Patient-Reported Outcomes and Long-Term Nonadherence to Aromatase Inhibitors

Abstract

Background: Nonadherence to aromatase inhibitors (AIs) is common and increases risk of breast cancer (BC) recurrence. We analyzed factors associated with nonadherence among patients enrolled in S1105, a randomized trial of text messaging.

Methods: At enrollment, patients were required to have been on an adjuvant AI for at least 30 days and were asked about financial, medication, and demographic factors. They completed patient-reported outcomes (PROs) representing pain (Brief Pain Inventory), endocrine symptoms (Functional Assessment of Cancer Therapy-Endocrine Symptoms), and beliefs about medications (Treatment Satisfaction Questionnaire for Medicine; Brief Medication Questionnaire). Our primary endpoint was AI nonadherence at 36 months, defined as urine AI metabolite assay of less than 10 ng/mL or no submitted specimen. We evaluated the association between individual baseline characteristics and nonadherence with logistic regression. A composite risk score reflecting the number of statistically significant baseline characteristics was examined.

Results: We analyzed data from 702 patients; median age was 60.9 years. Overall, 35.9% patients were nonadherent at 36 months. Younger patients (younger than age 65 years) were more nonadherent (38.8% vs 28.6%, odds ratio [OR] = 1.51, 95% confidence interval [CI] = 1.05 to 2.16; P = .02). Fourteen baseline PRO scales were each statistically significantly associated with nonadherence. In a composite risk model categorized into quartile levels, each increase in risk level was associated with a 46.5% increase in the odds of nonadherence (OR = 1.47, 95% CI =1.26 to 1.70; P < .001). The highest-risk patients were more than 3 times more likely to be nonadherent than the lowest-risk patients (OR = 3.14, 95% CI = 1.97 to 5.02; P < .001).

Conclusions: The presence of multiple baseline PRO-specified risk factors was statistically significantly associated with AI nonadherence. The use of these assessments can help identify patients for targeted interventions to improve adherence.