Citations

Abstract Context Biochemical test results are central to clinical decision-making for the diagnosis and management of Cushing syndrome (CS). With emerging research and increasing availability of different tests, updated consensus on the utility of these biomarkers is warranted. Objective To establish an updated consensus on the role of biomarkers in the diagnosis and monitoring of adrenocorticotropic hormone-dependent CS, address novel therapeutic approaches, and identify areas for future research. Design A modified 2-round Delphi panel was conducted. Consensus was defined as ≥70% agreement/disagreement for Likert-scale statements or ≥70% selection of the same option for single-choice questions. Setting Participants represented a range of international expertise. Participants Forty-one participants took part in the Delphi panel, with no attrition between rounds (one nonclinician was not required to complete the second round). An 8-member Steering Committee guided statement development. Results Of statements designed to reach consensus, 45% (14/31) and 44% (11/25) statements reached consensus in Rounds 1 and 2, respectively. Notably, most panelists reported the use of late-night salivary cortisol for diagnosis of mild CS and for monitoring following pituitary surgery or medical or radiation therapy. Most panelists responded that block-and-replace therapies can be considered in patients with cyclical or severe CS, and consensus was reached that restoration of circadian rhythm is a treatment goal for patients with CS. Conclusion Areas of alignment among experts on the diagnosis and monitoring of CS are presented. The findings from this study are intended to support clinicians in their clinical decision-making and highlight priority areas for future research.

Abstract Objective Advanced adrenocortical carcinoma (ACC) is treated with mitotane alone or combined with cytotoxic chemotherapy, yet outcomes remain poor and prognostic models in this setting are lacking. This study aimed to evaluate the prognostic value of clinical parameters in a large cohort of patients with advanced ACC undergoing systemic therapy. Methods Multicenter, international cohort study investigating 418 patients with advanced ACC (61.5% = women, median age = 52 years) from 11 centers. Patients received mitotane monotherapy (n = 161), etoposide + doxorubicin + cisplatin ± mitotane (n = 178), or second-line regimens (gemcitabine + capecitabine ± mitotane or temozolomide + mitotane, n = 79). Variables included age, cortisol excess, performance status (ECOG-PS), tumor burden, and neutrophil-to-lymphocyte ratio (NLR) at start of therapy. Outcomes were overall survival (OS), time to progression (TTP), and best objective response. Results Tumor burden, cortisol excess, ECOG-PS, and NLR ≥5 independently predicted shorter OS (hazard ratio [HR] 1.55-2.68). We developed an integrated ENSAT Risk Score for Advanced ACC combining these variables: tumor burden (0-2), cortisol excess (0/1), ECOG-PS (0-2), and NLR (0/1). A score >2 (poor-risk) was significantly associated with worse OS and TTP across all treatment groups (HRs for OS: 3.05-3.96; TTP: 2.53-3.08). It also predicted poorer response to mitotane (P < .01) and second-line therapies (P = .04). Conclusions The ENSAT Risk Score for Advanced ACC is a practical, prognostic tool for patients with advanced ACC receiving systemic therapy. Based on accessible clinical and biochemical markers, it can support treatment decisions and facilitate informed discussions in routine care.

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 Background Mitotane monotherapy is the standard adjuvant treatment for adrenocortical carcinoma (ACC), yet reliable predictors of treatment response remain lacking. Given the well-recognized interplay between inflammation and cancer progression, serum inflammation-based scores have shown prognostic significance in various malignancies, including ACC in palliative settings. However, their relevance during adjuvant mitotane therapy remains uncertain. This study aimed to assess the prognostic value of inflammation-scores in patients with ACC receiving adjuvant mitotane. Methods Multicenter ENSAT retrospective study including patients with ACC treated with adjuvant mitotane as first-line therapy. Clinical data including age, sex, ENSAT tumor stage, Ki67 index, resection status, and hormone secretion were collected at diagnosis. Inflammation-scores - neutrophil-to-lymphocyte ratio (NLR), derived NLR (dNLR), systemic immune inflammation index (SII), and pan-immune-inflammation value (PIV) - were calculated at diagnosis (pre-surgery) and at mitotane start. Median values of inflammation-scores at diagnosis defined low and high levels. Overall survival (OS) and time to progression (TTP) from mitotane start were the primary endpoints. Results The study included 395 patients (66% female; median age: 51 years). Median time to mitotane start was 54 days (IQR: 32–90). At diagnosis, patients with glucocorticoid excess (n=84) had significantly higher inflammation-scores than those without (n=104): NLR (3.61 vs 2.53), dNLR (2.31 vs 1.72), SII (864.1 vs 679.3), and PIV (531.6 vs 343.1); all p≤0.005. All scores significantly declined after surgery (p<0.05). Higher inflammatory scores at diagnosis were associated with worse OS (NLR: HR=3.85, 95%CI=1.95–7.59, p<0.001; dNLR: HR=3.19, 95%CI=1.67- 6.08, p<0.001; SII: HR=1.97, 95%CI = 1.07–3.61, p=0.03; PIV: HR=2.11, 95%CI=1.13-3.95, p=0.02). However, only the NLR and dNLR remained independently associated with OS at multivariate analysis adjusted for ENSAT stage, Ki67 index, and resection status (p<0.05). At mitotane start (n=372), high SII and PIV were associated with shorter TTP (SII: HR=1.36, 95%CI=1.02-1.82, p=0.03; PIV: HR=1.40, 95%CI=1.04-1-87, p=0.02), with only SII remaining significant at multivariate regression (p=0.04). Conclusions Inflammation-based scores are higher in patients with glucocorticoid excess and decrease postoperatively. NLR and dNLR at diagnosis, and SII at mitotane start, are associated with clinical outcomes in patients with ACC receiving mitotane adjuvant monotherapy. These readily available markers may help improve prognostic stratification in clinical practice.

Abstract Background Primary aldosteronism (PA) is a common treatable cause of hypertension. When caused by unilateral adrenal disease, it is potentially curable by adrenalectomy. However, specialized tests and other factors may delay definitive treatment. We assessed the time to adrenalectomy (TTA) for patients worldwide. Methods We conducted an international, multicentre retrospective study involving 39 centres from 15 countries to determine the total time taken from the first presentation to adrenalectomy and the intervals between each stage (screening, confirmatory, subtyping, and adrenalectomy). We included patients with PA who underwent adrenalectomy from January 1, 2018, to October 30, 2022. Post-adrenalectomy outcomes were evaluated using the Primary Aldosteronism Surgery Outcome criteria. We performed multivariable quantile and linear regression to identify characteristics associated with longer TTA. Results We included 861 patients, mean age 49.3 ± 11.1 years, and 44.5% were women. Overall median TTA was 13.5 months, IQR: 6.6-24.5. Median intervals were 0.1 months (screening), 1.0 months (confirmatory), 4.1 months (subtyping), and 4.3 months (adrenalectomy). On multivariable analysis, median TTA was increased by 5.4 months for each additional adrenal vein sampling (AVS) procedure. Other factors associated with longer TTA included adrenalectomy post-COVID-19, younger age, and additional screening tests. Compared with countries with routine AVS, those without AVS had a shorter TTA (6.1 vs 15.1 months, P < .001), but greater likelihood of absent/partial biochemical success post-adrenalectomy (27.4% vs 12.4%, P < .001). Conclusion Primary aldosteronism management is time-consuming worldwide, especially for subtyping tests and adrenalectomy. While omitting AVS reduces overall time, patients are less likely to achieve biochemical cure post-adrenalectomy.

BACKGROUND: Distinguishing between unilateral and bilateral primary aldosteronism, a major cause of secondary hypertension, is crucial due to different treatment approaches. While adrenal venous sampling is the gold standard, its invasiveness, limited availability, and often difficult interpretation pose challenges. This study explores the utility of circulating microRNAs (miRNAs) and machine learning in distinguishing between unilateral and bilateral forms of primary aldosteronism. METHODS: MiRNA profiling was conducted on plasma samples from 18 patients with primary aldosteronism taken during adrenal venous sampling on an Illumina MiSeq platform. Bioinformatics and machine learning identified 9 miRNAs for validation by reverse transcription real-time quantitative polymerase chain reaction. Validation was performed on a cohort consisting of 108 patients with known subdifferentiation. A 30-patient subset of the validation cohort involved both adrenal venous sampling and peripheral, the rest only peripheral samples. A neural network model was used for feature selection and comparison between adrenal venous sampling and peripheral samples, while a deep-learning model was used for classification. RESULTS: Our model identified 10 miRNA combinations achieving >85% accuracy in distinguishing unilateral primary aldosteronism and bilateral adrenal hyperplasia on a 30-sample subset, while also confirming the suitability of peripheral samples for analysis. The best model, involving 6 miRNAs, achieved an area under curve of 87.1%. Deep learning resulted in 100% accuracy on the subset and 90.9% sensitivity and 81.8% specificity on all 108 samples, with an area under curve of 86.7%. CONCLUSIONS: Machine learning analysis of circulating miRNAs offers a minimally invasive alternative for primary aldosteronism lateralization. Early identification of bilateral adrenal hyperplasia could expedite treatment initiation without the need for further localization, benefiting both patients and health care providers.

Abstract Disclosure: B. Vekony: None. G. Nyiro: None. Z. Herold: None. J. Fekete: None. F. Ceccato: None. S. Gruber: None. L. Kurzinger: None. M. Parasiliti-Caprino: None. B. Szeredas: None. S. Syed Mohammed Nazri: None. V. Fell: None. M. Bassiony: None. E.A. Azizan: None. I. Bancos: None. F. Beuschlein: None. P. Igaz: None. Background: The differentiation of uni- and bilateral forms of primary aldosteronism (PA) is of pivotal clinical relevance. Whereas unilateral PA warrants surgical treatment, bilateral PA is treated by aldosterone antagonists. The most reliable way to differentiate these two entities is adrenal venous sampling (AVS) that is an invasive method with limited availability and requiring great expertise. Aim: To develop a circulating blood-borne microRNA-based approach using machine learning for the differentiation of uni- and bilateral PA. Methods: Circulating microRNA profiling on an Illumina MiSeq platform was performed on total RNA samples isolated from EDTA-anticoagulated blood specimens taken by AVS from 18 pairs of right and left suprarenal veins (10 uni-, 8 bilateral PA). Significantly differentially expressed microRNAs were analyzed by a neural network (90-10% learner-tester cross-validation simulation). From the top 29 significantly differentially expressed microRNAs, 9 were selected for validation by Taqman RT-qPCR on a separate cohort of 30 AVS-confirmed samples (15-15 uni- and bilateral forms) both on plasma samples from adrenal as well as from peripheral veins. The method was finally tested on another independent cohort of peripheral blood samples from 80 patients (40 uni- and 40 bilateral PA). Results: Regarding the 9 microRNAs selected for validation, microRNA abundance was non-significantly lower in peripheral samples compared to AVS samples. By analyzing peripheral plasma samples, ten combinations of 4-8 microRNAs from the pool of 9 microRNAs turned out to have maximal sensitivity and specificity values over 85 %. The best combination included 6 microRNAs with a sensitivity of 86.3 % and a specificity of 87.91 % (AUC = 0.871). The inclusion of further parameters such as imaging, potassium and renin levels did not improve the model’s performance. Conclusion: The analysis of circulating blood-borne microRNAs represents a minimally invasive and potentially reliable way of differentiating uni- and bilateral PA. If bilateral PA is confirmed by the model, no more localization efforts would be necessary thus simplifying the management of PA patients. This would be relevant both from the patient’s and a public health perspective. Presentation: 6/3/2024

Abstract Disclosure: B. Vekony: None. G. Nyiro: None. Z. Herold: None. J. Fekete: None. F. Ceccato: None. S. Gruber: None. L. Kurzinger: None. M. Parasiliti-Caprino: None. B. Szeredas: None. S.K. Nazri: None. V. Fell: None. M. Bassiony: None. E.A. Azizan: None. I. Bancos: None. F. Beuschlein: None. P. Igaz: None. Background: The differentiation of uni- and bilateral forms of primary aldosteronism (PA) is of pivotal clinical relevance. Whereas unilateral PA warrants surgical treatment, bilateral PA is treated by aldosterone antagonists. The most reliable way to differentiate these two entities is adrenal venous sampling (AVS) that is an invasive method with limited availability and requiring great expertise. Aim: To develop a circulating blood-borne microRNA-based approach using machine learning for the differentiation of uni- and bilateral PA. Methods: Circulating microRNA profiling on an Illumina MiSeq platform was performed on total RNA samples isolated from EDTA-anticoagulated blood specimens taken by AVS from 18 pairs of right and left suprarenal veins (10 uni-, 8 bilateral PA). Significantly differentially expressed microRNAs were analyzed by a neural network (90-10% learner-tester cross-validation simulation). From the top 29 significantly differentially expressed microRNAs, 9 were selected for validation by Taqman RT-qPCR on a separate cohort of 30 AVS-confirmed samples (15-15 uni- and bilateral forms) both on plasma samples from adrenal as well as from peripheral veins. The method was finally tested on another independent cohort of peripheral blood samples from 80 patients (40 uni- and 40 bilateral PA). Results: Regarding the 9 microRNAs selected for validation, microRNA abundance was non-significantly lower in peripheral samples compared to AVS samples. By analyzing peripheral plasma samples, ten combinations of 4-8 microRNAs from the pool of 9 microRNAs turned out to have maximal sensitivity and specificity values over 85 %. The best combination included 6 microRNAs with a sensitivity of 86.3 % and a specificity of 87.91 % (AUC = 0.871). The inclusion of further parameters such as imaging, potassium and renin levels did not improve the model’s performance. Conclusion: The analysis of circulating blood-borne microRNAs represents a minimally invasive and potentially reliable way of differentiating uni- and bilateral PA. If bilateral PA is confirmed by the model, no more localization efforts would be necessary thus simplifying the management of PA patients. This would be relevant both from the patient’s and a public health perspective. Presentation: 6/3/2024

Background Corticotroph tumor progression (CTP) leading to Nelson’s syndrome (NS) is a severe and difficult-to-treat complication subsequent to bilateral adrenalectomy (BADX) for Cushing’s disease. Its characteristics are not well described, and consensus recommendations for diagnosis and treatment are missing. Methods A systematic literature search was performed focusing on clinical studies and case series (≥5 patients). Definition, cumulative incidence, treatment and long-term outcomes of CTP/NS after BADX were analyzed using descriptive statistics. The results were presented and discussed at an interdisciplinary consensus workshop attended by international pituitary experts in Munich on October 28, 2018. Results Data covered definition and cumulative incidence (34 studies, 1275 patients), surgical outcome (12 studies, 187 patients), outcome of radiation therapy (21 studies, 273 patients), and medical therapy (15 studies, 72 patients). Conclusions We endorse the definition of CTP-BADX/NS as radiological progression or new detection of a pituitary tumor on thin-section MRI. We recommend surveillance by MRI after 3 months and every 12 months for the first 3 years after BADX. Subsequently, we suggest clinical evaluation every 12 months and MRI at increasing intervals every 2–4 years (depending on ACTH and clinical parameters). We recommend pituitary surgery as first-line therapy in patients with CTP-BADX/NS. Surgery should be performed before extrasellar expansion of the tumor to obtain complete and long-term remission. Conventional radiotherapy or stereotactic radiosurgery should be utilized as second-line treatment for remnant tumor tissue showing extrasellar extension

Adrenocortical carcinoma (ACC) is an orphan disease lacking effective systemic treatment options. The low incidence of the disease and high cost of clinical trials are major obstacles in the search for improved treatment strategies. As a novel approach, registry-based clinical trials have been introduced in clinical research, so allowing for significant cost reduction, but without compromising scientific benefit. Herein, we describe how the European Network for the Study of Adrenal Tumours (ENSAT) could transform its current registry into one fit for a clinical trial infrastructure. The rationale to perform randomized registry-based trials in ACC is outlined including an analysis of relevant limitations and challenges. We summarize a survey on this concept among ENSAT members who expressed a strong interest in the concept and rated its scientific potential as high. Legal aspects, including ethical approval of registry-based randomization were identified as potential obstacles. Finally, we describe three potential randomized registry-based clinical trials in an adjuvant setting and for advanced disease with a high potential to be executed within the framework of an advanced ENSAT registry. Thus we, therefore, provide the basis for future registry-based trials for ACC patients. This could ultimately provide proof-of-principle of how to perform more effective randomized trials for an orphan disease.