Shamsuzzaman, Md

7529 Background: iAEs, such as cytokine release syndrome (CRS) and macrophage activation syndrome (MAS), can occur after infusion of chimeric antigen receptor T cell therapies such as ide-cel, but are typically low-grade and manageable with tocilizumab and corticosteroids. Although high-grade iAEs are rare with ide-cel, identification of patients at increased risk may improve management and remains an unmet need. Three composite biomarkers (multivariate models) of iAE risk were previously developed in a discovery cohort from the KarMMa and KarMMa-2 studies of ide-cel in RRMM (Mashadi-Hossein A, et al. J Clin Oncol 2023;41(16_suppl):e20005). Here, we validate these 3 prototype models for risk of developing high-grade iAEs after ide-cel infusion. Methods: Two models used pretreatment patient and routine clinical laboratory parameters; the third model also included change in 6 exploratory cytokines from baseline to 1 day following ide-cel infusion. To validate, each model was retrospectively applied to KarMMa-3 (NCT03651128) data in a blinded fashion, and sensitivity and specificity to identify grade ≥3 CRS and any-grade MAS were determined. Model performance thresholds used for sensitivity and specificity were 90% and 50%, respectively. Performance for identifying grade 2 CRS was also analyzed post hoc. Results: The first and simplest model comprised a manual algorithm with 7 features; it identified patients with grade ≥3 CRS or MAS with 85% sensitivity and 60% specificity. The second model comprised 19 routinely measured pretreatment features; it identified grade ≥3 CRS with 91% sensitivity and 59% specificity, and any-grade MAS with 60% sensitivity and 88% specificity. The third and most complex model comprised 7 pretreatment clinical features and 6 exploratory cytokines; it identified grade ≥3 CRS with 100% sensitivity and 51% specificity, and any-grade MAS with 100% sensitivity and 81% specificity. None of the models identified grade ≥2 CRS with passable sensitivity or specificity. Clustering analyses across all features showed that only a subset of grade 2 CRS cases was within the previously identified high-risk iAE cluster while the remaining grade 2 CRS cases were spread across other clusters. Conclusions: Two of the 3 composite biomarkers met validation criteria for grade ≥3 CRS risk. Criteria were not met for grade 2 CRS, suggesting these models are specific to higher-grade events and that grade 2 CRS represents a more heterogeneous group of patients. While high-grade iAEs are rare with ide-cel, these models may further optimize the robust benefit–risk profile that ide-cel has demonstrated by helping identify, prior to or shortly after infusion, patients most at risk for severe events. Clinical trial information: NCT03651128 .

e20005 Background: iAEs such as cytokine release syndrome (CRS) and neurotoxicity (NT) are common with CAR T cell therapies such as ide-cel; CRS and NT observed with ide-cel are generally low grade and manageable with tocilizumab (toci) and corticosteroids. Identifying iAE risk with sensitivity and specificity is challenging, suggesting multifactorial etiology and limitations evaluating dynamic processes at specific timepoints. Macrophage activation syndrome (MAS; per CTCAE) has a specific molecular profile representing a homogeneous subgroup within CRS, tending to be more severe/refractory to front-line management. Using longitudinal data on post-infusion soluble factors we aimed to develop a candidate post-infusion inflammatory risk score based on MAS molecular signature and determine associations with pt baseline characteristics. Methods: Statistical learning tools were applied to the longitudinal profile of 34 factors measured over 28 d after ide-cel infusion in 291 pts from KarMMa (NCT03361748) and KarMMa-2 (NCT03601078) to extract features describing the profiles. Unsupervised machine learning-based clustering was applied to these features and enrichment for MAS cases within each cluster was assessed. A metric describing membership in a cluster of interest was used as a candidate post-infusion inflammatory risk score for further correlative analyses. Results: Pts with MAS had cytokine profiles consistent with high levels of pro-inflammatory signalling across multiple inflammatory cell types. Cytokine profiles of MAS were qualitatively similar to those of CRS/NT; however, unsupervised clustering showed a distinct group of pts with MAS. A metric of similarity to the MAS-enriched cluster was defined as a candidate post-infusion inflammatory risk score, posited to identify pts more likely to have more severe/refractory iAEs. This inflammatory risk score positively correlated with CRS and NT grades and frequency of toci usage (Kruskal-Wallis test; all P < 0.001). A prototype predictive model based on baseline pt and clinical characteristics strongly correlated with post-infusion inflammatory risk score (Pearson; ρ = 0.88). Low blood counts, higher tumor burden, and elevated levels of inflammatory markers on the day of ide-cel infusion were associated with a higher inflammatory risk score. Conclusions: A molecular profile of severe/refractory iAEs was preliminarily identified in ide-cel treated pts with MM. This profile enabled derivation of a candidate post-infusion inflammatory risk score and a prototype predictive model of this risk score based on pt baseline characteristics was developed. These results may help identify pts at risk for severe/refractory iAEs, who may be potential candidates for closer monitoring or novel interventions, and warrant further study. Clinical trial information: NCT03361748 , NCT03601078 .