Identification of cytokine release syndrome and indicators of severity in retrospective databases among patients receiving immunotherapy

Abstract

Abstract Cytokine release syndrome (CRS) can occur following cancer immunotherapies, but is most often mild and of limited duration. International Classification of Diseases (ICD)‐10 codes allowing identification of CRS were introduced in 2020 but may be underutilized. We evaluated the performance of a published claims‐based algorithm to detect CRS (any grade) and high‐grade CRS (HG, grades 2‐5), as well as identified indicators of HG CRS in retrospective data. Adults with low‐grade and HG CRS during an encounter coinciding with administrations of blinatumomab or chimeric antigen receptor‐T therapy were identified in three types of retrospective databases (hospital chargemaster data, electronic health records, and administrative claims). The algorithm's sensitivity in detecting any CRS and HG CRS was reported. A least absolute shrinkage and selection operator (LASSO) regression model was developed to identify indicators of HG CRS. Performance of the model was evaluated using area under the curve (AUC). The sensitivity of the algorithm to detect any grade CRS ranged between 77%–100% and between 8%–80% for HG CRS, depending on the type of database. The LASSO model identified hypotension, positive pressure (including mechanical ventilation), tocilizumab, and vasopressors as indicators of HG CRS. AUC varied between 60% and 75%. The algorithm accurately detected any grade CRS for over three‐quarters of instances, but was not as reliable for HG CRS. Results varied based on database attributes. Hypotension, vasopressors, positive pressure, and tocilizumab were associated with HG CRS and may be methodologically helpful signals of CRS severity in retrospective data.

Keywords

• administrative claims
• bispecific antibodies
• chimeric antigen receptors
• cytokine release syndrome
• drug‐related side effects and adverse reactions
• electronic health records