Research Article Open Access

Determination of Predictors Associated With HIV/AIDS Patients on ART Using Accelerated Failure Time Model for Interval Censored Survival Data

Prafulla Kumar Swain1 and Gurprit Grover1
  • 1 University of Delhi, India
Current Research in Biostatistics
Volume 6 No. 1, 2016, 12-19

DOI: https://doi.org/10.3844/amjbsp.2016.12.19

Submitted On: 10 January 2015 Published On: 12 January 2016

How to Cite: Swain, P. K. & Grover, G. (2016). Determination of Predictors Associated With HIV/AIDS Patients on ART Using Accelerated Failure Time Model for Interval Censored Survival Data. Current Research in Biostatistics, 6(1), 12-19. https://doi.org/10.3844/amjbsp.2016.12.19

Abstract

The main objective of this paper is to identify the independent predictors affecting the survival of HIV/AIDS infected patients on Antiretroviral Therapy (ART), an interval censored event time outcome. A total of 2052 HIV/AIDS patients, who were on ART at Ram ManoharLohia Hospital, New Delhi, India, during the period of April 2004 to December 2010, were included for analysis. Accelerated Failure Time Models (AFTM) viz., exponential, Weibull, lognormal and loglogistic for interval censored survival data, have been used to determine the significant predictors for HIV/AIDS infected patients. The best model is selected on the basis of Akaike Information Criterion (AIC) and Bayesian Information Criterion (BIC) values. Out of 2052 HIV/AIDS patients 65.4% were males and 34.6% were females. A majority 93.7% of patients had CD4 cell counts below 350 cells/mm3 at the time of initiation of ART. The mean age of patients at diagnosis was 34.28±8.19 years. The prognostic factorsviz., age, sex, CD4 cell count, past smokers, baseline hemoglobin and baseline BMI are found to be statistically significant (p<0.000) for HIV/AIDS patients on ART. Hence, a special attention is needed for patients with low CD4 cell counts, low BMI and low hemoglobin. Lognormal AFT model is found to be the best model to identify the independent predictors for survival of HIV population.

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Keywords

  • HIV
  • AIDS
  • ART
  • Survival
  • Interval Censoring
  • AFTM