Group-based model better measure of treatment adherence

Treatment adherence is not always consistent, and new adherence patterns may result in more useful classifications.

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Group-based model better measure of treatment adherence
Group-based model better measure of treatment adherence

A group-based trajectory model (GBTM) is a more appropriate way to model dynamic behaviors and offers researchers an alternative to more traditional drug adherence measurements, suggested a study published in ClinicoEconomics and Outcomes Research.

GBTM is an alternative method of adherence metric that overcomes the limitation of adherence to long-term treatment, according to lead author Yunfeng Li, PhD, and colleagues.

The retrospective cohort study used databases to identify 21,168 patients with clinician-diagnosed psoriasis who were prescribed at least one biologic medication, with a total of 3,366 patients who met eligibility criteria. Patients were followed for 12-months.

Through the application of GBTM in a large population of patients who initiated biologic therapy for their psoriasis, four adherence trajectories were identified: 1) continuously high adherence; 2) high-then-low adherence; 3) moderate-then-low adherence; and 4) consistently moderate adherence.

No meaningful differences in adherence were evident for patients with either very good or very poor adherence. However, for patients with medium levels of adherence, different longitudinal patterns were evident depending on the classification model used (PDC versus GBTM).

Recognizing these patterns of adherence may enable more individual, sophisticated, and less error-prone study within this population, compared with the methods employed with PDC, according to the researchers.

“This study helps to illustrate that patient adherence is not always a simple phenomenon, nor is it necessarily consistent over time," wrote the study authors.

"Thus, identifying longitudinal and potentially dynamic patterns of adherence using GBTM may result in more useful classifications than would using a more traditional measure such as PDC."

References

  1. Li Y. Clinicoecon Outcomes Res. 2014:6 197–208.

Disclosure: This study was financially supported by Novartis Pharmaceuticals Corporation. Li is an employee of Novartis Pharmaceuticals Corporation.

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