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Data mining and analysis of adverse event signals associated with teprotumumab using the Food and Drug Administration adverse event reporting system database

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Abstract

Background

Teprotumumab was approved by the US Food and Drug Administration (FDA) for the treatment of thyroid eye disease in 2020. However, its adverse events (AEs) have not been investigated in real-world settings.

Aim

This study aimed to detect and evaluate AEs associated with teprotumumab in the real-world setting by conducting a pharmacovigilance analysis of the FDA Adverse Event Reporting System (FAERS) database.

Method

Reporting odds ratio (ROR) was used to detect risk signals from the data from January 2020 to March 2023 in the FAERS database.

Results

A total of 3,707,269 cases were retrieved, of which 1542 were related to teprotumumab. The FAERS analysis identified 99 teprotumumab-related AE signals in 14 System Organ Classes (SOCs). The most frequent AEs were muscle spasms (n = 287), fatigue (n = 174), blood glucose increase (n = 121), alopecia (n = 120), nausea (n = 118), hyperacusis (n = 117), and headache (n = 117). The AEs with strongest signal strengths were autophony (ROR = 14,475.49), deafness permanent (ROR = 1853.35), gingival recession (ROR = 190.74), deafness neurosensory (ROR = 129.89), nail growth abnormal (ROR = 103.67), onychoclasis (ROR = 73.58), ear discomfort (ROR = 72.88), and deafness bilateral (ROR = 62.46). Eleven positive AE signals were found at the standardized MedDRA queries (SMQs) level, of which the top five SMQs were hyperglycemia/new-onset diabetes mellitus, hearing impairment, gastrointestinal nonspecific symptoms and therapeutic procedures, noninfectious diarrhea, and hypertension. Age significantly increased the risk of hearing impairment.

Conclusion

This study identified potential new and unexpected AE signals of teprotumumab. Our findings emphasize the importance of pharmacovigilance analysis in the real world to identify and manage AEs effectively, ultimately improving patient safety during teprotumumab treatment.

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Funding

This work was supported by the Shanghai Municipal Health Commission.

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Author notes

  1. Sha Zhang and Yidong Wang have contributed equally to this work.

Authors and Affiliations

  1. Department of Pharmacy, Tongji Hospital, School of Medicine, Tongji University, Shanghai, China

    Sha Zhang, Zhan Qi, Shanshan Tong & Deqiu Zhu

  2. Department of Pharmacy, Ren Ji Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China

    Yidong Wang

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  1. Sha Zhang
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Zhang, S., Wang, Y., Qi, Z. et al. Data mining and analysis of adverse event signals associated with teprotumumab using the Food and Drug Administration adverse event reporting system database. Int J Clin Pharm 46, 471–479 (2024). https://doi.org/10.1007/s11096-023-01676-9

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  • DOI: https://doi.org/10.1007/s11096-023-01676-9

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