Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants
Nonadherence to oral immunosuppressive drugs in renal transplant patients remains a major challenge. The objective of this study was to develop an adherence-exposure model that 1) quantifies the impact of nonadherence patterns on cyclosporine levels and 2) identifies nonadherence patterns that are a...
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Veröffentlicht in: | Therapeutics and clinical risk management 2011-01, Vol.7, p.149-156 |
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description | Nonadherence to oral immunosuppressive drugs in renal transplant patients remains a major challenge. The objective of this study was to develop an adherence-exposure model that 1) quantifies the impact of nonadherence patterns on cyclosporine levels and 2) identifies nonadherence patterns that are associated with unfavorable transplantation outcomes.
This model quantified variability in drug exposure, expressed as the coefficient of variation (CV%), for time-averaged and trough cyclosporine levels (C(avg) and C(min), respectively), and percentage of days spent below the therapeutic C(min) target. Simulated patterns of nonadherence closely matched those observed in clinical practice for four nonadherence clusters and an "Others" category.
Patients in simulated nonadherence clusters 1-3 spent a mean (standard deviation) 5.8% (4.9), 9.0% (5.0), and 6.5% (3.4) of days below the C(min) target, compared with 76.8% (6.5) for cluster 4 and 38.3% (6.4) for the "Others" category. Mean (standard deviation) CV% values for C(min) were 24.1 (7.9), 35.4 (11.7), and 34.1 (10.6) for clusters 1-3, compared with 136.4 (23.6) for cluster 4 and 64.8 (10.3) for the "Others" category. Findings for C(avg) were similar.
Based on nonadherence patterns and known relationships between CV% for C(min) and C(avg), and transplantation outcomes, patients in cluster 4 and the "Others" category are expected to be at high risk of allograft rejection. The proposed drug adherence-exposure model is useful to identify high-risk patients who can be targeted for interventions aimed at enhancing drug adherence to optimize clinical long-term outcomes. |
doi_str_mv | 10.2147/TCRM.S16870 |
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This model quantified variability in drug exposure, expressed as the coefficient of variation (CV%), for time-averaged and trough cyclosporine levels (C(avg) and C(min), respectively), and percentage of days spent below the therapeutic C(min) target. Simulated patterns of nonadherence closely matched those observed in clinical practice for four nonadherence clusters and an "Others" category.
Patients in simulated nonadherence clusters 1-3 spent a mean (standard deviation) 5.8% (4.9), 9.0% (5.0), and 6.5% (3.4) of days below the C(min) target, compared with 76.8% (6.5) for cluster 4 and 38.3% (6.4) for the "Others" category. Mean (standard deviation) CV% values for C(min) were 24.1 (7.9), 35.4 (11.7), and 34.1 (10.6) for clusters 1-3, compared with 136.4 (23.6) for cluster 4 and 64.8 (10.3) for the "Others" category. Findings for C(avg) were similar.
Based on nonadherence patterns and known relationships between CV% for C(min) and C(avg), and transplantation outcomes, patients in cluster 4 and the "Others" category are expected to be at high risk of allograft rejection. The proposed drug adherence-exposure model is useful to identify high-risk patients who can be targeted for interventions aimed at enhancing drug adherence to optimize clinical long-term outcomes.</description><identifier>ISSN: 1178-203X</identifier><identifier>ISSN: 1176-6336</identifier><identifier>EISSN: 1178-203X</identifier><identifier>DOI: 10.2147/TCRM.S16870</identifier><identifier>PMID: 21691585</identifier><language>eng</language><publisher>New Zealand: Taylor & Francis Ltd</publisher><subject>cyclosporine ; Immunosuppressive agents ; kidney transplantation ; Kidney transplants ; logistic models ; Original Research ; Standard deviation ; Transplants & implants</subject><ispartof>Therapeutics and clinical risk management, 2011-01, Vol.7, p.149-156</ispartof><rights>2011. This work is licensed under https://creativecommons.org/licenses/by-nc/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.</rights><rights>2011 Maclean et al, publisher and licensee Dove Medical Press Ltd. 2011</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c410t-55ed3d409fdd776c5241511a8ebbe5a2e99473250d890897ef65134f48c0528c3</citedby></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3116802/pdf/$$EPDF$$P50$$Gpubmedcentral$$Hfree_for_read</linktopdf><linktohtml>$$Uhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC3116802/$$EHTML$$P50$$Gpubmedcentral$$Hfree_for_read</linktohtml><link.rule.ids>230,314,723,776,780,860,881,3849,27901,27902,53766,53768</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/21691585$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Maclean, J Ross</creatorcontrib><creatorcontrib>Pfister, Marc</creatorcontrib><creatorcontrib>Zhou, Zexun</creatorcontrib><creatorcontrib>Roy, Amit</creatorcontrib><creatorcontrib>Tuomari, Vickie A</creatorcontrib><creatorcontrib>Heifets, Michael</creatorcontrib><title>Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants</title><title>Therapeutics and clinical risk management</title><addtitle>Ther Clin Risk Manag</addtitle><description>Nonadherence to oral immunosuppressive drugs in renal transplant patients remains a major challenge. The objective of this study was to develop an adherence-exposure model that 1) quantifies the impact of nonadherence patterns on cyclosporine levels and 2) identifies nonadherence patterns that are associated with unfavorable transplantation outcomes.
This model quantified variability in drug exposure, expressed as the coefficient of variation (CV%), for time-averaged and trough cyclosporine levels (C(avg) and C(min), respectively), and percentage of days spent below the therapeutic C(min) target. Simulated patterns of nonadherence closely matched those observed in clinical practice for four nonadherence clusters and an "Others" category.
Patients in simulated nonadherence clusters 1-3 spent a mean (standard deviation) 5.8% (4.9), 9.0% (5.0), and 6.5% (3.4) of days below the C(min) target, compared with 76.8% (6.5) for cluster 4 and 38.3% (6.4) for the "Others" category. Mean (standard deviation) CV% values for C(min) were 24.1 (7.9), 35.4 (11.7), and 34.1 (10.6) for clusters 1-3, compared with 136.4 (23.6) for cluster 4 and 64.8 (10.3) for the "Others" category. Findings for C(avg) were similar.
Based on nonadherence patterns and known relationships between CV% for C(min) and C(avg), and transplantation outcomes, patients in cluster 4 and the "Others" category are expected to be at high risk of allograft rejection. The proposed drug adherence-exposure model is useful to identify high-risk patients who can be targeted for interventions aimed at enhancing drug adherence to optimize clinical long-term outcomes.</description><subject>cyclosporine</subject><subject>Immunosuppressive agents</subject><subject>kidney transplantation</subject><subject>Kidney transplants</subject><subject>logistic models</subject><subject>Original Research</subject><subject>Standard deviation</subject><subject>Transplants & implants</subject><issn>1178-203X</issn><issn>1176-6336</issn><issn>1178-203X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2011</creationdate><recordtype>article</recordtype><sourceid>8G5</sourceid><sourceid>BENPR</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNqFUkFvFCEUJkZj6-rJuyHx4KHZlgfDABcTs7FqUmPUarwRlnnTnWYHpsA09t9L3VpbL3J55PG97335-Ah5DuyQQ6OOTldfPh5-hVYr9oDsAyi95Ez8eHjnvkee5HzOWNMaA4_JHofWgNRyn3z_PLtQhv5qCGe0bJAO4-R8obGnIQbXbTBh8EgnVwqmkGkMFH9OMc8JaYk0JretM-McamuaEuZc-fJT8qh324zPbuqCfDt-e7p6vzz59O7D6s3J0jfAylJK7ETXMNN3nVKtl7wBCeA0rtcoHUdjGiW4ZJ02TBuFfStBNH2jPZNce7Egr3e807wesfMYShVkpzSMLl3Z6AZ7_yUMG3sWL62AahjjleBoR9DFS_wt_97w366Po1VMyjrx6mZlihcz5mLHIXvcbl3AOGertai8YPj_kUoIUKyWBXn5D_I8zilU5yyvp3IJAxV1sEP5FHNO2N9KBWavo2Cvo2B3UajoF3etucX--XvxCwmTsWM</recordid><startdate>20110101</startdate><enddate>20110101</enddate><creator>Maclean, J Ross</creator><creator>Pfister, Marc</creator><creator>Zhou, Zexun</creator><creator>Roy, Amit</creator><creator>Tuomari, Vickie A</creator><creator>Heifets, Michael</creator><general>Taylor & Francis Ltd</general><general>Dove Press</general><general>Dove Medical Press</general><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>3V.</scope><scope>7RV</scope><scope>7X7</scope><scope>7XB</scope><scope>88C</scope><scope>8AO</scope><scope>8FI</scope><scope>8FJ</scope><scope>8FK</scope><scope>8G5</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>CCPQU</scope><scope>DWQXO</scope><scope>FYUFA</scope><scope>GHDGH</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>K9.</scope><scope>KB0</scope><scope>M0S</scope><scope>M0T</scope><scope>M2O</scope><scope>MBDVC</scope><scope>NAPCQ</scope><scope>PIMPY</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>PRINS</scope><scope>Q9U</scope><scope>7X8</scope><scope>7U1</scope><scope>7U2</scope><scope>7U7</scope><scope>C1K</scope><scope>5PM</scope></search><sort><creationdate>20110101</creationdate><title>Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants</title><author>Maclean, J Ross ; Pfister, Marc ; Zhou, Zexun ; Roy, Amit ; Tuomari, Vickie A ; Heifets, Michael</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c410t-55ed3d409fdd776c5241511a8ebbe5a2e99473250d890897ef65134f48c0528c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2011</creationdate><topic>cyclosporine</topic><topic>Immunosuppressive agents</topic><topic>kidney transplantation</topic><topic>Kidney transplants</topic><topic>logistic models</topic><topic>Original Research</topic><topic>Standard deviation</topic><topic>Transplants & implants</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Maclean, J Ross</creatorcontrib><creatorcontrib>Pfister, Marc</creatorcontrib><creatorcontrib>Zhou, Zexun</creatorcontrib><creatorcontrib>Roy, Amit</creatorcontrib><creatorcontrib>Tuomari, Vickie A</creatorcontrib><creatorcontrib>Heifets, Michael</creatorcontrib><collection>PubMed</collection><collection>CrossRef</collection><collection>ProQuest Central (Corporate)</collection><collection>Nursing & Allied Health Database</collection><collection>Health & Medical Collection</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Healthcare Administration Database (Alumni)</collection><collection>ProQuest Pharma Collection</collection><collection>Hospital Premium Collection</collection><collection>Hospital Premium Collection (Alumni Edition)</collection><collection>ProQuest Central (Alumni) (purchase pre-March 2016)</collection><collection>Research Library (Alumni Edition)</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>ProQuest One Community College</collection><collection>ProQuest Central Korea</collection><collection>Health Research Premium Collection</collection><collection>Health Research Premium Collection (Alumni)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>ProQuest Health & Medical Complete (Alumni)</collection><collection>Nursing & Allied Health Database (Alumni Edition)</collection><collection>Health & Medical Collection (Alumni Edition)</collection><collection>Healthcare Administration Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Nursing & Allied Health Premium</collection><collection>Publicly Available Content Database</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central China</collection><collection>ProQuest Central Basic</collection><collection>MEDLINE - Academic</collection><collection>Risk Abstracts</collection><collection>Safety Science and Risk</collection><collection>Toxicology Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>Therapeutics and clinical risk management</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Maclean, J Ross</au><au>Pfister, Marc</au><au>Zhou, Zexun</au><au>Roy, Amit</au><au>Tuomari, Vickie A</au><au>Heifets, Michael</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants</atitle><jtitle>Therapeutics and clinical risk management</jtitle><addtitle>Ther Clin Risk Manag</addtitle><date>2011-01-01</date><risdate>2011</risdate><volume>7</volume><spage>149</spage><epage>156</epage><pages>149-156</pages><issn>1178-203X</issn><issn>1176-6336</issn><eissn>1178-203X</eissn><abstract>Nonadherence to oral immunosuppressive drugs in renal transplant patients remains a major challenge. The objective of this study was to develop an adherence-exposure model that 1) quantifies the impact of nonadherence patterns on cyclosporine levels and 2) identifies nonadherence patterns that are associated with unfavorable transplantation outcomes.
This model quantified variability in drug exposure, expressed as the coefficient of variation (CV%), for time-averaged and trough cyclosporine levels (C(avg) and C(min), respectively), and percentage of days spent below the therapeutic C(min) target. Simulated patterns of nonadherence closely matched those observed in clinical practice for four nonadherence clusters and an "Others" category.
Patients in simulated nonadherence clusters 1-3 spent a mean (standard deviation) 5.8% (4.9), 9.0% (5.0), and 6.5% (3.4) of days below the C(min) target, compared with 76.8% (6.5) for cluster 4 and 38.3% (6.4) for the "Others" category. Mean (standard deviation) CV% values for C(min) were 24.1 (7.9), 35.4 (11.7), and 34.1 (10.6) for clusters 1-3, compared with 136.4 (23.6) for cluster 4 and 64.8 (10.3) for the "Others" category. Findings for C(avg) were similar.
Based on nonadherence patterns and known relationships between CV% for C(min) and C(avg), and transplantation outcomes, patients in cluster 4 and the "Others" category are expected to be at high risk of allograft rejection. The proposed drug adherence-exposure model is useful to identify high-risk patients who can be targeted for interventions aimed at enhancing drug adherence to optimize clinical long-term outcomes.</abstract><cop>New Zealand</cop><pub>Taylor & Francis Ltd</pub><pmid>21691585</pmid><doi>10.2147/TCRM.S16870</doi><tpages>8</tpages><oa>free_for_read</oa></addata></record> |
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subjects | cyclosporine Immunosuppressive agents kidney transplantation Kidney transplants logistic models Original Research Standard deviation Transplants & implants |
title | Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants |
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