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Endocrine Abstracts (2016) 41 OC1.4 | DOI: 10.1530/endoabs.41.OC1.4

1Institute of Metabolism and Systems Research, University of Birmingham, Birmingham, UK; 2Centre for Endocrinology, Diabetes and Metabolism, Birmingham Health Partners, Birmingham, UK; 3Institute of Applied Health, University of Birmingham, Birmingham, UK; 4Endocrinology in Charlottenburg, Berlin, Germany; 5University of Turin, Turin, Italy; 6Unversity of Florence, Florence, Italy; 7Attikon Hospital, Athens, Greece; 8University of Warsaw, Warsaw, Poland; 9University of Galway, Galway, Ireland; 10Trinity College, Dublin, Ireland; 11Rene Descartes University, Paris, France; 12Ludwig-Maximilians-University of Munich, Munich, Germany; 13University of Wuerzburg, Wuerzburg, Germany; 14University of Groningen, Gronigen, The Netherlands.


Context: Adrenocortical carcinoma (ACC) is an aggressive malignancy with high recurrence rates. Regular post-operative follow-up imaging is essential, but associated with high radiation exposure and frequent diagnostic ambiguity. Urine steroid metabolomics has been described as a novel diagnostic tool for the detection of adrenocortical malignancy. Here we present the first clinical study assessing the performance of this innovative approach in the follow-up of patients with complete (R0) ACC resection.

Patients and Methods: We included 142 ACC patients from 13 centres registered with the European Network for the Study of Adrenal Tumours (ENSAT). We selected all patients recorded 2008-2015 fulfilling the following criteria: 1) recorded on the ENSAT registry as confirmed ACC with R0 primary tumour resection; 2) availability of at least two postoperative 24-hour urines, one whilst disease-free and the other after recurrence. The urine steroid metabolome was analysed by gas chromatography-mass spectrometry, with quantification of 38 distinct steroid metabolites. Biochemical detection of ACC recurrence was judged both by expert review and a machine learning-based computational algorithm.

Results: Recurrent disease was detected by imaging in 28 of 142 patients after a median of 21 (IQR 5–28) months following R0 resection. Steroid metabolome analysis diagnosed disease recurrence at the time of first abnormal imaging or earlier in 19/28 cases. The sensitivity of this approach was highest in patients who had provided a pre-operative urine sample (10/11 cases diagnosed correctly). Similarly, ACC recurrence was detected correctly in 11/12 patients not receiving adjuvant mitotane. By contrast, in patients on adjuvant mitotane, and hence downregulated global steroidogenesis, sensitivity was reduced (8/16 detected). In 8 patients, biochemical recurrence detection pre-dated the first radiological evidence of recurrence by >2 (range 3–10) months.

Conclusion: Our study provides proof-of-principle evidence for urine steroid metabolomics as a sensitive diagnostic tool for the prediction of ACC recurrence following R0 resection.

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