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Oxford University Press, The Journal of Clinical Endocrinology & Metabolism, 2023

DOI: 10.1210/clinem/dgad044

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Prevalence of functioning adrenal incidentalomas: a systematic review and meta-analysis

This paper was not found in any repository, but could be made available legally by the author.
This paper was not found in any repository, but could be made available legally by the author.

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Abstract

AbstractContextAdrenal hyperfunction is associated with an increased risk of cardiometabolic complications in subjects with adrenal incidentaloma (AI). Reliable prevalence estimates of functioning AIs are important to direct resources allocations.ObjectiveTo assess the prevalence of autonomous/possible autonomous cortisol secretion (ACS), primary aldosteronism (PA), pheochromocytoma (PHEO), and Cushing syndrome (CS) in patients with AI.MethodsWe performed a comprehensive search of multiple databases (PubMed, Ovid MEDLINE, Web of Science) for potentially relevant studies without language restriction, up to February 2022. Of the 1661 publications evaluated at title and abstract levels, 161 were examined as full text and 36 were included. Study level clinical data were extracted by 3 independent reviewers.ResultsThe overall prevalence of functioning AIs was 27.5% (95% CI 23.0, 32.5). ACS/possible ACS, with a prevalence of 11.7% (95% CI 8.6, 15.7), was the most frequent hormonal alteration, while PA occurred in 4.4% of the patients (95% CI 3.1, 6.2). Subgroup analysis showed that PA was more prevalent in patients from Asia than in patients from Europe/America; in contrast, ACS/possible ACS had a lower prevalence in Asian countries. At meta-regression analysis, the prevalence of ACS/possible ACS was influenced by the proportion of female patients, while the prevalence of PA was positively associated with the proportion of patients with hypertension and the publication year. Finally, PHEO and CS prevalence were 3.8% (95% CI 2.8, 5.0) and 3.1% (95% CI 2.3, 4.3) respectively.ConclusionThis meta-analysis provides extensive data on the prevalence of functioning AIs and the factors affecting heterogeneity in prevalence estimates.