This pilot phase I trial studies resveratrol in postmenopausal women with high body mass index. Chemoprevention is the use of certain drugs to keep cancer from forming. The use of resveratrol may keep cancer from forming. Studying samples of blood and urine in the laboratory from postmenopausal women who are taking resveratrol may help doctors learn more about the effects of resveratrol on biomarkers.
PRIMARY OBJECTIVES: I. To determine the effect of pharmacological doses of resveratrol on serum estradiol levels in post-menopausal women with high body mass index (BMI). SECONDARY OBJECTIVES: I. Assess the effect of resveratrol on serum estrone, testosterone, and sex hormone-binding globulin (SHBP). II. Assess the effect of resveratrol on serum levels of insulin and C-peptide. III. Assess the effect of resveratrol on adipocytokine expression and secretion as measured by serum leptin and adiponectin. IV. Assess the effect of resveratrol on inflammatory cytokines as measured by serum C-reactive protein (CRP). V. Assess the effect of resveratrol on oxidative stress as measured by urinary 8-isoprostaglandin F2 alpha (8-iso-PGF2 alpha) and 8-hydroxydeoxyguanosine (8OHdG). VI. Assess the safety of resveratrol intervention as measured by reported adverse events, complete blood count with differential (CBC/diff), comprehensive metabolic panel (CMP), and lipid profile. VII. Assess the relationship between systemic study agent exposure and biomarker modulation. OUTLINE: Patients receive resveratrol orally (PO) once daily (QD) for 12 weeks. After completion of study therapy, patients are followed up for 2 weeks
Study Type
INTERVENTIONAL
Allocation
NA
Purpose
BASIC_SCIENCE
Masking
NONE
Enrollment
46
Given PO
Correlative studies
Arizona Cancer Center - Tucson
Tucson, Arizona, United States
University of Arizona Health Sciences Center
Tucson, Arizona, United States
Change in serum estradiol levels in postmenopausal women with high BMI
A two-sided paired t-test will be performed to determine whether the change is significant at a significance level of 5%. If the data distribution indicates non-normality or skewedness in violation of the assumptions of the t-test, non-parametric tests will be used. Linear regression techniques will be used to adjust for potential confounders, e.g. age and BMI.
Time frame: From baseline to 12 weeks (post-intervention)
Change in serum estrone
Similar statistical analysis procedures as described for the primary endpoint will be performed to evaluate the changes of each of the endpoints at a significance level of 5%. Analysis will not be corrected for multiple comparisons but results will be interpreted cautiously. If the data distribution indicates non-normality or skewness, non-parametric tests will be used.
Time frame: From baseline to 12 weeks (post-intervention)
Change in serum testosterone
Similar statistical analysis procedures as described for the primary endpoint will be performed to evaluate the changes of each of the endpoints at a significance level of 5%. Analysis will not be corrected for multiple comparisons but results will be interpreted cautiously. If the data distribution indicates non-normality or skewness, non-parametric tests will be used.
Time frame: From baseline to 12 weeks (post-intervention)
Change in serum sex hormone-binding globulin (SHBG)
Similar statistical analysis procedures as described for the primary endpoint will be performed to evaluate the changes of each of the endpoints at a significance level of 5%. Analysis will not be corrected for multiple comparisons but results will be interpreted cautiously. If the data distribution indicates non-normality or skewness, non-parametric tests will be used.
Time frame: From baseline to 12 weeks (post-intervention)
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Change in serum levels of insulin
Similar statistical analysis procedures as described for the primary endpoint will be performed to evaluate the changes of each of the endpoints at a significance level of 5%. Analysis will not be corrected for multiple comparisons but results will be interpreted cautiously. If the data distribution indicates non-normality or skewness, non-parametric tests will be used.
Time frame: From baseline to 12 weeks (post-intervention)
Change in serum levels of C-peptide
Similar statistical analysis procedures as described for the primary endpoint will be performed to evaluate the changes of each of the endpoints at a significance level of 5%. Analysis will not be corrected for multiple comparisons but results will be interpreted cautiously. If the data distribution indicates non-normality or skewness, non-parametric tests will be used.
Time frame: From baseline to 12 weeks (post-intervention)
Change in serum leptin
Similar statistical analysis procedures as described for the primary endpoint will be performed to evaluate the changes of each of the endpoints at a significance level of 5%. Analysis will not be corrected for multiple comparisons but results will be interpreted cautiously. If the data distribution indicates non-normality or skewness, non-parametric tests will be used.
Time frame: From baseline to 12 weeks (post-intervention)
Change in serum adiponectin
Similar statistical analysis procedures as described for the primary endpoint will be performed to evaluate the changes of each of the endpoints at a significance level of 5%. Analysis will not be corrected for multiple comparisons but results will be interpreted cautiously. If the data distribution indicates non-normality or skewness, non-parametric tests will be used.
Time frame: From baseline to 12 weeks (post-intervention)
Change in inflammatory markers, measured by serum C-reactive protein
Similar statistical analysis procedures as described for the primary endpoint will be performed to evaluate the changes of each of the endpoints at a significance level of 5%. Analysis will not be corrected for multiple comparisons but results will be interpreted cautiously. If the data distribution indicates non-normality or skewness, non-parametric tests will be used.
Time frame: From baseline to 12 weeks (post-intervention)
Change in urinary 8-iso-PGF2alpha
Similar statistical analysis procedures as described for the primary endpoint will be performed to evaluate the changes of each of the endpoints at a significance level of 5%. Analysis will not be corrected for multiple comparisons but results will be interpreted cautiously. If the data distribution indicates non-normality or skewness, non-parametric tests will be used.
Time frame: From baseline to 12 weeks (post-intervention)
Change in urinary 8OHdG
Similar statistical analysis procedures as described for the primary endpoint will be performed to evaluate the changes of each of the endpoints at a significance level of 5%. Analysis will not be corrected for multiple comparisons but results will be interpreted cautiously. If the data distribution indicates non-normality or skewness, non-parametric tests will be used.
Time frame: From baseline to 12 weeks (post-intervention)
Incidence of reported adverse events
Descriptive statistics of the type and frequency of all adverse events will be generated, including 95% confidence intervals.
Time frame: Up to 12 weeks
Incidence of changes in CBC/diff, blood chemistry, and lipids
Time frame: Up to 12 weeks
Study agent/metabolite levels
The Spearman correlation coefficient will be calculated to evaluate the correlation between biomarker changes and study agent/metabolite levels. Linear regression techniques will be used to adjust for potential confounders, e.g. age and BMI.
Time frame: Up to 12 weeks