The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD).

Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips. Ausführliche Beschreibung

Gespeichert in:

Autor*in:	Rupa Kanapathipillai [verfasserIn] Hamish McManus [verfasserIn] Adeeba Kamarulzaman [verfasserIn] Poh Lian Lim [verfasserIn] David J Templeton [verfasserIn] Matthew Law [verfasserIn] Ian Woolley [verfasserIn]

Format:	E-Artikel
Sprache:	Englisch

Erschienen:	2014

Übergeordnetes Werk:	In: PLoS ONE - Public Library of Science (PLoS), 2007, 9(2014), 2, p e86122
Übergeordnetes Werk:	volume:9 ; year:2014 ; number:2, p e86122

Links:	Link aufrufen Link aufrufen Link aufrufen Journal toc

DOI / URN:	10.1371/journal.pone.0086122

Katalog-ID:	DOAJ054627494

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245	1	4	\|a The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD).
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520			\|a Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips.
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allfields	10.1371/journal.pone.0086122 doi (DE-627)DOAJ054627494 (DE-599)DOAJf5764fb91a4043c8b28c91d72c5e9aa1 DE-627 ger DE-627 rakwb eng Rupa Kanapathipillai verfasserin aut The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD). 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips. Medicine R Science Q Hamish McManus verfasserin aut Adeeba Kamarulzaman verfasserin aut Poh Lian Lim verfasserin aut David J Templeton verfasserin aut Matthew Law verfasserin aut Ian Woolley verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 9(2014), 2, p e86122 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:9 year:2014 number:2, p e86122 https://doi.org/10.1371/journal.pone.0086122 kostenfrei https://doaj.org/article/f5764fb91a4043c8b28c91d72c5e9aa1 kostenfrei http://europepmc.org/articles/PMC3917848?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2014 2, p e86122
spelling	10.1371/journal.pone.0086122 doi (DE-627)DOAJ054627494 (DE-599)DOAJf5764fb91a4043c8b28c91d72c5e9aa1 DE-627 ger DE-627 rakwb eng Rupa Kanapathipillai verfasserin aut The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD). 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips. Medicine R Science Q Hamish McManus verfasserin aut Adeeba Kamarulzaman verfasserin aut Poh Lian Lim verfasserin aut David J Templeton verfasserin aut Matthew Law verfasserin aut Ian Woolley verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 9(2014), 2, p e86122 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:9 year:2014 number:2, p e86122 https://doi.org/10.1371/journal.pone.0086122 kostenfrei https://doaj.org/article/f5764fb91a4043c8b28c91d72c5e9aa1 kostenfrei http://europepmc.org/articles/PMC3917848?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2014 2, p e86122
allfields_unstemmed	10.1371/journal.pone.0086122 doi (DE-627)DOAJ054627494 (DE-599)DOAJf5764fb91a4043c8b28c91d72c5e9aa1 DE-627 ger DE-627 rakwb eng Rupa Kanapathipillai verfasserin aut The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD). 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips. Medicine R Science Q Hamish McManus verfasserin aut Adeeba Kamarulzaman verfasserin aut Poh Lian Lim verfasserin aut David J Templeton verfasserin aut Matthew Law verfasserin aut Ian Woolley verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 9(2014), 2, p e86122 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:9 year:2014 number:2, p e86122 https://doi.org/10.1371/journal.pone.0086122 kostenfrei https://doaj.org/article/f5764fb91a4043c8b28c91d72c5e9aa1 kostenfrei http://europepmc.org/articles/PMC3917848?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2014 2, p e86122
allfieldsGer	10.1371/journal.pone.0086122 doi (DE-627)DOAJ054627494 (DE-599)DOAJf5764fb91a4043c8b28c91d72c5e9aa1 DE-627 ger DE-627 rakwb eng Rupa Kanapathipillai verfasserin aut The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD). 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips. Medicine R Science Q Hamish McManus verfasserin aut Adeeba Kamarulzaman verfasserin aut Poh Lian Lim verfasserin aut David J Templeton verfasserin aut Matthew Law verfasserin aut Ian Woolley verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 9(2014), 2, p e86122 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:9 year:2014 number:2, p e86122 https://doi.org/10.1371/journal.pone.0086122 kostenfrei https://doaj.org/article/f5764fb91a4043c8b28c91d72c5e9aa1 kostenfrei http://europepmc.org/articles/PMC3917848?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2014 2, p e86122
allfieldsSound	10.1371/journal.pone.0086122 doi (DE-627)DOAJ054627494 (DE-599)DOAJf5764fb91a4043c8b28c91d72c5e9aa1 DE-627 ger DE-627 rakwb eng Rupa Kanapathipillai verfasserin aut The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD). 2014 Text txt rdacontent Computermedien c rdamedia Online-Ressource cr rdacarrier Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips. Medicine R Science Q Hamish McManus verfasserin aut Adeeba Kamarulzaman verfasserin aut Poh Lian Lim verfasserin aut David J Templeton verfasserin aut Matthew Law verfasserin aut Ian Woolley verfasserin aut In PLoS ONE Public Library of Science (PLoS), 2007 9(2014), 2, p e86122 (DE-627)523574592 (DE-600)2267670-3 19326203 nnns volume:9 year:2014 number:2, p e86122 https://doi.org/10.1371/journal.pone.0086122 kostenfrei https://doaj.org/article/f5764fb91a4043c8b28c91d72c5e9aa1 kostenfrei http://europepmc.org/articles/PMC3917848?pdf=render kostenfrei https://doaj.org/toc/1932-6203 Journal toc kostenfrei GBV_USEFLAG_A SYSFLAG_A GBV_DOAJ GBV_ILN_11 GBV_ILN_20 GBV_ILN_22 GBV_ILN_23 GBV_ILN_24 GBV_ILN_31 GBV_ILN_34 GBV_ILN_39 GBV_ILN_40 GBV_ILN_60 GBV_ILN_62 GBV_ILN_63 GBV_ILN_65 GBV_ILN_69 GBV_ILN_70 GBV_ILN_73 GBV_ILN_74 GBV_ILN_95 GBV_ILN_105 GBV_ILN_110 GBV_ILN_151 GBV_ILN_161 GBV_ILN_170 GBV_ILN_171 GBV_ILN_206 GBV_ILN_213 GBV_ILN_224 GBV_ILN_230 GBV_ILN_235 GBV_ILN_285 GBV_ILN_293 GBV_ILN_370 GBV_ILN_602 GBV_ILN_702 GBV_ILN_2001 GBV_ILN_2003 GBV_ILN_2005 GBV_ILN_2006 GBV_ILN_2008 GBV_ILN_2009 GBV_ILN_2010 GBV_ILN_2011 GBV_ILN_2014 GBV_ILN_2015 GBV_ILN_2020 GBV_ILN_2021 GBV_ILN_2025 GBV_ILN_2031 GBV_ILN_2038 GBV_ILN_2044 GBV_ILN_2048 GBV_ILN_2050 GBV_ILN_2055 GBV_ILN_2056 GBV_ILN_2057 GBV_ILN_2061 GBV_ILN_2111 GBV_ILN_2113 GBV_ILN_2190 GBV_ILN_2522 GBV_ILN_4012 GBV_ILN_4037 GBV_ILN_4112 GBV_ILN_4125 GBV_ILN_4126 GBV_ILN_4249 GBV_ILN_4305 GBV_ILN_4306 GBV_ILN_4307 GBV_ILN_4313 GBV_ILN_4322 GBV_ILN_4323 GBV_ILN_4324 GBV_ILN_4325 GBV_ILN_4335 GBV_ILN_4338 GBV_ILN_4367 GBV_ILN_4700 AR 9 2014 2, p e86122
language	English
source	In PLoS ONE 9(2014), 2, p e86122 volume:9 year:2014 number:2, p e86122
sourceStr	In PLoS ONE 9(2014), 2, p e86122 volume:9 year:2014 number:2, p e86122
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container_title	PLoS ONE
authorswithroles_txt_mv	Rupa Kanapathipillai @@aut@@ Hamish McManus @@aut@@ Adeeba Kamarulzaman @@aut@@ Poh Lian Lim @@aut@@ David J Templeton @@aut@@ Matthew Law @@aut@@ Ian Woolley @@aut@@
publishDateDaySort_date	2014-01-01T00:00:00Z
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author	Rupa Kanapathipillai
spellingShingle	Rupa Kanapathipillai misc Medicine misc R misc Science misc Q The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD).
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topic_title	The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD)
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title	The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD).
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title_full	The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD)
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author_browse	Rupa Kanapathipillai Hamish McManus Adeeba Kamarulzaman Poh Lian Lim David J Templeton Matthew Law Ian Woolley
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title_sort	significance of hiv 'blips' in resource-limited settings: is it the same? analysis of the treat asia hiv observational database (tahod) and the australian hiv observational database (ahod)
title_auth	The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD).
abstract	Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips.
abstractGer	Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips.
abstract_unstemmed	Magnitude and frequency of HIV viral load blips in resource-limited settings, has not previously been assessed. This study was undertaken in a cohort from a high income country (Australia) known as AHOD (Australian HIV Observational Database) and another cohort from a mixture of Asian countries of varying national income per capita, TAHOD (TREAT Asia HIV Observational Database).Blips were defined as detectable VL (≥ 50 copies/mL) preceded and followed by undetectable VL (<50 copies/mL). Virological failure (VF) was defined as two consecutive VL ≥50 copies/ml. Cox proportional hazard models of time to first VF after entry, were developed.5040 patients (AHOD n = 2597 and TAHOD n = 2521) were included; 910 (18%) of patients experienced blips. 744 (21%) and 166 (11%) of high- and middle/low-income participants, respectively, experienced blips ever. 711 (14%) experienced blips prior to virological failure. 559 (16%) and 152 (10%) of high- and middle/low-income participants, respectively, experienced blips prior to virological failure. VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. Nonetheless, a substantial number of participants were switched to alternative regimens in the setting of blips.
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title_short	The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD).
url	https://doi.org/10.1371/journal.pone.0086122 https://doaj.org/article/f5764fb91a4043c8b28c91d72c5e9aa1 http://europepmc.org/articles/PMC3917848?pdf=render https://doaj.org/toc/1932-6203
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VL testing occurred at a median frequency of 175 and 91 days in middle/low- and high-income sites, respectively. Longer time to VF occurred in middle/low income sites, compared with high-income sites (adjusted hazards ratio (AHR) 0.41; p<0.001), adjusted for year of first cART, Hepatitis C co-infection, cART regimen, and prior blips. Prior blips were not a significant predictor of VF in univariate analysis (AHR 0.97, p = 0.82). Differing magnitudes of blips were not significant in univariate analyses as predictors of virological failure (p = 0.360 for blip 50-≤1000, p = 0.309 for blip 50-≤400 and p = 0.300 for blip 50-≤200). 209 of 866 (24%) patients were switched to an alternate regimen in the setting of a blip.Despite a lower proportion of blips occurring in low/middle-income settings, no significant difference was found between settings. 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The significance of HIV 'blips' in resource-limited settings: is it the same? analysis of the treat Asia HIV Observational Database (TAHOD) and the Australian HIV Observational Database (AHOD).

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