OBJECTIVES: To estimate mortality directly attributable to HIV in HIV-infected adults in low and middle income countries and discuss appropriate methodology. DESIGN: : Illustrative analysis of pooled data from six studies across sub-Saharan Africa and Thailand with data on individuals with known dates of seroconversion to HIV. METHODS: Five of the studies also had data from HIV-negative subjects and one had verbal autopsies. Data for HIV-negative cohorts were weighted by the initial age and sex distribution of the seroconverters. Using the survival of the HIV-negative group to represent the background mortality, net survival from HIV was calculated for the seroconverters using competing risk methods. Mortality from all causes and 'net' mortality were modelled using piecewise exponential regression. Alternative approaches are explored in the dataset without information on mortality of uninfected individuals. RESULTS: The overall effect of the net mortality adjustment was to increase survivorship proportionately by 2 to 5% at 6 years post-infection. The increase ranged from 2% at ages 15-24 to 22% in those 55 and over. Mortality rate ratios between sites were similar to corresponding ratios for all-cause mortality. CONCLUSION: Differences between HIV mortality in different populations and age groups are not explained by differences in background mortality, although this does appear to contribute to the excess at older ages. In the absence of data from uninfected individuals in the same population, model life tables can be used to calculate background rates.
OBJECTIVES: To estimate mortality directly attributable to HIV in HIV-infected adults in low and middle income countries and discuss appropriate methodology. DESIGN: : Illustrative analysis of pooled data from six studies across sub-Saharan Africa and Thailand with data on individuals with known dates of seroconversion to HIV. METHODS: Five of the studies also had data from HIV-negative subjects and one had verbal autopsies. Data for HIV-negative cohorts were weighted by the initial age and sex distribution of the seroconverters. Using the survival of the HIV-negative group to represent the background mortality, net survival from HIV was calculated for the seroconverters using competing risk methods. Mortality from all causes and 'net' mortality were modelled using piecewise exponential regression. Alternative approaches are explored in the dataset without information on mortality of uninfected individuals. RESULTS: The overall effect of the net mortality adjustment was to increase survivorship proportionately by 2 to 5% at 6 years post-infection. The increase ranged from 2% at ages 15-24 to 22% in those 55 and over. Mortality rate ratios between sites were similar to corresponding ratios for all-cause mortality. CONCLUSION: Differences between HIV mortality in different populations and age groups are not explained by differences in background mortality, although this does appear to contribute to the excess at older ages. In the absence of data from uninfected individuals in the same population, model life tables can be used to calculate background rates.
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