Patient-reported predictors of early treatment discontinuation: treatment-related symptoms and health-related quality of life among postmenopausal women with primary breast cancer randomized to anastrozole or exemestane on NCIC Clinical Trials Group (CCTG) MA.27 (E1Z03).

PURPOSE: Aromatase inhibitors are the most commonly prescribed adjuvant endocrine therapy for hormone-dependent early breast cancer in postmenopausal women. Among Canadian Cancer Trials Group MA.27 participants, anastrozole and exemestane had comparable 5-year event-free survival. This companion study examined differences in patient-reported treatment-related symptoms (TRS) and health-related quality of life (HRQL) among postmenopausal women randomized to anastrozole or exemestane. METHODS: MA.27 participants (N = 686, of 7576) randomized to 5 years of anastrozole (1 mg/day, n = 371, Arm A) or exemestane (25 mg/day, n = 315, Arm E) completed the 56-item Functional Assessment of Cancer Therapy-Endocrine Symptoms (FACT-ES) questionnaire to assess TRS and HRQL. The FACT-ES was completed at baseline, 3, 6, 12, and 24 months. RESULTS: No significant differences in FACT-ES median scores measuring TRS and HRQL were observed between treatment arms at any time point. Change in TRS from baseline was statistically significant at 3, 6, 12, and 24 months. HRQL was stable over time in both arms. Greater TRS burden was associated with poorer HRQL (coefficient = 0.57, p < 0.001). Twenty percent of patients discontinued AI therapy by month 24 and 32% discontinued AIs at 4 years. In both arms, patients reporting more side effect bother prior to initiating study treatment had a higher risk of discontinuing treatment before completing protocol therapy (hazard ratio [HR] 1.29, 95% CI 1.08-1.55, p = 0.01). CONCLUSIONS: TRS and HRQL were comparable between anastrozole and exemestane. TRS negatively affect HRQL. Women who report being bothered by treatment side effects prior to initiating an AI are at increased risk for early treatment discontinuation.

Supporting tool suite for production proteomics.

SUMMARY: The large amount of data produced by proteomics experiments requires effective bioinformatics tools for the integration of data management and data analysis. Here we introduce a suite of tools developed at Vanderbilt University to support production proteomics. We present the Backup Utility Service tool for automated instrument file backup and the ScanSifter tool for data conversion. We also describe a queuing system to coordinate identification pipelines and the File Collector tool for batch copying analytical results. These tools are individually useful but collectively reinforce each other. They are particularly valuable for proteomics core facilities or research institutions that need to manage multiple mass spectrometers. With minor changes, they could support other types of biomolecular resource facilities.