scholarly journals Parametric Cure Model versus Proportional Hazards Model in Survival Analysis of Breast Cancer and Other Malignancies

2013 ◽  
Vol 02 (04) ◽  
pp. 119-125 ◽  
Author(s):  
Shunzo Maetani ◽  
John W. Gamel
Keyword(s):  
Breast Cancer ◽  
Survival Analysis ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cure Model ◽  
Hazards Model ◽  
Model Versus

scholarly journals Evaluation of Changes on World Stock Exchanges in Connection with the SARS-CoV-2 Pandemic. Survival Analysis Methods

Risks ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 121
Author(s):  
Beata Bieszk-Stolorz ◽  
Krzysztof Dmytrów
Keyword(s):  
Survival Analysis ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Stock Exchange ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Stock Exchanges ◽  
Analysis Methods ◽  
Hazards Model ◽  
Kaplan Meier

The aim of our research was to compare the intensity of decline and then increase in the value of basic stock indices during the SARS-CoV-2 coronavirus pandemic in 2020. The survival analysis methods used to assess the risk of decline and chance of rise of the indices were: Kaplan–Meier estimator, logit model, and the Cox proportional hazards model. We observed the highest intensity of decline in the European stock exchanges, followed by the American and Asian plus Australian ones (after the fourth and eighth week since the peak). The highest risk of decline was in America, then in Europe, followed by Asia and Australia. The lowest risk was in Africa. The intensity of increase was the highest in the fourth and eleventh week since the minimal value had been reached. The highest odds of increase were in the American stock exchanges, followed by the European and Asian (including Australia and Oceania), and the lowest in the African ones. The odds and intensity of increase in the stock exchange indices varied from continent to continent. The increase was faster than the initial decline.

scholarly journals Deep learning-based risk stratification for HER2-negative breast cancer patients

2021 ◽  
Author(s):  
Mustafa I Jaber ◽  
Liudmila Beziaeva ◽  
Christopher W Szeto ◽  
Stephen C Benz
Keyword(s):  
Breast Cancer ◽  
Cancer Patients ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Digital Pathology ◽  
Tumor Stroma ◽  
Breast Cancer Patients ◽  
Spatial Image ◽  
Hazards Model ◽  
Level Information

In this paper, we present our analysis of the tumor microenvironment in digital pathology images to stratify risk in HER2-negative breast cancer patients using clinicopathological, spatial image, and cell-based features in a Cox's proportional hazard model. We start the analysis by processing a set of 304 training pathology images using our in-house pan-cancer trained tumor, stroma, and lymphocyte region identification convolutional neural networks. The next step is computation of spatial regions of interest, namely: lymphocytes within (and adjacent to) tumor, lymphocytes within (and adjacent to) stroma, and stroma within (and adjacent to) tumor areas. Various cell-level information in these regions are then summarized, augmented to clinicopathological data, and linked to patient's survival to train a Cox's proportional hazards model. The proposed model outperformed a baseline model based on clinicopathological features only in analysis of an untouched test set of 202 whole slide images with p 8.49E-08 (HR = 0.4273).

scholarly journals Survival Analysis of COVID-19 on Democracy with Cox Proportional Hazards Model

2020 ◽  
Author(s):  
Yue Zhao ◽  
Deepika Dilip
Keyword(s):  
United States ◽  
Survival Analysis ◽  
South Korea ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
The United States ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Effective Measure ◽  
Hazards Model

Abstract Background: The outbreak of Coronavirus disease 2019 (COVID-19) has struck us in many ways and we observed that China and South Korea found an effective measure to contain the virus. Conversely, the United States and the European countries are struggling to fight the virus. China is not considered a democracy and South Korea is less democratic than the United States. Therefore, we want to explore the association between the deaths of COVID-19 and democracy. Methods: We collected COVID-19 deaths data for each country from the Johns Hopkins University website and democracy indices of 2018 from the Economist Intelligence Unit website in May 2020. Then we conducted a survival analysis, regarding each country as a subject, with the Cox Proportional Hazards Model, adjusting for other selected variables. Result: The result showed that the association between democracy and deaths of COVID-19 was significant (P=0.04), adjusting for other covariates. Conclusion: In conclusion, less democratic governments performed better in containing the virus and controlling the number of deaths.

scholarly journals Survival Analysis for the Adjustment Phase Following Investment in Swiss Dairy Sheds

Agriculture ◽  
2019 ◽  
Vol 9 (11) ◽  
pp. 238
Author(s):  
Kramer ◽  
Schorr ◽  
Doluschitz ◽  
Lips
Keyword(s):  
Survival Analysis ◽  
Proportional Hazards ◽  
Planning Process ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Equity Capital ◽  
Cox Proportional Hazards Model ◽  
Farm Income ◽  
Hazards Model ◽  
Farm Accountancy Data Network

We analysed the adjustment phase following a dairy shed investment. On the basis of farm observations from both the Swiss Farm Accountancy Data Network (FADN) and a database of government-supported investments from 2003 through 2014, we focused on the imputed profit, the farm income minus opportunity costs for family labour and family capital. After investment, the analysed farms needed three years to return to the same profit level as that before the investment (median value). A Cox proportional-hazards model (survival analysis) showed that the probability of reattaining the imputed profit increased with equity capital. A reduction of the probability was related to a high imputed profit, a high off-farm income, high expenses for purchased animals and, in particular, a greater use of family labour before the investment. We conclude that the use of family labour after investment should be addressed more thoroughly during the planning process prior to an investment.

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