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Metabolic Subtyping of Adrenal Tumors: Prospective Multi-Center Cohort Study in Korea
- Source :
- Endocrinology and Metabolism, Vol 36, Iss 5, Pp 1131-1141 (2021), Endocrinology and Metabolism
- Publication Year :
- 2021
- Publisher :
- Korean Endocrine Society, 2021.
-
Abstract
- Background: Conventional diagnostic approaches for adrenal tumors require multi-step processes, including imaging studies and dynamic hormone tests. Therefore, this study aimed to discriminate adrenal tumors from a single blood sample based on the combination of liquid chromatography-mass spectrometry (LC-MS) and machine learning algorithms in serum profiling of adrenal steroids.Methods: The LC-MS-based steroid profiling was applied to serum samples obtained from patients with nonfunctioning adenoma (NFA, n=73), Cushing’s syndrome (CS, n=30), and primary aldosteronism (PA, n=40) in a prospective multicenter study of adrenal disease. The decision tree (DT), random forest (RF), and extreme gradient boost (XGBoost) were performed to categorize the subtypes of adrenal tumors.Results: The CS group showed higher serum levels of 11-deoxycortisol than the NFA group, and increased levels of tetrahydrocortisone (THE), 20α-dihydrocortisol, and 6β-hydroxycortisol were found in the PA group. However, the CS group showed lower levels of dehydroepiandrosterone (DHEA) and its sulfate derivative (DHEA-S) than both the NFA and PA groups. Patients with PA expressed higher serum 18-hydroxycortisol and DHEA but lower THE than NFA patients. The balanced accuracies of DT, RF, and XGBoost for classifying each type were 78%, 96%, and 97%, respectively. In receiver operating characteristics (ROC) analysis for CS, XGBoost, and RF showed a significantly greater diagnostic power than the DT. However, in ROC analysis for PA, only RF exhibited better diagnostic performance than DT.Conclusion: The combination of LC-MS-based steroid profiling with machine learning algorithms could be a promising one-step diagnostic approach for the classification of adrenal tumor subtypes.
- Subjects :
- medicine.medical_specialty
Adrenal Gland
Endocrinology, Diabetes and Metabolism
Adrenal Gland Neoplasms
Urology
Dehydroepiandrosterone
Adrenal neoplasm
Diseases of the endocrine glands. Clinical endocrinology
chemistry.chemical_compound
Cushing syndrome
Endocrinology
Primary aldosteronism
medicine
Humans
supervised machine learning
Tetrahydrocortisone
Prospective Studies
primary hyperaldosteronism
steroid metabolism
Receiver operating characteristic
business.industry
RC648-665
medicine.disease
chemistry
adrenal neoplasms
Original Article
Steroids
cushing syndrome
business
Chromatography, Liquid
Cohort study
Hormone
Subjects
Details
- ISSN :
- 20935978 and 2093596X
- Volume :
- 36
- Database :
- OpenAIRE
- Journal :
- Endocrinology and Metabolism
- Accession number :
- edsair.doi.dedup.....33c6dacac0b5b20e2f9ae5132c335e3e