A Conundrum of Peer Evaluation of Predicting Poor Prognostic Models Affecting the Mortality Rate of Covid -19

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
Yashaswini J ◽  
Niranjan K R ◽  
Beena Ullala Mata B N ◽  
Kaliprasad C S
Keyword(s):  
Prognostic Model ◽  
Statistical Information ◽  
Prognostic Models ◽  
Peer Evaluation ◽  
Research Teams ◽  
Emerging Nations ◽  
The World ◽  
Prognosis Model ◽  
Real World Datasets ◽  
Number Of Individuals

Mankind is confronting these days a histrionic pandemic scene with the Coronavirus proliferation over all continents. The Covid-19 pandemic outbreak is as yet not very much portrayed, and numerous research teams everywhere on the world are chipping away at one or the other restorative therapeutic issues or immunization issues. The outburst of COVID-19 has constituted a danger to wellbeing of world. With the expanding number of individuals tainted, medical services frameworks, particularly those in economically emerging nations, are bearing gigantic pressing factor for the devising a prognostic model. There is a dire requirement for the analysis of COVID-19 and the anticipation of inpatients. To diminish these issues, a data statistical information driven clinical aid framework is advanced in this paper. In view of two real world datasets in Wuhan, China, the proposed framework coordinates information from various sources with tools of Machine Learning (ML) to anticipate COVID-19 tainted likelihood of suspected patients in their first visit, and afterward foresee mortality of affirmed cases. As opposed to picking an interpretable calculation, this framework isolates the clarifications from ML models. It can do help to patient triaging and give some valuable guidance to specialists and doctors. A prognosis model is in the way of extraordinary premium for specialists to adjust their consideration methodology for therapeutic or diagnosis procedure.

A Conundrum of Peer Evaluation of Predicting Poor Prognostic Models Affecting the Mortality Rate of Covid -19

2021 ◽  
Vol 7 (3) ◽  
Author(s):  
Yashaswini J ◽  
Niranjan K R ◽  
Beena Ullala Mata B N ◽  
Kaliprasad C S
Keyword(s):  
Prognostic Model ◽  
Statistical Information ◽  
Prognostic Models ◽  
Peer Evaluation ◽  
Research Teams ◽  
Emerging Nations ◽  
The World ◽  
Prognosis Model ◽  
Real World Datasets ◽  
Number Of Individuals

Mankind is confronting these days a histrionic pandemic scene with the Coronavirus proliferation over all continents. The Covid-19 pandemic outbreak is as yet not very much portrayed, and numerous research teams everywhere on the world are chipping away at one or the other restorative therapeutic issues or immunization issues. The outburst of COVID-19 has constituted a danger to wellbeing of world. With the expanding number of individuals tainted, medical services frameworks, particularly those in economically emerging nations, are bearing gigantic pressing factor for the devising a prognostic model. There is a dire requirement for the analysis of COVID-19 and the anticipation of inpatients. To diminish these issues, a data statistical information driven clinical aid framework is advanced in this paper. In view of two real world datasets in Wuhan, China, the proposed framework coordinates information from various sources with tools of Machine Learning (ML) to anticipate COVID-19 tainted likelihood of suspected patients in their first visit, and afterward foresee mortality of affirmed cases. As opposed to picking an interpretable calculation, this framework isolates the clarifications from ML models. It can do help to patient triaging and give some valuable guidance to specialists and doctors. A prognosis model is in the way of extraordinary premium for specialists to adjust their consideration methodology for therapeutic or diagnosis procedure.

scholarly journals New prognostic models in glioblastoma: based ferroptosis-related genes and immune scores

2021 ◽  
Author(s):  
Xin-yu Li ◽  
Xi-tao Yang
Keyword(s):  
Prognostic Model ◽  
Cox Regression ◽  
Roc Curves ◽  
Prognostic Models ◽  
Roc Curve Analysis ◽  
Prognostic Assessment ◽  
Expression Of Genes ◽  
Prognosis Model ◽  
Degree Of Malignancy ◽  
High Degree

Abstract Background: Glioblastoma multiforme (GBM) has a high degree of malignancy and the clinical outcomes is dismal. Ferroptosis is critical to the development and progression of many diseases, such as cancer, cardiovascular diseases and aging. This study was designed to establish a sensitive prognostic model based on ferroptosis-related genes and immune scores to predict overall survival (OS) in patients with GBM. Methods: The expression of genes and associated clinical parameters was obtained from the publicly available TCGA , CGGA and GEO database. According to the immune scores, patient samples were assigned into two groups. Their biological function analyses were performed through differently expressed genes. By means of LASSO, unadjusted and adjusted Cox regression analyses, this predictive signature was constructed and validated by external databases.Results: A total of 4 ferroptosis-related genes (HMOX1,HSPB1,STEAP3,ZEB1)were ultimately screened as associated hub genes and utilized to construct a prognosis model. Then our constructed riskScore model significantly passed the validation in the external datasets of OS (all p < 0.05). Receiver operating characteristic (ROC) curve analysis was conducted. Finding the area under the ROC curves (AUCs) were 0.82 at 1 years, 0.75 at 3 years, 0.67 at 5 years. Functional analysis revealed that immune related processes were different between two risk groups.We also explored its association with immune infiltration.Conclusion: Our study successfully constructed a prognostic model containing 4 hub ferroptosis-related genes for GBM, helping clinicians predict patients’ OS and making the prognostic assessment more standardized. Future prospective studies are required to validate our findings.

scholarly journals The development and validation of prognostic models for overall survival in the presence of missing data in the training dataset: a strategy with a detailed example

2021 ◽  
Vol 5 (1) ◽  
Author(s):  
Kara-Louise Royle ◽  
David A. Cairns
Keyword(s):  
Overall Survival ◽  
Missing Data ◽  
Prognostic Model ◽  
Prognostic Index ◽  
Risk Groups ◽  
Prognostic Models ◽  
Training Dataset ◽  
Validation Process ◽  
Test Dataset ◽  
Development And Validation

Abstract Background The United Kingdom Myeloma Research Alliance (UK-MRA) Myeloma Risk Profile is a prognostic model for overall survival. It was trained and tested on clinical trial data, aiming to improve the stratification of transplant ineligible (TNE) patients with newly diagnosed multiple myeloma. Missing data is a common problem which affects the development and validation of prognostic models, where decisions on how to address missingness have implications on the choice of methodology. Methods Model building The training and test datasets were the TNE pathways from two large randomised multicentre, phase III clinical trials. Potential prognostic factors were identified by expert opinion. Missing data in the training dataset was imputed using multiple imputation by chained equations. Univariate analysis fitted Cox proportional hazards models in each imputed dataset with the estimates combined by Rubin’s rules. Multivariable analysis applied penalised Cox regression models, with a fixed penalty term across the imputed datasets. The estimates from each imputed dataset and bootstrap standard errors were combined by Rubin’s rules to define the prognostic model. Model assessment Calibration was assessed by visualising the observed and predicted probabilities across the imputed datasets. Discrimination was assessed by combining the prognostic separation D-statistic from each imputed dataset by Rubin’s rules. Model validation The D-statistic was applied in a bootstrap internal validation process in the training dataset and an external validation process in the test dataset, where acceptable performance was pre-specified. Development of risk groups Risk groups were defined using the tertiles of the combined prognostic index, obtained by combining the prognostic index from each imputed dataset by Rubin’s rules. Results The training dataset included 1852 patients, 1268 (68.47%) with complete case data. Ten imputed datasets were generated. Five hundred twenty patients were included in the test dataset. The D-statistic for the prognostic model was 0.840 (95% CI 0.716–0.964) in the training dataset and 0.654 (95% CI 0.497–0.811) in the test dataset and the corrected D-Statistic was 0.801. Conclusion The decision to impute missing covariate data in the training dataset influenced the methods implemented to train and test the model. To extend current literature and aid future researchers, we have presented a detailed example of one approach. Whilst our example is not without limitations, a benefit is that all of the patient information available in the training dataset was utilised to develop the model. Trial registration Both trials were registered; Myeloma IX-ISRCTN68454111, registered 21 September 2000. Myeloma XI-ISRCTN49407852, registered 24 June 2009.

Statistical Literacy as a Way to Achieve Social Consensus

Vestnik NSUEM ◽  
2022 ◽  
pp. 135-143
Author(s):  
M. V. Karmanov ◽  
O. A. Zolotareva
Keyword(s):  
National Security ◽  
State Policy ◽  
Statistical Information ◽  
The State ◽  
Statistical Literacy ◽  
Social Consensus ◽  
Russian State ◽  
The World ◽  
A Priority

The maintenance of civil peace and harmony in the Russian state from time immemorial has been defined as a priority that allows maintaining the integrity of both state and territorial. Global processes taking place in the world, epidemic waves of viruses, incessant local wars, diligent attempts to separate people and peoples bring to the fore the need to consolidate society in order to ensure the national security of the country. In this context, the importance of statistics increases, which significantly affects the perception of the dominant values by society, forms the attitude of people to the state policy being pursued. At the same time, the understanding of statistical information (figures, data) in a number of cases does not correspond to reality, making it difficult to adequately assess the existing situation, which is associated with an insufficient level of statistical literacy of the population, officials and specialists in various fields of activity.

Western Countries: Future of Multiculturalism in Context of Employment

2012 ◽  
pp. 16-25
Author(s):  
M. Klupt
Keyword(s):  
Social Structure ◽  
Present Article ◽  
Empirical Data ◽  
Statistical Information ◽  
Western World ◽  
The West ◽  
Western Countries ◽  
The World

Will immigrant minorities change the Western world? Two decades ago this question seemed irrelevant as it was expected that the West will change the world in its image. Today, the same question is perceived as rhetorical. The answer is obvious, and the dispute is merely over directions, extent and possible consequences of future changes. The center of this dispute is the multiculturalism – the concept, policy and praxis praising diversity of cultures and denying any of them a vested right to dominate not only in the world at large, but even in a particular country. The assessment of its perspectives presupposes a variety of research approaches in view of its complexity. In the present article only one of them is be used for the analysis focused on the employment of immigrant minorities from the world's South. The viability of such approach is based on two circumstances. Firstly, the employment indexes considered in ethnical context belong to the most important characteristics of ethno-social structure of a society. Secondly, the availability of broad statistical information about employment allows for resting upon empirical data, possibly avoiding a needless bias toward purely theoretical constructions.

scholarly journals Actually existing smart citizens: expertise and (non)participation in the making of the smart city

2018 ◽  
Author(s):  
Taylor Shelton ◽  
Thomas Lodato
Keyword(s):  
Smart City ◽  
Policy Making ◽  
Urban Governance ◽  
Smart Cities ◽  
Top Down ◽  
The World ◽  
Number Of Individuals

In response to the mounting criticism of emerging ‘smart cities’ strategies around the world, a number of individuals and institutions have attempted to pivot from discussions of smart cities towards a focus on ‘smart citizens’. While the smart citizen is most often seen as a kind of foil for those more stereotypically top-down, neoliberal, and repressive visions of the smart city that have been widely critiqued within the literature, this paper argues for an attention to the ‘actually existing smart citizen’, which plays a much messier and more ambivalent role in practice. This paper proposes the dual figures of ‘the general citizen’ and ‘the absent citizen’ as a heuristic for thinking about how the lines of inclusion and exclusion are drawn for citizens, both discursively and materially, in the actual making of the smart city. These figures are meant to highlight how the universal and unspecified figure of ‘the citizen’ is discursively deployed to justify smart city policies, while at the same time, actual citizens remain largely excluded from such decision and policy-making processes. Using a case study of Atlanta, Georgia and its ongoing smart cities initiatives, we argue that while the participation of citizens is crucial to any truly democratic mode of urban governance, the emerging discourse around the promise of smart citizenship fails to capture the realities of how citizens are actually discussed and enrolled in the making of these policies.

scholarly journals Development and Analysis of a Weighed Prognostic Model in Newly Diagnosed Multiple Myeloma Patients

Blood ◽  
2020 ◽  
Vol 136 (Supplement 1) ◽  
pp. 47-48
Author(s):  
Xue-Han Mao ◽  
Yan Xu ◽  
Yuting Yan ◽  
Jiahui Liu ◽  
Huishou Fan ◽  
...  
Keyword(s):  
Risk Factors ◽  
Multiple Myeloma ◽  
Multivariate Analysis ◽  
Prognostic Factors ◽  
High Risk ◽  
Prognostic Factor ◽  
Prognostic Model ◽  
Cytogenetic Abnormalities ◽  
Total Score Range ◽  
Prognosis Model

Background and Objective: Multiple myeloma (MM) is characterized with significant cytogenetic changes and complex tumor microenvironment, thus patient survival is extremely heterogeneous. Various disease-related or patient-related factors affect the prognosis of patients. This study tried to analyze the prognostic indicators of patients with newly-treated MM, especially explored the prognosis of multiple cytogenetic abnormalities and the ratio of lymphocytes to monocytes (LMR). Additionally, we established a comprehensive prognostic model to help determine the patient prognosis. Methods: After screening, 603 patients of untreated MM from January 2008 to June 2017, with complete baseline indicators were enrolled into the study. By univariate and multivariate Cox analysis, risk factors related to the prognosis of patients were evaluated, and a weighted prognosis model was established to compare the survival differences of patients in each risk stratification. Result: Optimal thresholds of ALC, LWR, NLR and LMR were determined by ROC curve and Youdex index: ALC = 1.415, LWR = 0.325, NLR = 1.935, LMR = 2.95. Survival analysis showed that patients with LMR ≤ 2.95, ALC ≥ 1.415 and LWR ≥ 0.325 had significantly better survival compared with their respective control groups. Cox multivariate analysis showed that among the four indicators, only LMR≤2.95 was an independent adverse prognostic factor for overall survival (OS)(Figure 1A). 17p deletion, 1q21 amplification, t (4; 14) / t (14; 16) were define as high-risk cytogenetic abnormalities (HRA). Of the 603 patients, about 60% were associated with at least one high-risk cytogenetic event. Among them, the occurrence of cumulative 0, 1, 2, and 3 HRA were 39.6% (239/603), 42.5% (256/603), 16.6% (100/603), and 1.3% (8/603), respectively. There was no significant difference in survival among patients with same number of HRAs. The median OS of patients with 0, 1 and ≥ 2 HRA were not reached, 62.1 months (95% CI, 49.3-74.9) and 30.4 months (95% CI, 24.5-36.3), respectively (p &lt;0.001)(Figure 1B).Final Cox regression model showed that age 65 ~ 74 (HR=1.77, 95%CI, 1.24-2.51, p=0.001), age ≥75 (HR=2.46, 95%CI, 1.69-3.58, p &lt; 0.001), LDH≥247 U/L (HR =1.65, 95%CI, 1.07-2.51, p=0.023), ISS stage III (HR=1.76, 95%CI, 1.24-2.50, p=0.002), LMR≤2.95 (HR=1.53, 95%CI, 1.08-2.18, p=0.017), 1 HRA (HR=1.87, 95%CI, 1.27-2.75, p=0.002) and ≥2 HRA (HR=3.48, 95%CI, 2.22-5.45, p&lt;0.001) are independent adverse prognostic factors for OS. Then weighted risk factors were summed to establish a comprehensive prognosis model, with a total score range of 0-6 points. Accordingly, the whole cohort was divided into low risk (0-1 points, 45.4%), intermediate risk (2 points, 27.9%), high risk (3 points, 19.2%) and ultra-high risk (4-6 points, 7.5 %) groups. The median OS of the four risk groups were 85.8 months (67.1-104.5), 49.0 months (44.7-53.3), 35.4 months (31.3-39.5), and 23.2 months (18.8-27.6), respectively (p&lt;0.001). The C-statistics of this prognostic model is 0.68 (95% CI, 0.64-0.71), which is significantly better than the D-S stage (C-statistics = 0.52, 95% CI, 0.50-0.55, p &lt;0.001), ISS (C-statistics = 0.60, 95% CI, 0.57-0.64, p &lt;0.001) and R-ISS stage (C-statistics = 0.60, 95% CI, 0.57-0.63, p &lt;0.001). Bootstrap resampling and calibration curve showed that the model has an accurate predictive effect on both short-term and long-term prognosis of patients(Figure 1C). Conclusion: In our analysis, ALC, LWR, LMR were associated with poor prognosis in NDMM patients, while NLR had no significant prognostic significance. Among the four indicators, LMR≤2.95 was the only independent prognostic factor. In NDMM patients, survival of patients with the same number of high-risk cytogenetic abnormalities were comparable with each other, regardless of whichever combination of HRA. Higher number of high-risk cytogenetic abnormalities were associated with worse prognosis. Cox multivariate analysis showed that, old age (65-74 years old, ≥75 years old), increased LDH (≥247 U/L), decreased LMR (≤2.95), ISS III, 1 HRA and ≥ 2 HRA were independent adverse prognostic factors that affect the OS of MM patients. 4. A comprehensive weighted prognostic model was established with the above factors, which was proved to effectively distinguish different prognosis of patients. Figure 1 Disclosures No relevant conflicts of interest to declare.

scholarly journals Identification of Multi-omics Biomarkers and Construction of the Novel Prognostic Model for Hepatocellular Carcinoma

2021 ◽  
Author(s):  
Xiaokai Yan ◽  
Chiying Xiao ◽  
Kunyan Yue ◽  
Min Chen ◽  
Hang Zhou
Keyword(s):  
Hepatocellular Carcinoma ◽  
Survival Analysis ◽  
Prognostic Model ◽  
Prognostic Models ◽  
Prognostic Indicators ◽  
Omics Data ◽  
Training Set ◽  
Test Set ◽  
Model Based ◽  
Cox Analysis

Abstract Background: Change in the genome plays a crucial role in cancerogenesis and many biomarkers can be used as effective prognostic indicators in diverse tumors. Currently, although many studies have constructed some predictive models for hepatocellular carcinoma (HCC) based on molecular signatures, the performance of which is unsatisfactory. To fill this shortcoming, we hope to construct a novel and accurate prognostic model with multi-omics data to guide prognostic assessments of HCC. Methods: The TCGA training set was used to identify crucial biomarkers and construct single-omic prognostic models through difference analysis, univariate Cox, and LASSO/stepwise Cox analysis. Then the performances of single-omic models were evaluated and validated through survival analysis, Harrell’s concordance index (C-index), and receiver operating characteristic (ROC) curve, in the TCGA test set and external cohorts. Besides, a comprehensive model based on multi-omics data was constructed via multiple Cox analysis, and the performance of which was evaluated in the TCGA training set and TCGA test set. Results: We identified 16 key mRNAs, 20 key lncRNAs, 5 key miRNAs, 5 key CNV genes, and 7 key SNPs which were significantly associated with the prognosis of HCC, and constructed 5 single-omic models which showed relatively good performance in prognostic prediction with c-index ranged from 0.63 to 0.75 in the TCGA training set and test set. Besides, we validated the mRNA model and the SNP model in two independent external datasets respectively, and good discriminating abilities were observed through survival analysis (P < 0.05). Moreover, the multi-omics model based on mRNA, lncRNA, miRNA, CNV, and SNP information presented a quite strong predictive ability with c-index over 0.80 and all AUC values at 1,3,5-years more than 0.84.Conclusion: In this study, we identified many biomarkers that may help study underlying carcinogenesis mechanisms in HCC, and constructed five single-omic models and an integrated multi-omics model that may provide effective and reliable guides for prognosis assessment and treatment decision-making.

scholarly journals Customer Perception Towards Online Shopping in Chennai City

2019 ◽  
Vol 8 (4S3) ◽  
pp. 278-280
Keyword(s):  
Online Shopping ◽  
The Internet ◽  
Internet Shopping ◽  
Web Based ◽  
Effective Utilization ◽  
Customer Perception ◽  
The World ◽  
Online Stores ◽  
Chennai City ◽  
Number Of Individuals

Online based purchasing is the way toward buying products and enterprises from traders who sell them online through Internet. Since the rise of the World Wide Web, sellers have tried to offer their items to individuals who browser the Internet. Customers can visit online stores from their homes and shop comfortably. Presently a day shopping has turned out to be mainstream among individuals through browsing which has increased their web knowledge and effective utilization of internet. So internet shopping has become accustomed to the buyers which made the researcher to study the perception on internet based shopping. The principle aim of the this research is to find out the opinion of the respondents towards internet shopping. These days, there has been a flood in web based shopping. The Internet has been utilized by clothing organizations to sell their items and advance their brands. As an ever increasing number of individuals purchase attire on the web, there have been an expanding number of inquires about.

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