Anwer, Faiz

*Authors contributed equally. Introduction. Two chimeric antigen receptor (CAR) T-cell therapies have been FDA approved for patients with relapsed/refractory multiple myeloma (RRMM): idecabtagene vicleucel (ide-cel) and ciltacabtagene autoleucel (cilta-cel). Prior work from our consortium identified racial and ethnic differences in safety and response to ide-cel among patients treated in the standard of care (SOC) setting; despite these differences, survival was similar across race and ethnicity. Here, we extend this work to investigate racial and ethnic differences in safety, efficacy, and outcomes in a larger cohort of patients treated with SOC ide-cel with longer follow-up and patients treated with SOC cilta-cel. Methods. Data for RRMM patients who underwent leukapheresis by 12/31/2022 and were treated with SOC ide-cel or cilta-cel were pooled across 19 institutions in the U.S. Multiple Myeloma Immunotherapy Consortium. We compared Non-Hispanic White, Non-Hispanic Black, and Hispanic (any race) patients, excluding other racial and ethnic groups due to small sample sizes that precluded sub-group investigations. Separately for each CAR T-cell therapy, racial and ethnic differences in baseline patient characteristics, safety, and treatment responses were examined using chi-square and Kruskal-Wallis rank sum tests. Kaplan-Meier survival curves and log-rank tests were used to examine progression-free survival (PFS) and overall survival (OS) by race and ethnicity. Results. Among 332 RRMM patients treated with ide-cel, Non-Hispanic Black and Hispanic patients comprised 17% and 10% of the cohort, respectively. Hispanic patients were younger at infusion compared to Non-Hispanic Black and Non-Hispanic White patients (55.5 vs. 63 vs. 66 years, p<0.001). Non-Hispanic Black patients had a higher disease burden (≥ 50% bone marrow plasma cell percentage) compared to Non-Hispanic White and Hispanic patients (35% vs. 20% vs. 19%, p=0.05), while a higher proportion of Non-Hispanic White patients had high-risk cytogenetics compared to Non-Hispanic Black and Hispanic patients (37% vs. 23% vs. 10%, p=0.003). Non-Hispanic Black patients were more likely to develop severe (≥ grade 3) cytopenia at day 30 (p<0.001) and day 90 (p=0.01) post-infusion, and these differences were particularly driven by higher rates of severe neutropenia among Non-Hispanic Black patients at these time points. Non-Hispanic White patients were more likely to achieve a best response of partial response (PR) or better (82%) compared to Non-Hispanic Black (75%) and Hispanic patients (63%, p=0.02). No other racial and ethnic differences in baseline patient characteristics (including cytopenias), safety, PFS, and OS were observed (p>0.05). Among 222 RRMM patients treated with cilta-cel, Non-Hispanic Black and Hispanic patients comprised 12% and 9% of the cohort, respectively. At baseline, Non-Hispanic Black and Hispanic patients were more likely to have anemia (p=0.01), and Non-Hispanic Black patients were more likely to have thrombocytopenia (p=0.02) and neutropenia (p=0.06) compared to Non-Hispanic White patients. No other differences in baseline patient characteristics were observed by race and ethnicity. While not statistically significant, a higher rate of severe (≥ grade 3) cytopenia at day 90 post-infusion was observed among Non-Hispanic Black and Hispanic patients compared to Non-Hispanic White patients (33% vs. 44% vs. 21%, p=0.07), similar to the ide-cel cohort. This finding was primarily driven by higher rates of severe neutropenia among Non-Hispanic Black patients and higher rates of anemia among Hispanic patients. No other racial and ethnic differences in safety, responses to cilta-cel, PFS, or OS were not observed in the cilta-cel cohort (p>0.05). Conclusion. In a large cohort of RRMM patients treated with SOC ide-cel or cilta-cel, we observed a higher rate of cytopenias post-infusion and inferior ide-cel responses among racial and ethnic minority patients compared to Non-Hispanic White patients. Despite these differences, survival was similar across race and ethnicity, suggesting that both available CAR T-cell therapies for RRMM patients can be utilized across all populations. Future studies that include larger patient cohorts of racially and ethnically diverse patients should be conducted to confirm these findings and additionally evaluate long-term outcomes.

Introduction Bispecific antibodies (BsAbs) have become a key component of treatment in relapsed/refractory multiple myeloma (MM). However, despite promising response rates demonstrated in clinical trials, BsAbs have been shown to have a distinct adverse event profile including increased risk of infections as compared with conventional treatment regimens. The aim of this study was to explore the infectious risk of MM patients on active treatment with Teclistamab. Methods This was a retrospective study of MM patients treated with Teclistamab at Taussig Cancer Center from December 16th 2022 to March 31st 2024. Patients who completed step up dosing and received at least one dose of Teclistamab at maintenance dose were included in the study. The study period spanned from the date of the first dose of Teclistamab up to 6 months after the last dose of Teclistamab, change in therapy or death. Infections which required inpatient hospitalization occurring during the study period were included in the study. Neutropenia was defined as absolute neutropenia count <1500 cells/uL. Hypogammaglobulinemia was defined as serum IgG levels below 700 mg/dL. Data were collected on baseline patient characteristics, MM disease characteristics, and infection characteristics. The primary endpoint was rate of infections per patient-year. Results A total of 58 MM patients who were treated with Teclistamab at Taussig Cancer Center were screened for the study. 46/58 (79.3%) of those patients met inclusion criteria and were included in the study. Among the 46 patients included in the study, there were 20 infectious episodes that required inpatient hospitalization, occurring among 18 patients. The median age of the 46 patients was 66 with an interquartile range (IQR) of 62-74. Patients had broad exposure to novel agents including proteasome inhibitors (46, 100.0%), immunomodulatory drugs (44, 95.7%) and monoclonal antibodies (44, 95.7%). Other notable treatment exposures included CAR T-cell therapy (15, 32.6%), and autologous stem cell transplant (3, 6.5%). 6/9 (66.7%) of patients who underwent previous CAR T-cell therapy and 2/3 (66.7%) of patients who underwent previous autologous stem cell transplant developed an infection requiring hospitalization. No statistically significant difference was found in patients with infection and prior CAR T-cell therapy or autologous hematopoietic stem cell transplant. The median number of lines of therapy from MM diagnosis to start of Teclistamab therapy was 7 (IQR: 5.5-8). The median time from start of Teclistamab therapy till first infectious episode was 84.5 days (IQR: 27-177). Bacterial infections were most common (12/20, 60%), with the most common organism being Streptococcus spp. (2/12, 17%). The most common source of infection was respiratory (10/20, 50%). Neutropenia was present at diagnosis for 5/20 (25%) infectious episodes with 4/5 (80%) of these episodes having Grade 4 neutropenia. Hypogammaglobulinemia occurred during the study period in 43/46 (93.5%) patients with a median IgG nadir of 168 (IQR: 118-320). 22/43 (51.2%) patients received intravenous immunoglobulin (IVIG) during the study period, with 3/22 (13.6%) of these patients going on to develop an infection that required inpatient hospitalization. Of the 21 patients not administered IVIG, 13/21 (61.9%) went on to develop an infection that required inpatient hospitalization (p-value .0016). The median length of hospital stay for all infectious episodes was 7.5 days (IQR: 4-12.5). 6/20 (30%) infectious episodes required ICU stay with a median length of stay of 4.5 days (IQR: 2-18). The overall rate of infections per patient-year was 0.82. The rate of infections per patient-year for the 22 patients with hypogammaglobulinemia who did receive IVIG was .28. The rate of infections per patient-year for the 21 patients with hypogammaglobulinemia who did not receive IVIG was 1.5 (p-value = .06). The overall infection-related mortality rate was 3/20 (15%). Conclusion Multiple myeloma patients treated with Teclistamab experienced a high rate of infections requiring hospitalization and ICU care while on active treatment regardless of prior CAR T-cell and autologous hemopoietic stem cell transplant. Preventive measures, such as administration of prophylactic IVIG to patients with hypogammaglobulinemia, improved outcomes and should be taken to reduce infectious risk in this susceptible patient population.

Background: Teclistamab (Tec), a first-in-class BCMA bispecific T-cell antibody, received regulatory approval for the treatment of RRMM based on the MajesTEC-1 study [Moreau et al, NEJM, 2022] which demonstrated an overall response rate (ORR) of 63% and median progression free survival (PFS) of 11.3 months. However, less than 15% (N=24) of patients (pts) enrolled in MajestTEC-1 were ≥75 years, an age cohort that is often underrepresented in clinical trials and comprises approximately one third of MM pts at diagnosis [SEER 22 2017-2021]. In this multicenter retrospective study, we report the real-world safety and efficacy of a large cohort of elderly (≥75 years) RRMM pts treated with Tec. Methods: Pts with RRMM who received standard-of-care Tec across 13 U.S. academic institutions were included in the study. The follow-up data cutoff was 30 April 2024. Pts were divided by age into two groups: age <75 years (<75 group) and age ≥75 years (≥75 group). High-risk cytogenetic abnormalities (HRCA) were defined as the presence of del(17p), t(4;14), t(14;16) and/or gain or amplification of 1q21. Disease response and progression was evaluated using IMWG criteria. Time-to-event analyses were evaluated using the Kaplan-Meier method. Cytokine release syndrome (CRS) and immune effector cell-associated neurotoxicity syndrome (ICANS) assessment was based on the American Society for Transplantation and Cellular Therapy consensus grading. Results: Among 385 pts, 83 (22%) were in the ≥75 group (median age 78, range 75-92) and 302 (78%) in the <75 group (median age 65, range 31-74). Compared to pts in the <75 group, those in the ≥75 group were more often white (78% vs. 63%, p=0.009). Both the ≥75 and <75 age groups had a median of 6 prior lines of therapy, a similar proportion with ECOG ≥2 at start of Tec (29% vs. 24%, respectively; p=0.37), and a high proportion of pts with triple-class-refractory disease (77% vs. 85%, p=0.06) and pts who would have been ineligible MajesTEC-1 (73% vs. 80%, p=0.20). In contrast, pts in the ≥75 group had a lower incidence of adverse MM risk factors compared to the <75 group, including HRCA (44.6% vs. 57.9%, p=0.03), ultra high-risk (≥2 HRCA) MM (12% vs. 24%, p=0.02), extramedullary disease (22% vs. 40%, p=0.02), hemoglobin <8 g/dL (10% vs. 21%, p=0.02) or albumin <3 g/dL (6% vs. 19%, p=0.04) at the time of starting Tec. Moreover, a lower proportion of pts in the ≥75 group had prior autologous stem cell transplantation (43% vs. 72%, p<0.0001) or prior BCMA-directed therapy (33% vs. 55%, p=0.0003). The median time from diagnosis to start of Tec was longer for pts in the ≥75 group (7.21 years vs. 5.81 years, p=0.02). There was no significant difference in rates of any-grade CRS (52% vs. 59%, p=0.27), CRS grade 2-4 (10% vs. 11%, p=0.74) or any-grade ICANS (19% vs. 13%, p=0.12) between the ≥75 and <75 age groups, respectively. Four pts in the entire cohort developed CRS grade 3-4, one of whom was in the ≥75 group. Ten pts developed grade 3 ICANS (none grade 4), three of whom were in the ≥75 group. There was no significant difference between the ≥75 group and <75 group in ORR (62% vs. 53%, p=0.17) and ≥very good partial response (VGPR) rate (53% vs. 44%, p=0.14). After a median follow-up period of 9.9 months (95% CI 9.6-10.6 months), the median PFS in the ≥75 group was 10.7 months (95% CI 6.6-NR) vs. 5.2 months (95% CI 6.6-NR) in the <75 group (p=0.005). At the time of data cut-off, the median overall survival (OS) for pts in the ≥75 group had not been reached (95% CI NR - NR) compared to 16.1 months (95% CI 14.0 - NR) in the <75 group (p=0.048). In multivariable analysis for the entire cohort, age ≥75 was not significantly associated with either PFS (HR 0.87, 95% CI 0.54-1.39; p=0.55) or OS (HR 0.60, 95% CI 0.30-1.19; p=0.15). Conclusions: This analysis of a large cohort of RRMM pts treated with Tec in the real-world setting demonstrates comparable efficacy and safety outcomes in elderly (aged ≥75 years) pts to those reported in the overall study population of MajesTEC-1. The adverse baseline disease characteristics and inferior efficacy in pts <75 years age compared to ≥75 years likely reflect patient selection and prescribing patterns in the early era of access to commercial BCMA bispecific therapy with Tec. In multivariable analysis there was no significant impact of age ≥75 on survival outcomes. OP, DD & LF: co-first authors. KKP, HCL & AGC: co-senior authors

Introduction. Ciltacabtagene autoleucel (cilta-cel) and idecabtagene vicleucel (ide-cel), two anti-B-cell maturation antigen (BCMA) CAR T therapies, have demonstrated remarkable responses and improved survival among patients with relapsed/refractory multiple myeloma (RRMM) in the clinical trials and standard of care (SOC) setting. Here, we compare safety, efficacy, and survival for patients treated with SOC ide-cel and cilta-cel. Methods. Data were from a retrospective chart review of RRMM patients leukapheresed by 12/31/2022 with the intent to receive SOC ide- or cilta-cel at 19 institutions in the US Multiple Myeloma Immunotherapy Consortium. An inverse probability of treatment weighting (IPTW) approach was used to compare outcomes by therapy type (cilta- vs. ide-cel), balancing on age, sex, race and ethnicity, performance status, extramedullary disease, high-risk cytogenetics, prior BCMA therapy, bone marrow plasma cells, penta-refractory status, lymphodepleting chemotherapy, baseline ferritin, low cell dose, and bridging therapy response. Logistic regression and Cox proportional hazard models were used to examine the association of treatment type with safety, efficacy, and survival accordingly, while adjusting for IPTW weights. We employed propensity score matching utilizing the same covariates to identify the association of treatment type with progression-free survival (PFS) within relevant patient sub-groups. Results. A total of 641 patients were leukapheresed by 12/31/2022 with ide-cel (n=386) and cilta-cel (n=255). 586 patients were infused (n=350 for ide-cel; n=236 for cilta-cel) with a median follow-up of 13.0 and 12.6 months, respectively. After IPTW, patient characteristics were well-balanced. Patients treated with cilta-cel were more likely to have grade ≥ 3 cytokine release syndrome (CRS) (OR=5.52, 95% CI=1.76-17.30, p=0.004), infections (OR=2.07, 95% CI=1.44-2.97, p<0.001), and delayed neurotoxicity (NT) (OR=20.97, 95% CI=4.75-92.42, p<0.001) compared to patients treated with ide-cel. In the cilta-cel cohort, 24 patients (10%) experienced delayed NT compared to 2 patients (1%) in the ide-cel cohort. Although not statistically significant, patients treated with cilta-cel were more likely to have any second primary malignancies (SPMs) (OR=1.87, 95% CI=0.94-3.71, p=0.08) and any SPMs excluding non-melanoma skin cancers (OR=1.78, 95% CI=0.78-4.10, p=0.2) but no association was observed for odds of hematologic SPMs (OR=0.98, 95% CI=0.26-3.61). No association was observed for therapy type with any or severe immune effector cell-associated neurotoxicity syndrome, any CRS, severe cytopenias, and non-relapse mortality. Compared to ide-cel, cilta-cel was associated with better treatment responses of ≥ complete response (OR=2.38, 95% CI=1.61-3.51, p<0.001) and ≥ partial response (OR=1.74, 95% CI=0.99-3.05, p=0.06). Patients treated with cilta-cel had a longer PFS and overall survival (OS) than ide-cel (HR=0.47, 95% CI=0.35-0.62, p<0.001 and HR=0.63, 95% CI=0.42-0.93, p=0.02, respectively), and these findings were similar in the intention to treat cohort (PFS: HR=0.44, 95% CI=0.34-0.55, p<0.001; OS: HR=0.55, 95% CI=0.41-0.73, p<0.001, respectively). We observed consistent findings when repeating the analyses restricting the ide-cel cohort to patients infused during the same time-period as FDA approval for cilta-cel (≥ March 2022), restricting to patients with data on all covariates, and restricting to sites that contributed data for both products. In a propensity matched population, (n=380; n=190 for cilta-cel and n=190 for ide-cel), patients treated with cilta-cel had superior PFS compared to those treated with ide-cel in most subgroups with respect to age and disease characteristics including extramedullary disease, high-risk cytogenetics, and elevated baseline ferritin (p<0.05). Conclusion. Our results suggest superior efficacy of cilta-cel with a higher incidence of certain toxicities compared to ide-cel in the SOC setting. This study provides valuable information for patient counseling and guiding the selection of CAR T-cell therapy for specific patient populations. Further validation through similar large-scale real-world experiences or prospective studies is needed to confirm our results and enhance applicability in the clinical setting. *DH, LP, & DD are co-first authors * YL, KP, & SS are co-last authors

Background: Tec is a BCMA-directed bispecific antibody (BsAb) approved for RRMM after ≥4 prior lines of therapy (LOT) based on the MajesTEC-1 trial. However, patients who had previously received a BCMA-DT were excluded from MajesTEC-1. Herein, we evaluated outcomes of RRMM patients with prior exposure to BCMA-DT treated with standard-of-care Tec. Methods: This was a multicenter retrospective cohort study. We compared variables between different groups using Chi-squared and Kruskal-Wallis tests, and assessed progression free survival (PFS) and overall survival (OS) using Kaplan Meier and Cox proportional hazards model. We used the maximally selected rank statistics method to determine the optimal cut-off point for continuous variables to find the most significant difference in PFS among different groups. Results: A total of 385 patients were included in this study. 193 patients had received a prior BCMA-DT, of whom 77%, 22%, and 1% had received 1, 2, and 3 prior anti-BCMA agents, respectively. In patients who had received a prior BCMA-DT, 35% were aged ≥70 years, 24% had ECOG performance status (PS) ≥2, 61% had high-risk FISH, 32% had extramedullary disease (EMD) at Tec initiation, and 42% were penta-refractory. Compared to the cohort without prior BCMA-DT (n=192), patients who were treated with prior BCMA-DT were more likely to have high risk FISH (61% vs 49%, p=0.02), and higher median number of prior LOT (7 vs 5, p <0.001). The specific types of prior BCMA-DTs with the respective overall response rate (ORR) to the most recent prior BCMA-DT were: antibody drug conjugate only (ADC, n=47, ORR 43%), chimeric antigen receptor T-cell therapy only (CAR T, n=99, ORR 86%), BsAb only (n=6, ORR 100%), ADC + CAR T (n=36, ORR 56%), and other ADC/CAR T/BsAb combinations (n=5, ORR 60%). Median follow up was 9.9 (95% CI:9.5-10.6) months. Patients with prior receipt of BCMA-DT had a lower ORR (51.4% vs 61.5%; p=0.012) and ≥very good partial response rate (39.4% vs 52.6%, p=0.009), but similar ≥complete response rate (22.3% vs 24%; p=0.78) to Tec compared to those without prior BCMA-DT. Moreover, patients with prior BCMA-DT had worse median PFS compared to patients without prior BCMA-DT (prior BCMA-DT: 4.6 months, 95% CI: 2.7-7.5; without prior BCMA-DT: 8.2 months, 95% CI: 5.7-12.2; p=0.017). On multivariable analysis incorporating prior BCMA-DT, age, cytogenetics, EMD, and ECOG PS, receipt of prior BCMA-DT was not independently associated with PFS (HR 1.25, 95% CI 0.95-1.64, p=0.1). The estimated 1-year OS rate was 58.9% (95% CI: 51.64-67.2) for the prior BCMA-DT group vs 65.1% (95% CI: 58.1-73.1) for the group without prior BCMA-DT, p=0.16. For the prior BCMA-DT cohort, response rates to Tec were numerically higher in patients who received CAR T (ORR 51.2%) followed by ADC (ORR 45.5%), and bispecific (ORR 30%) as their most recent prior BCMA-DT (p=0.39). No significant difference in PFS was noted when stratifying patients by number of prior BCMA-DTs, types of all prior BCMA-DTs received, type of most recent prior BCMA-DT, or depth of response to most recent BCMA-DT. Patients who responded to Tec had a numerically longer median time from most recent BCMA-DT exposure to Tec initiation compared to non-responders: 10.5 vs 7.5 months, p=0.48. We found that the optimal cut-off for time from last BCMA-DT exposure to Tec initiation was 8.7 months. Patients with > 8.7 months between last exposure to prior BCMA-DT and Tec initiation had a superior median PFS with Tec (8.1 months, 95% CI: 4.6-11.7) compared to patients with < 8.7 months from last exposure to prior BCMA-DT (2.5 months, 95% CI: 1.1-5.7), p=0.001. The toxicity profile for patients with prior BCMA-DT was similar to those who had not received a prior BCMA-DT. Grade ≥2 CRS occurred in 8.7% vs 13% (p=0.18), and grade ≥2 ICANS in 7.7% vs 6.7%, (p=0.85) of patients with and without prior BCMA-DT, respectively. Patients in the prior BCMA-DT cohort were more likely to have grade 3 thrombocytopenia in the first 30 days after Tec initiation (10.7% vs 6.6%; p=0.08). Conclusion: This is the largest study to date of any BCMA-directed BsAb among BCMA-exposed patients. Receipt of prior BCMA-DT was associated with a trend toward worse PFS, although not statistically significant, and lower likelihood of attaining an overall response. Waiting >9 months between sequencing BCMA therapies may be associated with improved PFS. D.D., M.A.V.M., J.A.D: co first authors; F.A., C.F., L.S.: co senior authors

The use of 4-drug induction regimens for treatment naïve newly diagnosed multiple myeloma (NDMM) is associated with improved depth of response and progression-free survival (PFS). However, head-to-head trials of 4-drug combinations are lacking, and instead, these regimens are typically compared to 3-drug backbones; limiting the ability to discern whether any additional benefit (or toxicity) is simply additive or represents a synergy (or interaction). We conducted a meta-analysis of phase 2 and phase 3 clinical trials that randomized treatment naïve NDMM patients to either a 4-drug or 3-drug induction regimen. We included 11 trials which represented 6509 unique patients. PFS for all trials in the meta-analysis was 54 months with a 4-drug induction and 8.9 months with a 3-drug induction (HR: 0.49; 95% CI: 0.45; 0.54), but there was no benefit to using a 4-drug induction that did not include an anti-CD38 antibody (PFS 4-drug 8.1 months, PFS 3-drug 8.0 months; HR 0.95; 95% CI 0.86; 1.06). Adverse events were more frequent with the quadruplet regimens but were predominately mild. High-grade (≥3) adverse events (AEs) that were more common with 4-drug regimens were infections (RR: 1.34; 95% CI 1.17; 1.54) and thrombocytopenia (RR: 1.39; 95% CI 1.12; 1.74). This study suggests that 4-drug induction regimens which include an anti-CD38 antibody improve efficacy although with additional toxicity in NDMM patients.

Introduction: In many cases, treatment decisions for multiple myeloma patients must be made in the absence of high quality randomized controlled clinical trials. As a result, many clinicians lean on prognostic models to drive treatment selection. The most widely used of these models incorporate a limited number of patient related factors that reflect tumor burden, cytogenetic features, or gene expression profiling. These prediction scores are derived from regression models that incorporate these variables at the time of diagnosis. They do not account for variables that change dynamically over time, do not explore the relationship between treatment selection and progression, and imperfectly predict survival outcomes. We designed a prognostic model based on an ensemble machine learning platform to predict progression in NDMM using Extreme Gradient Boosting Machine (XGBoost) combined with accelerated failure time modeling for survival analysis. Methods: We utilized a large retrospective data set containing treatment and response information for 1127 patients with newly diagnosed multiple myeloma (NDMM) treated at the Cleveland Clinic Foundation between 2000 and 2023. Following data preprocessing based on data completeness, 953 patient records were included in our training, testing, and cross validation datasets. For the purposes of our analysis, the initial dataset was randomly split into training (70%), testing (15%) and validation (15%) subsets at the patient level. We also defined the lower and upper bounds for each subset, which is critical due to the right-censored nature of survival data. Hyperparameters for XGBoost were optimized using Bayesian search, minimizing the negative log-likelihood. A random forest method was applied for the imputation of missing data (MissForest). We then trained the XGBoost model using GPU acceleration for enhanced computational efficiency. Finally, a log-rank test on predicted survival times was used to test the model's performance on patients with and without known progression. Results: Our preprocessed data set had 953 patients with a mean age at disease onset of 65 years and a slight male predominance (55%). Approximately 27% of patients harbored high cytogenetic risk disease and 3.5% of the cohort presented with extramedullary disease a diagnosis. At a median follow up of 35 months, 47% of patients had experienced disease progression or death. Induction therapy included an immunomodulatory drug in 40% of patients and proteasome inhibitors in 22%. Frontline autologous stem cell transplantation followed induction in 28% of patients. Median progression free survival in the overall data set was 44 months. These features were consistent across the randomly assigned training, testing, and validation cohorts. Following data preprocessing, 34 independent clinical and genomic variables including selection of first line treatment were assessed as model inputs each available record. Under optimized parameters, the model was trained with a maximum tree depth = 7 and a learning rate ~ 0.22 for the desired output of progression free survival (PFS). We then queried PFS for both the training and validation sets and divided patients into those known to have progressed and those without a progression event. Survival analysis was undertaken using predicted PFS values for patients known to have progressed and those who remained progression free. For the validation data set, our model successfully discerned between progressed and non-progressed cases (log-rank test statistic = 22.07, p < 0.005) (Figure 1). Discussion: We present a machine learning approach based on regularized gradient boosting that accurately discerns between patients who experience progression and those who remain progression free at a median ~35 months of follow-up in a large retrospective data set in patients presenting with NDMM. Further elaboration of our model will allow for the incorporation of large amounts data to predict survival outcomes on the basis of dynamic variables such as depth of response and treatment selection. With the ability to parse outcomes among multiple myeloma patients at high resolution, future clinicians and clinical trialists may be able to overcome limitations in trial design and patient-level therapy selection for both newly diagnosed and relapsed patients.

BackgroundDespite routine evaluation of cytogenetics in myeloma, little is known regarding the impact of high‐dose therapy (HDT) consolidation on overall survival (OS) or progression‐free survival (PFS) in patients who have high‐risk cytogenetics. The authors performed a meta‐analysis of randomized controlled trials (RCTs) to assess the heterogeneity of HDT efficacy according to cytogenetic risk.MethodsAll RCTs in patients who had newly diagnosed myeloma from 2000 to 2021 that compared upfront HDT versus standard‐dose therapy (SDT) consolidation were included. The primary objective was to assess the difference in HDT efficacy between standard‐risk and high‐risk cytogenetics in terms of the OS or PFS log(hazard ratio) (HR). The pooled OS and PFS HR was calculated according to cytogenetic‐risk subgroup using a random‐effects model, and heterogeneity (I2) (the percentage of total observed variability explained by between‐study differences) was assessed using an interaction test.ResultsAfter screening 3307 citations, 6 RCTs were included for PFS analysis, and 4 were included for OS analysis. The median follow‐up ranged from 3.1 to 7.8 years. The pooled OS HR for HDT versus SDT consolidation in patients with standard‐risk and high‐risk cytogenetics was 0.90 (95% confidence interval [CI], 0.70‐1.17; I2 = 0%) and 0.66 (95% CI, 0.45‐0.97; I2 = 0%), respectively. The difference in HDT efficacy in terms of OS between standard‐risk and high‐risk patients was statistically significant in favor of the high‐risk group (P for interaction = .03). The pooled PFS HR for HDT versus SDT was 0.65 (95% CI 0.56‐0.76; I2 = 0%) versus 0.52 (95% CI, 0.33‐0.83; I2 = 55%), respectively. The difference in HDT efficacy in terms of PFS between standard‐risk and high‐risk patients was not significant (P for interaction = .25).ConclusionsThe magnitude of OS benefit with upfront HDT is cytogenetics‐dependent. Patients with high‐risk cytogenetics should preferably receive upfront rather than delayed HDT consolidation.Lay Summary Upfront autologous stem cell transplantation improves overall survival in patients with newly diagnosed myeloma harboring high‐risk cytogenetics.

Abstract Background Allogeneic (off the shelf) chimeric antigen receptor (CAR) T-cell therapy addresses the logistical challenges, availability (including insufficient T-cell yields from low baseline absolute lymphocyte count), and variable product quality of autologous CAR T therapy. ALLO-715 is a genetically modified anti-BCMA AlloCAR T™ cell which uses Cellectis TALEN ® technology to disrupt the T-cell receptor alpha constant gene (TRAC) and the CD52 gene to reduce the risk of graft-versus-host disease (GvHD) and permit the use of ALLO-647, an anti-CD52 monoclonal antibody (mAb), for selective and transitory host lymphodepletion (LD). Methods UNIVERSAL is an open-label, Phase 1 trial (NCT04093596) in adults with relapsed/refractory (R/R) multiple myeloma who have received ≥3 prior lines of therapy including a proteasome inhibitor, immunomodulator, and anti-CD38 mAb. Patients (pts) must be refractory to their last treatment line. Pts receive LD followed by ALLO-715 at 1 of 4 dose levels (DLs) in a 3+3 dose escalation design: 40, 160, 320, and 480 x 10 6 CAR+ T cells. Several LD regimens are being evaluated: FCA39; FCA60; FCA90; and CA39; with fludarabine [F] 90 mg/m 2, cyclophosphamide [C] 900 mg/m 2, and ALLO-647 [A] 39, 60, or 90 mg divided over 3 days. Results As of June 21, 2021 data-cut, 47 subjects were enrolled; 42 were treated with ALLO-715; 5 progressed prior to treatment. Median time from enrollment to LD was 5 days and no treated pts required bridging therapy. Pts were heavily pretreated with a range of 3-11 prior lines of therapy; 42.9% were penta refractory. There were 19% ISS Stage III at screening, 34% had high risk cytogenetics, and 19% had extramedullary disease. The most common Grade (Gr) 3+ adverse events (AEs) included anemia, neutropenia, lymphopenia, and thrombocytopenia. Cytokine release syndrome (CRS) occurred in 52.4%, all Gr 1/2 except 1 pt with Gr 3. CRS was treated with tocilizumab (21.3%) and corticosteroids (12.8%). One pt (with Gr 2 CRS) experienced Gr 1 neurotoxicity that resolved. Gr 3+ infections occurred in 12.8% of pts, including 2 previously reported Gr 5 events (fungal pneumonia and adenovirus hepatitis). Early results from this trial have been presented previously (ASH 2020) and therefore the efficacy analysis on pts (n=26) treated at DL3 and DL4 with FCA LD, which are considered a more relevant cell dose and LD, is presented here (Table). In pts who received DL3 or DL4 (320 or 480 x 10 6 CAR T cells) (n=26), the ORR was 61.5% (95% CI: 40.6, 79.8); very good partial response or better (VGPR+) rate was 38.5% (95% CI: 20.2, 59.4). Median time to 1 st response was 16 days. The median follow-up for the DL3/DL4 pts was 7.4 months (95% CI: 3.6, 9.9) with a median duration of response of 8.3 months (95% CI: 1.5, not reached). Of the 10 pts with a best response of VGPR+, 8 were found to be negative by minimal residual disease (MRD) analysis. Conclusions UNIVERSAL demonstrates proof of concept for allogeneic CAR T therapy in multiple myeloma. ALLO-715 showed CAR T cell dose response relationship with higher doses (DL3/DL4) leading to clinically meaningful efficacy, including high VGPR+ rate of 38.5% and high MRD negativity without requiring leukapheresis or bridging therapy. ALLO-715 following LD with FCA has a tolerable safety profile. FCA induces a deep and durable window of lymphocyte depletion allowing CAR T cell expansion and persistence. A study using the next generation anti-BCMA CAR (ALLO-605) which supplies cytokine signaling to the CAR bearing cells is ongoing (IGNITE). The current UNIVERSAL trial continues to enroll, including a cohort with consolidation, and updated data will be presented at the meeting. Figure 1 Figure 1. Disclosures Mailankody: Allogene Therapeutics: Research Funding; Plexus Communications: Honoraria; Fate Therapeutics: Research Funding; Physician Education Resource: Honoraria; Bristol Myers Squibb/Juno: Research Funding; Jansen Oncology: Research Funding; Legend Biotech: Consultancy; Evicore: Consultancy; Takeda Oncology: Research Funding. Liedtke: Oncopeptides: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Membership on an entity's Board of Directors or advisory committees; Kite: Membership on an entity's Board of Directors or advisory committees; Kura Oncology: Membership on an entity's Board of Directors or advisory committees; Alnylam: Membership on an entity's Board of Directors or advisory committees; Pfizer: Honoraria; Bristol Myers Squibb: Membership on an entity's Board of Directors or advisory committees; GlaxoSmithKline: Membership on an entity's Board of Directors or advisory committees; Caelum: Membership on an entity's Board of Directors or advisory committees, Other: Clinical Trial Funding; Celgene: Membership on an entity's Board of Directors or advisory committees; Sanofi: Membership on an entity's Board of Directors or advisory committees; Takeda: Membership on an entity's Board of Directors or advisory committees; Janssen Pharmaceuticals: Membership on an entity's Board of Directors or advisory committees. Sidana: BMS: Consultancy; Magenta Therapeutics: Consultancy, Research Funding; Allogene: Research Funding; Janssen: Consultancy, Research Funding. Chhabra: GSK: Honoraria. Oluwole: Janssen: Consultancy; Pfizer: Consultancy; Curio Science: Consultancy; Kite, a Gilead Company: Consultancy, Research Funding. Kumar: Oncopeptides: Consultancy; Antengene: Consultancy, Honoraria; Astra-Zeneca: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Novartis: Research Funding; Celgene: Membership on an entity's Board of Directors or advisory committees, Research Funding; BMS: Consultancy, Research Funding; Adaptive: Membership on an entity's Board of Directors or advisory committees, Research Funding; Bluebird Bio: Consultancy; Roche-Genentech: Consultancy, Research Funding; Merck: Research Funding; Carsgen: Research Funding; Takeda: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Janssen: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; KITE: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Amgen: Consultancy, Research Funding; Beigene: Consultancy; Abbvie: Consultancy, Membership on an entity's Board of Directors or advisory committees, Research Funding; Tenebio: Research Funding; Sanofi: Research Funding. Nath: Actinium: Consultancy, Honoraria; Incyte: Consultancy, Honoraria. Anwer: Janssen pharmaceutical: Honoraria, Research Funding; Allogene Therapeutics: Research Funding; GlaxoSmithKline: Research Funding; BMS / Celgene: Honoraria, Research Funding. Raje: Caribou: Other; Janssen: Other; bluebird bio: Other; Amgen: Other; Celgene: Other; BMS: Other. Siegel: Bristol Myers Squibb: Honoraria, Speakers Bureau; Takeda: Honoraria; GlaxoSmithKline: Honoraria, Speakers Bureau; Celularity: Membership on an entity's Board of Directors or advisory committees; Karyopharm: Honoraria; Amgen Inc.: Honoraria; Janssen: Honoraria, Speakers Bureau. Karski: Allogene Therapeutics: Current Employment, Current equity holder in publicly-traded company; Crispr Therapeutics: Current equity holder in publicly-traded company; Nektar Therapeutics: Current equity holder in publicly-traded company. Lovelace: Allogene Therapeutics, Inc.: Current Employment. Lourbakos: Allogene Therapeutics, Inc.: Current Employment. Hari: Millenium: Membership on an entity's Board of Directors or advisory committees, Research Funding; Sanofi: Honoraria, Membership on an entity's Board of Directors or advisory committees, Research Funding, Speakers Bureau; Oncopeptides: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Adaptive Biotech: Honoraria, Membership on an entity's Board of Directors or advisory committees, Speakers Bureau; Janssen: Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Takeda: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; GSK: Consultancy, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Karyopharm: Consultancy; Amgen: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau; Celgene-BMS: Consultancy, Honoraria, Membership on an entity's Board of Directors or advisory committees, Other, Research Funding, Speakers Bureau.