Ku, E.J. Lee, C. Shim, J. Lee, S. Kim, K.-A. Kim, S.W. Rhee, Y. Kim, H.-J. Lim, J.S. Chung, C.H. Chun, S.W. Yoo, S.-J. Ryu, O.-H. Cho, H.C. Ram, Hong A. Ahn, C.H. Kim, J.H. Choi, M.H. 2024-01-19T13:33:26Z 2024-01-19T13:33:26Z 2022-01-10 2021-10 2093-596X https://pubs.kist.re.kr/handle/201004/116302 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. ？ 2021 Korean Endocrine Society. All rights reserved. English 대한내분비학회 Metabolic subtyping of adrenal tumors: Prospective multi-center cohort study in korea Article 10.3803/EnM.2021.1149 1 Endocrinology and Metabolism, v.36, no.5, pp.1131 - 1141 Endocrinology and Metabolism 36 5 1131 1141 N scie scopus kci ART002771035 000727577100021 2-s2.0-85119262523 Endocrinology & Metabolism Endocrinology & Metabolism Article PRIMARY ALDOSTERONISM CUSHINGS-SYNDROME DIAGNOSIS 18-HYDROXYCORTISOL 18-OXOCORTISOL SOCIETY MANAGEMENT SECRETION MS/MS Adrenal neoplasms Cushing syndrome Primary hyperaldosteronism Steroid metabolism Supervised machine learning