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Introduction: Although consistent use of tyrosine kinase inhibitors (TKIs) confers significant improvements in long-term survival for individuals with chronic myeloid leukemia (CML), only 70% of CML patients are adherent to TKIs. Understanding the factors that contribute to non-adherence and establishing dynamic adherence patterns in this population are essential aspects of targeted drug monitoring and intervention strategies. Methods: Newly diagnosed CML patients were identified in the MarketScan database and relevant covariate values extracted. Proportion of days covered (PDC) per 30-day interval was used to calculate adherence over a 12-month follow-up period. We conducted a latent profile analysis (LPA) on these PDC estimates to identify distinct, dynamic patterns of TKI adherence. Identified trajectories were grouped into four clinically relevant categories and predictors of membership in these categories were determined via multinomial logistic regression. Results: Four broad adherence categories were identified from the LPA: never adherent, initially non-adherent becoming adherent, initially adherent becoming non-adherent, and stable adherent. Results from the subsequent multinomial logistic regression indicated that younger age, female sex, greater monthly financial burden, fewer comorbidities, fewer concomitant medications, year of diagnosis, higher starting dose, TKI type, and a longer duration from diagnosis to treatment were significantly associated with membership in at least one of the three non-stable adherent groups. Conclusion: Select sociodemographic and clinical characteristics were found to predict membership in clinically meaningful groups of longitudinal TKI adherence. These findings could have major implications for informing personalized monitoring and intervention strategies for individuals who are likely to be non-adherent. [ABSTRACT FROM AUTHOR]

Background/objective: As pharmacists work to ensure reimbursement for chronic disease management services on the national level, evidence of their impact on important health metrics, such as medication adherence, is needed. However, summative evidence is lacking on the effectiveness of pharmacists to improve medication adherence in older adults. The objective was to assess the effectiveness of pharmacist‐led interventions on medication adherence in older adults (65+ years). Design/setting/participants: Using a systematic review and meta‐analytic approach, a comprehensive search of publications in PubMed, Scopus, CINAHL, Cochrane Central Register of Controlled Trials, Cochrane Database of Systematic Reviews, and Google Scholar was conducted through April 2, 2020 for randomized clinical trials of pharmacist‐led interventions to improve medication adherence in older adults. A standardized mean difference effect size (Cohen's d) was calculated for medication adherence in each study. Study effect sizes were pooled using a random‐effects model, with effect sizes weighted by inverse of its total variance. Measurements Medication adherence using any method of measurement. Results: Among 40 unique randomized trials of pharmacist‐led interventions with data from 8822 unique patients (mean age, range: 65–85 years), the mean effect size was 0.57 (k = 40; 95% Confidence Interval [CI]: 0.38–0.76). When two outlier studies were excluded from the analysis, the mean effect size reduced to 0.41 (k = 38; 95% CI: 0.27–0.54). A sensitivity analysis of medication adherence outcome by time point resulted in a mean effect size of 0.64 at 3 months (k = 12; 95% CI: 0.32–0.97), 0.30 at 6 months (k = 13; 95% CI: 0.11–0.48), 0.22 at 12 months (k = 12; 95% CI: 0.08–0.37), and 0.36 for outcome time points beyond 12 months (k = 5; 95% CI: 0.02–0.70). Conclusion: This meta‐analysis found a significant improvement in medication adherence among older adults receiving pharmacist‐led interventions. Implementation of pharmacist‐led interventions supported by Medicare reimbursement could ensure older adults' access to effective medication adherence support. [ABSTRACT FROM AUTHOR]

Objective: This study was undertaken to characterize trajectories of antiseizure medication (ASM) adherence in adults with newly treated epilepsy and to determine predictors of trajectories. Methods: This was a retrospective cohort study using Medicare. We included beneficiaries with newly treated epilepsy (one or more ASM and none in the preceding 2 years, plus International Classification of Diseases codes) in 2010–2013. We calculated the proportion of days covered (proportion of total days with any ASM pill supply) for 8 quarters or until death. Group‐based trajectory models characterized and determined predictors of trajectories. Results: We included 24 923 beneficiaries. Models identified four groups: early adherent (60%), early nonadherent (18%), late adherent (11%), and late nonadherent (11%). Numerous predictors were associated with being in the early nonadherent versus early adherent group: non‐White race (e.g., Black, odds ratio [OR] = 1.7, 95% confidence interval [CI] = 1.5–1.8), region (e.g., South vs. Northeast: OR = 1.2, 95% CI = 1.1–1.4), and once daily initial medication (OR = 1.1, 95% CI = 1.0–1.3). Predictors associated with decreased odds of being in the early nonadherent group included older age (OR =.9 per decade, 95% CI =.9–.9), female sex (OR =.9, 95% CI =.8–1.0), full Medicaid eligibility (OR =.6, 95% CI =.4–.8), neurologist visit (OR =.6, 95% CI =.6–.7), and initial older generation ASM (OR =.6, 95% CI =.6–.7). Significance: We identified four ASM adherence trajectories in individuals with newly treated epilepsy. Whereas risk factors for early nonadherence such as race or geographic region are nonmodifiable, our work highlighted a modifiable risk factor for early nonadherence: lacking a neurologist. These data may guide future interventions aimed at improving ASM adherence, in terms of both timing and target populations. [ABSTRACT FROM AUTHOR]