Fadlullah Muhammad Zaki Hidayatullah, Lin Ching-Nung, Coleman Samuel, Young Arabella, Naqash Abdul Rafeh, Hu-Lieskovan Siwen, Tan Aik Choon
Department of Oncological Sciences, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
Department of Biomedical Informatics, Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA.
Oncologist. 2024 May 3;29(5):415-421. doi: 10.1093/oncolo/oyae012.
Immune checkpoint inhibitors (ICIs) have significantly improved the survival of patients with cancer and provided long-term durable benefit. However, ICI-treated patients develop a range of toxicities known as immune-related adverse events (irAEs), which could compromise clinical benefits from these treatments. As the incidence and spectrum of irAEs differs across cancer types and ICI agents, it is imperative to characterize the incidence and spectrum of irAEs in a pan-cancer cohort to aid clinical management.
We queried >400 000 trials registered at ClinicalTrials.gov and retrieved a comprehensive pan-cancer database of 71 087 ICI-treated participants from 19 cancer types and 7 ICI agents. We performed data harmonization and cleaning of these trial results into 293 harmonized adverse event categories using Medical Dictionary for Regulatory Activities.
We developed irAExplorer (https://irae.tanlab.org), an interactive database that focuses on adverse events in patients administered with ICIs from big data mining. irAExplorer encompasses 71 087 distinct clinical trial participants from 343 clinical trials across 19 cancer types with well-annotated ICI treatment regimens and harmonized adverse event categories. We demonstrated a few of the irAE analyses through irAExplorer and highlighted some associations between treatment- or cancer-specific irAEs.
The irAExplorer is a user-friendly resource that offers exploration, validation, and discovery of treatment- or cancer-specific irAEs across pan-cancer cohorts. We envision that irAExplorer can serve as a valuable resource to cross-validate users' internal datasets to increase the robustness of their findings.
免疫检查点抑制剂（ICI）显著提高了癌症患者的生存率，并带来了长期持久的益处。然而，接受ICI治疗的患者会出现一系列被称为免疫相关不良事件（irAE）的毒性反应，这可能会削弱这些治疗的临床益处。由于不同癌症类型和ICI药物的irAE发生率和谱不同，因此必须在泛癌队列中描述irAE的发生率和谱，以辅助临床管理。
我们查询了在ClinicalTrials.gov注册的40多万项试验，并从19种癌症类型和7种ICI药物中检索了一个包含71087名接受ICI治疗参与者的综合泛癌数据库。我们使用《药物监管活动医学词典》对这些试验结果进行了数据协调和清理，将其归纳为293个协调一致的不良事件类别。
irAExplorer是一个用户友好的资源，可用于探索、验证和发现泛癌队列中治疗或癌症特异性的irAE。我们设想，irAExplorer可以作为一个有价值的资源，用于交叉验证用户的内部数据集，以增强其研究结果的稳健性。
