Serum steroid profiling in the diagnosis of adrenocortical carcinoma: a prospective cohort study

Document Type

Article

Publication Date

9-4-2024

Publication Title

The Journal of clinical endocrinology and metabolism

Abstract

CONTEXT: Guidelines suggest performing urine steroid profiling in patients with indeterminate adrenal tumors to make a noninvasive diagnosis of adrenocortical carcinoma (ACC). However, urine steroid profiling is not widely available.

OBJECTIVE: To determine the accuracy of clinically available serum 11-deoxycortisol, 17OH-progesterone, and 17OH-pregnenolone in diagnosing ACC.

METHODS: We conducted a prospective single-center cohort study of patients with adrenal masses evaluated between 2015-2023. Serum was analyzed by liquid chromatography-mass spectrometry for 17OH-pregnenolone, 17OH-progesterone, 11-deoxycortisol. Reference standard for adrenal mass included histopathology, imaging characteristics, imaging follow up of 2 years, or clinical follow up of 5 years. Localized Generalized Matrix Learning Vector Quantization (LGMLVQ) analysis was used to develop serum steroid score and assessed with area under receiver operating curve (AUROC).

RESULTS: Of 263 patients with adrenal masses, 44 (16.7%) were diagnosed with ACC, 161 (61%) with adrenocortical adenomas (ACAs), 27 (10%) with other adrenal malignancies, and 31 (12%) with other. Hounsfield unit (HU) ≥ 20 was demonstrated in all ACCs, in all but one other adrenal malignancy, and in 58 (31%) ACAs. All 3 steroids were higher in patients with ACCs vs non-ACCs, including when comparing ACCs with functioning ACAs, and with ACAs with HU ≥ 20 (P<0.0001 for all). LGMLVQ analysis yielded a serum steroid score that discriminated between ACC and non-ACC groups with a mean threshold fixed AUROC of 0.823.

CONCLUSIONS: We showed that measurements of 11-deoxycortisol, 17OH-progesterone, and 17OH-pregnenolone could be valuable in diagnosing ACC. After appropriate validation, serum steroid score could be integrated in clinical practice.

PubMed ID

39231247

ePublication

ePub ahead of print

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