Maia Lesosky1, Tracy Glass2, Brian Rambau2, Nei-Yuan Hsiao3, Elaine J Abrams4, Landon Myer2. 1. Division of Epidemiology & Biostatistics, School of Public Health & Family Medicine, University of Cape Town, Observatory, South Africa. Electronic address: lesosky@gmail.com. 2. Division of Epidemiology & Biostatistics, School of Public Health & Family Medicine, University of Cape Town, Observatory, South Africa. 3. Division of Medical Virology, Department of Pathology, University of Cape Town and National Health Laboratory Services, Observatory, South Africa. 4. ICAP at Columbia University, Mailman School of Public Health, Columbia University and College of Physicians and Surgeons, Columbia University, New York, NY.
Abstract
PURPOSE: The 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. METHODS: We simulated longitudinal viral load measures and reanalyzed cohort study data sets with longitudinal viral load measurements under different sampling strategies to estimate cumulative viremia. RESULTS: In 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. CONCLUSIONS: Sampling 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.
PURPOSE: The 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. METHODS: We simulated longitudinal viral load measures and reanalyzed cohort study data sets with longitudinal viral load measurements under different sampling strategies to estimate cumulative viremia. RESULTS: In 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. CONCLUSIONS: Sampling 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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