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Predictive Model of Therapy Outcomes in Breast Cancer Patients
Patients with breast cancer, who are treated with curative intent, have a combination of surgery (excision of the tumor) and a course of medical therapy (chemotherapy or endocrine treatment). Both treatments are associated with significant side effects. Chemotherapy is associated with nausea, vomiting, hair loss and bone marrow suppression, whereas endocrine therapy is associated with arthritis and menopausal symptoms. Patients taking either chemotherapy or endocrine treatment may experience a range of side effects. The range and severity of side effects experienced vary from patient to patient. Little or nothing is known about the reason for this difference. The aim of the investigators proposal is to develop a pretreatment test to identify patients who are likely to undergo moderate to severe side effects, and therefore help doctors and patients plan and optimize medical therapy. The pretreatment test will be based on identifying a metabolic profile which can differentiate those patients who are likely to have severe or moderate side effects from those with either no or mild side effects. To do this, the investigators will take urine and blood samples from patients before and after the administration of endocrine treatment or chemotherapy and generate metabolic profiles. Furthermore, the investigators aim to gain an understanding into why side effects experienced between different patients are so variable. To do this the investigators plan to perform cytokine analysis, targeted genetic analysis and pharmaokinetic analysis on blood sample collected from patients before and after treatment has commenced. Patients who have planned surgical excision of tumor and are recommended to receive medical therapy before or after surgery would be invited to join the study. Each patient will be required to make additional visits to the hospital to complete questionnaires regarding side effects experienced and for sample (urine and blood) collection. The investigators plan to r
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