Classification of microadenomas in patients with primary aldosteronism by steroid profiling. Issue 189 (May 2019) - Yang, Yuhong; Burrello, Jacopo; Burrello, Alessio; Eisenhofer, Graeme; Peitzsch, Mirko; Tetti, Martina; Knösel, Thomas; Beuschlein, Felix; Lenders, Jacques W.M.; Mulatero, Paolo; Reincke, Martin; Williams, Tracy Ann
Highlights: Steroid profiling used for random forest modelling of micro-APA, macro-APA and BAH. High accuracy for macro-APA and BAH, low accuracy for micro-APA classification. Micro-APA classification improved using novel diagnostic algorithm. Potential use to select patients with micro-APA for mandatory AVS. Abstract: In primary aldosteronism (PA) the differentiation of unilateral aldosterone-producing adenomas (APA) from bilateral adrenal hyperplasia (BAH) is usually performed by adrenal venous sampling (AVS) and/or computed tomography (CT). CT alone often lacks the sensitivity to identify micro-APAs. Our objectives were to establish if steroid profiling could be useful for the identification of patients with micro-APAs and for the development of an online tool to differentiate micro-APAs, macro-APAs and BAH. The study included patients with PA (n = 197) from Munich (n = 124) and Torino (n = 73) and comprised 33 patients with micro-APAs, 95 with macro-APAs, and 69 with BAH. Subtype differentiation was by AVS, and micro- and macro-APAs were selected according to pathology reports. Steroid concentrations in peripheral venous plasma were measured by liquid chromatography-tandem mass spectrometry. An online tool using a random forest model was built for the classification of micro-APA, macro-APA and BAH. Micro-APA were classified with low specificity (33%) but macro-APA and BAH were correctly classified with high specificity (93%). Improved classification of micro-APAs was achieved using a diagnostic algorithm integrating steroid profiling, CT scanning and AVS procedures limited to patients with discordant steroid and CT results. This would have increased the correct classification of micro-APAs to 68% and improved the overall classification to 92%. Such an approach could be useful to select patients with CT-undetectable micro-APAs in whom AVS should be considered mandatory.