Alsdorf, Winfried

Introduction: CARTITUDE-4 is a phase 3 randomized controlled trial (RCT) assessing the efficacy and safety of CARVYKTI (ciltacabtagene autoleucel; cilta-cel) versus pomalidomide, bortezomib and dexamethasone (PVd) or daratumumab, pomalidomide and dexamethasone (DPd) in patients with relapsed and refractory multiple myeloma (RRMM) with one to three prior line(s) of therapy that included an immunomodulatory agent (IMiD) and a proteasome inhibitor (PI), and who are refractory to lenalidomide. Based on the latest reported results from CARTITUDE-4, cilta-cel demonstrated superiority over PVd and DPd on progression-free survival (PFS), overall survival (OS) and response rates (overall response rate [ORR], very good partial response [VGPR] or better, and complete response [CR] or better [CR or better]). In 2023, an initial analysis was performed to compare the efficacy outcomes between all apheresed patients from the cilta-cel arm in CARTITUDE-4 vs doublet (Pd and Kd) and daratumumab-based triplet (DKd and DVd) therapy regimens in the same target population using available patient level data. Data from an updated prespecified data-cut of CARTITUDE-4 with median follow-up of 34 months became available, allowing for an updated assessment of the comparative efficacy, including OS, between cilta-cel and these treatment regimens. Methods: Individual patient data were collected from the CARTITUDE-4 (cilta-cel), CASTOR (DVd), CANDOR (DKd and Kd), and APOLLO (Pd) RCTs, from which patients who met CARTITUDE-4 eligibility criteria were identified. As no patients in the comparative trials had prior treatment with anti-CD38, patients with prior exposure to anti-CD38 therapies in the cilta-cel cohort were excluded. Key prognostic baseline covariates including refractory status, ISS stage, presence of extramedullary disease (EMD), and time to progression on prior line, were adjusted for using inverse probability of treatment weighting (IPTW), with average treatment effect in the treated weights. Differences in baseline characteristics were assessed using standardized mean differences. PFS, OS and response rates (ORR, ≥VGPR and ≥CR) were compared between cilta-cel versus the comparator regimens. Relative efficacy for PFS and OS was estimated with Hazard ratios (HRs) and 95% confidence intervals (CIs) using weighted Cox proportional hazards regression. Response endpoints were analyzed using weighted logistic regression estimating response rate ratios (RRs) and 95% CIs. Sensitivity analyses using alternative statistical approaches and including additional covariates were explored. Results: After the exclusion of 53 patients with prior exposure to an anti-CD38 therapy, 155 patients in the cilta-cel arm remained, and were compared to patients treated with DVd (n=44), DKd (n=98), Kd (n=46) and Pd (n=92) who met the CARTITUDE-4 inclusion criteria. Baseline covariates were well balanced across the cohorts after IPTW. Patients from the cilta-cel arm showed significant improvements in PFS versus all comparators, with adjusted HRs ranging from 0.21 vs DVd to 0.58 vs DKd (all p ≤0.01). Also, OS was significantly longer for cilta-cel versus all other regimens, with adjusted HRs ranging between 0.31 vs Pd to 0.55 vs DKd (all p ≤0.05). While comparative estimates for ORR and VGPR did not change versus the previously reported results, the relative benefit for cilta-cel versus other regimens further increased on deeper levels of response, with adjusted RR for ≥CR from 2.71 vs DKd to 31.47 vs Pd (all p≤0.001). Treatment with DKd consistently yielded the best results out of all comparator regimens but results were still significantly in favor of cilta-cel. Results of cilta-cel benefit were generally consistent across sensitivity analyses. Conclusions: Results from this updated analysis confirm the previously observed significant superiority of PFS and response outcomes of cilta-cel, whilst showing significant OS benefit compared to commonly used treatment regimens for this patient population. These findings provide valuable information to support cilta-cel as a highly effective treatment for RRMM patients who received 1-3 prior lines of therapy, including a PI and IMiD, and who are refractory to lenalidomide, particularly in countries where standard of care may be different from DPd/PVd.

Introduction: Recent efforts have shed light on the clinical and laboratory factors associated with toxicity and response to BCMA-directed CAR-T therapy in patients with relapsed/refractory multiple myeloma (RRMM). However, a major limitation of current scoring systems lies in their assessment at time of lymphodepletion. Because they are not determined before apheresis, they are ill-equipped to guide patient selection, anticipate level-of-care, or plan pre-emptive toxicity management strategies. We therefore aimed to characterize early predictors of CAR-T toxicity and response. Study Design: In this multicenter observational study, we examined demographic, clinical, and laboratory data across three distinct timepoints: indication (e.g., treatment decision), apheresis, and pre-lymphodepletion (LD). CRS and ICANS were graded according to ASTCT criteria. Hematotoxicity (ICAHT) was graded using EHA/EBMT criteria. Early infections (day 0-100) were defined based on microbiologic data or as a clinical infection syndrome, and graded per Hill et al, Blood 2018. Kaplan-Meier estimates of progression-free (PFS) and overall survival (OS) were compared by log-rank test. Cox proportional hazard models were applied to explore associations between pre-apheresis risk factors and key toxicity and survival outcomes. The CAR-HEMATOTOX (HT) score - encompassing markers of inflammation (e.g., CRP, ferritin) and marrow reserve (e.g., hemoglobin, ANC, platelet count) - was determined at each timepoint (Rejeski et al, Blood 2021). Results: We included 530 RRMM patients treated with standard-of-care cilta-cel (n=184) or ide-cel (n=346) across nine centers. Median age was 65 (range 31-88), median ECOG was 1 (IQR 0-1), and patients received a median of 5 prior lines of therapy (IQR 4-7). The median time from indication to apheresis was 16 days (IQR 7-52), while the median time from apheresis to infusion was 56 days (IQR 46-69). The proportion of high-risk patients by HT score did not change between the pre-apheresis and LD timepoints (19% vs. 20%, p=0.82). Most patients stayed either low-risk (n=388, 73.2%) or high-risk (n=68, 12.8%). However, 35 patients (6.6%) shifted from high-to-low risk, while 39 patients (7.4%) progressed from low-to-high risk - reflecting their response to bridging therapies. We noted considerable differences in morbidity and mortality based on the pre-apheresis HT score. Compared to their low-risk counterparts (score 0-2, n=427), high-risk patients (score ≥3, n=103) were hospitalized longer (12 vs. 15 days, p=0.009) and required more frequent ICU admissions (6% vs. 12%, p=0.05). They exhibited more severe early cytopenias (G3+: 8% vs. 25%, p<0.001) and late cytopenias (G3+: 7% vs. 21%, p<0.001), resulting in increased use of TPO agonists and stem cell boosts. Grade 3 or higher ICANS was also more common in HThigh patients (3% vs. 11%, p=0.006), as were severe infections (14% vs. 27%, p=0.007). We found increased non-relapsed mortality in HThigh patients (1-yr NRM 4.6% vs. 16.1%, p<0.001), but no significant difference in the occurrence of secondary malignancies (p>0.9). With a median follow-up of 12.4 months, HThigh patients showed inferior PFS (1-yr PFS 29% vs. 63%, p<0.0001) and OS (1-yr OS 49% vs. 83%, p<0.0001). Transitioning from a low-to-high score was linked to poor survival (1-yr PFS 26%), while the shift from high-to-low risk was associated with favorable outcomes (1-yr PFS 51%). In a multivariable Cox regression model of pre-apheresis features, a high HT score (aHR 2.52, p<0.0001), prior anti-BCMA therapy (aHR 1.55, p=0.04), history of extramedullary disease (aHR 1.42, p=0.02), and penta-refractoriness (aHR 1.45, p=0.02) were independently associated with PFS. Notably, the presence of more than 3 of these high-risk features defined an ultra-high-risk cohort of 28 patients (5.3%) with particularly dismal survival (1-year PFS 15%). Conclusions: Leveraging granular pre-apheresis data from a large international cohort, we identify early markers of toxicity and response in CAR-T-treated RRMM patients. The HT score - reflecting baseline inflammation and hematopoietic reserve - identified high-risk patients likely to benefit from pre-emptive toxicity mitigation strategies such as prophylactic stem cell collection. Most importantly, we characterize a small yet ultra-high-risk group of RRMM patients in need of more effective bridging and therapeutic options.