318 Immune checkpoint inhibitor-induced endocrinopathies in a large prospective cohort of Black and White cancer patients
Year: 2025
Type: article
Abstract: Objectives/Goals: Knowledge about predictive factors for immune-related endocrinopathies can help identify appropriate populations for specific screening approaches, provide recommendations for ICI therapy selection, guide clinical monitoring strategies to improve patient outcomes, and guide research efforts to provide equitable healthcare for all patients. Methods/Study Population: This is an analysis of the demographic and clinical data available of patients from DiRECT Cohort, a longitudinal study that prospectively follows adult cancer patients who self-identify as Black or White and undergo anti-PD-(L)1 ICI therapy. Endocrinopathies were graded using the CTCAE criteria. Kaplan–Meier method was used to calculate the incidence within the first year of treatment. Bivariate analysis (Chi-square and log-rank test) examined the associations between patient demographics, clinical characteristics, and endocrinopathies. Results/Anticipated Results: Among 955 patients, 13.20% developed endocrinopathies of any grade, most commonly hyper-/hypothyroidism and adrenal insufficiency, and 5.97% were at grade ≥2. Younger age (7.59% in age 30 vs. 4.72% in BMI ≤30, p = 0.022) showed significant associations. No significant difference was found in the incidence of grade ≥2 endocrinopathies by race (13.3 % in White and 10.79% in Black patients, p = 0.732). No association was found with cancer stage or comorbidities. Discussion/Significance of Impact: ICIs can lead to (irAEs). Endocrinopathies are a common type of irAEs, presenting a unique challenge. However, the current literature lacks real-time data and a comprehensive comparative analysis of variables like race. Identifying and understanding these variables ensures equatable access to safe and effective healthcare for all patients.
DOI: 10.1017/cts.2024.950
Authors: Hala Awad, E. Eva Culakova, Umanj Gada, Victor Clark, Melina Insalaco, Mustafa Mohammad, Karen Mustian, Gary Morrow, Song Yao, Charles Kamen
Institution: University of Rochester
Language: English
Subfield: Oncology
Field: Medicine
Domain: Health Sciences
Open Access status: gold
Estimated APC paid: $3,200
OpenAlex ID: W4408822550
