Abstract
Purpose of review – Adrenal masses are highly prevalent, found in 5% of the population. Differentiation of benign adrenocortical adenoma from adrenocortical carcinoma is currently hampered by the poor specificity and limited evidence base of imaging tests. This review summarizes the results of studies published to date on urine steroid metabolite profiling for distinguishing benign from malignant adrenal masses.
Recent findings: Three studies have described cohorts of at least 100 patients with adrenal tumors showing significant differences between urinary steroid metabolite excretions according to the nature of the underlying lesion, suggesting significant value of steroid metabolite profiling as a highly accurate diagnostic test.
Summary: Steroid profiling is emerging as a powerful novel diagnostic tool with a significant potential for improving the management for patients with adrenal tumors. While the current studies used gas chromatography-mass spectrometry for proof-of-concept, widespread use of the method in routine clinical care will depend on transferring the approach to high-throughput tandem mass spectrometry platforms. The use of computational data analysis in conjunction with urine steroid metabolite profiling, i.e. steroid metabolomics, adds accuracy and precision.
Recent findings: Three studies have described cohorts of at least 100 patients with adrenal tumors showing significant differences between urinary steroid metabolite excretions according to the nature of the underlying lesion, suggesting significant value of steroid metabolite profiling as a highly accurate diagnostic test.
Summary: Steroid profiling is emerging as a powerful novel diagnostic tool with a significant potential for improving the management for patients with adrenal tumors. While the current studies used gas chromatography-mass spectrometry for proof-of-concept, widespread use of the method in routine clinical care will depend on transferring the approach to high-throughput tandem mass spectrometry platforms. The use of computational data analysis in conjunction with urine steroid metabolite profiling, i.e. steroid metabolomics, adds accuracy and precision.
Original language | English |
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Pages (from-to) | 200–207 |
Journal | Current Opinion in Endocrinology and Diabetes |
Volume | 24 |
Issue number | 3 |
Early online date | 27 Feb 2017 |
Publication status | Published - Jun 2017 |