A multi-test strategy for adrenal tumours
Authors: Adina F Turcu, Axel K Walch
Journal: The Lancet Diabetes & Endocrinology (2020)

Broadening access to technology and its rapid evolution have transformed clinical care over the past half century. CT and MRI became widely available around 1980, and performance has steadily improved since. Incidental adrenal nodules were detected in only 0·4% of patients undergoing CT scans in the mid to late 1980s, but cross-sectional imaging studies now detect adrenal incidentalomas at least ten times more frequently.1Mendiratta-Lala M Avram A Turcu AF Dunnick NR Adrenal imaging.Endocrinol Metab Clin North Am. 2017; 46: 741-759Summary Full Text Full Text PDF PubMed Scopus (7) Google Scholar In tandem, the refined resolution and the ever increasing imaging volume (3 million in 1980 in the USA, reaching 88 million in 2018) expose numerous incidental findings, including adrenal nodules. Most adrenal incidentalomas are benign, non-functional adrenocortical adenomas.2Fassnacht M Arlt W Bancos I et al.Management of adrenal incidentalomas: European Society of Endocrinology Clinical Practice Guideline in collaboration with the European Network for the Study of Adrenal Tumors.Eur J Endocrinol. 2016; 175: G1-34Crossref PubMed Scopus (611) Google Scholar Adrenal cortical carcinomas (ACCs) are rare, with an overall incidence of only 1–2 cases per million in the general population per year, but they account for roughly 5% of all adrenal incidentalomas.3Else T Kim AC Sabolch A et al.Adrenocortical carcinoma.Endocr Rev. 2014; 35: 282-326Crossref PubMed Scopus (426) Google Scholar An additional 10–20% of patients with incidentally found adrenal masses display features suspicious for malignancy that cannot be resolved even with modern imaging modalities.4Dinnes J Bancos I Ferrante di Ruffano L et al.Imaging for the diagnosis of malignancy in incidentally discovered adrenal masses: a systematic review and meta-analysis.Eur J of Endocrinol. 2016; 175: R51-R64Crossref PubMed Scopus (82) Google Scholar ACC is typically highly aggressive, and timely diagnosis and surgical resection have the highest impact on prognosis. Biopsy does not accurately distinguish between benign and malignant adrenal cortical masses and, therefore, patients with suspicious imaging findings are commonly subjected to multiple radiological studies,2Fassnacht M Arlt W Bancos I et al.Management of adrenal incidentalomas: European Society of Endocrinology Clinical Practice Guideline in collaboration with the European Network for the Study of Adrenal Tumors.Eur J Endocrinol. 2016; 175: G1-34Crossref PubMed Scopus (611) Google Scholar anxiety, and, for many, potentially unnecessary surgery. In 2011, Arlt and colleagues5Arlt W Biehl M Taylor AE et al.Urine steroid metabolomics as a biomarker tool for detecting malignancy in adrenal tumors.J Clin Endocrinol Metab. 2011; 96: 3775-3784Crossref PubMed Scopus (274) Google Scholar reported a retrospective proof-of-principle assessment of urine steroid metabolomics—the combination of mass spectrometry-based steroid profiling with subsequent computational data analysis—as a diagnostic approach for suspicious adrenal incidentalomas. In the extended, international EURINE-ACT validation study, the same group has prospectively assessed this biomarker approach. In The Lancet Diabetes & Endocrinology, Irina Bancos and colleagues6Bancos I Taylor AE Chortis V et al.Urine steroid metabolomics for the differential diagnosis of adrenal incidentalomas in the EURINE-ACT study: a prospective test validation study.Lancet Endocrinol Metab. 2020; (published online July 23.)https://doi.org/10.1016/S2213-8587(20)30218-7Google Scholar describe the use of urine steroid metabolomics to complement imaging in the differential diagnosis of adrenal tumours. With the joint effort of investigators from 14 international centres over 6 years, the EURINE-ACT study included 2017 patients with newly diagnosed adrenal masses, making this the largest prospective study of adrenal incidentalomas so far. The study compared the diagnostic accuracy of initial imaging characteristics of the tumour and urine steroid metabolomics, separately or in combination, with histopathology (where available) or follow-up imaging as the reference standards. As a secondary analysis, they compared the standard CT tumour tissue attenuation threshold of 10 Hounsfield units (HU) with a cutoff of 20 HU. 98 (4·9%) patients were diagnosed as having ACC, all but one of whom had an unenhanced CT scan attenuation >20 HU. Compared with the 10 HU cutoff, using values more than 20 HU sacrificed 1% in sensitivity (100% reduced to 99%) but substantially increased specificity (64% increased to 80%). The authors conclude that the unenhanced CT attenuation cutoff should be raised to more than 20 HU from the 10 HU threshold endorsed by expert guidelines.2Fassnacht M Arlt W Bancos I et al.Management of adrenal incidentalomas: European Society of Endocrinology Clinical Practice Guideline in collaboration with the European Network for the Study of Adrenal Tumors.Eur J Endocrinol. 2016; 175: G1-34Crossref PubMed Scopus (611) Google Scholar A more important finding reported by Bancos and colleagues6Bancos I Taylor AE Chortis V et al.Urine steroid metabolomics for the differential diagnosis of adrenal incidentalomas in the EURINE-ACT study: a prospective test validation study.Lancet Endocrinol Metab. 2020; (published online July 23.)https://doi.org/10.1016/S2213-8587(20)30218-7Google Scholar comes from the use of urine steroid metabolomics. Urine steroid biomarkers were quantified by liquid chromatography-tandem mass spectrometry from 24 h urine specimens collected at diagnosis. A machine learning algorithm classified steroid profiles as indicating low, moderate, or high risk of ACC. The overall positive predictive value of the high-risk steroid profile was higher than for imaging alone (34·6% vs 19·7%) and increased further when combined with either tumour size 4 cm or greater or imaging characteristics suspicious of malignancy. When three criteria were used, they were applied in the order tumour size, imaging characteristics, then urine steroid metabolomics. A result of tumour size of 4 cm or greater, imaging characteristics suspicious for malignancy, and a urine steroid metabolomics profile indicating high risk of ACC had a positive predictive value of 76·4%. The introduction of urine steroid metabolomics into routine clinical practice would provide major advantages, as a high risk score would expedite the surgical tumour removal, avoiding potentially detrimental delays. Nevertheless, we note that while overall the negative predictive value of the proposed test was excellent, specificity was weak. Thus, urine steroid metabolomics should be limited to patients who have adrenal nodules larger than 4 cm and have qualitative imaging characteristics suggestive of malignancy. The EURINE-ACT study results suggest that this subgroup would equate to roughly 12% of patients with adrenal incidentalomas. Unlike CT and MRI, mass spectrometry was long used primarily in research and has been more broadly introduced into clinical laboratories only over the past decade. Advances in mass spectrometry technology, along with the ability to simultaneously quantify many analytes, have boosted interest in its clinical use. So far, the transition of multiplex steroid profiling from research to health care has been hampered by scarce availability of instrumentation and expertise. Additional practical considerations relate to the interpretation of results, which involve metabolites unfamiliar to most clinicians, although the interpretation of complex results by machine learning algorithms partly overcomes this limitation. Furthermore, routine implementation of urine steroid metabolomics will require cross-validation of employed assays against that used to generate the data for the machine learning algorithm to ensure reliable support of clinical decisions. Changes in assays are likely to require updates to computerised algorithms. One possible way to overcome assay variations is the use of cross-validation studies among international laboratories, combined with the use of regionally centralised analysis, which would ensure assay reliability and provide consistent computerised risk classification of steroid profiles. Bancos and colleagues' results in the EURINE-ACT validation study6Bancos I Taylor AE Chortis V et al.Urine steroid metabolomics for the differential diagnosis of adrenal incidentalomas in the EURINE-ACT study: a prospective test validation study.Lancet Endocrinol Metab. 2020; (published online July 23.)https://doi.org/10.1016/S2213-8587(20)30218-7Google Scholar open a new set of questions that will need to be addressed by future research and incorporated in practice guidelines. The best approach to patients classified as having intermediate or moderate risk of malignancy needs to be explored. Whether the diagnostic value of steroid metabolomics could be refined by adding analytes or parameters deserves further investigation. Further information is also needed on whether this test can better inform applications of adrenal biopsy in patients with adrenal nodules that can be conclusively diagnosed by histopathology. While the pace of progress in urine steroid metabolomics remains to be determined, the EURINE-ACT study has established the basis for computerised-assisted diagnostics using steroid profiling in adrenal incidentalomas, and it has illustrated the invaluable power of large-scale international collaborations in advancing clinical medicine. We declare no competing interests. Urine steroid metabolomics for the differential diagnosis of adrenal incidentalomas in the EURINE-ACT study: a prospective test validation studyAn 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. Full-Text PDF Open Access