The impact of monitoring HIV patients prior to treatment in resource-poor settings : insights from mathematical modelling
The roll-out of antiretroviral treatment (ART) in developing countries concentrates on finding patients currently in need, but over time many HIV-infected individuals will be identified who will require treatment in the future. We investigated the potential influence of alternative patient managemen...
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description | The roll-out of antiretroviral treatment (ART) in developing countries concentrates on finding patients currently in need, but over time many HIV-infected individuals will be identified who will require treatment in the future. We investigated the potential influence of alternative patient management and ART initiation strategies on the impact of ART programmes in sub-Saharan Africa.
We developed a stochastic mathematical model representing disease progression, diagnosis, clinical monitoring, and survival in a cohort of 1,000 hypothetical HIV-infected individuals in Africa. If individuals primarily enter ART programmes when symptomatic, the model predicts that only 25% will start treatment and, on average, 6 life-years will be saved per person treated. If individuals are recruited to programmes while still healthy and are frequently monitored, and CD4(+) cell counts are used to help decide when to initiate ART, three times as many are expected to be treated, and average life-years saved among those treated increases to 15. The impact of programmes can be improved further by performing a second CD4(+) cell count when the initial value is close to the threshold for starting treatment, maintaining high patient follow-up rates, and prioritising monitoring the oldest (> or = 35 y) and most immune-suppressed patients (CD4(+) cell count < or = 350). Initiating ART at higher CD4(+) cell counts than WHO recommends leads to more life-years saved, but disproportionately more years spent on ART.
The overall impact of ART programmes will be limited if rates of diagnosis are low and individuals enter care too late. Frequently monitoring individuals at all stages of HIV infection and using CD4 cell count information to determine when to start treatment can maximise the impact of ART. |
doi_str_mv | 10.1371/journal.pmed.0050053 |
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We developed a stochastic mathematical model representing disease progression, diagnosis, clinical monitoring, and survival in a cohort of 1,000 hypothetical HIV-infected individuals in Africa. If individuals primarily enter ART programmes when symptomatic, the model predicts that only 25% will start treatment and, on average, 6 life-years will be saved per person treated. If individuals are recruited to programmes while still healthy and are frequently monitored, and CD4(+) cell counts are used to help decide when to initiate ART, three times as many are expected to be treated, and average life-years saved among those treated increases to 15. The impact of programmes can be improved further by performing a second CD4(+) cell count when the initial value is close to the threshold for starting treatment, maintaining high patient follow-up rates, and prioritising monitoring the oldest (> or = 35 y) and most immune-suppressed patients (CD4(+) cell count < or = 350). Initiating ART at higher CD4(+) cell counts than WHO recommends leads to more life-years saved, but disproportionately more years spent on ART.
The overall impact of ART programmes will be limited if rates of diagnosis are low and individuals enter care too late. Frequently monitoring individuals at all stages of HIV infection and using CD4 cell count information to determine when to start treatment can maximise the impact of ART.</description><identifier>ISSN: 1549-1277</identifier><identifier>ISSN: 1549-1676</identifier><identifier>EISSN: 1549-1676</identifier><identifier>DOI: 10.1371/journal.pmed.0050053</identifier><identifier>PMID: 18336064</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Acquired immune deficiency syndrome ; Adult ; AIDS ; Anti-Retroviral Agents - administration & dosage ; Bacterial infections ; Biological and medical sciences ; CD4 Lymphocyte Count ; Developing countries ; Disease ; Disease Progression ; Evidence-Based Healthcare ; Global health ; Health care ; Health Policy ; HIV ; HIV Infection/AIDS ; HIV Infections - drug therapy ; Human immunodeficiency virus ; Humans ; Immune system ; Infections ; Infectious Diseases ; International organizations ; LDCs ; Mathematical models ; Medical sciences ; Medicine in Developing Countries ; Miscellaneous ; Models, Theoretical ; Patients ; Prevention and actions ; Public Health and Epidemiology ; Public health. Hygiene ; Public health. Hygiene-occupational medicine ; Resource Allocation ; Stochastic Processes</subject><ispartof>PLoS medicine, 2008-03, Vol.5 (3), p.403-412</ispartof><rights>COPYRIGHT 2008 Public Library of Science</rights><rights>2008 Hallett et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited: Hallett TB, Gregson S, Dube S, Garnett GP (2008) The Impact of Monitoring HIV Patients Prior to Treatment in Resource-Poor Settings: Insights from Mathematical Modelling. PLoS Med 5(3): e53. doi:10.1371/journal.pmed.0050053</rights><rights>2008 Hallett et al. 2008</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c792t-ce712734676cad0d86aa20b979f793b865f521b94322d3ee32eb6709e2f967ea3</citedby><cites>FETCH-LOGICAL-c792t-ce712734676cad0d86aa20b979f793b865f521b94322d3ee32eb6709e2f967ea3</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/PMC2265759/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC2265759/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,2095,2914,23846,27903,27904,53769,53771,79346,79347</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=20524142$$DView record in Pascal Francis$$Hfree_for_read</backlink><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/18336064$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><contributor>Salomon, Joshua A</contributor><creatorcontrib>HALLETT, T.B</creatorcontrib><creatorcontrib>GREGSON, S</creatorcontrib><creatorcontrib>GARNETT, G.P</creatorcontrib><title>The impact of monitoring HIV patients prior to treatment in resource-poor settings : insights from mathematical modelling</title><title>PLoS medicine</title><addtitle>PLoS Med</addtitle><description>The roll-out of antiretroviral treatment (ART) in developing countries concentrates on finding patients currently in need, but over time many HIV-infected individuals will be identified who will require treatment in the future. We investigated the potential influence of alternative patient management and ART initiation strategies on the impact of ART programmes in sub-Saharan Africa.
We developed a stochastic mathematical model representing disease progression, diagnosis, clinical monitoring, and survival in a cohort of 1,000 hypothetical HIV-infected individuals in Africa. If individuals primarily enter ART programmes when symptomatic, the model predicts that only 25% will start treatment and, on average, 6 life-years will be saved per person treated. If individuals are recruited to programmes while still healthy and are frequently monitored, and CD4(+) cell counts are used to help decide when to initiate ART, three times as many are expected to be treated, and average life-years saved among those treated increases to 15. The impact of programmes can be improved further by performing a second CD4(+) cell count when the initial value is close to the threshold for starting treatment, maintaining high patient follow-up rates, and prioritising monitoring the oldest (> or = 35 y) and most immune-suppressed patients (CD4(+) cell count < or = 350). Initiating ART at higher CD4(+) cell counts than WHO recommends leads to more life-years saved, but disproportionately more years spent on ART.
The overall impact of ART programmes will be limited if rates of diagnosis are low and individuals enter care too late. Frequently monitoring individuals at all stages of HIV infection and using CD4 cell count information to determine when to start treatment can maximise the impact of ART.</description><subject>Acquired immune deficiency syndrome</subject><subject>Adult</subject><subject>AIDS</subject><subject>Anti-Retroviral Agents - administration & dosage</subject><subject>Bacterial infections</subject><subject>Biological and medical sciences</subject><subject>CD4 Lymphocyte Count</subject><subject>Developing countries</subject><subject>Disease</subject><subject>Disease Progression</subject><subject>Evidence-Based Healthcare</subject><subject>Global health</subject><subject>Health care</subject><subject>Health Policy</subject><subject>HIV</subject><subject>HIV Infection/AIDS</subject><subject>HIV Infections - drug therapy</subject><subject>Human immunodeficiency virus</subject><subject>Humans</subject><subject>Immune system</subject><subject>Infections</subject><subject>Infectious Diseases</subject><subject>International organizations</subject><subject>LDCs</subject><subject>Mathematical models</subject><subject>Medical sciences</subject><subject>Medicine in Developing Countries</subject><subject>Miscellaneous</subject><subject>Models, Theoretical</subject><subject>Patients</subject><subject>Prevention and actions</subject><subject>Public Health and Epidemiology</subject><subject>Public health. 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We investigated the potential influence of alternative patient management and ART initiation strategies on the impact of ART programmes in sub-Saharan Africa.
We developed a stochastic mathematical model representing disease progression, diagnosis, clinical monitoring, and survival in a cohort of 1,000 hypothetical HIV-infected individuals in Africa. If individuals primarily enter ART programmes when symptomatic, the model predicts that only 25% will start treatment and, on average, 6 life-years will be saved per person treated. If individuals are recruited to programmes while still healthy and are frequently monitored, and CD4(+) cell counts are used to help decide when to initiate ART, three times as many are expected to be treated, and average life-years saved among those treated increases to 15. The impact of programmes can be improved further by performing a second CD4(+) cell count when the initial value is close to the threshold for starting treatment, maintaining high patient follow-up rates, and prioritising monitoring the oldest (> or = 35 y) and most immune-suppressed patients (CD4(+) cell count < or = 350). Initiating ART at higher CD4(+) cell counts than WHO recommends leads to more life-years saved, but disproportionately more years spent on ART.
The overall impact of ART programmes will be limited if rates of diagnosis are low and individuals enter care too late. Frequently monitoring individuals at all stages of HIV infection and using CD4 cell count information to determine when to start treatment can maximise the impact of ART.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>18336064</pmid><doi>10.1371/journal.pmed.0050053</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Acquired immune deficiency syndrome Adult AIDS Anti-Retroviral Agents - administration & dosage Bacterial infections Biological and medical sciences CD4 Lymphocyte Count Developing countries Disease Disease Progression Evidence-Based Healthcare Global health Health care Health Policy HIV HIV Infection/AIDS HIV Infections - drug therapy Human immunodeficiency virus Humans Immune system Infections Infectious Diseases International organizations LDCs Mathematical models Medical sciences Medicine in Developing Countries Miscellaneous Models, Theoretical Patients Prevention and actions Public Health and Epidemiology Public health. Hygiene Public health. Hygiene-occupational medicine Resource Allocation Stochastic Processes |
title | The impact of monitoring HIV patients prior to treatment in resource-poor settings : insights from mathematical modelling |
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