New Clinical Decision Support Score Based on Steroid Hormone Profiling in the Diagnosis of MACS

Overview

The recent development of quantitative steroid metabolome profiling could be of interest for the positive diagnosis of mild autonomous cortisol-secreting adenoma (MACS). The aim of the study is to develop a predictive model of MACS status or non-secreting adenoma (NSA) based on a panel of 19 serum steroids and three clinico-biological parameters (body mass index or BMI, fasting glycaemia, blood pressure) and to estimate its performance for the diagnosis of MACS in a cohort of patients followed in the endocrinology department of Bordeaux University Hospital.

Steroid assays are a central element in the aetiological diagnosis of adrenal tumors, but they are still limited to single assays (e.g. cortisol in Cushing's syndrome, aldosterone in primary hyperaldosteronism, etc.) which only partially reflect the endocrine disturbances caused by adrenal pathologies. The recent development of quantitative profiling of the circulating steroidome could lead to a reconsideration of the role of these single steroid assays in endocrinology. This involves simultaneously measuring of multiple steroids from a single blood or urine sample using liquid chromatography-mass spectrometry (LC-MS/MS). The steroid fingerprint obtained enables adrenal masses to be better characterised. Using machine learning methods, a predictive model of MACS status or NSA based on a panel of 19 serum steroids measured by LC-MS/MS and three clinico-biological parameters (body mass index or BMI, fasting glycaemia, blood pressure) will be develop. The blood sample used for the steroid assay will be taken at inclusion during a blood test carried out as part of routine care. Clinical, biological and morphological data obtained during the 24 months of study follow-up and as part of routine care will be collected retrospectively. All assays will be carried out in the hormonology laboratory of Bordeaux University Hospital (BUH) by LC-MS/MS. The development of the MACS/ANS status prediction model will be carried out by the BUH Methodological Support Unit for Clinical and Epidemiological Research (USMR). The performance and prognostic value of this new tool will be estimated in a cohort of patients followed in the BUH endocrinology department.

Conditions