Aaron N Winn1, Stacie B Dusetzina1,2,3,4. 1. Gillings School of Global Public Health, Department of Health Policy and Management, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 2. UNC Eshelman School of Pharmacy, Division of Pharmaceutical Outcomes and Policy, University of North Carolina at Chapel Hill, Chapel Hill, NC, USA. 3. UNC Lineberger Comprehensive Cancer Center, Chapel Hill, NC, USA. 4. Cecil G. Sheps Center for Health Services Research, Chapel Hill, NC, USA.
Abstract
PURPOSE: Studies examining adherence to endocrine therapy (ET) and breast cancer-related outcomes have traditionally used the proportion of days covered (PDC) by medication to define adherence which may mask true treatment-outcome associations for patients with different medication use behaviors. We use group-based trajectory models to examine the association between ET adherence patterns and mortality compared to a standard PDC adherence measure. METHODS: Using Surveillance, Epidemiology and End Results-Medicare data we included 9492 women with breast cancer who initiated ET between 2007 and 2010. We excluded women who died/recurred in the 12 months after ET initiation. We used monthly group-based trajectory models to characterize longitudinal adherence patterns and adjusted Cox proportional hazard models to estimate the association between ET adherence and mortality, comparing trajectory-based adherence to traditional PDC-based measures. RESULTS: Trajectory models identified five adherence groups: (i) high (56.2%); (ii) quick decline (9.5%); (iii) moderate decline (7.9%); (iv) quick decline, then increase (16.0%); and (v) slow decline (10.5%). Mortality was significantly associated with group assignment; compared to the high adherers, there was a significantly higher risk of death among quick declines (HR = 1.41, 95%CI = 1.09-1.72) and moderate declines (HR = 1.25, 95%CI = 1.00-1.55). Using the standard PDC adherence measure women with adherence <80% over the year had a higher risk of death than those with adherence ≥80% (HR = 1.21, 95%CI = 1.06-1.38). CONCLUSIONS: Defining ET adherence using trajectory models improved adherence measurement. These models could inform clinical practice by helping to identify common adherence patterns, potential areas for intervention and better isolate adherence-related outcomes in comparative effectiveness studies.
PURPOSE: Studies examining adherence to endocrine therapy (ET) and breast cancer-related outcomes have traditionally used the proportion of days covered (PDC) by medication to define adherence which may mask true treatment-outcome associations for patients with different medication use behaviors. We use group-based trajectory models to examine the association between ET adherence patterns and mortality compared to a standard PDC adherence measure. METHODS: Using Surveillance, Epidemiology and End Results-Medicare data we included 9492 women with breast cancer who initiated ET between 2007 and 2010. We excluded women who died/recurred in the 12 months after ET initiation. We used monthly group-based trajectory models to characterize longitudinal adherence patterns and adjusted Cox proportional hazard models to estimate the association between ET adherence and mortality, comparing trajectory-based adherence to traditional PDC-based measures. RESULTS: Trajectory models identified five adherence groups: (i) high (56.2%); (ii) quick decline (9.5%); (iii) moderate decline (7.9%); (iv) quick decline, then increase (16.0%); and (v) slow decline (10.5%). Mortality was significantly associated with group assignment; compared to the high adherers, there was a significantly higher risk of death among quick declines (HR = 1.41, 95%CI = 1.09-1.72) and moderate declines (HR = 1.25, 95%CI = 1.00-1.55). Using the standard PDC adherence measure women with adherence <80% over the year had a higher risk of death than those with adherence ≥80% (HR = 1.21, 95%CI = 1.06-1.38). CONCLUSIONS: Defining ET adherence using trajectory models improved adherence measurement. These models could inform clinical practice by helping to identify common adherence patterns, potential areas for intervention and better isolate adherence-related outcomes in comparative effectiveness studies.
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