Abstract S3-02: Associations between baseline patient-reported symptoms and discontinuation of adjuvant aromatase inhibitor (AI) therapy

Abstract

Abstract Background: Non-adherence and non-persistence with AI therapy are common and have been associated with increased mortality. A major reason for premature discontinuation of therapy is toxicity of AI therapy. We performed an exploratory analysis to investigate associations between patient-reported symptoms at the time of AI initiation and discontinuation of AI therapy due to toxicity. Methods: 503 postmenopausal women with early stage ER positive breast cancer were enrolled into a randomized open label clinical trial of exemestane versus letrozole for 2 years. Questionnaires about sleep quality (PSQI), mood disorders (CESD), and general symptoms (NSABP symptom questionnaire) were completed prior to AI initiation. For each item on the symptom questionnaire, responses were dichotomized as not at all vs any. To analyze total number of symptoms the following 4 symptoms were included: PSQI>5, CESD≥16, any degree of joint pain, and any degree of difficulty concentrating. Subjects were evaluated 1, 3, 6, 12, and 24 months after AI initiation. Reasons for treatment discontinuation were prospectively recorded. The primary endpoint of this exploratory analysis was treatment discontinuation due to toxicity ≤12 months following AI initiation. Linear and logistic regression analyses were performed to analyze associations between clinical factors and baseline symptoms and treatment discontinuation by 12 months. Results: One hundred forty-two subjects (28.8%) discontinued therapy because of toxicity by or at 12 months. On univariate analysis, poor sleep quality (PSQI>5), depression (CESD≥16), forgetfulness, and total number of symptoms were statistically significantly associated with treatment discontinuation. On multivariable logistic regression, treatment discontinuation due to toxicity was statistically significantly associated with AI medication, and there was a trend towards an association with both younger age and increasing total number of symptoms present at baseline. Univariate and multivariate analysis of baseline predictors of AI treatment discontinuation Univariate analysisMultivariate analysisSymptom/characteristic% subjectsOR (95% CI)P valueOR (95% CI)P valueAge (yrs) mean 58.0 (9.0)0.98 (0.96-1.00)0.060.98 (0.95-1.00)0.076Drug (vs letrozole) 49.5%1.47 (0.99-2.18)0.0541.57 (1.04-2.38)0.033Estradiol (BL, pg/ml) mean 10.6 (37.2)1.01 (0.997-1.02)0.151.01 (1.00-1.02)0.091Prior taxane (vs no) 32.7%1.23 (0.82-1.85)0.331.14 (0.73-1.78)0.57Total # symptoms1 vs 028.2%1.56 (0.89-2.73)0.0241.27 (0.70-2.31)0.092 2 vs 021.5%1.52 (0.84-2.77) 1.54 (0.83-2.88) ≥3 vs 023.7%2.41 (1.37-4.23) 2.10 (1.15-3.84) Depression 15.2%1.03 (1.01-1.06)0.012 Forgetfulness (vs none) 45.5%1.64 (1.11-2.43)0.014 Difficulty concentrating (vs none) 23.7%1.35 (0.86-2.11)0.19 Joint pain (vs none) 57.6%1.42 (0.95-2.12)0.09 Poor sleep quality (vs good) 47.4%1.84 (1.23-2.75)0.003 Vaginal dryness (vs none) 31.5%1.37 (0.91-2.08)0.14 CI: confidence interval; OR: odds ratio Conclusions: Patient-reported symptoms present prior to initiation of AI therapy may predispose patients to early discontinuation of treatment. Pre-emptive management of these symptoms, rather than treatment of AI toxicity after its development, may improve adherence to and persistence with therapy. Citation Information: Cancer Res 2013;73(24 Suppl): Abstract nr S3-02.