Forecasting Prevalence of HIV-1 Integrase Strand Transfer Inhibitor (INSTI) Drug Resistance: A Modeling Study
Antiretroviral therapy (ART) is a cornerstone of HIV-1 treatment and provides significant health benefits for patients with responsive HIV-1 strains. Integrase strand transfer inhibitors (INSTIs) are the newest class of ART. Although most HIV-1 cases are responsive, a small number are already resist...
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Veröffentlicht in: | Journal of acquired immune deficiency syndromes (1999) 2020-01, Vol.83 (1), p.65-71 |
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description | Antiretroviral therapy (ART) is a cornerstone of HIV-1 treatment and provides significant health benefits for patients with responsive HIV-1 strains. Integrase strand transfer inhibitors (INSTIs) are the newest class of ART. Although most HIV-1 cases are responsive, a small number are already resistant. Here, we forecast the prevalence of INSTI resistance amid wide-spread use.
We developed a stochastic model to simulate HIV-1 dynamics and INSTI resistance for raltegravir, elvitegravir, and dolutegravir. We forecast prevalence of INSTI resistance in adults living with HIV-1 over a 30-year period using parameter values and initial conditions that mimic HIV-1 dynamics Washington DC. We used the model to predict the amount of transmitted drug resistance (TDR) versus regimen-acquired drug resistance.
We forecast the prevalence of HIV-1 cases resistant to raltegravir as 0.41 (minimum: 0.21; maximum: 0.57), resistant to elvitegravir as 0.44 (minimum: 0.26; maximum: 0.60), and resistant to dolutegravir as 0.44 (minimum: 0.25; maximum: 0.65). Model output was greatly affected by the proportion of those living with HIV-1 on ART and the rate of converting from an INSTI-sensitive strain to an INSTI-resistant strain for chronically infected ART-experienced cases. We forecast that TDR will contribute minimally-if at all-to the overall proportion of resistant HIV-1 cases.
INSTI drug resistance has the potential to be a public health concern in the next 30 years. Although several parameters influence the predicted prevalence of INSTI drug resistance, TDR is unlikely to contribute substantially to future trends. |
doi_str_mv | 10.1097/QAI.0000000000002212 |
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We developed a stochastic model to simulate HIV-1 dynamics and INSTI resistance for raltegravir, elvitegravir, and dolutegravir. We forecast prevalence of INSTI resistance in adults living with HIV-1 over a 30-year period using parameter values and initial conditions that mimic HIV-1 dynamics Washington DC. We used the model to predict the amount of transmitted drug resistance (TDR) versus regimen-acquired drug resistance.
We forecast the prevalence of HIV-1 cases resistant to raltegravir as 0.41 (minimum: 0.21; maximum: 0.57), resistant to elvitegravir as 0.44 (minimum: 0.26; maximum: 0.60), and resistant to dolutegravir as 0.44 (minimum: 0.25; maximum: 0.65). Model output was greatly affected by the proportion of those living with HIV-1 on ART and the rate of converting from an INSTI-sensitive strain to an INSTI-resistant strain for chronically infected ART-experienced cases. We forecast that TDR will contribute minimally-if at all-to the overall proportion of resistant HIV-1 cases.
INSTI drug resistance has the potential to be a public health concern in the next 30 years. Although several parameters influence the predicted prevalence of INSTI drug resistance, TDR is unlikely to contribute substantially to future trends.</description><identifier>ISSN: 1525-4135</identifier><identifier>EISSN: 1944-7884</identifier><identifier>DOI: 10.1097/QAI.0000000000002212</identifier><identifier>PMID: 31809362</identifier><language>eng</language><publisher>United States: JAIDS Journal of Acquired Immune Deficiency Syndromes</publisher><subject>Antiretroviral agents ; Antiretroviral therapy ; Computer simulation ; Drug resistance ; Drug Resistance, Viral - drug effects ; HIV ; HIV Integrase - genetics ; HIV Integrase Inhibitors - pharmacology ; HIV-1 - drug effects ; Human immunodeficiency virus ; Humans ; Initial conditions ; Integrase ; Parameters ; Public health ; Stochastic models ; Stochasticity</subject><ispartof>Journal of acquired immune deficiency syndromes (1999), 2020-01, Vol.83 (1), p.65-71</ispartof><rights>JAIDS Journal of Acquired Immune Deficiency Syndromes</rights><rights>Copyright Lippincott Williams & Wilkins Ovid Technologies Jan 2020</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c4929-77df865bc54493f387c61ac05737c6c34b5a6aff9a4c5d717aa8bd5c8c5d43bf3</citedby><cites>FETCH-LOGICAL-c4929-77df865bc54493f387c61ac05737c6c34b5a6aff9a4c5d717aa8bd5c8c5d43bf3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf><![CDATA[$$Uhttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&CSC=Y&NEWS=N&PAGE=fulltext&PDF=y&D=ovft&AN=00126334-202001010-00009$$EPDF$$P50$$Gwolterskluwer$$H]]></linktopdf><linktohtml>$$Uhttp://ovidsp.ovid.com/ovidweb.cgi?T=JS&NEWS=n&CSC=Y&PAGE=fulltext&D=ovft&AN=00126334-202001010-00009$$EHTML$$P50$$Gwolterskluwer$$H</linktohtml><link.rule.ids>314,780,784,4609,27924,27925,64666,65461</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/31809362$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Northrop, Alex J.</creatorcontrib><creatorcontrib>Pomeroy, Laura W.</creatorcontrib><title>Forecasting Prevalence of HIV-1 Integrase Strand Transfer Inhibitor (INSTI) Drug Resistance: A Modeling Study</title><title>Journal of acquired immune deficiency syndromes (1999)</title><addtitle>J Acquir Immune Defic Syndr</addtitle><description>Antiretroviral therapy (ART) is a cornerstone of HIV-1 treatment and provides significant health benefits for patients with responsive HIV-1 strains. Integrase strand transfer inhibitors (INSTIs) are the newest class of ART. Although most HIV-1 cases are responsive, a small number are already resistant. Here, we forecast the prevalence of INSTI resistance amid wide-spread use.
We developed a stochastic model to simulate HIV-1 dynamics and INSTI resistance for raltegravir, elvitegravir, and dolutegravir. We forecast prevalence of INSTI resistance in adults living with HIV-1 over a 30-year period using parameter values and initial conditions that mimic HIV-1 dynamics Washington DC. We used the model to predict the amount of transmitted drug resistance (TDR) versus regimen-acquired drug resistance.
We forecast the prevalence of HIV-1 cases resistant to raltegravir as 0.41 (minimum: 0.21; maximum: 0.57), resistant to elvitegravir as 0.44 (minimum: 0.26; maximum: 0.60), and resistant to dolutegravir as 0.44 (minimum: 0.25; maximum: 0.65). Model output was greatly affected by the proportion of those living with HIV-1 on ART and the rate of converting from an INSTI-sensitive strain to an INSTI-resistant strain for chronically infected ART-experienced cases. We forecast that TDR will contribute minimally-if at all-to the overall proportion of resistant HIV-1 cases.
INSTI drug resistance has the potential to be a public health concern in the next 30 years. Although several parameters influence the predicted prevalence of INSTI drug resistance, TDR is unlikely to contribute substantially to future trends.</description><subject>Antiretroviral agents</subject><subject>Antiretroviral therapy</subject><subject>Computer simulation</subject><subject>Drug resistance</subject><subject>Drug Resistance, Viral - drug effects</subject><subject>HIV</subject><subject>HIV Integrase - genetics</subject><subject>HIV Integrase Inhibitors - pharmacology</subject><subject>HIV-1 - drug effects</subject><subject>Human immunodeficiency virus</subject><subject>Humans</subject><subject>Initial conditions</subject><subject>Integrase</subject><subject>Parameters</subject><subject>Public health</subject><subject>Stochastic models</subject><subject>Stochasticity</subject><issn>1525-4135</issn><issn>1944-7884</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2020</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><recordid>eNpdkMlOwzAQhi0EomxvgJAlLnBI8Z6EW1W2SOwtXCPHsduUNCm2A-LtcVU2MZbG_2hmPls_APsY9TFK45OHQdZHf4IQTNbAFk4Zi-IkYetBc8IjhinvgW3nZghhwVi6CXoUJyilgmyB-UVrtZLOV80E3lv9JmvdKA1bA6-y5wjDrPF6YqXTcOStbEo4DtkZbUNnWhWVby08ym5H4-wYntluAh-1q5yXAXIKB_CmLXW9ZI98V37sgg0ja6f3vu4d8HRxPh5eRdd3l9lwcB0plpI0iuPSJIIXiofvUkOTWAksFeIxDUpRVnAppDGpZIqXMY6lTIqSqyRUjBaG7oDDFXdh29dOO5_P2s424cmcUCISQTGhYYqtppRtnbPa5AtbzaX9yDHKlx7nweP8v8dh7eAL3hVzXf4sfZv6y31va6-te6m7d23zqZa1nwYeJoJSFhFEgg4nWqJT-gkecoVO</recordid><startdate>20200101</startdate><enddate>20200101</enddate><creator>Northrop, Alex J.</creator><creator>Pomeroy, Laura W.</creator><general>JAIDS Journal of Acquired Immune Deficiency Syndromes</general><general>Lippincott Williams & Wilkins Ovid Technologies</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>7T2</scope><scope>7T5</scope><scope>7TK</scope><scope>7U7</scope><scope>7U9</scope><scope>C1K</scope><scope>H94</scope><scope>K9.</scope></search><sort><creationdate>20200101</creationdate><title>Forecasting Prevalence of HIV-1 Integrase Strand Transfer Inhibitor (INSTI) Drug Resistance: A Modeling Study</title><author>Northrop, Alex J. ; Pomeroy, Laura W.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c4929-77df865bc54493f387c61ac05737c6c34b5a6aff9a4c5d717aa8bd5c8c5d43bf3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2020</creationdate><topic>Antiretroviral agents</topic><topic>Antiretroviral therapy</topic><topic>Computer simulation</topic><topic>Drug resistance</topic><topic>Drug Resistance, Viral - drug effects</topic><topic>HIV</topic><topic>HIV Integrase - genetics</topic><topic>HIV Integrase Inhibitors - pharmacology</topic><topic>HIV-1 - drug effects</topic><topic>Human immunodeficiency virus</topic><topic>Humans</topic><topic>Initial conditions</topic><topic>Integrase</topic><topic>Parameters</topic><topic>Public health</topic><topic>Stochastic models</topic><topic>Stochasticity</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Northrop, Alex J.</creatorcontrib><creatorcontrib>Pomeroy, Laura W.</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>Health and Safety Science Abstracts (Full archive)</collection><collection>Immunology Abstracts</collection><collection>Neurosciences Abstracts</collection><collection>Toxicology Abstracts</collection><collection>Virology and AIDS Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>AIDS and Cancer Research Abstracts</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><jtitle>Journal of acquired immune deficiency syndromes (1999)</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Northrop, Alex J.</au><au>Pomeroy, Laura W.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Forecasting Prevalence of HIV-1 Integrase Strand Transfer Inhibitor (INSTI) Drug Resistance: A Modeling Study</atitle><jtitle>Journal of acquired immune deficiency syndromes (1999)</jtitle><addtitle>J Acquir Immune Defic Syndr</addtitle><date>2020-01-01</date><risdate>2020</risdate><volume>83</volume><issue>1</issue><spage>65</spage><epage>71</epage><pages>65-71</pages><issn>1525-4135</issn><eissn>1944-7884</eissn><abstract>Antiretroviral therapy (ART) is a cornerstone of HIV-1 treatment and provides significant health benefits for patients with responsive HIV-1 strains. Integrase strand transfer inhibitors (INSTIs) are the newest class of ART. Although most HIV-1 cases are responsive, a small number are already resistant. Here, we forecast the prevalence of INSTI resistance amid wide-spread use.
We developed a stochastic model to simulate HIV-1 dynamics and INSTI resistance for raltegravir, elvitegravir, and dolutegravir. We forecast prevalence of INSTI resistance in adults living with HIV-1 over a 30-year period using parameter values and initial conditions that mimic HIV-1 dynamics Washington DC. We used the model to predict the amount of transmitted drug resistance (TDR) versus regimen-acquired drug resistance.
We forecast the prevalence of HIV-1 cases resistant to raltegravir as 0.41 (minimum: 0.21; maximum: 0.57), resistant to elvitegravir as 0.44 (minimum: 0.26; maximum: 0.60), and resistant to dolutegravir as 0.44 (minimum: 0.25; maximum: 0.65). Model output was greatly affected by the proportion of those living with HIV-1 on ART and the rate of converting from an INSTI-sensitive strain to an INSTI-resistant strain for chronically infected ART-experienced cases. We forecast that TDR will contribute minimally-if at all-to the overall proportion of resistant HIV-1 cases.
INSTI drug resistance has the potential to be a public health concern in the next 30 years. Although several parameters influence the predicted prevalence of INSTI drug resistance, TDR is unlikely to contribute substantially to future trends.</abstract><cop>United States</cop><pub>JAIDS Journal of Acquired Immune Deficiency Syndromes</pub><pmid>31809362</pmid><doi>10.1097/QAI.0000000000002212</doi><tpages>7</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Antiretroviral agents Antiretroviral therapy Computer simulation Drug resistance Drug Resistance, Viral - drug effects HIV HIV Integrase - genetics HIV Integrase Inhibitors - pharmacology HIV-1 - drug effects Human immunodeficiency virus Humans Initial conditions Integrase Parameters Public health Stochastic models Stochasticity |
title | Forecasting Prevalence of HIV-1 Integrase Strand Transfer Inhibitor (INSTI) Drug Resistance: A Modeling Study |
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