Abstract

PurposeThe use of cumulative measures of exposure to raised HIV viral load (viremia copy-years) is increasingly common in HIV prevention and treatment epidemiology due to the association of long-term elevated viral load with more rapid progression to disease. We sought to estimate the magnitude and direction of bias in a cumulative measure of viremia caused by different frequency of sampling and duration of follow-up. MethodsWe simulated longitudinal viral load measures and reanalyzed cohort study data sets with longitudinal viral load measurements under different sampling strategies to estimate cumulative viremia. ResultsIn both simulated and observed data, estimates of cumulative viremia by the trapezoidal rule show systematic upward bias when there are fewer sampling time points and/or increased duration between sampling time points, compared with estimation of full time series. Absolute values of cumulative viremia vary appreciably by the patterns of viral load over time, even after adjustment for total duration of follow-up. ConclusionsSampling bias due to differential frequency of sampling appears extensive and of meaningful magnitude in measures of cumulative viremia. Cumulative measures of viremia should be used only in studies with sufficient frequency of viral load measures and always as relative measures.

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