Chung, David J

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.

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

Background: Contemporary questions about treatment and outcomes of patients (pts) living with multiple myeloma (MM) demand efficient and timely evidence generation methods, where real-world/ everyday practice data can play an important role. Relevant potential applications include understanding and addressing disparities in treatment access, mitigating toxicities of novel therapies while maintaining quality of life, appropriately sequencing treatments within long-term management strategies, and disseminating and appropriately using surrogate endpoints in practice, such as minimal residual disease. However, existing real-world data (RWD) repositories are limited by an inability to implement interventions in response to issues identified through retrospective data analysis, which is pivotal for the use of newer therapies. The ASH Research Collaborative (ASH RC) MM Data Hub Program was developed to address these gaps. Methods: We developed a multicenter network of US-based tertiary academic medical centers, engaging site clinicians, patients, biostatisticians, informaticians, and data scientists. Initial activities included constructing a shared real-world MM data model comprised of consensus core data elements. Pt data from each site, dating back to at least 2019, is currently being entered through electronic case report forms, batch uploaded utilizing existing institutional data repositories, and soon direct electronic health record import in standard data acquisition formats. Data are aggregated in the Data Hub and shared in a confidential Site Portal with each site. The Portal allows sites to track their own pts, analyze outcomes, and identify ways to improve the quality of care provided to individuals living with MM. We also developed an innovative evidence generation learning community of site clinicians who meet monthly and collaborate on the “COVID-19 OutcomeS in Myeloma and the Impact of VaCcines (COSMIC)” study, a prospective, decentralized observational study that rapidly accrued pts and collects relevant practice information. The group also shares best practices in study conduct to accelerate study enrollment and execution. Results: The MM Data Hub Program now contains twelve centers: Memorial Sloan Kettering Cancer Center, Mayo Clinic, Icahn School of Medicine at Mount Sinai, University of California San Francisco, University of California Davis, Medical College of Wisconsin, Barbara Ann Karmanos Cancer Institute, University of North Carolina Medical Center at Chapel Hill, Emory University Hospital, Washington University School of Medicine in St. Louis, Dana-Farber Cancer Institute, and Atrium Health. From this Network, six centers have contributed data from 8,824 pts (2,825 with sufficiently complete data are included in this analysis). The median age at time of MM diagnosis is 63, and of the 627 deceased pts, the median age at death is 70.6 years, with median time to death from first MM diagnosis of 6 years. The proportions of pts by decade of diagnoses are 34.9% from 2020-2024; 57.6% from 2010-2019; 7.3% from 2000-2009; and 0.9% prior to 2000. 83.1% of pts had a diagnosis of plasma cell myeloma (non-light chain), and 14.4% of pts had a diagnosis of light chain myeloma. 42.3% of pts are female, and the self-reported patient races are: 85.0% white; 9.2% black or African; and 4.3% all other races (race was not documented in 1.5% of pts). 2.8% of pts are of Hispanic ethnicity. Participant data files are currently undergoing completion and cleaning procedures; the analysis will include updated results at the meeting, and a Network-wide analytic data set will be available for initial retrospective data analyses in early 2025. The COSMIC study opened for enrollment on January 22, 2024, and completed enrollment of 200 pts on May 17, 2024. Conclusions: The ASH RC Data Hub MM Program launched in 2023 and is comprised of 12 sites that collectively have contributed participant files for 8,824 pts thus far. Utilizing the structure of the Network, we successfully implemented and established the feasibility of collecting data directly from pts electronically to monitor SARS-CoV-2 vaccines and COVID-19 related outcomes. The Program serves as a successful proof-of-concept model, providing an enduring RWD resource and a prospective evidence generation platform for the myeloma community.

Background: The COVID-19 pandemic had an outsized impact on individuals with immune compromise, such as multiple myeloma, leading to increased rates of severe COVID, hospitalization, and death in these groups. The pandemic also demonstrated the need for rapid and efficient evidence generation to address rapidly changing medical needs and accelerated the use of innovative trial designs to accomplish this goal. Methods: We designed and established a prospective, decentralized study within a site-based provider network, COVID-19 OutcomeS in Myeloma and the Impact of VaCcines (COSMIC), for patients with multiple myeloma at ASH Research Collaborative sites to monitor outcomes related to COVID-19 infection and vaccination. The direct-to-patient approach was accomplished using a study application accessed with a QR code provided to patients during usual clinical care. All study activities occurred within the patient portal at Baseline, Day 30, and Day 180, minimizing burden on site personnel and staff. Study activities included eligibility confirmation, consenting, electronic health record (EHR) data permissions, and patient-reported outcome (PRO) surveys. PRO data (EORTC QLQ-C30, EORTC QLQ MY-20) were made available to clinicians through the portal to visualize results from their patients. Patients shared if they received a COVID-19 vaccination or booster and if they had a COVID-19 infection. Patients with a history of COVID-19 infection included method of confirmation and if hospitalization was required. Patients were provided compensation for participation. Automated text and email messages were sent at three separate intervals: 24 hours, Day 8, and Day 15 for participants who initiated but did not complete study activities. A personal email reminder per participant was sent for those whose second study visit window was approaching. ASH Research Collaborative clinicians met regularly to share best practices related to enrollment and study conduct, thereby creating an innovative evidence generation learning community. We studied the feasibility of data collection in a decentralized format by focusing on the number of participants who interacted with the system, those who consented, and those who completed baseline PRO assessments. Results: The COSMIC study rapidly accrued and consented 200 patients from eight participating ASH Research Collaborative sites over four months (1/22/2024 through 5/17/2024): 69% self-reported as non-Hispanic White (NHW). Of enrolled participants, 57.5% opted to permission sharing of their EHR data, which included disease and treatment-related clinical data, laboratory results, pathology reports, and imaging reports. A total of 196 patients (98%) provided demographic and COVID-related disease and vaccine data at baseline; nearly all of these patients (n=195) provided baseline PRO data, and 150 patients provided further information at Day 30 at the time of this analysis. Those who did not provide Day 30 data were not significantly different from those who did in terms of age (median: 68 [no Day 30 data] vs. 67 [Day 30 data] years; p=0.44), sex (41% [no Day 30 data] vs. 47% [Day 30 data] Female; p=0.47), or race (65% [no Day 30 data] vs. 71% [Day 30 data] NHW; p=0.60). A higher proportion of Hispanic patients were retained at Day 30 (13/15=87%) vs. 78% of non-Hispanic patients or those who declined reporting ethnicity (2/7=29%; p=0.007). COVID-19 vaccination data were submitted by 196 patients, 186 of whom had ever received a COVID-19 vaccination. Data on number, type, brand, and dates for these vaccinations were provided. Conclusions: The COSMIC study conducted by the ASH Research Collaborative was able to rapidly accrue a diverse cohort of patients using a decentralized workflow within a site-based provider network, with high consent and compliance rates. This platform, and the innovative evidence generation learning community of ASH Research Collaborative investigators and patients, sets a precedent to address a variety of real-world questions related to disease management, infections, vaccinations, and PROs in this population of patients with multiple myeloma.

Background: Data from the ASH Research Collaborative COVID-19 Registry for Hematology demonstrated that patients with multiple myeloma and other immune compromise had elevated risk for severe complications from COVID-19 infection. To address current evidence gaps and to demonstrate proof of concept for a pandemic preparedness and response network, the ASH Research Collaborative Multiple Myeloma Program developed a prospective, decentralized study within a site-based provider network to investigate COVID-19 infections, vaccinations, and quality of life in patients with multiple myeloma. Methods: We designed and established the COVID-19 OutcomeS in Myeloma and the Impact of VacCines (COSMIC) to study COVID-19 in patients with multiple myeloma at ASH Research Collaborative network sites. A study application was accessed with a QR code and shared with patients during usual clinical care. Patients provided consent, optionally gave permission for electronic health record data collection, and completed patient-reported outcomes (EORTC QLQ-C30 and MY20) at baseline, Day 30, and Day 180 through the study portal. Clinicians at participating sites facilitated study enrollment and shared best practices monthly to accelerate study execution. Study objectives related to feasibility of data collection in a decentralized format are reported in a separate abstract. Here, we report interim results related to SARS-CoV-2 vaccination history, COVID-19 infection, and how these relate to patient reported outcomes and clinical outcomes in enrolled participants. Results: The COSMIC study rapidly accrued and consented 200 patients from eight participating ASH Research Collaborative sites over four months (1/22/2024 through 5/17/2024). Consented participants' ages ranged from 29 to 93 years, with median of 67 years; 46% were female, 69% were non-Hispanic White (NHW), 17% were non-Hispanic Black (NHB), and 8% were Hispanic/Latino. Of the 196 patients who reported COVID-19 data, 111 (57%) reported at baseline that they had a history of COVID-19 infection, with 12 having required hospitalization for this (12/111=11%). Overall, 95% (186/196) reported a history of COVID-19 vaccination, where the median number of vaccinations was 4 (range: 1 to 6); 44 patients (23%) expressed willingness to discuss getting a yearly booster vaccine with their provider. At 1-month follow-up, there were 3 additional patients who reported a COVID-19 infection and 18 patients who received an additional COVID-19 vaccination. The baseline EORTC QLQ-C30 median Global Health Status/QOL score was 66.7 (mean=64.4, range: 8.3 - 100, n=196). This overall global QOL score was not significantly different between those who did vs. did not have a history of COVID-19 infection (mean [SD]: 63.7 [19.3] vs. 65.8 [17.6]; p=0.57). In analyses adjusted for age, biological sex, and race/ethnicity group, history of COVID-19 infection was not associated with HRQOL (odds ratio=0.93, 95% CI: 0.78 - 1.10; p=0.38). Data collection is ongoing and final study results will be reported at a later date. Conclusion: COSMIC is a prospective, decentralized study within a site-based provider network conducted by the ASH Research Collaborative Multiple Myeloma Program that demonstrates the feasibility of using an innovative evidence generation strategy to drive rapid accrual of patients to address a rapidly evolving area of need. The COSMIC study also provides proof of concept that a real-world evidence generation network can play an important role in national pandemic preparedness and response. The COSMIC experience reinforces the ability to accrue diverse patient populations representing the demographic of myeloma patients in the US.

Introduction Poor diet quality, elevated body mass index (BMI), insulin resistance, microbiome dysbiosis, inflammation as well as immune dysfunction have all been implicated in progression from monoclonal gammopathy of undetermined significance (MGUS) and smoldering multiple myeloma (SMM) to multiple myeloma (MM). Plant-based diets have been associated with reduced risk of MGUS and MM in epidemiological studies. Whether a dietary intervention can impact these modifiable risk factors and delay disease progression has not been investigated. Methods We conducted a pilot, single-arm trial providing controlled high fiber plant based dietary (HFPBD) intervention for 12 weeks and health coaching for 24 weeks in 20 patients with MGUS/SMM with BMI≥25 (NCT04920084). The primary endpoint was feasibility (adherence and BMI reduction). Secondary and exploratory endpoints included quality of life, metabolic markers (insulin, adiponectin, leptin, LDL cholesterol), microbiome (diversity and composition by 16S and shotgun sequencing) and immune profiling in peripheral blood (flow cytometry and Olink inflammation panel) and bone marrow (scRNAseq and ATACseq). We also conducted an in vivo study in transgenic Vk*MYC mice fed a high fiber or control diet at the phase of mouse(m)SMM. The mice were monitored for the progression to active mMM. Differences in microbiome and immune response profiles between high fiber- and control-treated mice were assessed via microbiome 16S sequencing and flow cytometry. Results The HFPBD intervention was safe, feasible, improved quality of life and addressed modifiable risk factors - metabolic profile (improved BMI, insulin resistance, adiponectin leptin ratio), microbiome profile (increased alpha-diversity and butyrate producers) and immune (decreased inflammation and increased anti-inflammatory classical monocyte) subsets. A reduction in long-term progression trajectory was observed in 2 patients. Consistently, the high fiber diet delayed progression from mSMM to mMM in Vk*MYC mice increasing median progression-free survival from 12 weeks in the control arm to 30 weeks in the high fiber diet intervention arm. Additionally, in the intervention arm 40% of mice did not progress to mMM during the study period whereas all mice in the control arm progressed. Both human and mouse data showed that HFPBD modulated gut microbiota composition favoring the expansion of butyrate-producing bacteria. Additionally, short-chain fatty acids were increased in the feces of mice fed a high fiber diet. Integrated analysis from human bone marrow and peripheral blood analysis indicated that the dietary intervention reduced inflammatory biomarkers and skewed the immune response towards T helper and CD14+ monocytes. Consistently, the bone marrow of Vk*MYC mice fed high fiber diet was more infiltrated by IFNg-producing T lymphocytes while displaying less exhausted T cells and immunosuppressive myeloid cells. Conclusion This is the first interventional clinical trial and in vivo study to show that a HFPBD intervention may delay progression from MGUS/SMM to MM. To our knowledge there has been no similar dietary interventional study in hematological cancers or solid tumors. Together our in vivo and clinical data support the beneficial anti-inflammatory role of a HFPBD providing a link between diet, microbiota, and immune modulation to delay disease progression in MGUS/SMM.

High dose chemotherapy followed by autologous hematopoietic cell transplantation (auto HCT) is a standard therapy for patients with plasma cell disorders (PCD). A barrier to improving candidate selection for auto HCT is appraisal of risk for transplant related complications. Electrocardiography (ECG) is a standard pre-HCT test to evaluate the potential for arrhythmia and structural heart disease. We hypothesized that an artificial intelligence (AI) based interpretation of ECG waveform data (AI-ECG) could enhance risk prediction for cardiac-specific and other outcomes following auto HCT for patients with PCD. To test this hypothesis, we used several AI-ECG tools developed using a deep-learning based approach that were trained to predict comorbidity (Attia et al, Lancet 2019 & Grogan et al, Mayo Clin Proc 2021). Model outputs include a scaled prediction value indicating increasing risk for atrial fibrillation/flutter (AF), reduced ejection fraction (EF), or cardiac amyloidosis. We evaluated this tool in 9,225 ECGs obtained from 849 patients (median 6 ECGs/patient, inter-quartile range: 3-12) who underwent first or subsequent auto HCT at Memorial Sloan Kettering Cancer Center between 2016-2022 and who had a diagnosis of multiple myeloma (N = 810), amyloidosis (N = 37), or other PCD (N = 2). The endpoints were to determine whether baseline AI-ECG prediction of AF risk correlated with peri-transplant AF events, and to explore whether model outputs correlated with survival and other cardiac clinical outcomes. The mean age of patients was 61.0 years (range 23.7 - 81.2) and median follow up was 2.7 years post auto HCT. Contributing cardiovascular risk factors included a prior history of AF (N = 101, 11.9%), coronary or cerebrovascular disease (N = 95, 11.2%), and diabetes mellitus (N = 98, 11.5%). Reduced dose melphalan (< 200 mg/m 2) was administered in 26%. The HCT-comorbidity index (HCT-CI) was high risk (≥3) in 52.7%. The one-year overall survival and progression-free survival in the whole cohort was 94% (95% confidence interval (95% CI): 92 - 95%) and 86% (84 - 89%), respectively. Among patients not in AF at pre HCT evaluation, the 90-day cumulative incidence of AF was 5.6% (4.2 - 7.3%). In univariable competing risk regression, baseline pre HCT AI-ECG appraisal of AF risk was strongly correlated with incidence AF in patients who were in sinus rhythm before HCT (hazard ratio (HR): 25.1, 95% CI: 11.7 - 53.7, p < 0.001). In a multivariable model adjusting for patient age and HCT-CI, AI-ECG AF predicted risk remained associated with incidence of post HCT AF (HR: 13.4, 95% CI: 5.9 - 30.4, p < 0.001). Considering a decision threshold identified during original model training, AI-ECG predicted AF events with an accuracy of 75% (Mcnemar's p < 2 x 10 -16). The precision, recall, and F1-score were 0.94, 0.77, and 0.85, respectively. AI-ECG predicted age correlated highly with actual patient age (Spearman rho = 0.59, p < 2 x 10 -16). Amyloid risk scores were highly correlated with a known clinical history of amyloidosis (median 0.45 versus 0.05, Wilcoxon rank-sum p < 0.001). Patients with EF < 50% had greater prediction scores for cardiomyopathy compared to patients with normal EF (median 0.23 versus 0.01, Wilcoxon rank-sum p <0.001). In univariable analysis, increasing AI-ECG predicted age (HR 1.02, CI: 1.003 - 1.04, p = 0.02) and predicted AF risk score (HR: 3.2, CI: 1.4 - 7.2, p = 0.006) were associated with risk for death, whereas predicted amyloid score and predicted low EF were not associated with decreased survival. In multivariable analysis of all patients that considered patient age, hematopoietic comorbidity index, and remission status at HCT, increasing predicted AF score trended towards association with increased risk for death (HR: 2.3, 95%CI: 1.0 - 5.5, p = 0.059). Predicted AF score correlated highly with the HCT-CI and patient age. Finally, we examined whether risk prediction for low EF correlated with peri-HCT fluid overload (FO) defined by absolute weight gain. The incidence of ≥ 10% weight gain (grade 2 FO) and ≥ 20% weight gain (grade 3 FO) at 180 days post HCT was 7.4% (95% CI: 5.8%, 9.3%) and 1.0% (95% CI: 0.5%, 1.8%), respectively. Predicted low EF was not associated with development of either grade 2 or grade 3 FO in this population. In summary, AI-ECG predicts episodes of AF in patients undergoing auto HCT for PCD and may augment transplant risk appraisal when considered in conjunction with other measures of comorbidity.