Modeling Patterns of Medication Adherence in Primary Open-Angle Glaucoma

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.

Prospective cohort study.

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.

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.

Medication adherence trajectory groups.

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, P = 0.042) and declining (B = -0.303, P = 0.028) adherence groups.

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.

Proprietary or commercial disclosure may be found in the Footnotes and Disclosures at the end of this article.