Presentation description

Immune-related adverse events (irAEs) are critical complications of immune checkpoint inhibitors (ICIs) in cancer treatment, often necessitating treatment discontinuation for patient safety. This study aims to develop an algorithm using real-world data from the Flatiron Health Database to identify treatment discontinuations due to irAEs in cancer patients. Data from the Flatiron Health Database, involving patients with advanced melanoma, lung, bladder, colorectal, and head and neck cancers, were analyzed using R software. Four algorithms were developed:

Algorithm 1: Included patients diagnosed with an irAE.
Algorithm 2: Included patients with irAE diagnoses subsequent steroid use
Algorithm 3: Added patients with no subsequent ICI after an irAE diagnosis.
Algorithm 4: Combined irAE diagnoses, subsequent steroid use, and no subsequent ICI.

Steroids assessed included Dexamethasone, Methylprednisolone, Prednisone, and several others. Diagnostic codes were used to identify irAEs, and cross tabulations compared patient distributions in each algorithm category with those flagged for treatment cancellation and those who died within 30 days of their first irAE diagnosis. Across all cancers, 104,615 patients were analyzed. The algorithms identified treatment cancellations as follows:

Algorithm 1: 34.28% of patients (n = 61,181)
Algorithm 2: 37.39% (n = 18,081)
Algorithm 3: 42.73% (n = 20,024)
Algorithm 4: 43.54% (n = 5,329)

Mortality rates within 30 days of the first irAE were:

Algorithm 1: 5.67%
Algorithm 2: 3.69%
Algorithm 3: 1.86%
Algorithm 4: 1.01%