Endocrine practice : official journal of the American College of Endocrinology and the American Association of Clinical Endocrinologists · 2025
Assessment of Drug Induced Thyroid Dysfunction Risk Using the United States Food and Drug Administration Adverse Event Reporting System.
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Li Ruixue, Liu Tianqi, Li Ting, Zhao Zinan, Zhao Fei, Chen Di, Huang Jing, Xu Wenfeng, Jin Pengfei
Аннотация
OBJECTIVE: To quantify drug-specific associations with thyroid dysfunction (TD) using data from FDA Adverse Event Reporting System and to identify agents with significant disproportionality signals.
METHODS: Using data from FDA Adverse Event Reporting System (Q1 2004 to Q1 2025), disproportionality analysis (reporting odds ratio; Bayesian confidence propagation neural network) was employed to assess signals of drug-induced TD. Univariate analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate logistic regression were applied to identify independent risk factors. Time-to-onset analysis was used to evaluate the timing of TD following drug initiation.
RESULTS: A total of 44 317 reports associated with TD were identified, with a higher proportion involving female patients (60.3%). The median patient age was 59 years (interquartile range [IQR]: 45-69 years). Signal detection identified 172 suspect drugs significantly associated with TD. Following disproportionality screening, drug candidates with a reporting odds ratio whose 95% confidence interval lower bound exceeded 1, cell count a > 100, and P-adjust < 0.01 were advanced to LASSO regression. LASSO identified 43 drugs associated with TD. In the multivariable logistic regression model, female sex, the 45-59-year age group, and the 43 drugs were independent risk factors for drug-associated TD. Furthermore, the median time-to-onset for drug-induced TD was 34 days (IQR: 7-105 days), with approximately 75% of cases occurring within the first 100 days of drug initiation.
CONCLUSION: This study identified multiple drugs significantly associated with TD and highlighted sex, age, and specific medications as independent risk factors. These findings support improved pharmacovigilance and clinical awareness of drug-induced TD.
METHODS: Using data from FDA Adverse Event Reporting System (Q1 2004 to Q1 2025), disproportionality analysis (reporting odds ratio; Bayesian confidence propagation neural network) was employed to assess signals of drug-induced TD. Univariate analysis, least absolute shrinkage and selection operator (LASSO) regression, and multivariate logistic regression were applied to identify independent risk factors. Time-to-onset analysis was used to evaluate the timing of TD following drug initiation.
RESULTS: A total of 44 317 reports associated with TD were identified, with a higher proportion involving female patients (60.3%). The median patient age was 59 years (interquartile range [IQR]: 45-69 years). Signal detection identified 172 suspect drugs significantly associated with TD. Following disproportionality screening, drug candidates with a reporting odds ratio whose 95% confidence interval lower bound exceeded 1, cell count a > 100, and P-adjust < 0.01 were advanced to LASSO regression. LASSO identified 43 drugs associated with TD. In the multivariable logistic regression model, female sex, the 45-59-year age group, and the 43 drugs were independent risk factors for drug-associated TD. Furthermore, the median time-to-onset for drug-induced TD was 34 days (IQR: 7-105 days), with approximately 75% of cases occurring within the first 100 days of drug initiation.
CONCLUSION: This study identified multiple drugs significantly associated with TD and highlighted sex, age, and specific medications as independent risk factors. These findings support improved pharmacovigilance and clinical awareness of drug-induced TD.