A coarsened multinomial regression model for perinatal mother to child transmission of HIV

<p>Abstract</p> <p>Background</p> <p>In trials designed to estimate rates of perinatal mother to child transmission of HIV, HIV assays are scheduled at multiple points in time. Still, infection status for some infants at some time points may be unknown, particularly whe...

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Main Authors: Brown Elizabeth R, Gard Charlotte C
Format: Article
Language:English
Published: BMC 2008-07-01
Series:BMC Medical Research Methodology
Online Access:http://www.biomedcentral.com/1471-2288/8/46
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spelling doaj-403ceb46aa264f6fa1c1e015c039c77e2020-11-25T00:40:39ZengBMCBMC Medical Research Methodology1471-22882008-07-01814610.1186/1471-2288-8-46A coarsened multinomial regression model for perinatal mother to child transmission of HIVBrown Elizabeth RGard Charlotte C<p>Abstract</p> <p>Background</p> <p>In trials designed to estimate rates of perinatal mother to child transmission of HIV, HIV assays are scheduled at multiple points in time. Still, infection status for some infants at some time points may be unknown, particularly when interim analyses are conducted.</p> <p>Methods</p> <p>Logistic regression models are commonly used to estimate covariate-adjusted transmission rates, but their methods for handling missing data may be inadequate. Here we propose using coarsened multinomial regression models to estimate cumulative and conditional rates of HIV transmission. Through simulation, we compare the proposed models to standard logistic models in terms of bias, mean squared error, coverage probability, and power. We consider a range of treatment effect and visit process scenarios, while including imperfect sensitivity of the assay and contamination of the endpoint due to early breastfeeding transmission. We illustrate the approach through analysis of data from a clinical trial designed to prevent perinatal transmission.</p> <p>Results</p> <p>The proposed cumulative and conditional models performed well when compared to their logistic counterparts. Performance of the proposed cumulative model was particularly strong under scenarios where treatment was assumed to increase the risk of in utero transmission but decrease the risk of intrapartum and overall perinatal transmission and under scenarios designed to represent interim analyses. Power to estimate intrapartum and perinatal transmission was consistently higher for the proposed models.</p> <p>Conclusion</p> <p>Coarsened multinomial regression models are preferred to standard logistic models for estimation of perinatal mother to child transmission of HIV, particularly when assays are missing or occur off-schedule for some infants.</p> http://www.biomedcentral.com/1471-2288/8/46
collection DOAJ
language English
format Article
sources DOAJ
author Brown Elizabeth R
Gard Charlotte C
spellingShingle Brown Elizabeth R
Gard Charlotte C
A coarsened multinomial regression model for perinatal mother to child transmission of HIV
BMC Medical Research Methodology
author_facet Brown Elizabeth R
Gard Charlotte C
author_sort Brown Elizabeth R
title A coarsened multinomial regression model for perinatal mother to child transmission of HIV
title_short A coarsened multinomial regression model for perinatal mother to child transmission of HIV
title_full A coarsened multinomial regression model for perinatal mother to child transmission of HIV
title_fullStr A coarsened multinomial regression model for perinatal mother to child transmission of HIV
title_full_unstemmed A coarsened multinomial regression model for perinatal mother to child transmission of HIV
title_sort coarsened multinomial regression model for perinatal mother to child transmission of hiv
publisher BMC
series BMC Medical Research Methodology
issn 1471-2288
publishDate 2008-07-01
description <p>Abstract</p> <p>Background</p> <p>In trials designed to estimate rates of perinatal mother to child transmission of HIV, HIV assays are scheduled at multiple points in time. Still, infection status for some infants at some time points may be unknown, particularly when interim analyses are conducted.</p> <p>Methods</p> <p>Logistic regression models are commonly used to estimate covariate-adjusted transmission rates, but their methods for handling missing data may be inadequate. Here we propose using coarsened multinomial regression models to estimate cumulative and conditional rates of HIV transmission. Through simulation, we compare the proposed models to standard logistic models in terms of bias, mean squared error, coverage probability, and power. We consider a range of treatment effect and visit process scenarios, while including imperfect sensitivity of the assay and contamination of the endpoint due to early breastfeeding transmission. We illustrate the approach through analysis of data from a clinical trial designed to prevent perinatal transmission.</p> <p>Results</p> <p>The proposed cumulative and conditional models performed well when compared to their logistic counterparts. Performance of the proposed cumulative model was particularly strong under scenarios where treatment was assumed to increase the risk of in utero transmission but decrease the risk of intrapartum and overall perinatal transmission and under scenarios designed to represent interim analyses. Power to estimate intrapartum and perinatal transmission was consistently higher for the proposed models.</p> <p>Conclusion</p> <p>Coarsened multinomial regression models are preferred to standard logistic models for estimation of perinatal mother to child transmission of HIV, particularly when assays are missing or occur off-schedule for some infants.</p>
url http://www.biomedcentral.com/1471-2288/8/46
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