2022
DOI: 10.1177/20552173221101150
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Static and group-based trajectory analyses of factors associated with non-adherence in patients with multiple sclerosis newly-initiating once- or twice-daily oral disease-modifying therapy

Abstract: Background Increased understanding of adherence may facilitate optimal targeting of interventions. Objective To utilize group-based trajectory modeling (GBTM) to understand longitudinal patterns of adherence and factors associated with non-adherence in patients with multiple sclerosis (MS) newly-initiating once-/twice-daily oral disease-modifying therapy (DMT) (fingolimod, dimethyl fumarate, or teriflunomide). Methods Commercial plan data were analyzed using proportion of days covered (PDC) to evaluate factors… Show more

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“…Compared to the above-mentioned metrics, group-based trajectory modelling can describe behaviour over time. For instance, in a study by Nicholas et al (2022) , 39.5% of patients with multiple sclerosis were non-adherent to oral disease-modifying treatment. While conducting this analysis, they found three patterns of adherence: the “immediate non-adherence”, the “gradual non-adherence”, and the “adherence” group.…”
Section: Discussionmentioning
confidence: 99%
“…Compared to the above-mentioned metrics, group-based trajectory modelling can describe behaviour over time. For instance, in a study by Nicholas et al (2022) , 39.5% of patients with multiple sclerosis were non-adherent to oral disease-modifying treatment. While conducting this analysis, they found three patterns of adherence: the “immediate non-adherence”, the “gradual non-adherence”, and the “adherence” group.…”
Section: Discussionmentioning
confidence: 99%