Vassiliadi, Dimitra A.

Abstract Disclosure: A. Prete: HRA Pharmaceuticals, Lundbeck, Diurnal. L. Adbi: None. J.T. Bain: None. F. Shaheen: None. O. Suntornlohanakul: None. E. Deflorenne: None. A. Blanchard: None. M. Nestola: None. C. Pamporaki: None. I. Tizianel: None. E. Nowak: None. J. Bertherat: None. D.A. Vassiliadi: None. I. Bancos: None. C.M. Dennedy: None. D. Kastelan: None. M. Fassnacht: None. P. Mulatero: None. U. Ambroziak: None. A. Tabarin: None. M. Quinkler: None. S. Puglisi: None. J. Deinum: None. G.Å. Ueland: None. L. Lenzini: None. F. Beuschlein: None. M. Reincke: None. F. Ceccato: None. G. Eisenhofer: None. S.M. Corsello: None. L. Amar: None. M. Zennaro: None. N. Karavitaki: None. A.E. Taylor: None. W. Arlt: None. Introduction: Twenty-four-hour urinary free cortisol is used to diagnose Cushing’s syndrome (CS); amongst its limitations is failure to differentiate ACTH-dependent CS (AD-CS) from ACTH-independent CS (AI-CS). We tested the performance of urine steroid metabolomics (USM), the computational analysis of 24-hour urine steroid metabolome data by machine learning, for the diagnosis and differential diagnosis of CS. Given the physiological diurnal rhythm of cortisol secretion and its loss in CS, we also hypothesised that the difference in glucocorticoid excretion between CS and controls should be higher during nighttime, thereby facilitating more sensitive detection of CS. Methods: 264 subjects completed a 24-hour urine collection (40 AD-CS, 103 AI-CS due to adrenocortical adenoma or hyperplasia, 121 healthy subjects). A subset of 52 individuals (13 CS, 39 healthy) provided a nighttime urine collection and a daytime urine collection. Mass spectrometry-based multi-steroid profiling was used to quantify the urinary excretion of 27 steroid metabolites. Data were analysed by generalised matrix learning vector quantisation (a prototype-based supervised machine learning approach), multiple linear regression adjusted for age, sex, and BMI, and multiple logistic regression adjusted for age, sex, and BMI. Results: Twenty-four-hour USM demonstrated very high accuracy in differentiating CS from healthy individuals (AUC-ROC 0.99, 95%CI 0.99-0.99), reflected by higher urinary excretion of glucocorticoid and glucocorticoid precursor metabolites in CS. USM yielded high accuracy in differentiating AD-CS from AI-CS (AUC-ROC 0.91, 95%CI 0.89-0.94), with androgen metabolites being the most discriminatory. We observed significant sex differences in steroid excretion in both healthy individuals and those with CS. Women exhibited markedly lower excretion of both glucocorticoids and mineralocorticoids compared to men: average glucocorticoid excretion was reduced by 43% in healthy women and 30% in CS women, while average mineralocorticoid excretion was 29% lower in healthy women and 51% lower in CS women (results adjusted for age and BMI). Timed steroid excretion in healthy individuals reflected the diurnal pattern of adrenal steroid secretion, with lower nighttime than daytime excretion of glucocorticoid metabolites. Nighttime glucocorticoid metabolite excretion (AUC-ROC 1.00, 95%CI 0.99-1.00) performed better than daytime (AUC-ROC 0.91, 95%CI 0.77-1.00) and 24-hour excretion (AUC-ROC 0.94, 95%CI 0.86-1.00) in separating CS cases from healthy individuals. Conclusions: USM is a non-invasive, one-step candidate test for the accurate diagnosis and differential diagnosis of CS. Timed nighttime urine collection leverages cortisol circadian rhythmicity and improves the diagnostic accuracy of the current reference standard 24-hour collection. Presentation: Sunday, July 13, 2025

ABSTRACT Objective Data on bone health in patients with mild autonomous cortisol secretion (MACS) are limited and heterogenous. We sought to assess the prevalence of osteoporosis and symptomatic fragility fractures in patients with adrenal adenomas and hypercortisolism, and explore associations with the degree of cortisol excess and frailty. Design This multicenter cross ‐sectional study involved prospective enrollment of adults with nonfunctioning adrenal adenomas (NFA), MACS, Cushing syndrome (CS) and referent subjects without adrenal disorders during the study period (January 2019–September 2022). All participants completed a bone health questionnaire at enrollment and had dual‐energy X ‐ray absorptiometry bone mineral density assessment within 12‐months. Final analyses were adjusted for age, sex, body mass index, smoking status, alcohol use. Results Participants included 117 with NFA (median age 62 years, 80% women), 191 with MACS (median age 63 years, 74% women), 62 with CS (median age 50 years, 92% women), and 101 referent subjects (median age 59 years, 47% women). Both patients with CS (OR: 3.0, 95% CI: 1.1–8.3) and MACS (OR: 2.2, 95% CI: 1.9–4.9) had a higher prevalence of osteoporosis when compared to referents. Among patients with MACS, only those with post 1‐mg dexamethasone suppression test (post‐1mg‐DST) cortisol > 83 nmol/L had a higher prevalence of osteoporosis when compared to referents (OR: 3.2, 95% CI: 1.4–7.5) and NFA (OR: 2.2, 95% CI: 1.1–4.4). For clinical fragility fractures, only patients with CS showed an increased prevalence when compared to referents (OR: 6.1, 95% CI: 1.7–26.4) and NFA (OR: 3.8, 95% CI: 1.3–11.2). Prevalence of clinical fragility fractures was similar to referents in patients with MACS (OR: 1.8, 95% CI: 0.6–6.9) and NFA (OR: 1.5, 95% CI: 0.4–6.1), and was not associated with post‐1mg‐DST cortisol or frailty in the MACS and NFA groups. Conclusion Patients with CS, and those with MACS and post‐1mg‐DST cortisol > 83 nmol/L, exhibited a higher burden of osteoporosis. However, only CS was associated with an elevated risk of symptomatic fragility fractures.

Abstract Bilateral adrenal masses, increasingly encountered in clinical practice, manifest across diverse contexts, including incidental discovery, malignancy staging, and targeted imaging after hormonal diagnosis of adrenal disorders. The spectrum encompasses various pathologies, such as cortical adenomas, macronodular adrenal disease, pheochromocytomas, myelolipomas, infiltrative disorders, and primary and secondary malignancies. Notably, not all masses in both adrenal glands necessarily share the same etiology, often exhibiting diverse causes. Recently, the European Society of Endocrinology and the European Network for the Study of Adrenal Tumors updated guidelines, introduced a 4-option schema based on imaging, aiding in targeted hormonal testing and management. This “Approach to the Patient” review delves into the latest advancements in imaging, biochemical, and genetic approaches for the diagnostic and management nuances of bilateral adrenal masses. It provides insights and a contemporary framework for navigating the complexities associated with this clinical entity.

Purpose of review To discuss the most recent findings on the pathophysiology, the genetic and molecular causes of primary bilateral adrenal hyperplasia (PBAH). The diagnostic approach of patients with PBAH will also be presented in detail with an emphasis on the emerging diagnostic tools and finally, the treatment of PBAH will be discussed with an emphasis on the newest surgical and medical treatment approaches. Recent findings PBAH is a highly heterogeneous condition mostly detected incidentally on abdominal imaging. Based on the size of the nodules, PBAH is subdivided into primary bilateral macronodular adrenal hyperplasia (PBMAH) and micronodular adrenal hyperplasia. A substantial proportion of patients with PBMAH harbor a germline mutation of the armadillo repeat containing 5 tumor suppression gene and therefore genetic testing is strongly recommended. Measurements of plasma or urinary multisteroid profiles show promising results in that PBMAH has a distinctive plasma steroid fingerprint that can help in diagnosis and subtyping of PBMAH. Finally, although surgery is the mainstay of treatment of patients with PBAH, medical therapy is increasingly emerging as an alternative option. Summary PBAH is a poorly studied and therefore a challenging disease to diagnose and treat. Hopefully with these newest diagnostic and therapeutic tools, a more comprehensive approach will be adopted.

Abstract Context Patients with adrenal insufficiency require increased hydrocortisone cover during major stress to avoid a life-threatening adrenal crisis. However, current treatment recommendations are not evidence-based. Objective To identify the most appropriate mode of hydrocortisone delivery in patients with adrenal insufficiency who are exposed to major stress. Design and Participants Cross-sectional study: 122 unstressed healthy subjects and 288 subjects exposed to different stressors (major trauma [N = 83], sepsis [N = 100], and combat stress [N = 105]). Longitudinal study: 22 patients with preserved adrenal function undergoing elective surgery. Pharmacokinetic study: 10 patients with primary adrenal insufficiency undergoing administration of 200 mg hydrocortisone over 24 hours in 4 different delivery modes (continuous intravenous infusion; 6-hourly oral, intramuscular or intravenous bolus administration). Main Outcome Measure We measured total serum cortisol and cortisone, free serum cortisol, and urinary glucocorticoid metabolite excretion by mass spectrometry. Linear pharmacokinetic modeling was used to determine the most appropriate mode and dose of hydrocortisone administration in patients with adrenal insufficiency exposed to major stress. Results Serum cortisol was increased in all stress conditions, with the highest values observed in surgery and sepsis. Continuous intravenous hydrocortisone was the only administration mode persistently achieving median cortisol concentrations in the range observed during major stress. Linear pharmacokinetic modeling identified continuous intravenous infusion of 200 mg hydrocortisone over 24 hours, preceded by an initial bolus of 50–100 mg hydrocortisone, as best suited for maintaining cortisol concentrations in the required range. Conclusions Continuous intravenous hydrocortisone infusion should be favored over intermittent bolus administration in the prevention and treatment of adrenal crisis during major stress.

Abstract Context Urine steroid metabolomics, combining mass spectrometry-based steroid profiling and machine learning, has been described as a novel diagnostic tool for detection of adrenocortical carcinoma (ACC). Objective, Design, Setting This proof-of-concept study evaluated the performance of urine steroid metabolomics as a tool for postoperative recurrence detection after microscopically complete (R0) resection of ACC. Patients and Methods 135 patients from 14 clinical centers provided postoperative urine samples, which were analyzed by gas chromatography–mass spectrometry. We assessed the utility of these urine steroid profiles in detecting ACC recurrence, either when interpreted by expert clinicians or when analyzed by random forest, a machine learning-based classifier. Radiological recurrence detection served as the reference standard. Results Imaging detected recurrent disease in 42 of 135 patients; 32 had provided pre- and post-recurrence urine samples. 39 patients remained disease-free for ≥3 years. The urine “steroid fingerprint” at recurrence resembled that observed before R0 resection in the majority of cases. Review of longitudinally collected urine steroid profiles by 3 blinded experts detected recurrence by the time of radiological diagnosis in 50% to 72% of cases, improving to 69% to 92%, if a preoperative urine steroid result was available. Recurrence detection by steroid profiling preceded detection by imaging by more than 2 months in 22% to 39% of patients. Specificities varied considerably, ranging from 61% to 97%. The computational classifier detected ACC recurrence with superior accuracy (sensitivity = specificity = 81%). Conclusion Urine steroid metabolomics is a promising tool for postoperative recurrence detection in ACC; availability of a preoperative urine considerably improves the ability to detect ACC recurrence.