Beuschlein, Felix

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.

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. Adrenal aldosterone excess is the most common cause of secondary hypertension and is associated with increased cardiovascular morbidity. However, adverse metabolic risk in primary aldosteronism extends beyond hypertension, with increased rates of insulin resistance, type 2 diabetes, and osteoporosis, which cannot be easily explained by aldosterone excess. METHODS. We performed mass spectrometry–based analysis of a 24-hour urine steroid metabolome in 174 newly diagnosed patients with primary aldosteronism (103 unilateral adenomas, 71 bilateral adrenal hyperplasias) in comparison to 162 healthy controls, 56 patients with endocrine inactive adrenal adenoma, 104 patients with mild subclinical, and 47 with clinically overt adrenal cortisol excess. We also analyzed the expression of cortisol-producing CYP11B1 and aldosterone-producing CYP11B2 enzymes in adenoma tissue from 57 patients with aldosterone-producing adenoma, employing immunohistochemistry with digital image analysis. RESULTS. Primary aldosteronism patients had significantly increased cortisol and total glucocorticoid metabolite excretion (all P < 0.001), only exceeded by glucocorticoid output in patients with clinically overt adrenal Cushing syndrome. Several surrogate parameters of metabolic risk correlated significantly with glucocorticoid but not mineralocorticoid output. Intratumoral CYP11B1 expression was significantly associated with the corresponding in vivo glucocorticoid excretion. Unilateral adrenalectomy resolved both mineralocorticoid and glucocorticoid excess. Postoperative evidence of adrenal insufficiency was found in 13 (29%) of 45 consecutively tested patients. CONCLUSION. Our data indicate that glucocorticoid cosecretion is frequently found in primary aldosteronism and contributes to associated metabolic risk. Mineralocorticoid receptor antagonist therapy alone may not be sufficient to counteract adverse metabolic risk in medically treated patients with primary aldosteronism. FUNDING. Medical Research Council UK, Wellcome Trust, European Commission.