Eisenhofer, Graeme

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

AbstractAimThe aim of this study was to systematically appraise the quality of a sample of COVID-19-related systematic reviews (SRs) and discuss internal validity threats affecting the COVID-19 body of evidence.DesignWe conducted a scoping review of the literature. SRs with or without meta-analysis (MA) that evaluated clinical data, outcomes or treatments for patients with COVID-19 were included.Main outcome measuresWe extracted quality characteristics guided by A Measurement Tool to Assess Systematic Reviews-2 to calculate a qualitative score. Complementary evaluation of the most prominent published limitations affecting the COVID-19 body of evidence was performed.ResultsA total of 63 SRs were included. The majority were judged as a critically low methodological quality. Most of the studies were not guided by a pre-established protocol (39, 62%). More than half (39, 62%) failed to address risk of bias when interpreting their results. A comprehensive literature search strategy was reported in most SRs (54, 86%). Appropriate use of statistical methods was evident in nearly all SRs with MAs (39, 95%). Only 16 (33%) studies recognised heterogeneity in the definition of severe COVID-19 as a limitation of the study, and 15 (24%) recognised repeated patient populations as a limitation.ConclusionThe methodological and reporting quality of current COVID-19 SR is far from optimal. In addition, most of the current SRs fail to address relevant threats to their internal validity, including repeated patients and heterogeneity in the definition of severe COVID-19. Adherence to proper study design and peer-review practices must remain to mitigate current limitations.

Abstract Coronavirus disease 2019 (Covid-19) has affected millions of people and may disproportionately affect those with hypertension and diabetes. Because of inadequate methods in published systematic reviews, the prevalence of diabetes and hypertension and associated risks of poor outcomes in Covid-19 patients are unknown. We searched databases from December 1, 2019, to April 6, 2020, and selected observational peer-reviewed studies in English of patients with Covid-19. Independent reviewers extracted data on study participants, interventions, and outcomes and assessed risk of bias, and the certainty of evidence. We included 65 (15 794 participants) observational studies at moderate to high risk of bias. Overall prevalence of diabetes and hypertension was 12% (95% confidence interval [CI], 10-15; n = 12 870; I2: 89%), and 17% (95% CI, 13-22; n = 12 709; I2: 95%), respectively. In severe Covid-19, the prevalence of diabetes and hypertension were 18% (95% CI, 16-20; n = 1099; I2: 0%) and 32% (95% CI, 16-54; n = 1078; I2: 63%), respectively. Unadjusted relative risk for intensive care unit admission and mortality were 1.96 (95% CI, 1.19-3.22; n = 8890; I2: 80%; P = .008) and 2.78 (95% CI, 1.39-5.58; n = 2058; I2: 75%; P = .0004) for diabetics; and 2.95 (95% CI, 2.18-3.99; n = 1737; I2: 0%; P < .001) and 2.39 (95% CI, 1.54-3.73; n = 3107; I2: 66%; P < .001) for hypertensives. Neither diabetes (1.50; 95% CI, 0.90-2.50; n = 1991; I2: 74%; P = .119) nor hypertension (1.48; 95% CI, 0.99-2.23; n = 2023; I2: 69%; P = .058) was associated with severe Covid-19. In conclusion, the risk of intensive care unit admission and mortality for patients with diabetes or hypertension who developed Covid-19 is increased compared with those without these comorbidities. PROSPERO registration number CRD42020176582.

AbstractCOVID-19 was declared a global pandemic by the WHO and has affected millions of patients around the world. COVID-19 disproportionately affects persons with endocrine conditions, thus putting them at an increased risk for severe disease. We discuss the mechanisms that place persons with endocrine conditions at an additional risk for severe COVID-19 and review the evidence. We also suggest precautions and management of endocrine conditions in the setting of global curfews being imposed and offer practical tips for uninterrupted endocrine care.

Abstract Context Cross-sectional imaging with CT or MRI is regarded as a first-choice modality for tumor localization in patients with pheochromocytoma and paraganglioma (PPGL). 123I-labeled metaiodobenzylguanidine (123I-MIBG) is widely used for functional imaging but the added diagnostic value is controversial. Objective To establish the virtual impact of adding 123I-MIBG scintigraphy to CT or MRI on diagnosis and treatment of PPGL. Design International multicenter retrospective study. Intervention None. Patients Two hundred thirty-six unilateral adrenal, 18 bilateral adrenal, 48 unifocal extra-adrenal, 12 multifocal, and 26 metastatic PPGL. Main Outcome Measures Patients underwent both anatomical imaging (CT and/or MRI) and 123I-MIBG scintigraphy. Local imaging reports were analyzed centrally by two independent observers who were blinded to the diagnosis. Imaging-based diagnoses determined by CT/MRI only, 123I-MIBG only, and CT/MRI combined with 123I-MIBG scintigraphy were compared with the correct diagnoses. Results The rates of correct imaging-based diagnoses determined by CT/MRI only versus CT/MRI plus 123I-MIBG scintigraphy were similar: 89.4 versus 88.8%, respectively (P = 0.50). Adding 123I-MIBG scintigraphy to CT/MRI resulted in a correct change in the imaging-based diagnosis and ensuing virtual treatment in four cases (1.2%: two metastatic instead of nonmetastatic, one multifocal instead of single, one unilateral instead of bilateral adrenal) at the cost of an incorrect change in seven cases (2.1%: four metastatic instead of nonmetastatic, two multifocal instead of unifocal and one bilateral instead of unilateral adrenal). Conclusions For the initial localization of PPGL, the addition of 123I-MIBG scintigraphy to CT/MRI rarely improves the diagnostic accuracy at the cost of incorrect interpretation in others, even when 123I-MIBG scintigraphy is restricted to patients who are at risk for metastatic disease. In this setting, the impact of 123I-MIBG scintigraphy on clinical decision-making appears very limited.

BACKGROUND Pheochromocytomas are rare catecholamine-producing tumors derived in more than 30% of cases from mutations in 9 tumor-susceptibility genes identified to date, including von Hippel-Lindau tumor suppressor (VHL); succinate dehydrogenase complex, subunit B, iron sulfur (Ip) (SDHB); and succinate dehydrogenase complex, subunit D, integral membrane protein (SDHD). Testing of multiple genes is often undertaken at considerable expense before a mutation is detected. This study assessed whether measurements of plasma metanephrine, normetanephrine, and methoxytyramine, the O-methylated metabolites of catecholamines, might help to distinguish different hereditary forms of the tumor. METHODS Plasma concentrations of O-methylated metabolites were measured by liquid chromatography with electrochemical detection in 173 patients with pheochromocytoma, including 38 with multiple endocrine neoplasia type 2 (MEN 2), 10 with neurofibromatosis type 1 (NF1), 66 with von Hippel-Lindau (VHL) syndrome, and 59 with mutations of SDHB or SDHD. RESULTS In contrast to patients with VHL, SDHB, and SDHD mutations, all patients with MEN 2 and NF1 presented with tumors characterized by increased plasma concentrations of metanephrine (indicating epinephrine production). VHL patients usually showed solitary increases in normetanephrine (indicating norepinephrine production), whereas additional or solitary increases in methoxytyramine (indicating dopamine production) characterized 70% of patients with SDHB and SDHD mutations. Patients with NF1 and MEN 2 could be discriminated from those with VHL, SDHB, and SDHD gene mutations in 99% of cases by the combination of normetanephrine and metanephrine. Measurements of plasma methoxytyramine discriminated patients with SDHB and SDHD mutations from those with VHL mutations in an additional 78% of cases. CONCLUSIONS The distinct patterns of plasma catecholamine O-methylated metabolites in patients with hereditary pheochromocytoma provide an easily used tool to guide cost-effective genotyping of underlying disease-causing mutations.