Determinant factors of survival time in a cohort study on HIV patient using by time-varying cox model: Fars province, south of Iran

Authors

  • Haleh Hgaem Research Center for Health Sciences, Epidemiology Dept., Shiraz University of Medical Sciences, Shiraz, I.R. Iran
  • Maliheh Abdollahi Epidemiology Dept., Shiraz University of Medical Sciences, Shiraz, I.R. Iran
Abstract:

Background and aims: The pandemic of AIDS is a global emergency and one of the biggest challenges in social and individual life. This study aimed to evaluate the survival time of HIV patients and its effective factors. Methods: This historical cohort study was conducted on the individuals infected with HIV in Fars province, south of Iran, during 2006 to 2013. The study data were obtained from information documented in the patients’ records. For statistical analysis, at first, Kaplan-Meier survival analysis was used as univariate method and then, time varying Cox regression model was applied as multiple analyses. Results: The findings of the present study implied that some variables could play the role of risk factors in HIV patients, and shorten the patients’ life span e.g. older age, female gender, unemployment, delay in HIV diagnosis, drug injection, and higher Hemoglobin (HGB) levels. Conclusion: Many factors affect HIV patients’ survival time. Some of these factors, such as gender and genetic factors, are irreversible. However, some others, including drug injection, are preventable. This implies that in order to slow down the speed of HIV conversion to AIDS and delay the occurrence of death, special attention must be paid to these factors and changing the patients’ conditions accordingly.

Upgrade to premium to download articles

Sign up to access the full text

Already have an account?login

similar resources

a study on insurer solvency by panel data model: the case of iranian insurance market

the aim of this thesis is an approach for assessing insurer’s solvency for iranian insurance companies. we use of economic data with both time series and cross-sectional variation, thus by using the panel data model will survey the insurer solvency.

The Effect of Time-dependent Prognostic Factors on Survival of Non-Small Cell Lung Cancer using Bayesian Extended Cox Model

  Abstract Background: Lung cancer is one of the most common cancers around the world. The aim of this study was to use Extended Cox Model (ECM) with Bayesian approach to survey the behavior of potential time-varying prognostic factors of Non-small cell lung cancer. Materials and Methods: Survival status of all 190 patients diagnosed with Non-Small Cell lung cancer referring to hospitals in ...

full text

a time-series analysis of the demand for life insurance in iran

با توجه به تجزیه و تحلیل داده ها ما دریافتیم که سطح درامد و تعداد نمایندگیها باتقاضای بیمه عمر رابطه مستقیم دارند و نرخ بهره و بار تکفل با تقاضای بیمه عمر رابطه عکس دارند

My Resources

Save resource for easier access later

Save to my library Already added to my library

{@ msg_add @}


Journal title

volume 4  issue 2

pages  145- 155

publication date 2017-04-01

By following a journal you will be notified via email when a new issue of this journal is published.

Hosted on Doprax cloud platform doprax.com

copyright © 2015-2023