Related Experiment Video
Updated: Jan 27, 2026

Exergaming in Older People Living with HIV Improves Balance, Mobility and Ameliorates Some Aspects of Frailty
Published on: October 6, 2016
[Survival analysis of people living with HIV/AIDS in Sichuan province, 1991-2017]
1Department of AIDS/STD Control and Prevention, Sichuan Provincial Center for Disease Control and Prevention, Chengdu 610041, China.
Abstract:
Objective: To analyze the survival time of people living with HIV/AIDS and related influencing factors in Sichuan province during 1991-2017. Methods: A retrospective cohort study was conducted to analyze the data of 143 988 HIV/AIDS cases. The data were collected from Chinese HIV/AIDS Comprehensive Information Management System. Life table method was used to calculate the survival proportion of the cases, and Cox proportion hazard regression model was used to identify the factors related with survival time. Results: Among 143 988 HIV/AIDS cases a total of 30 420 cases died of AIDS related diseases (21.1%) and the average survival time was 11.51 years (95%CI: 11.39-11.64). Multivariate Cox regression analysis showed that the influencing factors for the survival of HIV/AIDS cases were gender (male vs. female, HR=1.35, 95%CI: 1.32-1.40), education level (primary school or below vs. junior middle school: HR=1.15, 95%CI: 1.12-1.18), ethnic group (Han vs. other ethnic groups, HR=1.46, 95%CI: 1.41-1.52), occupation (farmer vs. other occupations: HR=1.26, 95%CI: 1.22-1.29), age (≥55 years old vs. 15-24 years old: HR=3.18, 95%CI: 3.02- 3.36), disease phase (AIDS vs. HIV infection: HR=1.44, 95%CI: 1.39-1.48), antiretroviral therapy (ART) (receiving ART vs. receiving no ART: HR=0.20, 95%CI: 0.19-0.20), and CD(4)(+)T cell counts at diagnosis (>500 cells/μl vs.<200 cells/μl: HR=0.42, 95%CI: 0.40-0.45). Conclusions: The average survival time of HIV/AIDS cases was 11.51 years in Sichuan during 1991- 2017. The risk factors for the survival of the cases were male, education level of primary school or below, Han ethnic group, farmer, old age at diagnosis, disease phase, The protective factors for the survival of HIV/AIDS cases were receiving ART and higher CD(4)(+) T cell counts at diagnosis.
Related Concept Videos
Introduction To Survival Analysis
The primary goal of survival analysis is to estimate survival time—the time...
Comparing the Survival Analysis of Two or More Groups
Truncation in Survival Analysis
Left truncation occurs when individuals who experienced the event of interest before a certain time are not included in the study. This is often due to a "delayed entry" into the study where only those who survive until a certain entry point are...
Assumptions of Survival Analysis
Cancer Survival Analysis
Parametric Survival Analysis: Weibull and Exponential Methods
Weibull Distribution
The Weibull distribution is a flexible model used in parametric survival analysis. It can handle both increasing and decreasing hazard rates, depending on its shape parameter...

