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1270 Predicting risk factors for severe immune-related adverse events requiring hospitalization from checkpoint inhibitors
  1. Jordyn Silverstein1,
  2. Michelle Wang1,
  3. Francis Wright1,
  4. Joy Huang1,
  5. Jessica Santhakumar1,
  6. Eva Duvalyan1,
  7. Arabella Young2,
  8. Daniel Kim1,
  9. Kimberly De Dios1,
  10. Sam Brondfield1 and
  11. Zoe Quandt1
  1. 1University of California, San Francisco, San Francisco, CA, USA
  2. 2Huntsman Cancer Institute, University of Utah, Salt Lake City, UT, USA


Background As immune checkpoint inhibitors (CPI) are increasingly approved for the treatment of multiple cancer types, hospitalizations related to severe immune-related adverse events (irAE) will increase in tandem. Here, we identify risk factors that predict hospitalization from an irAE to help guide clinical decision-making for future patients on CPI therapy.

Methods This retrospective case-control study included patients exposed to CPIs who were hospitalized from 1/2012 to 12/2020 at our tertiary care hospital by computationally extracting data from the electronic health record. We then performed manual chart review to include only confirmed irAE-related hospitalizations. Controls were patients who had received CPI therapy without an irAE hospitalization matched by gender, age and cancer type to the cases. Controls were manually chart reviewed for data abstraction and to confirm there was not an irAE hospitalization. We assessed association of hospitalization with variables of interest using student t and fisher exact as appropriate. We included variables in the multivariate logistic regression analysis that had p < 0.10 in the univariate analysis.

Results Of 3137 patients treated with CPIs, 114 (3.6%) were hospitalized for irAEs, resulting in 124 hospitalizations. In this preliminary analysis, 158 controls were reviewed. Patients who were hospitalized did not have significant differences in age, gender, race, cancer type, body mass index, Eastern Cooperative Oncology Group (ECOG) performance status, smoking and alcohol history, and Charlson Comorbidity Index (table 1). The hospitalized group had more patients treated with combination therapy (PD-1/L1 and CTLA-4) (33.3% vs 13.3%) and less PD-1/L1 monotherapy (60.5% vs 82.9%) (p=0.001). The hospitalized group also had less prior CPI therapy (12.9% vs 31.0%, p=0.001). Patients hospitalized for an irAE had more pre-existing autoimmune conditions although not statistically significant (13.7% vs 6.9%, p=0.065). After multivariate logistic regression, pre-existing autoimmune condition (OR 2.41, 95% CI: 1.01–5.75 p=0.048) and combination immunotherapy (4.02, 2.13–7.59 p<0.001) was associated with increased odds of hospitalization, while prior CPI therapy was associated with decreased odds (0.32, 0.16–0.65 p=0.001) (table 2).

Conclusions This real-world data suggest patients who have a pre-existing autoimmune condition or are being treated with combination immunotherapy had higher odds of an irAE hospitalization, while tolerating prior CPI therapy decreased odds of hospitalization. Understanding who is at risk for these events is critical both for weighing the risks and benefits of therapy, monitoring for toxicities, as well as eventually developing treatments that can prevent, modify or treat irAEs.

Ethics Approval This study was approved by the UCSF Human Research Protection Program [#17–22987].

Abstract 1270 Table 1

Baseline demographics and univariate of cases vs matched controls. *Comparing white to other races/ethnicities, **comparing ever used alcohol (prior or current) to never, ***comparing autoimmune condition to no autoimmune condition, comparing all cancers to melanoma

Abstract 1270 Table 2

Multivariate logistic regression analysis to predict hospitalization from an irAE

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