Incidence and predictors of first line antiretroviral regimen modification in western Kenya
Limited antiretroviral treatment regimens in resource-limited settings require long-term sustainability of patients on the few available options. We evaluated the incidence and predictors of combined antiretroviral treatment (cART) modifications, in an outpatient cohort of 955 patients who initiated...
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| Veröffentlicht in: | PloS one 2014-04, Vol.9 (4), p.e93106-e93106 |
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| creator | Inzaule, Seth Otieno, Juliana Kalyango, Joan Nafisa, Lillian Kabugo, Charles Nalusiba, Josephine Kwaro, Daniel Zeh, Clement Karamagi, Charles |
| description | Limited antiretroviral treatment regimens in resource-limited settings require long-term sustainability of patients on the few available options. We evaluated the incidence and predictors of combined antiretroviral treatment (cART) modifications, in an outpatient cohort of 955 patients who initiated cART between January 2009 and January 2011 in western Kenya.
cART modification was defined as either first time single drug substitution or switch. Incidence rates were determined by Poisson regression and risk factor analysis assessed using multivariate Cox regression modeling.
Over a median follow-up period of 10.7 months, 178 (18.7%) patients modified regimens (incidence rate (IR); 18.6 per 100 person years [95% CI: 16.2-21.8]). Toxicity was the most common cited reason (66.3%). In adjusted multivariate Cox piecewise regression model, WHO disease stage III/IV (aHR; 1.82, 95%CI: 1.25-2.66), stavudine (d4T) use (aHR; 2.21 95%CI: 1.49-3.30) and increase in age (aHR; 1.02, 95%CI: 1.0-1.04) were associated with increased risk of treatment modification within the first year post-cART. Zidovudine (AZT) and tenofovir (TDF) use had a reduced risk for modification (aHR; 0.60 95%CI: 0.38-0.96 and aHR; 0.51 95%CI: 0.29-0.91 respectively). Beyond one year of treatment, d4T use (aHR; 2.75, 95% CI: 1.25-6.05), baseline CD4 counts ≤350 cells/mm3 (aHR; 2.45, 95%CI: 1.14-5.26), increase in age (aHR; 1.05 95%CI: 1.02-1.07) and high baseline weight >60kg aHR; 2.69 95% CI: 1.58-4.59) were associated with risk of cART modification.
Early treatment initiation at higher CD4 counts and avoiding d4T use may reduce treatment modification and subsequently improve sustainability of patients on the available limited options. |
| doi_str_mv | 10.1371/journal.pone.0093106 |
| format | Article |
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cART modification was defined as either first time single drug substitution or switch. Incidence rates were determined by Poisson regression and risk factor analysis assessed using multivariate Cox regression modeling.
Over a median follow-up period of 10.7 months, 178 (18.7%) patients modified regimens (incidence rate (IR); 18.6 per 100 person years [95% CI: 16.2-21.8]). Toxicity was the most common cited reason (66.3%). In adjusted multivariate Cox piecewise regression model, WHO disease stage III/IV (aHR; 1.82, 95%CI: 1.25-2.66), stavudine (d4T) use (aHR; 2.21 95%CI: 1.49-3.30) and increase in age (aHR; 1.02, 95%CI: 1.0-1.04) were associated with increased risk of treatment modification within the first year post-cART. Zidovudine (AZT) and tenofovir (TDF) use had a reduced risk for modification (aHR; 0.60 95%CI: 0.38-0.96 and aHR; 0.51 95%CI: 0.29-0.91 respectively). Beyond one year of treatment, d4T use (aHR; 2.75, 95% CI: 1.25-6.05), baseline CD4 counts ≤350 cells/mm3 (aHR; 2.45, 95%CI: 1.14-5.26), increase in age (aHR; 1.05 95%CI: 1.02-1.07) and high baseline weight >60kg aHR; 2.69 95% CI: 1.58-4.59) were associated with risk of cART modification.
Early treatment initiation at higher CD4 counts and avoiding d4T use may reduce treatment modification and subsequently improve sustainability of patients on the available limited options.</description><identifier>ISSN: 1932-6203</identifier><identifier>EISSN: 1932-6203</identifier><identifier>DOI: 10.1371/journal.pone.0093106</identifier><identifier>PMID: 24695108</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acquired immune deficiency syndrome ; Adult ; Age Factors ; AIDS ; Analysis ; Anti-Retroviral Agents - administration & dosage ; Antiretroviral agents ; Antiretroviral drugs ; Antiviral agents ; Biology and Life Sciences ; CD4 antigen ; CD4 Lymphocyte Count ; Disease control ; Disease prevention ; Dosage and administration ; Drug dosages ; Drug therapy ; Drug Therapy, Combination - methods ; Epidemiology ; Factor analysis ; Female ; Follow-Up Studies ; Health aspects ; Highly active antiretroviral therapy ; HIV ; HIV infection ; HIV Infections - blood ; HIV Infections - drug therapy ; HIV Infections - epidemiology ; HIV Infections - immunology ; Hospitals ; Human immunodeficiency virus ; Humans ; Immunology ; Incidence ; Infections ; Kenya ; Male ; Medical prognosis ; Medical research ; Medical schools ; Medicine and health sciences ; Patients ; Poisson density functions ; Regression analysis ; Regression models ; Research and Analysis Methods ; Retrospective Studies ; Risk analysis ; Risk Factors ; Statistical analysis ; Stavudine ; Sustainability ; Tenofovir ; Toxicity ; Zidovudine</subject><ispartof>PloS one, 2014-04, Vol.9 (4), p.e93106-e93106</ispartof><rights>COPYRIGHT 2014 Public Library of Science</rights><rights>2014 Inzaule et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2014 Inzaule et al 2014 Inzaule et al</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c692t-9a18007d8440c5b36b54fe036aa72ab66afd35d9232b9fe732155deb9476d4c93</citedby><cites>FETCH-LOGICAL-c692t-9a18007d8440c5b36b54fe036aa72ab66afd35d9232b9fe732155deb9476d4c93</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3973699/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3973699/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2096,2915,23847,27903,27904,53769,53771,79346,79347</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/24695108$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Sued, Omar</contributor><creatorcontrib>Inzaule, Seth</creatorcontrib><creatorcontrib>Otieno, Juliana</creatorcontrib><creatorcontrib>Kalyango, Joan</creatorcontrib><creatorcontrib>Nafisa, Lillian</creatorcontrib><creatorcontrib>Kabugo, Charles</creatorcontrib><creatorcontrib>Nalusiba, Josephine</creatorcontrib><creatorcontrib>Kwaro, Daniel</creatorcontrib><creatorcontrib>Zeh, Clement</creatorcontrib><creatorcontrib>Karamagi, Charles</creatorcontrib><title>Incidence and predictors of first line antiretroviral regimen modification in western Kenya</title><title>PloS one</title><addtitle>PLoS One</addtitle><description>Limited antiretroviral treatment regimens in resource-limited settings require long-term sustainability of patients on the few available options. We evaluated the incidence and predictors of combined antiretroviral treatment (cART) modifications, in an outpatient cohort of 955 patients who initiated cART between January 2009 and January 2011 in western Kenya.
cART modification was defined as either first time single drug substitution or switch. Incidence rates were determined by Poisson regression and risk factor analysis assessed using multivariate Cox regression modeling.
Over a median follow-up period of 10.7 months, 178 (18.7%) patients modified regimens (incidence rate (IR); 18.6 per 100 person years [95% CI: 16.2-21.8]). Toxicity was the most common cited reason (66.3%). In adjusted multivariate Cox piecewise regression model, WHO disease stage III/IV (aHR; 1.82, 95%CI: 1.25-2.66), stavudine (d4T) use (aHR; 2.21 95%CI: 1.49-3.30) and increase in age (aHR; 1.02, 95%CI: 1.0-1.04) were associated with increased risk of treatment modification within the first year post-cART. Zidovudine (AZT) and tenofovir (TDF) use had a reduced risk for modification (aHR; 0.60 95%CI: 0.38-0.96 and aHR; 0.51 95%CI: 0.29-0.91 respectively). Beyond one year of treatment, d4T use (aHR; 2.75, 95% CI: 1.25-6.05), baseline CD4 counts ≤350 cells/mm3 (aHR; 2.45, 95%CI: 1.14-5.26), increase in age (aHR; 1.05 95%CI: 1.02-1.07) and high baseline weight >60kg aHR; 2.69 95% CI: 1.58-4.59) were associated with risk of cART modification.
Early treatment initiation at higher CD4 counts and avoiding d4T use may reduce treatment modification and subsequently improve sustainability of patients on the available limited options.</description><subject>Acquired immune deficiency syndrome</subject><subject>Adult</subject><subject>Age Factors</subject><subject>AIDS</subject><subject>Analysis</subject><subject>Anti-Retroviral Agents - administration & dosage</subject><subject>Antiretroviral agents</subject><subject>Antiretroviral drugs</subject><subject>Antiviral agents</subject><subject>Biology and Life Sciences</subject><subject>CD4 antigen</subject><subject>CD4 Lymphocyte Count</subject><subject>Disease control</subject><subject>Disease prevention</subject><subject>Dosage and administration</subject><subject>Drug dosages</subject><subject>Drug therapy</subject><subject>Drug Therapy, Combination - methods</subject><subject>Epidemiology</subject><subject>Factor analysis</subject><subject>Female</subject><subject>Follow-Up Studies</subject><subject>Health aspects</subject><subject>Highly active antiretroviral therapy</subject><subject>HIV</subject><subject>HIV infection</subject><subject>HIV Infections - blood</subject><subject>HIV Infections - drug therapy</subject><subject>HIV Infections - epidemiology</subject><subject>HIV Infections - immunology</subject><subject>Hospitals</subject><subject>Human immunodeficiency virus</subject><subject>Humans</subject><subject>Immunology</subject><subject>Incidence</subject><subject>Infections</subject><subject>Kenya</subject><subject>Male</subject><subject>Medical prognosis</subject><subject>Medical research</subject><subject>Medical schools</subject><subject>Medicine and health sciences</subject><subject>Patients</subject><subject>Poisson density functions</subject><subject>Regression analysis</subject><subject>Regression models</subject><subject>Research and Analysis Methods</subject><subject>Retrospective Studies</subject><subject>Risk 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and predictors of first line antiretroviral regimen modification in western Kenya</title><author>Inzaule, Seth ; Otieno, Juliana ; Kalyango, Joan ; Nafisa, Lillian ; Kabugo, Charles ; Nalusiba, Josephine ; Kwaro, Daniel ; Zeh, Clement ; Karamagi, Charles</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c692t-9a18007d8440c5b36b54fe036aa72ab66afd35d9232b9fe732155deb9476d4c93</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Acquired immune deficiency syndrome</topic><topic>Adult</topic><topic>Age Factors</topic><topic>AIDS</topic><topic>Analysis</topic><topic>Anti-Retroviral Agents - administration & dosage</topic><topic>Antiretroviral agents</topic><topic>Antiretroviral drugs</topic><topic>Antiviral agents</topic><topic>Biology and Life Sciences</topic><topic>CD4 antigen</topic><topic>CD4 Lymphocyte Count</topic><topic>Disease control</topic><topic>Disease 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analysis</topic><topic>Regression models</topic><topic>Research and Analysis Methods</topic><topic>Retrospective Studies</topic><topic>Risk analysis</topic><topic>Risk Factors</topic><topic>Statistical analysis</topic><topic>Stavudine</topic><topic>Sustainability</topic><topic>Tenofovir</topic><topic>Toxicity</topic><topic>Zidovudine</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Inzaule, Seth</creatorcontrib><creatorcontrib>Otieno, Juliana</creatorcontrib><creatorcontrib>Kalyango, Joan</creatorcontrib><creatorcontrib>Nafisa, Lillian</creatorcontrib><creatorcontrib>Kabugo, Charles</creatorcontrib><creatorcontrib>Nalusiba, Josephine</creatorcontrib><creatorcontrib>Kwaro, Daniel</creatorcontrib><creatorcontrib>Zeh, Clement</creatorcontrib><creatorcontrib>Karamagi, Charles</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE 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Omar</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Incidence and predictors of first line antiretroviral regimen modification in western Kenya</atitle><jtitle>PloS one</jtitle><addtitle>PLoS One</addtitle><date>2014-04-01</date><risdate>2014</risdate><volume>9</volume><issue>4</issue><spage>e93106</spage><epage>e93106</epage><pages>e93106-e93106</pages><issn>1932-6203</issn><eissn>1932-6203</eissn><abstract>Limited antiretroviral treatment regimens in resource-limited settings require long-term sustainability of patients on the few available options. We evaluated the incidence and predictors of combined antiretroviral treatment (cART) modifications, in an outpatient cohort of 955 patients who initiated cART between January 2009 and January 2011 in western Kenya.
cART modification was defined as either first time single drug substitution or switch. Incidence rates were determined by Poisson regression and risk factor analysis assessed using multivariate Cox regression modeling.
Over a median follow-up period of 10.7 months, 178 (18.7%) patients modified regimens (incidence rate (IR); 18.6 per 100 person years [95% CI: 16.2-21.8]). Toxicity was the most common cited reason (66.3%). In adjusted multivariate Cox piecewise regression model, WHO disease stage III/IV (aHR; 1.82, 95%CI: 1.25-2.66), stavudine (d4T) use (aHR; 2.21 95%CI: 1.49-3.30) and increase in age (aHR; 1.02, 95%CI: 1.0-1.04) were associated with increased risk of treatment modification within the first year post-cART. Zidovudine (AZT) and tenofovir (TDF) use had a reduced risk for modification (aHR; 0.60 95%CI: 0.38-0.96 and aHR; 0.51 95%CI: 0.29-0.91 respectively). Beyond one year of treatment, d4T use (aHR; 2.75, 95% CI: 1.25-6.05), baseline CD4 counts ≤350 cells/mm3 (aHR; 2.45, 95%CI: 1.14-5.26), increase in age (aHR; 1.05 95%CI: 1.02-1.07) and high baseline weight >60kg aHR; 2.69 95% CI: 1.58-4.59) were associated with risk of cART modification.
Early treatment initiation at higher CD4 counts and avoiding d4T use may reduce treatment modification and subsequently improve sustainability of patients on the available limited options.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24695108</pmid><doi>10.1371/journal.pone.0093106</doi><oa>free_for_read</oa></addata></record> |
| fulltext | fulltext |
| identifier | ISSN: 1932-6203 |
| ispartof | PloS one, 2014-04, Vol.9 (4), p.e93106-e93106 |
| issn | 1932-6203 1932-6203 |
| language | eng |
| recordid | cdi_plos_journals_1512317476 |
| source | MEDLINE; DOAJ Directory of Open Access Journals; EZB-FREE-00999 freely available EZB journals; PubMed Central; Free Full-Text Journals in Chemistry; Public Library of Science (PLoS) |
| subjects | Acquired immune deficiency syndrome Adult Age Factors AIDS Analysis Anti-Retroviral Agents - administration & dosage Antiretroviral agents Antiretroviral drugs Antiviral agents Biology and Life Sciences CD4 antigen CD4 Lymphocyte Count Disease control Disease prevention Dosage and administration Drug dosages Drug therapy Drug Therapy, Combination - methods Epidemiology Factor analysis Female Follow-Up Studies Health aspects Highly active antiretroviral therapy HIV HIV infection HIV Infections - blood HIV Infections - drug therapy HIV Infections - epidemiology HIV Infections - immunology Hospitals Human immunodeficiency virus Humans Immunology Incidence Infections Kenya Male Medical prognosis Medical research Medical schools Medicine and health sciences Patients Poisson density functions Regression analysis Regression models Research and Analysis Methods Retrospective Studies Risk analysis Risk Factors Statistical analysis Stavudine Sustainability Tenofovir Toxicity Zidovudine |
| title | Incidence and predictors of first line antiretroviral regimen modification in western Kenya |
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