scholarly journals ANALISIS KETAHANAN HIDUP PENDERITA DENGUE HEMORRHAGIC FEVER (DEMAM BERDARAH) DENGAN REGRESI COX KEGAGALAN PROPORSIONAL (Studi Kasus : Rumah Sakit Islam Nahdlatul Ulama Demak)

2021 ◽  
Vol 10 (3) ◽  
pp. 367-376
Author(s):  
Putri Qodar Ummayah ◽  
Sudarno Sudarno ◽  
Budi Warsito
Keyword(s):  
Survival Analysis ◽  
Dengue Fever ◽  
Dengue Hemorrhagic Fever ◽  
Recovery Time ◽  
Hemorrhagic Fever ◽  
Proportional Hazard ◽  
Hazard Regression ◽  
Cox Proportional Hazard ◽  
Cox Proportional Hazard Regression ◽  
The Relationship

Dengue hemorrhagic fever is an acute febrile disease caused by the dengue virus, which enters the human bloodstream through the bite of a mosquito of the genus Aedes Aegypti or Aedes Albopictus. Based on World Health Organization (WHO) records, it is estimated that 500,000 dengue hemorrhagic fever patients require hospital treatment every year and most of the sufferers are children. To analyze the relationship between recovery time in dengue fever patients and the factors that influence it using regression analysis, the dependent variable is the failure time and the function of the response variable tends to fail constant so to find out the relationship using Cox proportional hazard regression. Cox proportional hazard regression is a regression model that is often used in survival analysis. Survival analysis is a method used to describe data analysis in terms of time from the time of origin defined until a certain event occurs. In this study, the recovery time of dengue fever patients as a function of failure is proportional. The observations used by the researchers for each patient were not the same. The population of this study were all patients with dengue fever. The data used was obtained from the medical record section for data on the length of hospitalization of patients regarding the recovery of patients with dengue fever. The conclusion of the research shows that the factors that affect the recovery time of dengue fever patients are hematocrit, platelets, immunoglobulin G, and immunoglobulin M. 

scholarly journals PENERAPAN REGRESI COX PROPORTIONAL HAZARD UNTUK MENDUGA FAKTOR-FAKTOR YANG MEMENGARUHI LAMA MENCARI KERJA

2013 ◽  
Vol 2 (3) ◽  
pp. 7
Author(s):  
I GEDE ARI SUDANA ◽  
NI LUH PUTU SUCIPTAWATI ◽  
LUH PUTU IDA HARINI
Keyword(s):  
Survival Analysis ◽  
Censored Data ◽  
Proportional Hazards ◽  
Cox Proportional Hazards ◽  
Proportional Hazard ◽  
Hazard Regression ◽  
Cox Proportional Hazards Regression ◽  
Cox Proportional Hazard ◽  
Proportional Hazards Regression ◽  
Cox Proportional Hazard Regression

Survival analysis is a statistical method that accommodates the collection of censored data. One of popular method in survival analysis is the Cox Proportional Hazard Regression. The Cox Proportional Hazard Regression can be used to see old looking for work where data may contain censored data. This article aims investigate the characteristics of job seekers and the variables that affect old looking for work. To establish the best model using Stepwise Selection method. Prior to that the assumption of Cox Proportional Hazards Regression is tested using log minus log curve. The results obtained from Cox Proportional Hazards Regression model is as follows  

scholarly journals Penanganan Ties Event dalam Regresi Cox Proportional Hazard Menggunakan Metode Breslow (Kasus: Pasien Rawat Inap DBD di RSAL Jala Ammari Makassar)

2020 ◽  
Vol 2 (1) ◽  
pp. 13
Author(s):  
Herawati Hafid ◽  
Muhammad Nadjib Bustan ◽  
Muhammad Kasim Aidid
Keyword(s):  
Survival Analysis ◽  
Dengue Hemorrhagic Fever ◽  
Recovery Rate ◽  
Cox Model ◽  
Hemorrhagic Fever ◽  
Hazard Ratio ◽  
Partial Likelihood ◽  
P Value ◽  
Proportional Hazard ◽  
Cox Proportional Hazard

Abstrak Analisis Survival adalah prosedur statistika yang digunakan untuk menganalisis data dimana peubah yang diperhatikan adalah waktu sampai terjadinya suatu event. Waktu dapat dinyatakan dalam hitungan hari, minggu, bulan dan tahun. Salah satu tujuan dari analisis survival adalah untuk mengetahui hubungan antara waktu kejadian  peubah bebas yang terukur pada saat dilakukan penelitian. Metode yang sering digunakan dalam analisis survival khususnya data kesehatan adalah Regresi Cox Proportional Hazard (PH) karena distribusinya tidak tergantung pada asumsi waktu kejadian. Dalam suatu data seperti data pasien penderita penyakit Demam Berdarah Dengue (DBD) ditemukan adanya data kejadian bersama (ties event) yang berpengaruh pada pembentukan himpunan risikonya pada bagian estimasi parameter model cox,pada kasus kejadian bersama (ties event) dilakukan modifikasi pada partial likelihood untuk mengetahui faktor-faktor yang mempengaruhi laju kesembuhan pasien penderita penyakit DBD. Adapun hasil analisisnya, diperoleh faktor yang paling berpengaruh terhadap laju kesembuhan penyakit DBD yakni leukosit dengan p-value =0,097< α 0,05, dan nilai hazard ratio sebesar 1,1024 serta faktor yang kedua yaitu hematokrit dengan p-value =0,0141< α 0,05, dan nilai hazard ratio sebesar 1,595. Kata Kunci: Analisis Survival, Regresi Cox PH, Ties Event, Metode Breslow, Demam Berdarah Dengue (DBD). Abstract Survival analysis is a statistical procedure that is used to analyze data where the variables considered are the time until the occurrence of an event. Time can be expressed in days, weeks, months and years. One of the objectives of survival analysis is to find out the relationship between the time of occurrence of independent variables measured at the time of the study. The method often used in survival analysis, especially health data, is Cox Proportional Hazard (PH) Regression because its distribution does not depend on the assumption of the time of the event. In a data such as data on patients with Dengue Hemorrhagic Fever (DHF) data, there were ties event data that influenced the formation of risk sets in the cox model parameter estimation section, in the case of ties event modifications were made to the partial likelihood for know the factors that influence the recovery rate of patients with DHF. As for the results of the analysis, the factors that most influence the recovery rate of leucocyte dengue fever with p-value = 0,097 < α = 0,05 and the hazard ratio of 1.1024 and the second factor is the hematocrit with p-value = 0,0141 < α = 0,05 and the hazard ratio valueamounting to 1,595. Keywords: Survival Analysis, Cox PH Regression, Ties Event, Breslow Method, Dengue Hemorrhagic Fever (DHF).

scholarly journals AB0292 EFFICACY AND SAFETY OF TWO BIOSIMILAR ETANERCEPT AFTER THE SWITCH FROM THEIR CORRESPONDING ORIGINATOR IN THE TREATMENT OF PATIENTS WITH AUTOIMMUNE ARTHRITIS; A RETROSPECTIVE ANALYSIS IN A REAL LIFE SETTING

2020 ◽  
Vol 79 (Suppl 1) ◽  
pp. 1445.1-1445
Author(s):  
F. Girelli ◽  
A. Ariani ◽  
M. Bruschi ◽  
A. Becciolini ◽  
L. Gardelli ◽  
...  
Keyword(s):  
Regression Analysis ◽  
Disease Duration ◽  
Retention Rate ◽  
Real Life ◽  
Autoimmune Arthritis ◽  
Proportional Hazard ◽  
Hazard Regression ◽  
Cox Proportional Hazard ◽  
Real Life Setting ◽  
Cox Proportional Hazard Regression

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

Association between Preoperative Monocyte-to-Lymphocyte Ratio and Late Arteriovenous Fistula Dysfunction in Hemodialysis Patients: A Cohort Study

2021 ◽  
pp. 1-7
Author(s):  
Shouliang Hu ◽  
Dan Wang ◽  
Tean Ma ◽  
Fanli Yuan ◽  
Yong Zhang ◽  
...  
Keyword(s):  
Cohort Study ◽  
Arteriovenous Fistula ◽  
Vessel Diameter ◽  
Transluminal Angioplasty ◽  
Proportional Hazard ◽  
Clinical Value ◽  
Hazard Regression ◽  
Lymphocyte Ratio ◽  
Cox Proportional Hazard ◽  
Cox Proportional Hazard Regression

<b><i>Background:</i></b> Inflammation appears to be at the biological core of arteriovenous fistula (AVF) dysfunction, and the occurrence of AVF dysfunction is related to high death and disability in hemodialysis (HD) patients. Despite several studies on the correlations between AVF dysfunction and inflammatory indicators, how AVF dysfunction is related to the monocyte-to-lymphocyte ratio (MLR) is much unclear. We hypothesize that preoperative MLR is associated with AVF dysfunction in Chinese HD patients. <b><i>Methods:</i></b> In this single-center retrospective cohort study, totally 769 adult HD patients with a new AVF created between 2011 and 2019 were included. Association of preoperative MLR with AVF dysfunction (thrombosis or decrease of normal vessel diameter by &#x3e;50%, requiring either surgical revision or percutaneous transluminal angioplasty) was assessed by multivariable Cox proportional hazard regression. <b><i>Results:</i></b> The patients were aged 55.8 ± 12.2 years and were mostly males (55%). During the average 32-month follow-up (maximum 119 months), 223 (29.0%) patients had permanent vascular access dysfunction. In adjusted multivariable Cox proportional hazard regression analyses, the risk of AVF dysfunction was 4.32 times higher with 1 unit increase in MLR (hazard ratio [HR]: 5.32; 95% confidence interval [CI]: 3.1–9.11). Compared with patients with MLR &#x3c;0.28, HRs associated with an MLR of 0.28–0.41 and ≥0.41 are 1.54 (95% CI: 1.02–2.32) and 3.17 (2.18–4.62), respectively. <b><i>Conclusions:</i></b> A higher preoperative MLR is independently connected with a severer risk of AVF dysfunction in HD patients. Its clinical value should be determined in the future.

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
Keyword(s):  
Blood Pressure ◽  
Systolic Blood Pressure ◽  
Regression Model ◽  
Diastolic Blood Pressure ◽  
Proportional Hazard ◽  
Hazard Regression ◽  
Cox Proportional Hazard ◽  
History Of ◽  
Cox Proportional Hazard Regression ◽  
Sugar Levels

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.

scholarly journals Factors that influence the recovery of TB patients using Cox proportional hazard regression

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
ZURNILA MARLI KESUMA ◽  
HIZIR SOFYAN ◽  
LATIFAH RAHAYU ◽  
WARDATUL JANNAH
Keyword(s):  
Control Program ◽  
Proportional Hazard ◽  
Cure Rate ◽  
Hazard Regression ◽  
Cox Proportional Hazard ◽  
National Tuberculosis Control Program ◽  
Record Data ◽  
National Tuberculosis ◽  
The Government ◽  
Cox Proportional Hazard Regression

Tuberculosis (TB) is an infectious disease which is one of the biggest health problems in the world, including Indonesia. The government, through the National Tuberculosis Control program, has made various efforts to control tuberculosis. However, this problem was exacerbated by the dramatic increase in the incidence of tuberculosis. This study aimed to determine the Cox proportional hazard regression model and the factors that affect the cure rate of TB patients. We used medical record data for inpatient TB patients for the period July-December 2017 at dr. Zainoel Abidin Hospital. The results showed that with α = 0.1, the factors that influenced the recovery of TB patients were the type of cough, the symptoms of bloody cough and symptoms of sweating at night.  There were 33.93% of patients who did not work. This category included students, domestic helpers, and those who did not work until they suffered from tuberculosis and were treated at dr. Zainoel Abidin Hospital. The hazard ratio (failure ratio) showed that the tendency or cure rate for TB patients who did not experience cough symptoms was 70% greater than patients who experienced phlegm cough symptoms. The cure rate for TB patients who experienced coughing up blood symptoms was 53% greater than patients without these symptoms. The cure rate for TB patients who experienced  symptoms of sweating at night was 54% greater than patients who did not sweat at night.

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