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Updated: Mar 6, 2026
The α-test: Rapid Cell-free CD4 Enumeration Using Whole Saliva
Published on: May 16, 2012
Joint estimation of CD4+ cell progression and survival in untreated individuals with HIV-1 infection
1Medical Research Council Centre for Outbreak Analysis and Modelling, Department of Infectious Disease Epidemiology, Imperial College London, London, UK.
Objective:
We compiled the largest dataset of seroconverter cohorts to date from 25 countries across Africa, North America, Europe, and Southeast/East (SE/E) Asia to simultaneously estimate transition rates between CD4 cell stages and death, in antiretroviral therapy (ART)-naive HIV-1-infected individuals.
Design:
A hidden Markov model incorporating a misclassification matrix was used to represent natural short-term fluctuations and measurement errors in CD4 cell counts. Covariates were included to estimate the transition rates and survival probabilities for each subgroup.
Results:
The median follow-up time for 16 373 eligible individuals was 4.1 years (interquartile range 1.7-7.1), and the mean age at seroconversion was 31.1 years (SD 8.8). A total of 14 525 individuals had recorded CD4 cell counts pre-ART, 1885 died, and 6947 initiated ART. Median (interquartile range) survival for men aged 20 years at seroconversion was 13.0 (12.4-13.4), 11.6 (10.9-12.3), and 8.3 years (7.9-8.9) in Europe/North America, Africa, and SE/E Asia, respectively. Mortality rates increase with age (hazard ratio 2.22, 95% confidence interval 1.84-2.67 for >45 years compared with <25 years) and vary by region (hazard ratio 2.68, 1.75-4.12 for Africa and 1.88, 1.50-2.35 for Asia compared with Europe/North America). CD4 cell decline was significantly faster in Asian cohorts compared with Europe/North America (hazard ratio 1.45, 1.36-1.54).
Conclusion:
Mortality and CD4 cell progression rates exhibited regional and age-specific differences, with decreased survival in African and SE/E Asian cohorts compared with Europe/North America and in older age groups. This extensive dataset reveals heterogeneities between regions and ages, which should be incorporated into future HIV models.
