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Antiretroviral Treatment Cohort Analysis Using Time-Updated CD4 Counts: Assessment of Bias with Different Analytic Methods

BACKGROUND: Survival analysis using time-updated CD4+ counts during antiretroviral therapy is frequently employed to determine risk of clinical events. The time-point when the CD4+ count is assumed to change potentially biases effect estimates but methods used to estimate this are infrequently repor...

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Autores principales: Kranzer, Katharina, Lewis, James J., White, Richard G., Glynn, Judith R., Lawn, Stephen D., Middelkoop, Keren, Bekker, Linda-Gail, Wood, Robin
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3219676/
https://www.ncbi.nlm.nih.gov/pubmed/22114687
http://dx.doi.org/10.1371/journal.pone.0027763
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author Kranzer, Katharina
Lewis, James J.
White, Richard G.
Glynn, Judith R.
Lawn, Stephen D.
Middelkoop, Keren
Bekker, Linda-Gail
Wood, Robin
author_facet Kranzer, Katharina
Lewis, James J.
White, Richard G.
Glynn, Judith R.
Lawn, Stephen D.
Middelkoop, Keren
Bekker, Linda-Gail
Wood, Robin
author_sort Kranzer, Katharina
collection PubMed
description BACKGROUND: Survival analysis using time-updated CD4+ counts during antiretroviral therapy is frequently employed to determine risk of clinical events. The time-point when the CD4+ count is assumed to change potentially biases effect estimates but methods used to estimate this are infrequently reported. METHODS: This study examined the effect of three different estimation methods: assuming i) a constant CD4+ count from date of measurement until the date of next measurement, ii) a constant CD4+ count from the midpoint of the preceding interval until the midpoint of the subsequent interval and iii) a linear interpolation between consecutive CD4+ measurements to provide additional midpoint measurements. Person-time, tuberculosis rates and hazard ratios by CD4+ stratum were compared using all available CD4+ counts (measurement frequency 1–3 months) and 6 monthly measurements from a clinical cohort. Simulated data were used to compare the extent of bias introduced by these methods. RESULTS: The midpoint method gave the closest fit to person-time spent with low CD4+ counts and for hazard ratios for outcomes both in the clinical dataset and the simulated data. CONCLUSION: The midpoint method presents a simple option to reduce bias in time-updated CD4+ analysis, particularly at low CD4 cell counts and rapidly increasing counts after ART initiation.
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spelling pubmed-32196762011-11-23 Antiretroviral Treatment Cohort Analysis Using Time-Updated CD4 Counts: Assessment of Bias with Different Analytic Methods Kranzer, Katharina Lewis, James J. White, Richard G. Glynn, Judith R. Lawn, Stephen D. Middelkoop, Keren Bekker, Linda-Gail Wood, Robin PLoS One Research Article BACKGROUND: Survival analysis using time-updated CD4+ counts during antiretroviral therapy is frequently employed to determine risk of clinical events. The time-point when the CD4+ count is assumed to change potentially biases effect estimates but methods used to estimate this are infrequently reported. METHODS: This study examined the effect of three different estimation methods: assuming i) a constant CD4+ count from date of measurement until the date of next measurement, ii) a constant CD4+ count from the midpoint of the preceding interval until the midpoint of the subsequent interval and iii) a linear interpolation between consecutive CD4+ measurements to provide additional midpoint measurements. Person-time, tuberculosis rates and hazard ratios by CD4+ stratum were compared using all available CD4+ counts (measurement frequency 1–3 months) and 6 monthly measurements from a clinical cohort. Simulated data were used to compare the extent of bias introduced by these methods. RESULTS: The midpoint method gave the closest fit to person-time spent with low CD4+ counts and for hazard ratios for outcomes both in the clinical dataset and the simulated data. CONCLUSION: The midpoint method presents a simple option to reduce bias in time-updated CD4+ analysis, particularly at low CD4 cell counts and rapidly increasing counts after ART initiation. Public Library of Science 2011-11-17 /pmc/articles/PMC3219676/ /pubmed/22114687 http://dx.doi.org/10.1371/journal.pone.0027763 Text en Kranzer et al. http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited.
spellingShingle Research Article
Kranzer, Katharina
Lewis, James J.
White, Richard G.
Glynn, Judith R.
Lawn, Stephen D.
Middelkoop, Keren
Bekker, Linda-Gail
Wood, Robin
Antiretroviral Treatment Cohort Analysis Using Time-Updated CD4 Counts: Assessment of Bias with Different Analytic Methods
title Antiretroviral Treatment Cohort Analysis Using Time-Updated CD4 Counts: Assessment of Bias with Different Analytic Methods
title_full Antiretroviral Treatment Cohort Analysis Using Time-Updated CD4 Counts: Assessment of Bias with Different Analytic Methods
title_fullStr Antiretroviral Treatment Cohort Analysis Using Time-Updated CD4 Counts: Assessment of Bias with Different Analytic Methods
title_full_unstemmed Antiretroviral Treatment Cohort Analysis Using Time-Updated CD4 Counts: Assessment of Bias with Different Analytic Methods
title_short Antiretroviral Treatment Cohort Analysis Using Time-Updated CD4 Counts: Assessment of Bias with Different Analytic Methods
title_sort antiretroviral treatment cohort analysis using time-updated cd4 counts: assessment of bias with different analytic methods
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3219676/
https://www.ncbi.nlm.nih.gov/pubmed/22114687
http://dx.doi.org/10.1371/journal.pone.0027763
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