ABSTRACT
BACKGROUND: Breast cancer patients undergoing chemotherapy (CT) experience fatigue and other side-effects. Studies exploring interventions with a plant-based, high-protein diet on fatigue and body composition are lacking. The effects of these interventions on fatigue, body mass index (BMI), and body composition were evaluated. METHOD: Newly diagnosed breast cancer patients who were scheduled for adjuvant CT (n = 103) were randomly assigned to the intervention or control group. Study outcomes included fatigue using fatigue symptom inventory and body composition using bioelectric impedance analyzer done at the start of CT, 3rd CT, and 3 weeks after CT. Linear mixed models were used to compare groups over time. RESULTS: Fatigue decreased from 57% to 28% in the intervention group and increased from 65% to 78% in the control group (p < 0.001). BMI decreased by 0.7 ± 0.8 kg/m2 in the intervention group, while the decrease was 0.4 ± 1.3 kg/m2 in the control group (p = 0.015). Fat mass decreased in the intervention group (p < 0.001) and muscle mass improved in the intervention group and decreased in the control group (p < 0.05). CONCLUSIONS: A plant-based, high-protein diet during CT resulted in positive changes in fatigue, BMI and body composition.
Subject(s)
Breast Neoplasms , Diet, High-Protein , Humans , Female , Breast Neoplasms/complications , Breast Neoplasms/drug therapy , Chemotherapy, Adjuvant/adverse effects , Body Mass Index , Fatigue/etiology , Quality of LifeABSTRACT
Breast cancer (BC) is a heterogeneous disease. Numerous chemotherapeutic agents are available for early stage or advanced/metastatic breast cancer to provide maximum benefit with minimum side effects. However, the clinical outcome of patients with the same clinical and pathological characteristics and treated with similar treatments may show major differences and a vast majority of patients still develop treatment resistance and eventually succumb to disease. It remains an unmet need to identify specific molecular defects, new biomarkers to enable clinicians to adopt individualized treatment for every patient in terms of endocrine, chemotherapy or targeted therapy which will improve clinical outcomes in BC. Our study aimed to identify frequent hotspot mutation profile in BC by targeted deep sequencing in cancer-related genes using Illumina Truseq amplicon/Swift Accel-Amplicon panel and MiSeq technology in an IRB-approved prospective study in a CLIA compliant laboratory. All the cases had pathology review for stage, histological type, hormonal status and Ki-67. Data was processed using Strand NGS™. Mutations identified in the tumor were assessed for 'actionability' i.e. response to therapy and impact on prognosis.
