The Journal of clinical endocrinology and metabolism · 2022
The Changing Face of Drug-induced Adrenal Insufficiency in the Food and Drug Administration Adverse Event Reporting System.
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Raschi Emanuel, Fusaroli Michele, Massari Francesco, Mollica Veronica, Repaci Andrea, Ardizzoni Andrea, Poluzzi Elisabetta, Pagotto Uberto, Di Dalmazi Guido
Аннотация
CONTEXT: Adrenal insufficiency (AI) is a life-threatening condition complicating heterogeneous disorders across various disciplines, with challenging diagnosis and a notable drug-induced component.
OBJECTIVE: This work aimed to describe the spectrum of drug-induced AI through adverse drug event reports received by the US Food and Drug Administration (FDA).
METHODS: A retrospective disproportionality analysis reporting trends of drug-induced AI was conducted on the FDA Adverse Event Reporting System (FAERS) (> 15 000 000 reports since 2004). AE reports were extracted from FAERS over the past 2 decades. Interventions included cases containing any of the preferred terms in the Medical Dictionary for Regulatory Activities describing AI, and signals of disproportionate reporting for drugs recorded in 10 or more cases as primary suspect.
RESULTS: We identified 8496 cases of AI: 97.5% serious, 41.1% requiring hospitalization. AI showed an exponential increase throughout the years, with 5282 (62.2%) cases in 2015 to 2020. We identified 56 compounds associated with substantial disproportionality: glucocorticoids (N = 1971), monoclonal antibodies (N = 1644, of which N = 1330 were associated with immune checkpoint inhibitors-ICIs), hormone therapy (N = 291), anti-infectives (N = 252), drugs for hypercortisolism or adrenocortical cancer diagnosis/treatment (N = 169), and protein kinase inhibitors (N = 138). Cases of AI by glucocorticoids were stable in each 5-year period (22%-27%), whereas those by monoclonal antibodies, largely ICIs, peaked from 13% in 2010 to 2015 to 33% in 2015 to 2020.
CONCLUSION: We provide a comprehensive insight into the evolution of drug-induced AI, highlighting the heterogeneous spectrum of culprit drug classes and the emerging increased reporting of ICIs. We claim for the urgent identification of predictive factors for drug-induced AI, and the establishment of screening and educational protocols for patients and caregivers.
OBJECTIVE: This work aimed to describe the spectrum of drug-induced AI through adverse drug event reports received by the US Food and Drug Administration (FDA).
METHODS: A retrospective disproportionality analysis reporting trends of drug-induced AI was conducted on the FDA Adverse Event Reporting System (FAERS) (> 15 000 000 reports since 2004). AE reports were extracted from FAERS over the past 2 decades. Interventions included cases containing any of the preferred terms in the Medical Dictionary for Regulatory Activities describing AI, and signals of disproportionate reporting for drugs recorded in 10 or more cases as primary suspect.
RESULTS: We identified 8496 cases of AI: 97.5% serious, 41.1% requiring hospitalization. AI showed an exponential increase throughout the years, with 5282 (62.2%) cases in 2015 to 2020. We identified 56 compounds associated with substantial disproportionality: glucocorticoids (N = 1971), monoclonal antibodies (N = 1644, of which N = 1330 were associated with immune checkpoint inhibitors-ICIs), hormone therapy (N = 291), anti-infectives (N = 252), drugs for hypercortisolism or adrenocortical cancer diagnosis/treatment (N = 169), and protein kinase inhibitors (N = 138). Cases of AI by glucocorticoids were stable in each 5-year period (22%-27%), whereas those by monoclonal antibodies, largely ICIs, peaked from 13% in 2010 to 2015 to 33% in 2015 to 2020.
CONCLUSION: We provide a comprehensive insight into the evolution of drug-induced AI, highlighting the heterogeneous spectrum of culprit drug classes and the emerging increased reporting of ICIs. We claim for the urgent identification of predictive factors for drug-induced AI, and the establishment of screening and educational protocols for patients and caregivers.