Evidence map›Paper›PMID 40225409›Full record

ArticleOphthalmology science

Modeling Patterns of Medication Adherence in Primary Open-Angle Glaucoma.

Shervonne Poleon, Michael Twa, Yu-Mei Schoenberger-Godwin, Mathew Fifolt, Lyne Racette

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Article in Ophthalmology science. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

5 authors.

Shervonne PoleonDepartment of Optometry and Vision Science, School of Optometry, University of Alabama at Birmingham, Birmingham, Alabama.
Michael TwaUniversity of Houston College of Optometry, Houston, Texas.
Yu-Mei Schoenberger-GodwinDivision of Preventive Medicine, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama.
Mathew FifoltDepartment of Health Care Organization and Policy, School of Public Health, University of Alabama at Birmingham, Birmingham, Alabama.
Lyne RacetteDepartment of Ophthalmology and Visual Sciences, Heersink School of Medicine, University of Alabama at Birmingham, Birmingham, Alabama.

Funding

Visual Phenotyping CoreP30EY003039 · NEI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI Paul Douglas Gamlin · 1985 to 2026
$16.9M
Early detection of glaucoma progression using a novel individualized approachR01EY025756 · NEI · UNIVERSITY OF ALABAMA AT BIRMINGHAM · PI RACETTE, LYNE · 2016 to 2021
$1.9M
NEI NIH HHS P30 EY003039NEI NIH HHS R01 EY025756
6 · The paper itself

Abstract

Objective: To use group-based trajectory modeling to identify patterns of medication adherence in patients with primary open-angle glaucoma (POAG) and to identify factors associated with each pattern. Design: Prospective cohort study. Participants: Seventy-two patients with POAG who were enrolled in a National Institutes of Health-funded progression study at the University of Alabama at Birmingham were included in this study. Patients were required to be >18 years of age, have a diagnosis of POAG, and be prescribed hypotensive eye drops to treat their glaucoma. Methods: Fifty-two weeks of mean weekly medication adherence data were collected using Medication Event Monitoring Systems. Group-based trajectory modeling was used to estimate models with 2, 3, 4, 5, and 6 medication adherence trajectory groups. Self-reported race and illness perception were included as covariates. The model with the lowest Bayesian information criterion (which provides a measure of the trade-off between model fit and model complexity) and the highest number of clinically relevant trajectory groups was deemed optimal. Main Outcome Measures: Medication adherence trajectory groups. Results: The Bayesian information criterion was -1041.1 for the 2-group model, -755.9 for the 3-group model, -643.8 for the 4-group model, -590.4 for the 5-group model, and -559.0 for the 6-group model. We identified the 4-group model as the most optimal. The 4 trajectory groups estimated by this model were near-perfect adherence (51.8% of participants), good adherence (23.2% of participants), declining adherence (18.1% of participants), and poor adherence (6.9% of participants). Compared with the poor adherence group, a higher illness perception score predicted a lower probability of membership in the good (B = -0.276, Conclusions: Medication adherence is an important clinical outcome that is associated with disease severity and disease progression in POAG. Further investigation of this important topic may reveal other shared clinical characteristics that can be used to identify patients who may be at risk for adverse clinical outcomes such as glaucoma progression. Financial Disclosures: Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.

Indexed as

GBTMGlaucomaMedication adherenceModeling

Identifiers

PMID40225409
PMCPMC11987622

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.