SFEBES2026 Oral Communications Adrenal and Cardiovascular (6 abstracts)
Serum steroid metabolomics is inferior to urine steroid metabolomics in the detection of adrenocortical carcinoma
James Hawley 1,2 , Angela Taylor 3 , Roland Veen 4,1 , Lida Abdi 1 , Alessandro Prete 5 , Vasileios Chortis 6 , Vera Dosedelova 1 , Carl Jenkinson 1 , Conall Dennedy 7 , Magalie Haissaguerre 8 , Dimitra Vassiliadi 9 , Urszula Ambroziak 10 , Martin Fassnacht 11,12 , Darko Kastelan 13 , Irina Bancos 14 , Alice Sitch 15 , Michael Biehl 4,1 & Wiebke Arlt 1,16
1MRC Laboratory of Medical Sciences, London, United Kingdom; 2Manchester University NHS Foundation Trust, Manchester, United Kingdom; 3Department of Metabolism and Systems Science, School of Medical Sciences, College of Medicine and Health, University of Birmingham, Birmingham, United Kingdom; 4Bernoulli Institute of Mathematics, Computer Science and Artificial Intelligence, Groningen University, Groningen, Netherlands; 5University of Birmingham, Birmingham, United Kingdom; 6Department of Metabolism and Systems Science, School of Medical Sciences, College of Medicine and Health, University of Birmingham, Birmingham, UK, Birmingham, United Kingdom; 7School of Medicine, National University of Ireland Galway, Galway, Ireland; 8Department of Endocrinology, Hôpital Haut Lévêque, CHU de Bordeaux, Pessac, France; 9Department of Endocrinology, Diabetes and Metabolism, Evangelismos Hospital, Athens, Greece; 10Department of Internal Medicine and Endocrinology, Medical University of Warsaw, Warsaw, Poland; 11Division of Endocrinology and Diabetes, Department of Internal Medicine I, University Hospital Würzburg, University of Würzburg, Wurzburg, Germany; 12Comprehensive Cancer Center Mainfranken, University Hospital Würzburg, University of Würzburg, Wurzburg, Germany; 1311Department of Endocrinology, University Hospital Centre Zagreb, Zagreb, Croatia; 14Division of Endocrinology, Diabetes, Metabolism and Nutrition, Mayo Clinic, Rochester, MN, USA, Rochester, USA; 15Department of Applied Health Sciences, School of Health Sciences, College of Medicine and Health, University of Birmingham, Birmingham, United Kingdom; 16Institute of Clinical Sciences, Imperial College London, London, United Kingdom
Background: Differentiating malignant adrenocortical carcinoma (ACC) from benign adrenocortical adenoma (ACA) remains challenging. Diagnosis often relies on multimodal imaging; however, this lacks specificity. Urine steroid metabolomics (USM), a combination of multi-steroid profiling by LC-MS/MS and machine learning, has been shown to significantly improve diagnostic accuracy over imaging only. LC-MS/MS analysis is more widely available for serum steroids than urinary steroid metabolites. However, to date, the comparative utility of serum steroid metabolomics (SSM) has not been investigated.
Objective: To compare the utility of SSM and USM for detecting ACC.
Design: We included paired 24-h urine and morning serum samples from 462 patients with confirmed ACC (n = 78) and ACA (n = 384), recruited in the prospective EURINE-ACT study. All samples were analysed by LC-MS/MS, measuring 14 serum steroids (androgens, glucocorticoids, core precursors) and 14 equivalent urinary steroid metabolites. ACA and ACC were randomly selected into training (n = 157) and test (n = 305) sets. Results from 157 patients (40 ACC, 117 ACA) were used to train serum- and urine-specific machine learning algorithms utilising generalised matrix learning vector quantisation (GMLVQ). The two locked algorithms were then applied to the serum and urine results, respectively, obtained in the prospective test cohort comprising 305 patients (38 ACC, 267 ACA). Diagnostic performance was assessed using Receiver Operating Characteristic curve analysis and chi squared tests.
Results: Applying the locked USM algorithm to the 24-h urine steroid profiling results of the test cohort produced an AUROC (Area Under the Receiver Operating Characteristic curve) of 0.90 (95%CI 0.84-0.96). By contrast, the SSM algorithm applied to the serum steroid profiling results of the test cohorts produced an AUROC of 0.78 (95%CI 0.69-0.87). Chi squared analysis revealed a significant difference between USM and SSM (P = 0.02).
Conclusion: SSM is diagnostically inferior to USM, which remains the test of choice for detecting ACC.
Volume 117
Article tools
My recent searches
My recently viewed abstracts
Authors
Endocrine Abstracts
ISSN 1470-3947 (print) | ISSN 1479-6848 (online)
© Bioscientifica 2026 |
Privacy policy |
Cookie settings
BiosciAbstracts
Bioscientifica Abstracts is the gateway to a series of products that provide a permanent, citable record of abstracts for biomedical and life science conferences.
Find out more