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Group-based trajectory modeling to assess adherence to biologics among patients with psoriasis

BACKGROUND: Proportion of days covered (PDC), a commonly used adherence metric, does not provide information about the longitudinal course of adherence to treatment over time. Group-based trajectory model (GBTM) is an alternative method that overcomes this limitation. METHODS: The statistical princi...

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Autores principales: Li, Yunfeng, Zhou, Huanxue, Cai, Beilei, Kahler, Kristijan H, Tian, Haijun, Gabriel, Susan, Arcona, Steve
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3986333/
https://www.ncbi.nlm.nih.gov/pubmed/24748809
http://dx.doi.org/10.2147/CEOR.S59339
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author Li, Yunfeng
Zhou, Huanxue
Cai, Beilei
Kahler, Kristijan H
Tian, Haijun
Gabriel, Susan
Arcona, Steve
author_facet Li, Yunfeng
Zhou, Huanxue
Cai, Beilei
Kahler, Kristijan H
Tian, Haijun
Gabriel, Susan
Arcona, Steve
author_sort Li, Yunfeng
collection PubMed
description BACKGROUND: Proportion of days covered (PDC), a commonly used adherence metric, does not provide information about the longitudinal course of adherence to treatment over time. Group-based trajectory model (GBTM) is an alternative method that overcomes this limitation. METHODS: The statistical principles of GBTM and PDC were applied to assess adherence during a 12-month follow-up in psoriasis patients starting treatment with a biologic. The optimal GBTM model was determined on the basis of the balance between each model’s Bayesian information criterion and the percentage of patients in the smallest group in each model. Variables potentially predictive of adherence were evaluated. RESULTS: In all, 3,249 patients were included in the analysis. Four GBTM adherence groups were suggested by the optimal model, and patients were categorized as demonstrating continuously high adherence, high-then-low adherence, moderate-then-low adherence, or consistently moderate adherence during follow-up. For comparison, four PDC groups were constructed: PDC Group 4 (PDC ≥75%), PDC Group 3 (25%≤ PDC <50%), PDC Group 2 (PDC <25%), and PDC Group 1 (50%≤ PDC <75%). Our findings suggest that the majority of patients (97.9%) from PDC Group 2 demonstrated moderate-then-low adherence, whereas 96.4% of patients from PDC Group 4 showed continuously high adherence. The remaining PDC-based categorizations did not capture patients with uniform adherence behavior based on GBTM. In PDC Group 3, 25.3%, 17.2%, and 57.5% of patients exhibited GBTM-defined consistently moderate adherence, moderate-then-low adherence, or high-then-low adherence, respectively. In PDC Group 1, 70.8%, 23.6%, and 5.7% of patients had consistently moderate adherence, high-then-low adherence, and continuously high adherence, respectively. Additional analyses suggested GBTM-based categorization was best predicted by patient age, sex, certain comorbidities, and particular drug use. CONCLUSION: GBTM is a more appropriate way to model dynamic behaviors and offers researchers an alternative to more traditional drug adherence measurements.
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spelling pubmed-39863332014-04-18 Group-based trajectory modeling to assess adherence to biologics among patients with psoriasis Li, Yunfeng Zhou, Huanxue Cai, Beilei Kahler, Kristijan H Tian, Haijun Gabriel, Susan Arcona, Steve Clinicoecon Outcomes Res Original Research BACKGROUND: Proportion of days covered (PDC), a commonly used adherence metric, does not provide information about the longitudinal course of adherence to treatment over time. Group-based trajectory model (GBTM) is an alternative method that overcomes this limitation. METHODS: The statistical principles of GBTM and PDC were applied to assess adherence during a 12-month follow-up in psoriasis patients starting treatment with a biologic. The optimal GBTM model was determined on the basis of the balance between each model’s Bayesian information criterion and the percentage of patients in the smallest group in each model. Variables potentially predictive of adherence were evaluated. RESULTS: In all, 3,249 patients were included in the analysis. Four GBTM adherence groups were suggested by the optimal model, and patients were categorized as demonstrating continuously high adherence, high-then-low adherence, moderate-then-low adherence, or consistently moderate adherence during follow-up. For comparison, four PDC groups were constructed: PDC Group 4 (PDC ≥75%), PDC Group 3 (25%≤ PDC <50%), PDC Group 2 (PDC <25%), and PDC Group 1 (50%≤ PDC <75%). Our findings suggest that the majority of patients (97.9%) from PDC Group 2 demonstrated moderate-then-low adherence, whereas 96.4% of patients from PDC Group 4 showed continuously high adherence. The remaining PDC-based categorizations did not capture patients with uniform adherence behavior based on GBTM. In PDC Group 3, 25.3%, 17.2%, and 57.5% of patients exhibited GBTM-defined consistently moderate adherence, moderate-then-low adherence, or high-then-low adherence, respectively. In PDC Group 1, 70.8%, 23.6%, and 5.7% of patients had consistently moderate adherence, high-then-low adherence, and continuously high adherence, respectively. Additional analyses suggested GBTM-based categorization was best predicted by patient age, sex, certain comorbidities, and particular drug use. CONCLUSION: GBTM is a more appropriate way to model dynamic behaviors and offers researchers an alternative to more traditional drug adherence measurements. Dove Medical Press 2014-04-10 /pmc/articles/PMC3986333/ /pubmed/24748809 http://dx.doi.org/10.2147/CEOR.S59339 Text en © 2014 Li et al. This work is published by Dove Medical Press Limited, and licensed under Creative Commons Attribution – Non Commercial (unported, v3.0) License The full terms of the License are available at http://creativecommons.org/licenses/by-nc/3.0/. Non-commercial uses of the work are permitted without any further permission from Dove Medical Press Limited, provided the work is properly attributed.
spellingShingle Original Research
Li, Yunfeng
Zhou, Huanxue
Cai, Beilei
Kahler, Kristijan H
Tian, Haijun
Gabriel, Susan
Arcona, Steve
Group-based trajectory modeling to assess adherence to biologics among patients with psoriasis
title Group-based trajectory modeling to assess adherence to biologics among patients with psoriasis
title_full Group-based trajectory modeling to assess adherence to biologics among patients with psoriasis
title_fullStr Group-based trajectory modeling to assess adherence to biologics among patients with psoriasis
title_full_unstemmed Group-based trajectory modeling to assess adherence to biologics among patients with psoriasis
title_short Group-based trajectory modeling to assess adherence to biologics among patients with psoriasis
title_sort group-based trajectory modeling to assess adherence to biologics among patients with psoriasis
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3986333/
https://www.ncbi.nlm.nih.gov/pubmed/24748809
http://dx.doi.org/10.2147/CEOR.S59339
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