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 Incidence and Survival Changes in Patients with Esophageal Adenocarcinoma during 1984–2013

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Zhang Haiyu ◽  
Pei Xiaofeng ◽  
Mo Xiangqiong ◽  
Qiu Junlan ◽  
Zheng Xiaobin ◽  
...  
Keyword(s):  
United States ◽  
Risk Factors ◽  
Esophageal Adenocarcinoma ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
The United States ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hazards Model ◽  
Potential Risk Factors

Purpose. The morbidity of esophageal adenocarcinoma (EAC) has significantly increased in Western countries. We aimed to identify trends in incidence and survival in patients with EAC in the recent 30 years and then analyzed potential risk factors, including race, sex, age, and socioeconomic status (SES). Methods. All data were collected from the Surveillance, Epidemiology, and End Results or SEER database. Kaplan–Meier analysis and the Cox proportional hazards model were conducted to compare the differences in survival between variables, including sex, race, age, and SES, as well as to evaluate the association of these factors with prognosis. Results. A total of 16,474 patients with EAC were identified from 1984 to 2013 in the United States. Overall incidence increased every 10 years from 1.8 to 3.1 to 3.9 per 100. Overall survival gradually improved (p<0.0001), which was evident in male patients ((hazard ratio (HR) = 1.111; 95% confidence interval (CI) (1.07, 1.15)); however, the 5-year survival rate remained low (20.1%). The Cox proportional hazards model identified old age, black ethnicity, and medium/high poverty as risk factors for EAC (HR = 1.018; 95% CI (1.017, 1.019; HR = 1.240, 95% CI (1.151,1.336), HR = 1.000, 95% CI (1.000, 1.000); respectively). Conclusions. The incidence of EAC in the United States increased over time. Survival advantage was observed in white patients and patients in the low-poverty group. Sex was an independent prognostic factor for EAC, but this finding has to be confirmed by further research.

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 Use of the Living Kidney Donor Profile Index in the Canadian Kidney Transplant Recipient Population: A Validation Study

2020 ◽  
Vol 7 ◽  
pp. 205435812090697
Author(s):  
Mohamed Shantier ◽  
Yanhong Li ◽  
Monika Ashwin ◽  
Olsegun Famure ◽  
Sunita K. Singh
Keyword(s):  
Validation Study ◽  
Graft Failure ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
External Validation ◽  
The United States ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Living Kidney Donor ◽  
Hazards Model

Background: The Living Kidney Donor Profile Index (LKDPI) was derived in a cohort of kidney transplant recipients (KTR) from the United States to predict the risk of total graft failure. There are important differences in patient demographics, listing practices, access to transplantation, delivery of care, and posttransplant mortality in Canada as compared with the United States, and the generalizability of the LKDPI in the Canadian context is unknown. Objective: The purpose of this study was to externally validate the LKDPI in a large contemporary cohort of Canadian KTR. Design: Retrospective cohort validation study. Setting: Toronto General Hospital, University Health Network, Toronto, Ontario, Canada Patients: A total of 645 adult (≥18 years old) living donor KTR between January 1, 2006 and December 31, 2016 with follow-up until December 31, 2017 were included in the study. Measurements: The predictive performance of the LKDPI was evaluated. The outcome of interest was total graft failure, defined as the need for chronic dialysis, retransplantation, or death with graft function. Methods: The Cox proportional hazards model was used to examine the relation between the LKDPI and total graft failure. The Cox proportional hazards model was also used for external validation and performance assessment of the model. Discrimination and calibration were used to assess model performance. Discrimination was assessed using Harrell’s C statistic and calibration was assessed graphically, comparing observed versus predicted probabilities of total graft failure. Results: A total of 645 living donor KTR were included in the study. The median LKDPI score was 13 (interquartile range [IQR] = 1.1, 29.9). Higher LKDPI scores were associated with an increased risk of total graft failure (hazard ratio = 1.01; 95% confidence interval [CI] = 1.0-1.02; P = .02). Discrimination was poor (C statistic = 0.55; 95% CI = 0.48-0.61). Calibration was as good at 1-year posttransplant but suboptimal at 3- and 5-years posttransplant. Limitations: Limitations include a relatively small sample size, predicted probabilities for assessment of calibration only available for scores of 0 to 100, and some missing data handled by imputation. Conclusions: In this external validation study, the predictive ability of the LKDPI was modest in a cohort of Canadian KTR. Validation of prediction models is an important step to assess performance in external populations. Potential recalibration of the LKDPI may be useful prior to clinical use in external cohorts.

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.

Comparison of Valvulopathy Risk with Lorcaserin and Phenterminetopiramate for Weight Loss

2019 ◽  
Vol 14 (1) ◽  
pp. 74-78
Author(s):  
Michael Guo ◽  
Mahyar Etminan ◽  
Bruce Carleton
Keyword(s):  
Weight Loss ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Adverse Outcome ◽  
The United States ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hazards Model ◽  
Hazard Ratios ◽  
One Year

Background: Lorcaserin and phentermine-topiramate are two drugs marketed for obesity that have shown moderate efficacy after one year of use. However, concerns over risks of serious cardiovascular harms including valvulopathy have been brought up for both drugs, prompting an epidemiologic investigation to quantify this adverse outcome using real-world clinical data. </P><P> Objective: To compare rates of valvulopathy between the weight-loss drugs lorcaserin and phentermine-topiramate. </P><P> Methods: A retrospective cohort study using the PharMetrics database from the United States was conducted. From approximately 9 million subjects captured in the database from 2006 to 2016, we identified all patients who had received at least one prescription for lorcaserin or phentermine-topiramate. Users of either drug were followed to the first mutually exclusive diagnosis of non-congenital valvulopathy defined as having received an international classification for diseases, ninth revision clinical modification [ICD-9- CM] code for valvulopathy, or to the end of the study period. A Cox Proportional Hazards model was then constructed to compute adjusted hazard ratios (HRs) to compare the rates of valvulopathy between users of the two drugs. </P><P> Results: We identified 1,981 lorcaserin users and 1,806 phentermine-topiramate users. Rates of valvulopathy for lorcaserin and phentermine-topiramate cohorts were 26 and 24 per 1000-person-years, respectively. The crude and adjusted hazard ratios (HRs) comparing the two cohorts with respect to valvulopathy were 1.28 (95% CI: 0.73,2.26) and 1.16 (95% CI: 0.65-2.05), respectively. </P><P> Conclusion: Our analysis suggests comparable rates of valvulopathy between lorcaserin and phentermine-topiramate users. Clinicians are advised to consider the risk of valvular disease when medically managing obesity.

scholarly journals Cox Proportional Hazards Model for Identification of the Prognostic Factors in the Survival of Acute Liver Failure Patients in India

2018 ◽  
Vol 2 ◽  
pp. 53-74
Author(s):  
Shankar Prasad Khanal ◽  
V. Sreenivas ◽  
S.K. Acharya
Keyword(s):  
Survival Analysis ◽  
Prognostic Factors ◽  
Liver Failure ◽  
Cerebral Edema ◽  
Goodness Of Fit ◽  
Proportional Hazards ◽  
Proportional Hazards Model ◽  
Cox Proportional Hazards ◽  
Cox Proportional Hazards Model ◽  
Hazards Model

Background: Acute Liver Failure (ALF) is a kind of dangerous rare liver injury among all liver diseases. Different statistical methods such as Logistic regression, Kaplan-Meier estimate of survival function followed by Log-rank test and semi-parametric approaches of survival analysis has been applied in order to identify the significant risk factors of ALF patients. In most of the studies, regression models used in this setup has not been evaluated by model assumptions and their goodness of fit tests.Objective: To apply appropriate survival analysis technique to identify the prognostic factors in the survival of ALF patients, to develop prognostic index, and to predict survival probability for different scenario.Materials and Methods: The study is based on the retrospective cohort study design with altogether 1099 ALF patients taken from the liver clinic, All India Institute of Medical Sciences, New Delhi India. Cox regression has been considered as the suitable model for handling this time to event data, and the assumptions of the model, goodness of fit of the model was assessed and survival probabilities were predicted.Results: This study has identified six prognostic factors namely age, prothrombin time, cerebral edema, total serum bilirubin, serum creatinine and etiology for ALF patients. The hazards of mortality [HR: 2.38; 95% C.I.: (1.99, 2.85), p < 0.001] is the highest for cerebral edema among all these prognostic factors. Nearly 9%, 26%, 39%, 50%, 59% and 63% of ALF patients with a PI of 1, 3, 5, 7, 9 and 10 respectively die by 3 days of hospital stay.Conclusion: The developed Cox Proportional Hazards model with six prognostic factors has satisfied the model assumptions and goodness of fit tests. The risk score and the predicted survival probabilities will be immensely helpful to the hepatologists to make a quick decision regarding the likely prognosis of a patient at admission and helpful in triaging the ALF patients for liver transplant.Nepalese Journal of Statistics, Vol. 2, 53-74

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