ABSTRACT
BACKGROUND: As targeted cancer therapies and molecular profiling become widespread, the era of "precision oncology" is at hand. However, cancer genomes are complex, making mutation-specific outcomes difficult to track. We created a proof-of-principle, CUSTOM-SEQ: Continuously Updating System for Tracking Outcome by Mutation, to Support Evidence-based Querying, to automatically calculate and display mutation-specific survival statistics from electronic health record data. METHODS: Patients with cancer genotyping were included, and clinical data was extracted through a variety of algorithms. Results were refreshed regularly and injected into a standard reporting platform. Significant results were highlighted for visual cueing. A subset was additionally stratified by stage, smoking status, and treatment exposure. RESULTS: By August 2015, 4310 patients with a median follow-up of 17 months had sufficient data for survival calculation. As expected, epidermal growth factor receptor (EGFR) mutations in lung cancer were associated with superior overall survival, hazard ratio (HR) = 0.53 (P < .001), validating the approach. Guanine nucleotide binding protein (G protein), q polypeptide (GNAQ) mutations in melanoma were associated with inferior overall survival, a novel finding (HR = 3.42, P < .001). Smoking status was not prognostic for epidermal growth factor receptor-mutated lung cancer patients, who also lived significantly longer than their counterparts, even with advanced disease (HR = 0.54, P = .001). INTERPRETATION: CUSTOM-SEQ represents a novel rapid learning system for a precision oncology environment. Retrospective studies are often limited by study of specific time periods and can lead to incomplete conclusions. Because data is continuously updated in CUSTOM-SEQ, the evidence base is constantly growing. Future work will allow users to interactively explore populations by demographics and treatment exposure, in order to further investigate significant mutation-specific signals.
Subject(s)
Algorithms , Electronic Health Records , Lung Neoplasms/genetics , Mutation , Neoplasms/genetics , Cohort Studies , Computational Biology , DNA, Neoplasm , Epidermal Growth Factor/genetics , Follow-Up Studies , Genotype , Humans , Information Storage and Retrieval , Kaplan-Meier Estimate , Lung Neoplasms/mortality , Neoplasms/mortality , Precision Medicine , Proportional Hazards Models , Tobacco SmokingABSTRACT
PURPOSES/OBJECTIVES: To compare sleep quality and disturbance, fatigue, and depressive symptoms between breast cancer survivors and healthy women experiencing hot flashes and to examine relationships among sleep and remaining variables (fatigue, depressive symptoms, and frequency of hot flashes). DESIGN: Cross-sectional, descriptive, comparative pilot study. SETTING: University-based outpatient setting. SAMPLE: 15 breast cancer survivors and 15 healthy women matched on age, race, and menopausal status. All women had untreated hot flashes (no hormone replacement therapy or other hot flash treatments). METHODS: Questionnaires (sleep quality and disturbance, fatigue, and depression); two ambulatory, 24-hour sternal skin conductance monitoring sessions (hot flash frequency); and medical records review. MAIN RESEARCH VARIABLES: Sleep quality and disturbance, fatigue, depressive symptoms, and objective hot flash frequency. FINDINGS: The majority of participants evidenced poor sleep quality and high sleep disturbance (73% of breast cancer survivors and 67% of healthy women above a cutoff score of 5). Sleep duration was significantly shorter for breast cancer survivors in contrast to healthy women. Nighttime flashes were experienced by 67% of breast cancer survivors and 37% of healthy women. No group differences were found in fatigue, depressive symptoms, or objective hot flash frequency. Global sleep scores were significantly positively correlated with fatigue and depression but not with hot flash frequency. CONCLUSIONS: Findings suggest that sleep disturbance is common in menopausal breast cancer survivors and healthy women, is not necessarily related to hot flashes, and may stem from a multifactorial etiology. IMPLICATIONS FOR NURSING: Menopausal breast cancer survivors who present with any one of these symptoms should be screened for all symptoms both during and after treatment.
