Background
Cutaneous immune-related adverse events (cirAEs) are the most common form of immune-related adverse events after immune-checkpoint inhibitor (ICI) treatment, affecting up to 40% of ICI recipients and ranging in severity from mild to life-threatening.1 Although the mechanisms underlying cirAEs remain poorly understood, evidence suggests that cirAEs may be early prognostic indicators of therapeutic response.2 3 Identifying cirAE risk factors can thus help stratify ICI candidates at the highest risk of toxicity and shed light on immune response mechanisms during ICI treatment. The goal of this study is to analyze seasonal and regional variation in cirAE development using a multi-center cohort of ICI recipients.
Methods
Briefly, we utilized the TriNetX Dataworks Network which provides deidentified data on more than 90 million patients from 66 health care organizations in the US. We used a validated approach4 based on ICD-10 codes to define the ICI cohort and to identify cirAE cases. We built competing-risks Fine-Gray and Prais-Winsten regression models to test the association between cirAE risk and the season of ICI initiation, while controlling for age, sex, self-reported race and ethnicity, ICI target, ICI year, cancer type, regional variation, and autocorrelation expected in time-series data.
Results
The ICI cohort comprised 15,253 patients between January 2010 and December 2019, of whom 2,413 patients (15.8%) developed cirAEs. The absolute rate of cirAEs was highest in the fall season (43%), followed by the spring (21%), winter (19%), and summer (17%) seasons (table 1). Using competing-risks and Prais-Winsten models, the risk of cirAE was significantly associated with starting ICI in the winter (β, 0.006; 95% CI, 0.001–0.012, P=0.013) (table 2). This seasonality was robust to sensitivity analysis after excluding all diagnoses of eczema which often flares in the winter.
Analysis of geographic variation in cirAE development in the United States revealed the highest rate in the west (35%), followed by the south (29%), northeast (21%), and midwest (16%). Multivariate competing-risks analysis showed significantly increased risk of cirAE development in the west (HR, 2.42; 95% CI, 2.18–2.68; P<0.001), while there was decreased cirAE risk in the northeast (HR, 0.87; 95% CI, 0.77–0.99; P=0.029) (figure 1).
Conclusions
Seasonal and geographic variation in cirAE development was observed. The absolute rate of cirAE diagnoses was highest in the fall, while initiating ICI treatment in the winter was associated with significantly increased risk of cirAE development, after multivariate adjustment and correcting for autocorrelation. Within the U.S., ICI recipients in the west had the highest risk of cirAE development.
References
Thompson LL, Krasnow NA, Chang MS, et al. Patterns of Cutaneous and Noncutaneous Immune-Related Adverse Events Among Patients With Advanced Cancer. JAMA Dermatol. 2021;157(5):577–582. doi:10.1001/jamadermatol.2021.0326
Zhang S, Tang K, Wan G, et al. Cutaneous immune-related adverse events are associated with longer overall survival in advanced cancer patients on immune checkpoint inhibitors: A multi-institutional cohort study. J Am Acad Dermatol. 2023;88(5):1024–1032. doi:10.1016/j.jaad.2022.12.048
Socinski MA, Jotte RM, Cappuzzo F, et al. Association of Immune-Related Adverse Events With Efficacy of Atezolizumab in Patients With Non-Small Cell Lung Cancer: Pooled Analyses of the Phase 3 IMpower130, IMpower132, and IMpower150 Randomized Clinical Trials. JAMA Oncol. 2023;9(4):527–535. doi:10.1001/jamaoncol.2022.7711
Chen W, Wan G, Nguyen N, et al. Identification of cutaneous immune-related adverse events by International Classification of Diseases codes and medication administration. JAAD Int. 2022;9:112–115. doi:10.1016/j.jdin.2022.08.001
Abstract 1251 Table 1
Basic characteristic of the study population
Abstract 1251 Table 2
Prais-Winsten regression of 6-month cirAE risk on ICI start season. Spring was used as a reference group
Abstract 1251 Figure 1
Seasonal and regional variation in cirAEs. (A) Forest plot of the multivariate competing-risks regression model (Fine-Gray) for cirAE development, showing the hazard ratio of cirAE compared to no-irAE controls. Geographic variation is noted. (B and C) Bar graphs showing the frequency of ICI initiation and cirAE diagnosis per month and season, respectively. (D and E) Line graphs showing the predicted 1-year risk of cirAE per month and season, respectively. Predictions were made using the Fine-Gray model from (A)