Antiretroviral treatment cohort analysis using time-updated CD4 counts: assessment of bias with different analytic methods.
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.This stu...
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doaj-3b182a27b7fd47f8b8b74d4dfbcbff4e2020-11-24T22:17:20ZengPublic Library of Science (PLoS)PLoS ONE1932-62032011-01-01611e2776310.1371/journal.pone.0027763Antiretroviral treatment cohort analysis using time-updated CD4 counts: assessment of bias with different analytic methods.Katharina KranzerJames J LewisRichard G WhiteJudith R GlynnStephen D LawnKeren MiddelkoopLinda-Gail BekkerRobin WoodSurvival 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.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.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.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.http://europepmc.org/articles/PMC3219676?pdf=render |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Katharina Kranzer James J Lewis Richard G White Judith R Glynn Stephen D Lawn Keren Middelkoop Linda-Gail Bekker Robin Wood |
spellingShingle |
Katharina Kranzer James J Lewis Richard G White Judith R Glynn Stephen D Lawn Keren Middelkoop Linda-Gail Bekker Robin Wood Antiretroviral treatment cohort analysis using time-updated CD4 counts: assessment of bias with different analytic methods. PLoS ONE |
author_facet |
Katharina Kranzer James J Lewis Richard G White Judith R Glynn Stephen D Lawn Keren Middelkoop Linda-Gail Bekker Robin Wood |
author_sort |
Katharina Kranzer |
title |
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_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_sort |
antiretroviral treatment cohort analysis using time-updated cd4 counts: assessment of bias with different analytic methods. |
publisher |
Public Library of Science (PLoS) |
series |
PLoS ONE |
issn |
1932-6203 |
publishDate |
2011-01-01 |
description |
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.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.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.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. |
url |
http://europepmc.org/articles/PMC3219676?pdf=render |
work_keys_str_mv |
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