Abstract Recent therapeutic advances, including bispecific antibodies (bsAbs), have improved outcomes for patients with relapsed/refractory multiple myeloma (RRMM). However, early mortality (EM) remains a significant challenge, even in the era of novel immunotherapies. We conducted a multicenter, retrospective analysis of real-world patients with RRMM treated with commercial bsAbs to evaluate the incidence and causes of EM. Between May 2022 and June 2025, a total of 441 patients were treated across 7 countries. EM, defined as death within 12 months of therapy initiation, occurred in 148 patients (34%), with a median time from bsAb initiation to death of 2.87 months (interquartile range, 1.38-6.85). The leading cause of EM was progressive disease (72%), followed by infection (13%); regardless of the cause of death, 82% had active disease at the time of death. Our findings highlight that despite encouraging efficacy, EM remains high among real-world bsAb recipients, emphasizing the need for improved disease control strategies and supportive care interventions.
Feasibility of decentralized real-world monitoring of SARS-CoV-2 booster vaccines and COVID-19 outcomes in myeloma
Abstract Patients with multiple myeloma have an elevated risk of severe complications from severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2; COVID-19) infection. To demonstrate proof of concept for a pandemic preparedness and response network, the American Society of Hematology Research Collaborative Multiple Myeloma Program developed a prospective, decentralized study within a site-based provider network. In the COVID-19 outcomes in myeloma and the impact of vaccines (COSMIC) study, patients provided consent, permitted electronic health record data collection, completed patient-reported outcomes at baseline, day 30, and day 180 through an electronic study portal, and were compensated for participation. Clinicians at participating sites facilitated study recruitment and shared best practices monthly to accelerate study execution. The COSMIC study rapidly consented 201 patients from 8 participating sites over 4 months (22 January 2024 through 17 May 2024). Consented participants were 30 to 93 years old, with a median age of 67; 46% were female, 69% were non-Hispanic White, 17% were non-Hispanic Black, and 8% were Hispanic/Latino. Patient-reported data completion was 97% at baseline, 81% at 1 month, and 79% at 6 months. At baseline, 55% of patients reported a history of COVID-19 infection and had received a median of 4 SARS-CoV-2 vaccines. For all patients, there were an additional 18 COVID-19 infections and 57 vaccines received during the 6-month observation period. There were no significant differences in health-related quality of life over time or by history of COVID-19 infection. COSMIC demonstrates the feasibility of an innovative evidence generation strategy to drive rapid accrual of patients to address an evolving area of need. This trial was registered at www.clinicaltrials.gov as #NCT05831787.
A High-Fiber, Plant-Based Diet in Myeloma Precursor Disorders: Results from the NUTRIVENTION Clinical Trial and Preclinical Vk*MYC Model
Cancer Discovery | December 4, 2025 | Volume: 16 | Issue: 4 | Pages: 697-720
Abstract Consumption of a Western diet and high body mass index (BMI) are risk factors for progression from premalignant phenotypes to multiple myeloma, a hematologic cancer. In the NUTRIVENTION trial (NCT04920084), we administered a high-fiber, plant-based diet (HFPBD; meals for 12 weeks, coaching for 24 weeks) to 23 participants with myeloma precursor states and elevated BMI. The intervention was feasible and improved quality of life and modifiable risk factors: metabolic (BMI, insulin resistance), microbiome (diversity, composition), and immune (inflammation, monocyte subsets). Disease progression trajectory improved (n = 2) or was stable. Findings were translated to Vk*MYC mice modeling the myeloma precursor state, in which a high-fiber diet (HFD) delayed disease progression through improved metabolism and microbiome composition, leading to increased short-chain fatty acid production that reinvigorated antitumor immunity and inhibited tumor growth. These effects from fiber consumption were independent of calorie restriction and weight loss. A HFD is a low-risk intervention that may delay progression to myeloma. Significance: A HFPBD in participants with precursor plasma cell disorders and an elevated BMI improved metabolic, microbiome, and immune biomarkers of disease. In a subset, it may delay progression to myeloma. In mouse models, a HFD delayed progression to myeloma independent of calorie restriction. See related commentary by Fairfield and Reagan, p. 623
Derivation and external validation of a venous thromboembolism risk prediction model in asparaginase-treated ALL
Abstract The incidence of venous thromboembolism (VTE) in patients with acute lymphoblastic leukemia (ALL) receiving asparaginase-based induction is high despite primary thromboprophylaxis. Our aim was to derive and externally validate a VTE risk prediction model in patients with ALL receiving asparaginase-based induction. We conducted a multicenter retrospective cohort study of patients (aged ≥18 years) with newly diagnosed ALL receiving asparaginase-based induction. The derivation and external validation cohorts included 306 and 94 patients, respectively. Primary outcome was VTE at any site. A cause-specific Cox proportional hazards model stratified by thromboprophylaxis and center was performed to identify VTE risk factors in the derivation cohort. A risk prediction model for VTE at 30 days was derived using variables with P value < .05 in the multivariable model and was tested in the validation cohort. VTE risk factors on multivariable analysis in the derivation cohort included D-dimer ≥1 μg fibrinogen equivalent unit per mL (hazard ratio [HR], 2.64; 95% confidence interval [CI], 1.07-6.5) and hemoglobin (HR for each 1 g/dL increment, 1.19; 95% CI, 1.06-1.34) at ALL diagnosis. A VTE risk score based on these variables distinguished between a 4% (95% CI, 0.72-12) and 20% (95% CI, 14-27) 30-day cumulative incidence of VTE in the derivation cohort, with similar findings in the validation cohort (area under the curve, 0.56). The negative predictive value for VTE at 30 days was 96% and 93% in the derivation and validation cohorts, respectively, and the positive predictive value was 20% in both. We derived and validated a model using D-dimer and hemoglobin, which stratifies VTE risk in patients with ALL receiving asparaginase-based induction.
Genomics Define Malignant Transformation in Myeloma Precursor Conditions
Journal of Clinical Oncology | October 8, 2025 | Volume: 44 | Issue: 3 | Pages: 188-199
Multiple myeloma (MM) is consistently preceded by monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM). While these precursor conditions are asymptomatic, they are not entirely benign and carry a lifelong risk of progression to MM. Unlike other cancers defined by pathology, malignant transformation from MGUS or SMM to MM has so far relied on demonstration of clinical end-organ damage as morphology and cytogenetics cannot reliably distinguish them. In this study, using genomic data from 374 patients with MGUS or SMM (277 training, 97 validation), to our knowledge, we demonstrate for the first time the ability to identify malignant transformation in MGUS and SMM. We introduce the concept of genomic MM and genomic MGUS to differentiate the subsets of MGUS and SMM that are biologically malignant with genomic features indistinguishable from MM from the subset that is premalignant and unlikely to progress to malignancy. Importantly, we find that most SMM has biological features of malignant transformation indistinguishable from MM. As expected, this subset that we consider having genomic MM is associated with a high risk of progression to MM although some patients remained progression-free beyond 5 years. Conversely, 60% of MGUS and 10% of SMM have no evidence of malignant transformation (genomic MGUS), with no progression during follow-up. Integration of genomic features with the 2/20/20 International Myeloma Working Group model significantly improved the prediction of progression among genomic MM. These findings support the use of genomic criteria to refine the classification and the risk stratification in myeloma precursor conditions.
Genomic Classification and Individualized Prognosis in Multiple Myeloma
Journal of Clinical Oncology | January 9, 2024 | Volume: 42 | Issue: 11 | Pages: 1229-1240
PURPOSE Outcomes for patients with newly diagnosed multiple myeloma (NDMM) are heterogenous, with overall survival (OS) ranging from months to over 10 years. METHODS To decipher and predict the molecular and clinical heterogeneity of NDMM, we assembled a series of 1,933 patients with available clinical, genomic, and therapeutic data. RESULTS Leveraging a comprehensive catalog of genomic drivers, we identified 12 groups, expanding on previous gene expression–based molecular classifications. To build a model predicting individualized risk in NDMM (IRMMa), we integrated clinical, genomic, and treatment variables. To correct for time-dependent variables, including high-dose melphalan followed by autologous stem-cell transplantation (HDM-ASCT), and maintenance therapy, a multi-state model was designed. The IRMMa model accuracy was significantly higher than all comparator prognostic models, with a c-index for OS of 0.726, compared with International Staging System (ISS; 0.61), revised-ISS (0.572), and R2-ISS (0.625). Integral to model accuracy was 20 genomic features, including 1q21 gain/amp, del 1p, TP53 loss, NSD2 translocations, APOBEC mutational signatures, and copy-number signatures (reflecting the complex structural variant chromothripsis). IRMMa accuracy and superiority compared with other prognostic models were validated on 256 patients enrolled in the GMMG-HD6 (ClinicalTrials.gov identifier: NCT02495922 ) clinical trial. Individualized patient risks were significantly affected across the 12 genomic groups by different treatment strategies (ie, treatment variance), which was used to identify patients for whom HDM-ASCT is particularly effective versus patients for whom the impact is limited. CONCLUSION Integrating clinical, demographic, genomic, and therapeutic data, to our knowledge, we have developed the first individualized risk-prediction model enabling personally tailored therapeutic decisions for patients with NDMM.
Effect of additional cytogenetic abnormalities on survival in arsenic trioxide-treated acute promyelocytic leukemia
AbstractFrontline arsenic trioxide (ATO)–based treatment regimens achieve high rates of long-term relapse-free survival in treating acute promyelocytic leukemia (APL) and form the current standard of care. Refining prognostic estimates for newly diagnosed patients treated with ATO-containing regimens remains important in continuing to improve outcomes and identify patients who achieve suboptimal outcomes. We performed a pooled analysis of exclusively ATO-treated patients at a single academic institution and from the ALLG APML4 and Alliance C9710 studies to determine the prognostic importance of additional cytogenetic abnormalities and/or complex karyotype. We demonstrated inferior event-free survival for patients harboring complex karyotype (hazard ratio [HR], 3.74; 95% confidence interval [CI], 1.63-8.56; P = .002), but not for patients harboring additional cytogenetic abnormalities (HR, 2.13; 95% CI, 0.78-5.82; P = .142). These data support a role for full karyotypic analysis of all patients with APL and indicate a need for novel treatment strategies to overcome the adverse effect of APL harboring complex karyotype.