance index, and both KRAS and TP53 mutations were closely associated with high risk scores. In addition, CXCL10 was predominantly expressed by tumor associated macrophages and its receptor CXCR3 was highly expressed in T cells at the single-cell level.ConclusionsThis study comprehensively investigated the tumor microenvironment and verified immune/stromal-related biomarkers for pancreatic cancer.

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