Large-scale characterization of real-world adverse events (AE) on immune checkpoint inhibitors (ICI)
At ESMO AI & Digital Oncology, we presented our study on the large-scale characterization of real-world adverse events on immune checkpoint inhibitors.
Challenges:
* ICI are used in most cancers but can cause life-long toxicity. Vulnerable populations are understudied in clinical trials.
* Characterizing real-world ICI adverse events is a challenge: treatment-emergent adverse events data are fragmented, often free text, and not all adverse events are ICI-related (e.g. rash may be chemotherapy related or ICI-related).
The study aims:
1. Develop machine-readable phenotypes of potentially ICI-related adverse events
2. Characterize ICI adverse events incidence across regimens and tumor types
3. Estimate toxicity-driven discontinuation of ICI
The study aims:
1. Develop machine-readable phenotypes of potentially ICI-related adverse events
2. Characterize ICI adverse events incidence across regimens and tumor types
3. Estimate toxicity-driven discontinuation of ICI
