Dataset Information

Urine steroid metabolomics for the differential diagnosis of adrenal incidentalomas in the EURINE-ACT study: a prospective test validation study.

ABSTRACT: BACKGROUND:Cross-sectional imaging regularly results in incidental discovery of adrenal tumours, requiring exclusion of adrenocortical carcinoma (ACC). However, differentiation is hampered by poor specificity of imaging characteristics. We aimed to validate a urine steroid metabolomics approach, using steroid profiling as the diagnostic basis for ACC. METHODS:We did a prospective multicentre study in adult participants (age ?18 years) with newly diagnosed adrenal masses. We assessed the accuracy of diagnostic imaging strategies based on maximum tumour diameter (?4 cm vs <4 cm), imaging characteristics (positive vs negative), and urine steroid metabolomics (low, medium, or high risk of ACC), separately and in combination, using a reference standard of histopathology and follow-up investigations. With respect to imaging characteristics, we also assessed the diagnostic utility of increasing the unenhanced CT tumour attenuation threshold from the recommended 10 Hounsfield units (HU) to 20 HU. FINDINGS:Of 2169 participants recruited between Jan 17, 2011, and July 15, 2016, we included 2017 from 14 specialist centres in 11 countries in the final analysis. 98 (4·9%) had histopathologically or clinically and biochemically confirmed ACC. Tumours with diameters of 4 cm or larger were identified in 488 participants (24·2%), including 96 of the 98 with ACC (positive predictive value [PPV] 19·7%, 95% CI 16·2-23·5). For imaging characteristics, increasing the unenhanced CT tumour attenuation threshold to 20 HU from the recommended 10 HU increased specificity for ACC (80·0% [95% CI 77·9-82·0] vs 64·0% [61·4-66.4]) while maintaining sensitivity (99·0% [94·4-100·0] vs 100·0% [96·3-100·0]; PPV 19·7%, 16·3-23·5). A urine steroid metabolomics result indicating high risk of ACC had a PPV of 34·6% (95% CI 28·6-41·0). When the three tests were combined, in the order of tumour diameter, positive imaging characteristics, and urine steroid metabolomics, 106 (5·3%) participants had the result maximum tumour diameter of 4 cm or larger, positive imaging characteristics (with the 20 HU cutoff), and urine steroid metabolomics indicating high risk of ACC, for which the PPV was 76·4% (95% CI 67·2-84·1). 70 (3·5%) were classified as being at moderate risk of ACC and 1841 (91·3%) at low risk (negative predictive value 99·7%, 99·4-100·0). INTERPRETATION:An unenhanced CT tumour attenuation cutoff of 20 HU should replace that of 10 HU for exclusion of ACC. A triple test strategy of tumour diameter, imaging characteristics, and urine steroid metabolomics improves detection of ACC, which could shorten time to surgery for patients with ACC and help to avoid unnecessary surgery in patients with benign tumours. FUNDING:European Commission, UK Medical Research Council, Wellcome Trust, and UK National Institute for Health Research, US National Institutes of Health, the Claire Khan Trust Fund at University Hospitals Birmingham Charities, and the Mayo Clinic Foundation for Medical Education and Research.

SUBMITTER: Bancos I

PROVIDER: S-EPMC7447976 | biostudies-literature | 2020 Sep

REPOSITORIES: biostudies-literature

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Urine steroid metabolomics for the differential diagnosis of adrenal incidentalomas in the EURINE-ACT study: a prospective test validation study.

Bancos Irina I Taylor Angela E AE Chortis Vasileios V Sitch Alice J AJ Jenkinson Carl C Davidge-Pitts Caroline J CJ Lang Katharina K Tsagarakis Stylianos S Macech Magdalena M Riester Anna A Deutschbein Timo T Pupovac Ivana D ID Kienitz Tina T Prete Alessandro A Papathomas Thomas G TG Gilligan Lorna C LC Bancos Cristian C Reimondo Giuseppe G Haissaguerre Magalie M Marina Ljiljana L Grytaas Marianne A MA Sajwani Ahmed A Langton Katharina K Ivison Hannah E HE Shackleton Cedric H L CHL Erickson Dana D Asia Miriam M Palimeri Sotiria S Kondracka Agnieszka A Spyroglou Ariadni A Ronchi Cristina L CL Simunov Bojana B Delivanis Danae A DA Sutcliffe Robert P RP Tsirou Ioanna I Bednarczuk Tomasz T Reincke Martin M Burger-Stritt Stephanie S Feelders Richard A RA Canu Letizia L Haak Harm R HR Eisenhofer Graeme G Dennedy M Conall MC Ueland Grethe A GA Ivovic Miomira M Tabarin Antoine A Terzolo Massimo M Quinkler Marcus M Kastelan Darko D Fassnacht Martin M Beuschlein Felix F Ambroziak Urszula U Vassiliadi Dimitra A DA O'Reilly Michael W MW Young William F WF Biehl Michael M Deeks Jonathan J JJ Arlt Wiebke W

The lancet. Diabetes & endocrinology 20200723 9

<h4>Background</h4>Cross-sectional imaging regularly results in incidental discovery of adrenal tumours, requiring exclusion of adrenocortical carcinoma (ACC). However, differentiation is hampered by poor specificity of imaging characteristics. We aimed to validate a urine steroid metabolomics approach, using steroid profiling as the diagnostic basis for ACC.<h4>Methods</h4>We did a prospective multicentre study in adult participants (age ≥18 years) with newly diagnosed adrenal masses. We assess ...[more]

PMID: 32711725

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Project description:OBJECTIVE:To determine all-cause mortality risk in patients with and without adrenal incidentaloma. METHODS:Retrospective cohort study of patients with CT abdomen performed within 24 h of emergency room presentation at an academic medical center from January 1, 2005, to December 31, 2009, without history of adrenal disease, adrenal lab testing, or cancer. Incidentaloma cohort identified by database query of imaging reports followed by manual review and matched to no-nodule controls at 3:1 on age?±?1 year and exam date ±?3 months. Mortality ascertained by in-hospital deaths and National Death Index query. Survival analysis performed with Kaplan-Meier curves and Cox proportional hazards models. RESULTS:Among 42,575 adults with abdominal CT exams, 969 adrenal incidentaloma patients and 2907 no-nodule controls were identified. All 3876 individuals entered survival analysis with 31,182 person-years at risk (median follow-up 8.9 years [IQR, 6.9-10.7]). All-cause mortality was significantly higher among those with adrenal incidentalomas (353/969, 36.4%) compared with those without (919/2907, 31.6%; mortality difference 7.6 per 1000 person-years; multivariable-adjusted hazard ratio [aHR] 1.14; 95% CI, 1.003-1.29). Exploratory analyses, limited by missing covariates, found that adrenal incidentalomas were associated with significantly increased incidence of malignancy (aHR 1.61; 95% CI, 1.22-2.12), diabetes (aHR 1.43; 95% CI, 1.18-1.71), heart failure (aHR 1.32; 95% CI, 1.07-1.63), peripheral vascular disease (aHR 1.28; 95% CI, 1.95-1.56), renal disease (aHR 1.21; 95% CI, 1.01-1.44), and chronic pulmonary disease (aHR 1.22; 95% CI, 1.01-1.46) compared with controls. CONCLUSIONS:Adrenal incidentalomas are associated with increased mortality and may represent a clinically valuable biomarker. KEY POINTS:• Adrenal incidentalomas are associated with increased mortality. • Adrenal incidentaloma size is not predictive of mortality. • On exploratory analyses, adrenal incidentalomas are associated with chronic illnesses.

Project description:There is a lack of experimental reference materials and standards for metabolomics measurements, such as urine, plasma, and other human fluid samples. Reasons include difficulties with supply, distribution, and dissemination of information about the materials. Additionally, there is a long lead time because reference materials need their compositions to be fully characterized with uncertainty, a labor-intensive process for material containing thousands of relevant compounds. Furthermore, data analysis can be hampered by different methods using different software by different vendors. In this work, we propose an alternative implementation of reference materials. Instead of characterizing biological materials based on their composition, we propose using untargeted metabolomic data such as nuclear magnetic resonance (NMR) or gas and liquid chromatography-mass spectrometry (GC-MS and LC-MS) profiles. The profiles are then distributed with the material accompanying the certificate, so that researchers can compare their own metabolomic measurements with the reference profiles. To demonstrate this approach, we conducted an interlaboratory study (ILS) in which seven National Institute of Standards and Technology (NIST) urine Standard Reference Material®s (SRM®s) were distributed to participants, who then returned the metabolomic data to us. We then implemented chemometric methods to analyze the data together to estimate the uncertainties in the current measurement techniques. The participants identified similar patterns in the profiles that distinguished the seven samples. Even when the number of spectral features is substantially different between platforms, a collective analysis still shows significant overlap that allows reliable comparison between participants. Our results show that a urine suite such as that used in this ILS could be employed for testing and harmonization among different platforms. A limited quantity of test materials will be made available for researchers who are willing to repeat the protocols presented here and contribute their data.

Project description:BackgroundHeterogeneity of prostate cancer (PCa) contributes to inaccurate cancer screening and diagnosis, unnecessary biopsies, and overtreatment. We intended to develop non-invasive urine tests for accurate PCa diagnosis to avoid unnecessary biopsies.MethodsUsing a machine learning program, we identified a 25-Gene Panel classifier for distinguishing PCa and benign prostate. A non-invasive test using pre-biopsy urine samples collected without digital rectal examination (DRE) was used to measure gene expression of the panel using cDNA preamplification followed by real-time qRT-PCR. The 25-Gene Panel urine test was validated in independent multi-center retrospective and prospective studies. The diagnostic performance of the test was assessed against the pathological diagnosis from biopsy by discriminant analysis. Uni- and multivariate logistic regression analysis was performed to assess its diagnostic improvement over PSA and risk factors. In addition, the 25-Gene Panel urine test was used to identify clinically significant PCa. Furthermore, the 25-Gene Panel urine test was assessed in a subset of patients to examine if cancer was detected after prostatectomy.ResultsThe 25-Gene Panel urine test accurately detected cancer and benign prostate with AUC of 0.946 (95% CI 0.963-0.929) in the retrospective cohort (n?=?614), AUC of 0.901 (0.929-0.873) in the prospective cohort (n?=?396), and AUC of 0.936 (0.956-0.916) in the large combination cohort (n?=?1010). It greatly improved diagnostic accuracy over PSA and risk factors (p?<?0.0001). When it was combined with PSA, the AUC increased to 0.961 (0.980-0.942). Importantly, the 25-Gene Panel urine test was able to accurately identify clinically significant and insignificant PCa with AUC of 0.928 (95% CI 0.947-0.909) in the combination cohort (n?=?727). In addition, it was able to show the absence of cancer after prostatectomy with high accuracy.ConclusionsThe 25-Gene Panel urine test is the first highly accurate and non-invasive liquid biopsy method without DRE for PCa diagnosis. In clinical practice, it may be used for identifying patients in need of biopsy for cancer diagnosis and patients with clinically significant cancer for immediate treatment, and potentially assisting cancer treatment follow-up.

Project description:BackgroundIncidental adrenal masses are commonly detected during imaging for other pathologies. 10% of the elderly population has an 'adrenal incidentaloma', up to 20% of these show low-grade autonomous cortisol secretion and 60% of patients with autonomous cortisol secretion have insulin resistance. Cortisol excess is known to cause insulin resistance, an independent cardiovascular risk marker, however in patients with adrenal incidentalomas it is unknown whether their insulin resistance is secondary to the excess cortisol and therefore potentially reversible. In a proof of concept study we examined the short-term effects of glucocorticoid receptor (GR) antagonism in patients with an adrenal incidentaloma to determine whether their insulin resistance was reversible.Methodology/principal findingsIn a prospective open-label pilot study, six individuals with adrenal incidentalomas and autonomous cortisol secretion were treated with mifepristone (a GR antagonist) 200 mg twice daily and studied for 4 weeks on a Clinical Research Facility. Insulin resistance at four weeks was assessed by insulin resistance indices, lnHOMA-IR and lnMatsuda, and AUC insulin during a 2-hour glucose tolerance test. Biochemical evidence of GR blockade was shown in all individuals and across the group there was a significant reduction in insulin resistance: lnHOMA-IR (1.0vs0.6; p = 0.03), lnHOMA-%beta (4.8vs4.3; p = 0.03) and lnMatsuda (1.2vs1.6; p = 0.03). Five out of six individuals showed a reduction in insulin AUC >7237 pmol/l.min, and in two patients this showed a clinically significant cardiovascular benefit (as defined by the Helsinki heart study).ConclusionsShort-term GR antagonism is sufficient to reduce insulin resistance in some individuals with adrenal incidentalomas and mild cortisol excess. Further assessment is required to assess if the responses may be used to stratify therapy as adrenal incidentalomas may be a common remediable cause of increased cardiovascular risk.Trial registrationClinicalTrials.gov NCT00721201.

Project description:Objective: Germline ARMC5 mutations are considered to be the main genetic cause of primary macronodular adrenal hyperplasia (PMAH). PMAH is associated with high variability of cortisol secretion caused from subclinical hypercortisolism to overt Cushing's syndrome (CS), in general due to bilateral adrenal nodules and rarely could also be due to non-synchronic unilateral adrenal nodules. The frequency of adrenal incidentalomas (AI) associated with PMAH is unknown. This study evaluated germline allelic variants of ARMC5 in patients with bilateral and unilateral AI and in patients with overt CS associated with bilateral adrenal nodules. Methods: We performed a retrospective multicenter study involving 123 patients with AI (64 bilateral; 59 unilateral). We also analyzed 20 patients with ACTH pituitary independent overt CS associated with bilateral adrenal nodules. All patients underwent germline genotyping analysis of ARMC5; abdominal CT and were classified as normal, possible or autonomous cortisol secretion, according to the low doses of dexamethasone suppression test. Results: We identified only one pathogenic allelic variant among the patients with bilateral AI. We did not identify any pathogenic allelic variants of ARMC5 in patients with unilateral AI. Thirteen out of 20 patients (65%) with overt CS and bilateral adrenal nodules were carriers of pathogenic germline ARMC5 allelic variants, all previously described. The germline ARMC5 mutation was observed in only one patient with bilateral AI; it was associated with autonomous cortisol secretion and showed to be a familial form. Conclusion: The rarity of germline ARMC5 mutations in AI points to other molecular mechanisms involved in this common adrenal disorder and should be investigated. In contrast, patients with overt Cushing's syndrome and bilateral adrenal nodules had the presence of ARMC5 mutations that were with high prevalence and similar to the literature. Therefore, we recommend the genetic analysis of ARMC5 for patients with established Cushing's syndrome and bilateral adrenal nodules rather than patients with unilateral AI.

Dataset Information

Urine steroid metabolomics for the differential diagnosis of adrenal incidentalomas in the EURINE-ACT study: a prospective test validation study.

Publications

Urine steroid metabolomics for the differential diagnosis of adrenal incidentalomas in the EURINE-ACT study: a prospective test validation study.

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