Spontaneous and Immune Checkpoint Inhibitor-Induced Autoimmune Diseases: Analysis of Temporal Information by Using the Japanese Adverse Drug Event Report Database
- PMID: 34110613
- DOI: 10.1007/s40261-021-01042-5
Spontaneous and Immune Checkpoint Inhibitor-Induced Autoimmune Diseases: Analysis of Temporal Information by Using the Japanese Adverse Drug Event Report Database
Erratum in
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Correction to: Spontaneous and Immune Checkpoint Inhibitor-Induced Autoimmune Diseases: Analysis of Temporal Information by Using the Japanese Adverse Drug Event Report Database.Clin Drug Investig. 2021 Oct;41(10):927-928. doi: 10.1007/s40261-021-01084-9. Clin Drug Investig. 2021. PMID: 34554485 No abstract available.
Abstract
Background and objective: Immune checkpoint inhibitors (ICIs) such as programmed cell death protein 1 (PD-1) and cytotoxic T-lymphocyte antigen 4 (CTLA-4) inhibitors have greatly improved cancer treatment. However, they are associated with immune-related adverse events, including autoimmune diseases (ADs) owing to their immune enhancement effect. As there are few comprehensive studies of ADs by ICIs, it is necessary to analyze the period information of drug-induced ADs. We also assumed that the temporal information may be useful to estimate the similarity of the pathogenic mechanism between spontaneous and ICI-induced ADs.
Methods: A period analysis including the Weibull analysis was performed on ICI-induced ADs using the Japanese Adverse Drug Event Report (JADER) database. For evaluating the similarity of spontaneous and ICI-induced ADs, a hierarchical cluster analysis was conducted to compare the different onset-time ranges.
Results: Type 1 diabetes mellitus, autoimmune colitis, and pemphigoid occurred earlier with CTLA-4 inhibitors (median: 46, 29.5 and 28 days, respectively) than with PD-1 inhibitors (> 130 days). Myasthenia gravis had a median time to onset of approximately 1 month, and the risk of onset would increase over time in ipilimumab combination therapy. This result reveals ADs that require attention. Using cluster analysis, we estimated six clusters with different patterns of onset times. Based on these results and a detailed previous research survey, the possible pathogenesis of drug-induced ADs was also discussed.
Conclusions: This paper describes risk profiles with temporal information of ICI-induced ADs and proposes certain indicators for deciphering the mechanism of AD onset.
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