Gender difference in HIV‐1 RNA viral loads
Objectives To test and characterize the dependence of viral load on gender in different countries and racial groups as a function of CD4 T‐cell count. Methods Plasma viral load data were analysed for >30 000 HIV‐infected patients attending clinics in the USA [HIV Insight™ (Cerner Corporation, Vie...
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Veröffentlicht in: | HIV medicine 2005-05, Vol.6 (3), p.170-178 |
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creator | Donnelly, CA Bartley, LM Ghani, AC Le Fevre, AM Kwong, GP Cowling, BJ Van Sighem, AI De Wolf, F Rode, RA Anderson, RM |
description | Objectives
To test and characterize the dependence of viral load on gender in different countries and racial groups as a function of CD4 T‐cell count.
Methods
Plasma viral load data were analysed for >30 000 HIV‐infected patients attending clinics in the USA [HIV Insight™ (Cerner Corporation, Vienna, VA, USA) and Plum Data Mining LLC (East Meadow, NY, USA) databases] and the Netherlands (Athena database; HIV Monitoring Foundation, Amsterdam, Netherlands). Log‐normal regression models were used to test for an effect of gender on viral load while adjusting for covariates and allowing the effect to depend on CD4 T‐cell count. Sensitivity analyses were performed to test the robustness of conclusions to assumptions regarding viral loads below the lower limit of quantification (LLOQ).
Results
After adjusting for covariates, women had (nonsignificantly) lower viral loads than men (HIV Insight™:−0.053 log10 HIV‐1 RNA copies/mL, P=0.202; Athena: −0.005 log10 copies/mL, P=0.667; Plum:−0.072 log10 copies/mL, P=0.273). However, further investigation revealed that the gender effect depended on CD4 T‐cell count. Women had consistently higher viral loads than men when CD4 T‐cell counts were at most 50 cells/μL, and consistently lower viral loads than men when CD4 T‐cell counts were greater than 350 cells/μL. These effects were remarkably consistent when estimated independently for the racial groups with sufficient data available in the HIV Insight™ and Plum databases.
Conclusions
The consistent relationship between gender‐related differences in viral load and CD4 T‐cell count demonstrated here explains the diverse findings previously published. |
doi_str_mv | 10.1111/j.1468-1293.2005.00285.x |
format | Article |
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To test and characterize the dependence of viral load on gender in different countries and racial groups as a function of CD4 T‐cell count.
Methods
Plasma viral load data were analysed for >30 000 HIV‐infected patients attending clinics in the USA [HIV Insight™ (Cerner Corporation, Vienna, VA, USA) and Plum Data Mining LLC (East Meadow, NY, USA) databases] and the Netherlands (Athena database; HIV Monitoring Foundation, Amsterdam, Netherlands). Log‐normal regression models were used to test for an effect of gender on viral load while adjusting for covariates and allowing the effect to depend on CD4 T‐cell count. Sensitivity analyses were performed to test the robustness of conclusions to assumptions regarding viral loads below the lower limit of quantification (LLOQ).
Results
After adjusting for covariates, women had (nonsignificantly) lower viral loads than men (HIV Insight™:−0.053 log10 HIV‐1 RNA copies/mL, P=0.202; Athena: −0.005 log10 copies/mL, P=0.667; Plum:−0.072 log10 copies/mL, P=0.273). However, further investigation revealed that the gender effect depended on CD4 T‐cell count. Women had consistently higher viral loads than men when CD4 T‐cell counts were at most 50 cells/μL, and consistently lower viral loads than men when CD4 T‐cell counts were greater than 350 cells/μL. These effects were remarkably consistent when estimated independently for the racial groups with sufficient data available in the HIV Insight™ and Plum databases.
Conclusions
The consistent relationship between gender‐related differences in viral load and CD4 T‐cell count demonstrated here explains the diverse findings previously published.</description><identifier>ISSN: 1464-2662</identifier><identifier>EISSN: 1468-1293</identifier><identifier>DOI: 10.1111/j.1468-1293.2005.00285.x</identifier><identifier>PMID: 15876283</identifier><language>eng</language><publisher>Oxford, UK: Blackwell Science Ltd</publisher><subject>Adult ; CD4 Lymphocyte Count ; CD4 T‐cell count ; Data Collection ; Databases, Factual ; Female ; gender ; HIV ; HIV Infections - immunology ; HIV Infections - virology ; HIV-1 ; Human immunodeficiency virus 1 ; Humans ; Male ; Regression Analysis ; Sex Distribution ; Statistics, Nonparametric ; United States ; Viral Load</subject><ispartof>HIV medicine, 2005-05, Vol.6 (3), p.170-178</ispartof><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c3975-2734979a65989b308d2a135f945a68191ed4b77eb5667f17efaf9339e0e9a5b23</citedby><cites>FETCH-LOGICAL-c3975-2734979a65989b308d2a135f945a68191ed4b77eb5667f17efaf9339e0e9a5b23</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://onlinelibrary.wiley.com/doi/pdf/10.1111%2Fj.1468-1293.2005.00285.x$$EPDF$$P50$$Gwiley$$H</linktopdf><linktohtml>$$Uhttps://onlinelibrary.wiley.com/doi/full/10.1111%2Fj.1468-1293.2005.00285.x$$EHTML$$P50$$Gwiley$$H</linktohtml><link.rule.ids>315,781,785,1418,1434,27929,27930,45579,45580,46414,46838</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/15876283$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Donnelly, CA</creatorcontrib><creatorcontrib>Bartley, LM</creatorcontrib><creatorcontrib>Ghani, AC</creatorcontrib><creatorcontrib>Le Fevre, AM</creatorcontrib><creatorcontrib>Kwong, GP</creatorcontrib><creatorcontrib>Cowling, BJ</creatorcontrib><creatorcontrib>Van Sighem, AI</creatorcontrib><creatorcontrib>De Wolf, F</creatorcontrib><creatorcontrib>Rode, RA</creatorcontrib><creatorcontrib>Anderson, RM</creatorcontrib><title>Gender difference in HIV‐1 RNA viral loads</title><title>HIV medicine</title><addtitle>HIV Med</addtitle><description>Objectives
To test and characterize the dependence of viral load on gender in different countries and racial groups as a function of CD4 T‐cell count.
Methods
Plasma viral load data were analysed for >30 000 HIV‐infected patients attending clinics in the USA [HIV Insight™ (Cerner Corporation, Vienna, VA, USA) and Plum Data Mining LLC (East Meadow, NY, USA) databases] and the Netherlands (Athena database; HIV Monitoring Foundation, Amsterdam, Netherlands). Log‐normal regression models were used to test for an effect of gender on viral load while adjusting for covariates and allowing the effect to depend on CD4 T‐cell count. Sensitivity analyses were performed to test the robustness of conclusions to assumptions regarding viral loads below the lower limit of quantification (LLOQ).
Results
After adjusting for covariates, women had (nonsignificantly) lower viral loads than men (HIV Insight™:−0.053 log10 HIV‐1 RNA copies/mL, P=0.202; Athena: −0.005 log10 copies/mL, P=0.667; Plum:−0.072 log10 copies/mL, P=0.273). However, further investigation revealed that the gender effect depended on CD4 T‐cell count. Women had consistently higher viral loads than men when CD4 T‐cell counts were at most 50 cells/μL, and consistently lower viral loads than men when CD4 T‐cell counts were greater than 350 cells/μL. These effects were remarkably consistent when estimated independently for the racial groups with sufficient data available in the HIV Insight™ and Plum databases.
Conclusions
The consistent relationship between gender‐related differences in viral load and CD4 T‐cell count demonstrated here explains the diverse findings previously published.</description><subject>Adult</subject><subject>CD4 Lymphocyte Count</subject><subject>CD4 T‐cell count</subject><subject>Data Collection</subject><subject>Databases, Factual</subject><subject>Female</subject><subject>gender</subject><subject>HIV</subject><subject>HIV Infections - immunology</subject><subject>HIV Infections - virology</subject><subject>HIV-1</subject><subject>Human immunodeficiency virus 1</subject><subject>Humans</subject><subject>Male</subject><subject>Regression Analysis</subject><subject>Sex Distribution</subject><subject>Statistics, Nonparametric</subject><subject>United States</subject><subject>Viral Load</subject><issn>1464-2662</issn><issn>1468-1293</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2005</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNqNkM1Kw0AQxxdRbK2-guTkycT9yH6Bl1K0LRQFUa_LJpmFlDSpu1bbm4_gM_okJm3Ro85lBub3n4EfQhHBCWnrap6QVKiYUM0SijFPMKaKJ-sD1P9ZHG7nNKZC0B46CWGOMZFM42PUI1xJQRXro8sx1AX4qCidAw91DlFZR5Pp89fHJ4ke7obRW-ltFVWNLcIpOnK2CnC27wP0dHvzOJrEs_vxdDScxTnTksdUslRLbQXXSmcMq4JawrjTKbdCEU2gSDMpIeNCSEckOOs0YxowaMszygboYnd36ZuXFYRXsyhDDlVla2hWwQipMONK_QkSqVIqUtyCagfmvgnBgzNLXy6s3xiCTafUzE1nznTmTKfUbJWadRs93_9YZQsofoN7hy1wvQPeywo2_z5sWsntwL4BBTyB2w</recordid><startdate>200505</startdate><enddate>200505</enddate><creator>Donnelly, CA</creator><creator>Bartley, LM</creator><creator>Ghani, AC</creator><creator>Le Fevre, AM</creator><creator>Kwong, GP</creator><creator>Cowling, BJ</creator><creator>Van Sighem, AI</creator><creator>De Wolf, F</creator><creator>Rode, RA</creator><creator>Anderson, RM</creator><general>Blackwell Science Ltd</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7U9</scope><scope>H94</scope><scope>7X8</scope></search><sort><creationdate>200505</creationdate><title>Gender difference in HIV‐1 RNA viral loads</title><author>Donnelly, CA ; Bartley, LM ; Ghani, AC ; Le Fevre, AM ; Kwong, GP ; Cowling, BJ ; Van Sighem, AI ; De Wolf, F ; Rode, RA ; Anderson, RM</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c3975-2734979a65989b308d2a135f945a68191ed4b77eb5667f17efaf9339e0e9a5b23</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2005</creationdate><topic>Adult</topic><topic>CD4 Lymphocyte Count</topic><topic>CD4 T‐cell count</topic><topic>Data Collection</topic><topic>Databases, Factual</topic><topic>Female</topic><topic>gender</topic><topic>HIV</topic><topic>HIV Infections - immunology</topic><topic>HIV Infections - virology</topic><topic>HIV-1</topic><topic>Human immunodeficiency virus 1</topic><topic>Humans</topic><topic>Male</topic><topic>Regression Analysis</topic><topic>Sex Distribution</topic><topic>Statistics, Nonparametric</topic><topic>United States</topic><topic>Viral Load</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Donnelly, CA</creatorcontrib><creatorcontrib>Bartley, LM</creatorcontrib><creatorcontrib>Ghani, AC</creatorcontrib><creatorcontrib>Le Fevre, AM</creatorcontrib><creatorcontrib>Kwong, GP</creatorcontrib><creatorcontrib>Cowling, BJ</creatorcontrib><creatorcontrib>Van Sighem, AI</creatorcontrib><creatorcontrib>De Wolf, F</creatorcontrib><creatorcontrib>Rode, RA</creatorcontrib><creatorcontrib>Anderson, RM</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Virology and AIDS Abstracts</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>MEDLINE - Academic</collection><jtitle>HIV medicine</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Donnelly, CA</au><au>Bartley, LM</au><au>Ghani, AC</au><au>Le Fevre, AM</au><au>Kwong, GP</au><au>Cowling, BJ</au><au>Van Sighem, AI</au><au>De Wolf, F</au><au>Rode, RA</au><au>Anderson, RM</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Gender difference in HIV‐1 RNA viral loads</atitle><jtitle>HIV medicine</jtitle><addtitle>HIV Med</addtitle><date>2005-05</date><risdate>2005</risdate><volume>6</volume><issue>3</issue><spage>170</spage><epage>178</epage><pages>170-178</pages><issn>1464-2662</issn><eissn>1468-1293</eissn><abstract>Objectives
To test and characterize the dependence of viral load on gender in different countries and racial groups as a function of CD4 T‐cell count.
Methods
Plasma viral load data were analysed for >30 000 HIV‐infected patients attending clinics in the USA [HIV Insight™ (Cerner Corporation, Vienna, VA, USA) and Plum Data Mining LLC (East Meadow, NY, USA) databases] and the Netherlands (Athena database; HIV Monitoring Foundation, Amsterdam, Netherlands). Log‐normal regression models were used to test for an effect of gender on viral load while adjusting for covariates and allowing the effect to depend on CD4 T‐cell count. Sensitivity analyses were performed to test the robustness of conclusions to assumptions regarding viral loads below the lower limit of quantification (LLOQ).
Results
After adjusting for covariates, women had (nonsignificantly) lower viral loads than men (HIV Insight™:−0.053 log10 HIV‐1 RNA copies/mL, P=0.202; Athena: −0.005 log10 copies/mL, P=0.667; Plum:−0.072 log10 copies/mL, P=0.273). However, further investigation revealed that the gender effect depended on CD4 T‐cell count. Women had consistently higher viral loads than men when CD4 T‐cell counts were at most 50 cells/μL, and consistently lower viral loads than men when CD4 T‐cell counts were greater than 350 cells/μL. These effects were remarkably consistent when estimated independently for the racial groups with sufficient data available in the HIV Insight™ and Plum databases.
Conclusions
The consistent relationship between gender‐related differences in viral load and CD4 T‐cell count demonstrated here explains the diverse findings previously published.</abstract><cop>Oxford, UK</cop><pub>Blackwell Science Ltd</pub><pmid>15876283</pmid><doi>10.1111/j.1468-1293.2005.00285.x</doi><tpages>9</tpages></addata></record> |
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source | Wiley Online Library - AutoHoldings Journals; MEDLINE; IngentaConnect Free/Open Access Journals; EZB-FREE-00999 freely available EZB journals; Wiley Online Library (Open Access Collection) |
subjects | Adult CD4 Lymphocyte Count CD4 T‐cell count Data Collection Databases, Factual Female gender HIV HIV Infections - immunology HIV Infections - virology HIV-1 Human immunodeficiency virus 1 Humans Male Regression Analysis Sex Distribution Statistics, Nonparametric United States Viral Load |
title | Gender difference in HIV‐1 RNA viral loads |
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