scholarly journals PERBANDINGAN MODEL REGRESI COX PROPORTIONAL HAZARD MENGGUNAKAN METODE BRESLOW DAN EFRON (Studi Kasus: Penderita Stroke di RSUD Tugurejo Kota Semarang)

2019 ◽  
Vol 8 (1) ◽  
pp. 93-105
Author(s):  
Eri Setiani ◽  
Sudarno Sudarno ◽  
Rukun Santoso

Cox proportional hazard regression is a regression model that is often used in survival analysis. Survival analysis is phrase used to describe analysis of data in the form of times from a well-defined time origin until occurrence of some particular even or end-point. In analysis survival sometimes ties are found, namely there are two or more individual that have together event. This study aims to apply Cox model on ties event using two methods, Breslow and Efron and determine factors that affect survival of stroke patients in Tugurejo Hospital Semarang. Dependent variable in this study is length of stay, then independent variables are gender, age, type of stroke, history of hypertension, systolic blood pressure, diastolic blood pressure, blood sugar levels, and BMI. The two methods give different result, Breslow has four significant variables there are type of stroke, history of hypertension, systolic blood pressure, and diastolic blood pressure, while Efron contains five significant variables such as type of stroke, history of hypertension, systolic blood pressure, diastolic blood pressure and blood sugar levels. From the smallest AIC criteria obtained the best Cox proportional hazard regression model is Efron method. Keywords: Stroke, Cox Proportional Hazard Regression model, Breslow method, Efron method.

2019 ◽  
Vol 12 (2) ◽  
pp. 200
Author(s):  
Sudarno Sudarno ◽  
Eri Setiani

Cox proportional hazard regression is a regression model that is often used in survival analysis. Survival analysis is phrase used to describe analysis of data in the form of times from a well-defined time origin until occurrence of some particular be death. In analysis survival sometimes ties are found, namely there are two or more individual that have together event. The objectives of this research are applied Cox proportional hazard regression on ties event using Breslow methodand determine factors that affect survival of stroke patients in Tugurejo Hospital Semarang. The response variable is length of stay at hospital, and the predictors are gender, age, type of stroke, history of hypertension, systolic blood pressure, diastolic blood pressure, blood sugar levels, and body mass index. The factors cause stroke disease by significant are type of stroke, history of hypertension, systolic blood pressure, diastolic blood pressure, and blood sugar level. By the survivorship function that the patients have been looked after at hospital greater than 20 days, they have probability of healthy be little even go to death. A person in order to be healthy must notice and prevent some factors cause disease.


2019 ◽  
Vol 25 (1) ◽  
pp. 57-64
Author(s):  
Susin Park ◽  
Nam Kyung Je

Background: Anticoagulation therapy is recommended for stroke prevention in high-risk patients with atrial fibrillation (AF). This study aimed to estimate the time to switch from warfarin to a direct oral anticoagulant (DOAC) and identify the factors associated with it. Methods: By using claims data, we studied 7111 warfarin-using patients with nonvalvular AF who were aged ≥65 years. The Kaplan-Meier analysis was performed to estimate the time to switch from warfarin to a DOAC, and Cox proportional hazard regression analysis was used to estimate the influencing factors. Results: Approximately one-third of the patients (2403, 33.8%) switched from warfarin to a DOAC during the study period. Female sex, aged between 75 and 79 years, having a Medical Aid or Patriots and Veterans Insurance, hypertension, and history of prior stroke, and transient ischemic attack or thromboembolism (prior stroke/TIA/TE) were associated with a significantly shorter time to switch. The odds of switching to a DOAC were increased by approximately 1.2-fold in the women and 1.4-fold in the patients with prior stroke/TIA/TE. Conclusions: Approximately one-third of the warfarin-using patients switched from warfarin to a DOAC within 6 months after the change in the DOAC reimbursement criteria. In the Cox proportional hazard regression analysis, the factors that affected anticoagulant switching from warfarin to a DOAC were female sex and history of prior stroke/TIA/TE.


2021 ◽  
Vol 10 (1) ◽  
pp. 1
Author(s):  
MAHFUZ HUDORI

Linear regression model cannot be used to analyze the relationship between survival time and independent variables, it is because the linear regression model is not able to handle censored data. Regression can be used to analyze survival data is cox proportional hazard regression. This research studies factors that influence study time drop out of Civil Engineering students at Universitas International Batam using the cox proportional hazard regression model approach. The independent variable that influenced study time drop out of Civil Engineering students at Universitas International Batam was the Cumulative Achievement Index and Work Status.


2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1445.1-1445
Author(s):  
F. Girelli ◽  
A. Ariani ◽  
M. Bruschi ◽  
A. Becciolini ◽  
L. Gardelli ◽  
...  

Background:The available biosimilars of etanercept are as effective and well tolerated as their bio originator molecule in the naive treatment of chronic autoimmune arthritis. More data about the switching from the bio originator are needed.Objectives:To compare the clinical outcomes of the treatment with etanercept biosimilars (SB4 and GP2015) naïve and after the switch from their corresponding originator in patients affected by autoimmune arthritis in a real life settingMethods:We retrospectively analyzed the baseline characteristics and the retention rate in a cohort of patients who received at least a course of etanercept (originator or biosimilar) in our Rheumatology Units from January 2000 to January 2020. We stratified the study population according to biosimilar use. Descriptive data are presented by medians (interquartile range [IQR]) for continuous data or as numbers (percentages) for categorical data. Drug survival distribution curves were computed by the Kaplan-Meier method and compared by a stratified log-rank test. A Cox proportional hazards regression analysis stratified by indication, drug, age, disease duration, sex, treatment line, biosimilar use and prescription year was performed. P values≤0.05 were considered statistically significant.Results:477 patients (65% female, median age 56 [46-75] years, median disease duration 97 [40.25-178.75] months) treated with etanercept were included in the analysis. 257 (53.9%) were affect by rheumatoid arthritis, 139 (29.1%) by psoriatic arthritis, and 81 (17%) by axial spondylarthritis. 298 (62.5%) were treated with etanercept originator, 97 (20.3%) with SB4, and 82 (17.2%) with GP2015. Among the biosimilars 90/179 (50.3%) patients were naïve to etanercept treatment. Among the 89 switchers we observed 8 treatment discontinuations: one due to surgical infection complication, three due to disease flare, two due to subjective worsening and one due to remission. The overall 6- and 12-month retentions rate were 92.8% and 80.2%. The 6- and 12-month retention rate for etanercept, SB4 and GP2015 were 92.7%, 93.4% and 90.2%, and 82%, 74.5% and 88.1% respectively, without significant differences among the three groups (p=0.374). Patients switching from originator to biosimilars showed and overall higher treatment survival when compared to naive (12-month retention rate 81.2% vs 70.8%, p=0.036). The Cox proportional hazard regression analysis highlighted that the only predictor significantly associated with an overall higher risk of treatment discontinuation was the year of prescription (HR 1.08, 95% CI 1.04 to 1.13; p<0.0001).Conclusion:In our retrospective study etanercept originator and its biosimilars (SB4 and GP2015) showed the same effectiveness. Patients switching from originator to biosimilar showed an significant higher retention rate when compared to naive. The only predictor of treatment discontinuation highlighted by the Cox proportional hazard regression analysis was the year of treatment prescription.Disclosure of Interests:Francesco Girelli: None declared, Alarico Ariani: None declared, Marco Bruschi: None declared, Andrea Becciolini Speakers bureau: Sanofi-Genzyme, UCB and AbbVie, Lucia Gardelli: None declared, Maurizio Nizzoli: None declared


Sign in / Sign up

Export Citation Format

Share Document