Philip, Errol James

Abstract Background Immune checkpoint inhibitors can result in serious, long-lasting immune-related adverse events (irAEs). Early identification of symptoms predictive of irAEs could enhance monitoring and timely intervention. This study assessed whether symptoms within the first 8 weeks of treatment could predict subsequent development of immune-related adrenal insufficiency(AI) or hypothyroidism. Methods This retrospective cohort study analyzed prospectively collected data from the I-SPY2 trial, a phase 2 platform trial for high-risk stage II/III breast cancer across 30 U.S. sites. The cohort included 482 women treated with experimental immunotherapy agents concurrent with weekly paclitaxel neoadjuvant chemotherapy. The primary outcomes were grade ≥ 1 hypothyroidism or AI, adjudicated by an independent safety group, up to 1-year post-treatment. Symptoms and irAEs were assessed using the Common Terminology Criteria for Adverse Events. Symptom burden was quantified as area under the curve (AUC) based on symptom grade and duration. Predictive modeling was performed using logistic regression and ROC analysis; symptom enrichment between cases and controls was evaluated using Fisher’s exact tests. Results Among 482 participants, 107 (22.2%) developed irAEs, with hypothyroidism (n = 61, 12.7%) occurring more frequently than AI (n = 38, 7.9%) at medians of 99 and 105 days from treatment initiation, respectively. Symptom enrichment analysis identified early predictive symptoms. Fatigue (17.2% vs 6.8%, p = 0.011) and rash (20.7% vs 7.8%, p = 0.0037) were predictive of hypothyroidism, while diarrhea (45.9% vs 31%, p = 0.048), constipation (5.4% vs 0.2%, p = 0.018), and taste changes (5.4% vs 0.5%, p = 0.034) were associated with AI. A predictive model demonstrated moderate performance (AUC 0.65 for AI, p < 0.0001; AUC 0.61 for hypothyroidism, p = 0.012). Model accuracy in an external validation cohort was 72.8% for AI and 74.7% for hypothyroidism. Conclusions This study presents a predictive framework to identify patients at risk for adrenal insufficiency and hypothyroidism as irAEs, enabling personalized care and proactive intervention to improve treatment outcomes and safety.

72 Background: The integration of biopsychosocial screening programs (BSP) has been promoted as a way by which to identify unmet needs and to provide tailored treatments to patients. Studies have reported mixed outcomes regarding the impact of such services on hospital admissions during cancer treatment. This study sought to evaluate the effect of a BSP on hospital admissions and length of stay among a large, heterogenous sample of patients diagnosed with cancer (March 2020 to December 2021). Methods: We enrolled consecutive patients diagnosed with cancer receiving treatment at a single institution located in the capital of Brazil. We assessed patients’ characteristics via chart review (e.g., age, sex, histology, hospital admission, length of hospitalization). In addition, as per the BSP protocol, patients were assessed via standardized self-report questionnaires (Distress Thermometer, FACT-G, Patient-Generated Subjective Global Assessment), and appropriate interventions are provided. This program was offered at no cost to all patients and engagement was voluntary. We compared the number of hospital admissions and length of stay between groups (patients who participated in the BSP vs. those who did not). Mixed linear models adjusted for selected characteristics (age, type of cancer and disease stage) were assessed. Results: A total of 1014 patients were included in this analysis. From the total sample, 84% participated in the BSP and 20% were hospitalized for an average of 9 days (ranging from 1-80 days). Mostly patients were female (63%), median age was 63 years old. Breast cancer (26%), hematological (18%), and gastrointestinal cancer (14%) were the most common types of cancer, and the majority had advanced disease (stage III-IV; 67%). Compared to those who engaged in the BSP, patient’s characteristics were well balanced, however, the proportion of patients hospitalized during their cancer treatment was higher among patients who did not participate in the BSP (27% vs 8%: P = 0.001), as was the length of hospitalization spent more days in the hospital than patients who has participated in the BSP (M = 9.5 days vs M = 4.2 days; P = 0.001). Conclusions: Our findings suggest the benefit of a BSP in reducing hospitalizations and length of stay among patients with cancer. An integrated model of care may assist in targeting patient’s unmet needs and may positively impact clinical and hospital-based outcomes. This is the first study to evaluate the effects of a BSP among a Brazilian population using real world data.