O'Reilly, Michael W

Abstract Disclosure: C.S. Pan: None. E. Melson: None. T. Ogiliev: None. D. Zhou: None. S.Y. Ng: None. F. Rezai: None. Z. Olateju: None. E. Radcliffe: None. P. Balendran: None. A. Radcliffe: None. G.M. Lau: None. J. Sheikh: None. H. Kaur: None. C. Cooper: None. F. Abdelhameed: None. F. Pang: None. S. Bhatt: None. D. Shabbir: None. M. Davitadze: None. A. Prete: None. C.L. Ronchi: None. I. Bancos: None. V. Chortis: None. J.D. Newell-Price: None. H.L. Simpson: None. H. Gleeson: None. K. Manolopoulos: None. J. Chu: None. M.W. O'Reilly: None. W. Arlt: None. C. Gillett: None. P. Kempegowda: None. O. SIMBA team: None. Introduction: Simulation via Instant Messaging - Birmingham Advance (SIMBA) is an effective educational platform in increasing clinicians’ confidence in managing various endocrine conditions (Melson, 2020). However, it has lacked input from the patients living with these conditions. We hypothesize that engaging patients and members of the public can inform clinicians to better tailor management to suit the concerns and expectations of patients. Methods: Two virtual simulation sessions covering topics related to Polycystic Ovary Syndrome (PPI-PCOS) and Adrenal conditions (PPI-Adrenal) were organized for clinicians. Nine cases were simulated using anonymized real-life patient data. Members of the general public living with PCOS or Adrenal conditions were recruited from several support groups to undergo a workshop-style discussion to provide their opinions on how representative the cases were and how the management of the condition could be improved. At the end of the simulations, all clinicians and patients were invited to a panel discussion led by expert consultants over Zoom incorporating the summaries from the workshops. Pre- and post-simulation surveys were distributed to measure the change in clinicians’ confidence using Wilcoxon signed-rank test. Thematic analysis was used to identify gaps in knowledge and expectations between clinicians and patients with PCOS or Adrenal conditions. Results: Self-reported confidence by clinicians in the management of PCOS (n=25) and Adrenal conditions (n=23) increased post-simulation (PPI-PCOS simulated:+41.0%, p<0.001; non-simulated:+40.0%, p<0.001. PPI-Adrenal simulated:+22.5% (p=0.0001); non-simulated:+24.0% (p=0.0005)). 90% and 100% of patients agreed PPI-PCOS benefits patients to understand their condition better, and helps clinicians and patients understand each other’s perspectives respectively, whereas this is true for 80% of patients from PPI-Adrenal regarding both aspects. Recurring themes identified through thematic analysis included approach to handling complexities resulting in delayed diagnosis or management, the need for personalized care, lack of information provided to patients with regards to the progression of symptoms, complications or treatment received. Conclusion: PPI-PCOS and PPI-Adrenal were effective in increasing the knowledge and understanding of PCOS and Adrenal conditions for both members of the general public and healthcare professionals. They also helped narrow the gap in knowledge and expectations by exchanging perspectives through a common dialogue. Presentation: Thursday, June 15, 2023

Abstract Objective 11-oxygenated androgens significantly contribute to the circulating androgen pool. Understanding the physiological variation of 11-oxygenated androgens and their determinants is essential for clinical interpretation, for example, in androgen excess conditions. We quantified classic and 11-oxygenated androgens in serum and saliva across the adult age and body mass index (BMI) range, also analyzing diurnal and menstrual cycle-dependent variation. Design Cross-sectional. Morning serum samples were collected from 290 healthy volunteers (125 men, 22-95 years; 165 women, 21-91 years). Morning saliva samples were collected by a sub-group (51 women and 32 men). Diurnal saliva profiles were collected by 13 men. Twelve women collected diurnal saliva profiles and morning saliva samples on 7 consecutive days during both follicular and luteal menstrual cycle phases. Methods Serum and salivary steroids were quantified by liquid chromatography–tandem mass spectrometry profiling assays. Results Serum classic androgens decreased with age-adjusted BMI, for example, %change kg/m2 for 5α-dihydrotestosterone: men −5.54% (95% confidence interval (CI) −8.10 to −2.98) and women −1.62% (95%CI −3.16 to −0.08). By contrast, 11-oxygenated androgens increased with BMI, for example, %change kg/m2 for 11-ketotestosterone: men 3.05% (95%CI 0.08-6.03) and women 1.68% (95%CI −0.44 to 3.79). Conversely, classic androgens decreased with age in both men and women, while 11-oxygenated androgens did not. Salivary androgens showed a diurnal pattern in men and in the follicular phase in women; in the luteal phase, only 11-oxygenated androgens showed diurnal variation. Conclusions Classic androgens decrease while active 11-oxygenated androgens increase with increasing BMI, pointing toward the importance of adipose tissue mass for the activation of 11-oxygenated androgens. Classic but not 11-oxygenated androgens decline with age.

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.