Data Mining: Precision Analytical Retrospective Data Correlation

Overview

Data from previously analyzed clinical samples tested by Precision Analytical, Inc. will be mined to identify and select samples from patients reporting hormone supplement use. Patient demographics (BMI, for example), different therapies and expected changes in hormone levels will be analyzed and hormone metabolite patterns will be compared. Samples will be deidentified prior to analysis.

The investigators have a list of 10 estrogen metabolites, 8 androgen metabolites, two progesterone metabolites, 4 cortisol metabolites, free cortisol, six organic acids, 8-hydroxy-2'-deoxyguanosine (8-OHdG), and melatonin that are measured on patient urine samples and cortisol and cortisone on patient saliva samples. The investigators would like to both reinforce the validation of the accuracy of these urinary markers and examine how these markers associate with patient demographics, symptoms, hormone therapy doses and routes of administration. This study will involve analysis of existing data from routine clinical care. All data will be deidentified and each set of results will be given a study ID number. The key will be held by Danielle Martinot and will contain only the original Precision Analytical sample accession number and the new study ID (identification). No identifying PHI (Protected Health Information) will be accessible to the PI. These data will be used to evaluate the following hypotheses: 1) Urinary hormone measures accurately reflect expected changes in hormones with regard to circadian rhythm, menstrual status, and use of hormonal medications; 2) Urinary metabolites of cortisol will show a stronger association with body mass index and symptoms related to cortisol production as compared to salivary measures; 3) Urine values of reproductive hormones and organic acids will correlate to the dosing of estrogen and androgens more strongly than to progesterone creams; 4) 8-OHdG, a measure of oxidative stress, and melatonin will be correlated with age and BMI; and 5) Urinary hormone measures will capture age-related changes in hormone regulation.

Conditions

Eligibility

Locations (1)

Outcomes