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Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants
BACKGROUND AND OBJECTIVES: 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 nonad...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Dove Medical Press
2011
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3116802/ https://www.ncbi.nlm.nih.gov/pubmed/21691585 http://dx.doi.org/10.2147/TCRM.S16870 |
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author | Maclean, J Ross Pfister, Marc Zhou, Zexun Roy, Amit Tuomari, Vickie A Heifets, Michael |
author_facet | Maclean, J Ross Pfister, Marc Zhou, Zexun Roy, Amit Tuomari, Vickie A Heifets, Michael |
author_sort | Maclean, J Ross |
collection | PubMed |
description | BACKGROUND AND OBJECTIVES: 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. DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS: 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. RESULTS: 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. CONCLUSION: 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. |
format | Online Article Text |
id | pubmed-3116802 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2011 |
publisher | Dove Medical Press |
record_format | MEDLINE/PubMed |
spelling | pubmed-31168022011-06-20 Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants Maclean, J Ross Pfister, Marc Zhou, Zexun Roy, Amit Tuomari, Vickie A Heifets, Michael Ther Clin Risk Manag Original Research BACKGROUND AND OBJECTIVES: 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. DESIGN, SETTING, PARTICIPANTS, AND MEASUREMENTS: 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. RESULTS: 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. CONCLUSION: 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. Dove Medical Press 2011 2011-04-11 /pmc/articles/PMC3116802/ /pubmed/21691585 http://dx.doi.org/10.2147/TCRM.S16870 Text en © 2011 Maclean et al, publisher and licensee Dove Medical Press Ltd. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited. |
spellingShingle | Original Research Maclean, J Ross Pfister, Marc Zhou, Zexun Roy, Amit Tuomari, Vickie A Heifets, Michael Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants |
title | Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants |
title_full | Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants |
title_fullStr | Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants |
title_full_unstemmed | Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants |
title_short | Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants |
title_sort | quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3116802/ https://www.ncbi.nlm.nih.gov/pubmed/21691585 http://dx.doi.org/10.2147/TCRM.S16870 |
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