Onco-metabolism: defining the prognostic significance of obesity and diabetes in women with brain metastases from breast cancer.
Publication/Presentation Date
11-1-2018
Abstract
PURPOSE: Metabolic dysregulation has been implicated as a molecular driver of breast cancer in preclinical studies, especially with respect to metastases. We hypothesized that abnormalities in patient metabolism, such as obesity and diabetes, may drive outcomes in breast cancer patients with brain metastases.
METHODS: We retrospectively identified 84 consecutive patients with brain metastases from breast cancer treated with intracranial radiation therapy. Radiation was delivered as whole-brain radiation to a median dose of 3000 cGy or stereotactic radiosurgery to a median dose of 2100 cGy. Kaplan Meier curves were generated for overall survival (OS) data and Mantel-Cox regression was performed to detect differences in groups.
RESULTS: At analysis, 81 survival events had occurred and the median OS for the entire cohort was 21.7 months. Despite similar modified graded prognostic assessments, resection rates, and receptor status, BMI ≥ 25 kg/m
CONCLUSIONS: Elevated BMI or diabetes may negatively impact both overall survival and local control in patients with brain metastases from breast cancer, highlighting the importance of the translational development of therapeutic metabolic interventions. Given its prognostic significance, BMI should be used as a stratification in future clinical trial design in this patient population.
Volume
172
Issue
1
First Page
221
Last Page
230
ISSN
1573-7217
Published In/Presented At
McCall, N. S., Simone, B. A., Mehta, M., Zhan, T., Ko, K., Nowak-Choi, K., Rese, A., Venkataraman, C., Andrews, D. W., Anne', P. R., Dicker, A. P., Shi, W., & Simone, N. L. (2018). Onco-metabolism: defining the prognostic significance of obesity and diabetes in women with brain metastases from breast cancer. Breast cancer research and treatment, 172(1), 221–230. https://doi.org/10.1007/s10549-018-4880-1
Disciplines
Business Administration, Management, and Operations | Health and Medical Administration | Management Sciences and Quantitative Methods
PubMedID
30022328
Department(s)
Administration and Leadership
Document Type
Article