scholarly journals Bayesian Joint Modelling of Longitudinal and Survival Data of HIV/AIDS Patients: A Case Study at Bale Robe General Hospital, Ethiopia

2017 ◽  
Vol 6 (4) ◽  
pp. 182 ◽  
Author(s):  
Ahmed Hasan Dessiso
Keyword(s):  
General Hospital ◽  
Survival Data ◽  
Aids Patients ◽  
Joint Modelling ◽  
Longitudinal And Survival Data ◽  
Hiv Aids

The Epidemiological Analysis of HIV/AIDS Patients: Sexually Transmitted Diseases Department VS. Other Departments in A General Hospital of Shanghai, China

2021 ◽  
Vol 19 ◽  
Author(s):  
Yue Yu ◽  
Liangliang Shen ◽  
Yufei Li ◽  
Jingjun Zhao ◽  
Heping Liu
Keyword(s):  
Sexually Transmitted Diseases ◽  
General Hospital ◽  
Demographic Characteristics ◽  
Hiv Screening ◽  
Aids Patients ◽  
Important Place ◽  
Sexually Transmitted ◽  
Positive Rate ◽  
Social Demographic ◽  
Hiv Aids

Background: Hospital is an important place for HIV/AIDS screening, and a general hospital is composed of multiple departments. Different departments have different levels of understanding of HIV/AIDS, especially the sexually transmitted diseases (STD) department is the main place for HIV/AIDS screening. Objective: The study aims to validate the common knowledge that the STD department is an important place for HIV/AIDS screening by comparing the epidemiological characteristics of HIV/AIDS patients in the STD department and other departments in Tongji Hospital, which can provide a theoretical basis for the precise and differentiated control of HIV/AIDS. Methods: A total of 283,525 HIV screening cases were analyzed from January 1st 2006 to December 31st 2018 in the STD department and other departments. The epidemiological data of 226 HIV/AIDS cases were retrospectively analyzed. Results : Firstly, the incidence of HIV/AIDS in the population served by Tongji Hospital was higher than that in Shanghai and China. Secondly, the positive rate of HIV screening test in the STD department was ten times higher than that of other departments. Thirdly, the social-demographic characteristics of HIV/AIDS patients in the STD department were different from those in other departments. Fourthly, there were differences in age, education, marital status and number of sex partners between men who have sex with men (MSM) and men who have sex with women (MSW). Fifthly, there was no difference except age in social-demographic characteristics of MSM between the STD department and other departments. Sixthly, compared with other departments, the majority of HIV/AIDS patients in the STD department were MSM. Seventhly, syphilis and HIV co-infection were not statistically significant in HIV/AIDS patients between the STD department and other departments. Conclusion: Firstly, the significantly higher positive rate of an HIV screening test in the STD department emphasizes its importance as a place for screening HIV/AIDS patients. Secondly, HIV/AIDS patients diagnosed in the general hospital were mainly transmitted by sexual contact, and MSM accounted for the most part of these patients. More attention should be paid to screen outpatients, especially in the STD department and young men.

scholarly journals Flexible parametric joint modelling of longitudinal and survival data

2012 ◽  
Vol 31 (30) ◽  
pp. 4456-4471 ◽  
Author(s):  
Michael J. Crowther ◽  
Keith R. Abrams ◽  
Paul C. Lambert
Keyword(s):  
Survival Data ◽  
Joint Modelling ◽  
Longitudinal And Survival Data

scholarly journals JMcmprsk: An R Package for Joint Modelling of Longitudinal and Survival Data with Competing Risks

The R Journal ◽  
2021 ◽  
Vol 13 (1) ◽  
pp. 53
Author(s):  
Hong Wang ◽  
Ning Li ◽  
Shanpeng Li ◽  
Gang Li
Keyword(s):  
Competing Risks ◽  
Survival Data ◽  
R Package ◽  
Joint Modelling ◽  
Longitudinal And Survival Data

scholarly journals Pulmonary Tuberculosis in HIV/AIDS Patients Attending Art Clinic in Bududa General Hospital, Bududa District, Uganda

2019 ◽  
Vol 07 (03) ◽  
pp. 135-142
Author(s):  
Kalyetsi Rogers ◽  
Nafungo Gertrude ◽  
Muwanguzi Enoch
Keyword(s):  
Pulmonary Tuberculosis ◽  
General Hospital ◽  
Aids Patients ◽  
Hiv Aids

scholarly journals Assessing importance of biomarkers: A Bayesian joint modelling approach of longitudinal and survival data with semi-competing risks

2020 ◽  
pp. 1471082X2093336
Author(s):  
Fan Zhang ◽  
Ming-Hui Chen ◽  
Xiuyu Julie Cong ◽  
Qingxia Chen
Keyword(s):  
Disease Progression ◽  
Competing Risks ◽  
Survival Data ◽  
Marginal Likelihood ◽  
Cox Proportional Hazards Model ◽  
Terminal Event ◽  
Joint Modelling ◽  
Patient Reported ◽  
Longitudinal And Survival Data ◽  
Time Varying Covariates

Longitudinal biomarkers such as patient-reported outcomes (PROs) and quality of life (QOL) are routinely collected in cancer clinical trials or other studies. Joint modelling of PRO/QOL and survival data can provide a comparative assessment of patient-reported changes in specific symptoms or global measures that correspond to changes in survival. Motivated by a head and neck cancer clinical trial, we develop a class of trajectory-based models for longitudinal and survival data with disease progression. Specifically, we propose a class of mixed effects regression models for longitudinal measures, a cure rate model for the disease progression time ([Formula: see text]) and a Cox proportional hazards model with time-varying covariates for the overall survival time ([Formula: see text]) to account for [Formula: see text] and treatment switching. Under the semi-competing risks framework, the disease progression is the non-terminal event, the occurrence of which is subject to a terminal event of death. The properties of the proposed models are examined in detail. Within the Bayesian paradigm, we derive the decompositions of the deviance information criterion (DIC) and the logarithm of the pseudo-marginal likelihood (LPML) to assess the fit of the longitudinal component of the model and the fit of each survival component, separately. We further develop [Formula: see text]DIC as well as [Formula: see text]LPML to determine the importance and contribution of the longitudinal data to the model fit of the [Formula: see text] and [Formula: see text] data.

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