Feasibility of decentralized real-world monitoring of SARS-CoV-2 booster vaccines and COVID-19 outcomes in myeloma.

Introduction

Across medicine, patients, clinicians, and researchers face critical questions every day related to illness and care delivery for which insufficient evidence exists to guide management. This is especially true in multiple myeloma (MM), 1 of 2 conditions prioritized within the American Society of Hematology (ASH) Research Collaborative (RC). The ASH RC established a real-world data infrastructure, the ASH RC Data Hub, a national registry developed to generate real-world evidence to catalyze meaningful, measurable, and sustainable changes in practice that improve patient outcomes. 1 , 2 National stakeholders have called for investment in longitudinal registries because of persistent care quality gaps. 3 Unfortunately, the traditional biomedical evidence generation enterprise in the United States is extremely expensive and inefficient, 4 , 5 , 6 and registries can serve as a strategically coordinated registry network (CRN) to bolster research and expedite evidence generation. CRNs engage partners such as regulators, industry professionals, clinicians, and patients who seek to derive value from real-world evidence to address their distinct interests and evidentiary needs. 7

Limitations in evidence generation efficiency were particularly exposed during the COVID-19 pandemic. Early in the pandemic, case series and registry evidence suggested high mortality rates for patients with MM who acquired COVID-19 infection, while also showing disparities by race/ethnicity, which illustrated the intersection of social and medical vulnerabilities to compound risk. 8 , 9 Taken together, these observations highlighted the need for rapid evidence generation to improve outcomes in high-risk populations.

The development of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) vaccines offered a pathway to reduce adverse outcomes; however, immunocompromised patients, including those with hematologic malignancies, continued to experience an elevated rate of adverse outcomes, 10 , 11 , 12 which may have been related to prior therapeutic exposures. 13 Quality of life (QOL), functioning, and symptoms are known to be affected by underlying hematologic disease and treatment; however, the degree to which these parameters are further affected by COVID-19 infection and SARS-CoV-2 vaccination in this population remains uncertain. A mechanism was needed to rapidly and efficiently evaluate vaccine uptake, exposures, and patient-centered outcomes to generate real-world evidence on the impact of COVID-19 infection and SARS-CoV-2 vaccination among patients diagnosed with MM.

Thus, the ASH RC designed the COVID-19 outcomes in myeloma and the impact of vaccines (COSMIC) study, a decentralized real-world feasibility study implemented within the ASH RC Data Hub MM Research Network, to bypass efficiency constraints of site-based research associated with traditional mechanisms while preserving rigorous, patient-centered outcome measurement. This study aimed to establish a proof of concept for adapting a national data hub program to assess pandemic preparedness and, more broadly, to address urgent evidence generation needs across hematology. This article reports the design and feasibility outcomes of the COSMIC study, which was conducted through the ASH RC MM Data Hub Program.

Methods

This was a prospective, decentralized study conducted between 22 January 2024 and 1 December 2024. The study was reviewed and approved by the Western Copernicus Group Institutional Review Board, and all study procedures followed applicable ethical standards. The study was registered on ClinicalTrials.gov in accordance with reporting requirements and to ensure transparency in study conduct and design ( NCT05831787 ).

Eligible participants included individuals with a diagnosis of MM, per the International Myeloma Working Group, and were enrolled across disease phases, including induction, maintenance, and relapsed/refractory disease. 14 Participants were required to have internet access, an active patient portal (or willingness to activate), and to agree to sign the study-specific informed consent and authorization form electronically. Those without internet access, those with cognitive impairment precluding ability to provide informed consent, and non-English speaking individuals were excluded from the study. Participants were identified through chart review at 8 US academic medical centers that are part of the ASH RC MM Research Network. These centers reflect geographic and sociodemographic diversity, and all have large populations of individuals living with myeloma and clinicians dedicated to the care of these individuals.

Eight participating centers identified prospective, eligible participants and either provided them with an institutional review board–approved flyer during an in-person visit with their MM physician or care team or shared the flyer virtually using electronic health record (EHR) patient-facing software. The flyer included a high-level overview of the study, along with a link and a quick response code that directed patients to the study portal. The study portal was developed and maintained by Eureka Research (San Francisco, CA) and was used to collect all study data, including screening, informed consent and authorization, patient-generated health data, EHR transmission for patients whose health data resided in an EPIC systems platform, and patient-reported outcomes. Physicians and care team members were not engaged in the consenting process or any other research study activities.

A target enrollment of ∼200 participants was selected to balance feasibility, anticipated recruitment rates across participating sites, and the primary objective of assessing PRO completion and retention rather than clinical outcomes. Baseline demographic information, COVID-19 vaccinations, COVID-19 infections, and COVID-19–related hospitalizations were entered directly by participants using the study portal. COVID-19 infections were primarily ascertained via participant self-report, with EHR confirmation available for a subset of participants who consented to data linkage. For participants who consented to the use of their EHR data (57.5%), disease- and treatment-related clinical data, laboratory results, pathology reports, and imaging reports were captured. Eureka Health transmitted these data directly to the ASH RC, the study sponsor, at the conclusion of the study.

At baseline (time of COSMIC enrollment), day 30 (+15 days), and day 180 (+30 days), participants completed the European Organization for Research and Treatment of Cancer’s (EORTC) QOL (QOL) Questionnaire–Core 30 (QLQ-C30) and EORTC QOL Questionnaire–MM Module (QLQ-MY30) for comprehensive QOL characterization across physical, emotional, and social domains. 15 , 16 Participants were compensated upon completion of each study visit in the amounts of $200 at baseline, $100 at day 30, and $100 at day 180. Compensation amounts were determined based on the time required to complete each visit and to support longitudinal retention. Health care personnel at sites where participants received care were able to review PRO results corresponding to their patients through a study portal. ASH RC staff designed QOL scoring visual reports at the participant level ( Figure 1 provides an example of aggregated data across patients). These visuals were designed to facilitate easier access and comprehension, as well as for sharing with participants during clinic visits. Figure 1. CONSORT-style diagram. Data on patients approached but not enrolled were limited due to the decentralized recruitment model and are noted as such.

The ASH RC study team monitored participant visits and used system-generated and manual reminders to encourage visit completion when deadlines approached. Participants received remuneration for data completion at baseline and follow-up time points.

The primary study end point was the percentage completion (feasibility) of baseline, 30-day, and 6-month clinical and PRO data capture from 200 consented patients. Additional end points included the proportion of patients who received a SARS-CoV-2 booster before or during study participation, the incidence of patient-reported, test-confirmed COVID-19 infections, and hospitalization or death due to COVID-19.

The study was not designed to evaluate the efficacy or safety of SARS-CoV-2 vaccines; therefore, event reporting was recommended to occur through usual standards of practice.

Demographic and clinical characteristics were summarized and evaluated within and between groups of interest, including between those with and without follow-up data at given time points, and those with and without a history of COVID-19 infection. Χ 2 tests and Fisher exact tests were used to compare categorical outcomes between groups, and Wilcoxon rank-sum test was used to compare continuous outcomes between groups. Univariate and multivariable logistic regression models were used to evaluate the influence of varied factors of interest on history of having had a prior COVID-19 infection. PROs were evaluated and scored at baseline, 1 month, and 6 months, and area under the curve approaches were used to evaluate patterns of change in these measures over this time frame. Graphical analyses were also used to evaluate overall patterns in these measures.

Results

A total of 201 participants enrolled in the study ( Figure 1 ). The first patient consented on 22 January 2024, and the enrollment goal of 200 patients was met on 17 May 2024, which was 44 days ahead of the anticipated recruitment milestone date. Baseline demographic data for all 201 participants are shown in Table 1 . The median age of participants was 68 years (range, 30-93). The cohort was racially and ethnically diverse, with 17.3% identifying as Black or African American, 7.7% as Hispanic or Latino/Latina, and 69.4% as non-Hispanic White (NHW). The sample composed of slightly more male (54.1%) than female (45.9%), consistent with the known epidemiology of MM. One participant withdrew from the study, and an additional 6 patients were lost to follow-up after study entry and effectively dropped out of the study. Of 196 participants who provided information at baseline on prior history of COVID-19 infection, 111 (56.6%) reported prior infection, 81 (41.3%) no prior infection, and 4 (2.1%) did not know. Table 1. Baseline data Total (N = 201) Age, y Mean (SD) 66.1 (10.21) Median 68.0 Range 30.0-93.0 Race, n (%) American Indian or Alaskan Native 1 (0.5) American Indian or Alaskan Native/White 1 (0.5) Asian 8 (4.1) Asian/Native Hawaiian or Pacific Islander 1 (0.5) Black or African American 34 (17.3) Decline to answer 2 (1.0) Native Hawaiian or Pacific Islander 1 (0.5) Other 5 (2.6) White 143 (73.0) Missing 5 Birth sex, n (%) Male 106 (54.1) Female 90 (45.9) Missing 5 Hispanic ethnicity, n (%) Hispanic or Latino/Latina 15 (7.7) Not Hispanic or Latino/Latina 174 (88.8) Decline to answer 7 (3.6) Missing 5 Race/ethnicity group, n (%) Non-Hispanic Black 33 (16.8) NHW 136 (69.4) Hispanic or Latino/Latina 15 (7.7) Other 12 (6.1) Missing 5 SD, standard deviation.

Table 2 presents the PRO instrument completion rates by visit: 97% of patients completed baseline PROs, with 81% completing PROs at the 1-month follow-up and 79% at the 6-month follow-up. Overall, there were no significant differences in sociodemographics or other variables among patients who completed PROs compared to those who did not complete PROs at each time point. Baseline demographic and clinical characteristics were compared between participants who completed day 180 PRO assessments and those who did not assess potential survivorship or attrition bias. Table 2. Proportion of participants completing PRO instruments Visit No. of patients who completed/total patients Proportion completed (exact binomial CI) Baseline 195/201 0.97 (0.94-0.99) 1-month follow-up 162/201 0.81 (0.74-0.86) 6-month follow-up 159/201 0.79 (0.73-0.85)

We investigated potential differences in baseline characteristics based on history of COVID-19 infection ( supplemental Table 1 ). Although differences were observed by age and race, no differences were found in vaccine history or baseline health-related QOL between the groups. Of those who reported a history of COVID-19 infection, 10.8% reported that ≥1 prior infection had caused hospitalization. In multivariable logistic regression modeling ( supplemental Table 2 ), we confirmed that, in our cohort, older patients had a lower likelihood of having a history of COVID-19 infection (for each 10-year increase in age, odds ratio [OR], 0.63; 95% confidence interval [CI], 0.45-0.89; P = .008). In addition, identifying as non-Hispanic Black was also associated with a lower likelihood of having a history of COVID-19 infection than NHW patients with myeloma (OR, 0.29; 95% CI, 0.12-0.69; P = .005). Hispanic ethnicity did not appear to be significantly associated with a history of COVID-19 infection in relation to NHW (OR, 1.48; 95% CI, 0.37-5.89; P = .58), although there were limited numbers of patients in this subgroup (n = 15). Despite the limited numbers of patients with myeloma in our cohort who identified as non-Hispanic and a race other than White or Black/African American (here, labeled as “other race”), this group was associated with reduced likelihood of having prior history of COVID-19 infection, with an effect size similar to that of the non-Hispanic Black group (OR, 0.26; 95% CI, 0.07-0.95; P = .042). No significant associations were observed between prior COVID-19 infection and birth sex or baseline global QOL.

Notwithstanding the limited time frame for follow-up as part of this study, we demonstrated the ability to capture incident events of interest, such as COVID-19 infections and vaccinations occurring during follow-up ( supplemental Table 3 ). COVID-19 infections were ascertained via participant self-report, with EHR verification available for a subset of participants who consented to data linkage. At the 1-month visit, 3 patients (1.9%) reported interval COVID-19 infections, with an additional 15 patients (9.3%) reporting interval COVID-19 infection at the 6-month visit. Of those with follow-up data available at the given time points, 18 patients (11.1%) reported receiving interval SARS-CoV-2 vaccines at the 1-month visit, and 39 patients (24.1%) reported receiving interval SARS-CoV-2 vaccines at the 6-month visit. Clinical characteristics, treatment status, and comorbidities were collected via participant report and supplemented with EHR data when available; 58% of participants consented to EHR linkage.

We examined the longitudinal QOL assessments from the EORTC QLQ-C30 and QLQ-MY20 instruments. Overall, domain scores remained stable over time ( Figure 2 ), and there were no apparent differences in the global health status/QOL score over time between patients with or without a history of COVID-19 infection ( Figure 3 ). QOL scores over time as a function of baseline QOL score are shown in supplemental Figures 1 and 2 . Figure 2. Example physical functioning scores for patients across the study period. Visuals were shared with site principal investigators to facilitate review and interpretation of patients’ QOL during study participation. Dashed horizontal lines indicate the minimally important difference (MID; ±5 points), representing the threshold for clinically meaningful change in physical functioning from baseline. Figure 3. Example pain scores over time by history of COVID-19 infection. Visuals were shared with site principal investigators to facilitate review and interpretation of patients’ QOL during study participation. Dashed horizontal lines indicate the MID (±5 points), representing the threshold for clinically meaningful change in physical functioning from baseline.

Although there was no relationship with COVID-19 history, the QLQ-C30 and QLQ-MY-20 scores demonstrated significant functional impairment and symptom burden in our cohort ( supplemental Tables 1 and 2 ). For example, 129 patients (66.2%) reported at least some trouble with long walks, 80 patients (41.1%) needed to stay in a bed or chair at least some of the time, and 96 patients (49.5%) were at least somewhat limited in their work or daily activities. Prevalent symptoms included dyspnea (39.7% of patients), pain (73.9%), feeling weak (64.7%), and feeling tired (85.6%). Back pain and neuropathy were commonly experienced. Among patients, 92.8% reported thinking about their illness, 55.3% were worried about dying, and 91.6% were worried about their health in the future.

Discussion

The COSMIC study was a prospective, decentralized study that demonstrated proof of concept in both its ability to meet specific evidence needs during the COVID-19 endemic in an immunocompromised population and its ability to serve as an efficient platform for broader evidence generation in hematology. In MM and other hematologic conditions, early pandemic registry data underscored COVID-19–related risk, 17 illustrating the need for this type of platform to generate just-in-time evidence in the future.

Consistent with emerging best practices for decentralized clinical research, COSMIC demonstrated the feasibility of rapid patient enrollment and longitudinal follow-up through a site-based provider network and a data hub program while minimizing site burden. The US Food and Drug Administration guidance documents encourage the use of real-world data to generate real-world evidence and decentralized and hybrid research approaches when appropriate, which may include remote data capture and patient-facing interfaces that lower barriers to participation. 18 Large-scale studies such as the virtualized CHIEF-HF randomized trial demonstrate that these approaches are feasible on a national scale, supporting the premise underlying COSMIC. 19 , 20

COSMIC enrolled a diverse, real-world cohort of individuals with MM who had a history of SARS-CoV-2 infection or had received the mRNA COVID-19 vaccination. Enrollment concluded ahead of schedule, because providers and patients found the study simple to discuss and easy to access, with minimal incremental workload for sites beyond disseminating materials or speaking with patients during routine visits. A “help desk”–style support system provided by the ASH RC assisted participants who encountered usability issues with the platform. Monthly calls with participating physician site representatives and brief newsletters from the ASH RC principal investigators shared with other network principal investigators facilitated shared learning and process improvement, an approach used in learning health systems and multisite real-world evidence programs. 1 , 21

The cohort was sociodemographically diverse and reflective of the populations of the participating sites. Engagement and retention were reasonable, with 79% of patients continuing to provide data at 6 months and no significant sociodemographic differences between those who were retained and those lost to follow-up, suggesting that the retained cohort maintained generalizability. Participant compensation, low study activity burden for participants, and reminders from ASH RC staff likely contributed to retention.

A substantial proportion of participants reported a history of COVID-19 infection or SARS-CoV-2 vaccination at baseline and additional events during follow-up, indicating that the decentralized design was capable of capturing time-sensitive information during a pandemic. At the same time, the PRO data provided clinical context about patient functioning, symptoms, and QOL. A history of COVID-19 infection did not appear to have a significant relationship with overall QOL PROs in this cohort. The receipt of SARS-CoV-2 vaccines also did not appear to have a significant detrimental impact on PROs, because PRO trajectories remained stable despite reports of additional vaccines received during the study period. The study population had substantial functional deficits and symptom burden at baseline and throughout the 6-month observation. Thus, the effects of disease and treatment may have outweighed the impact of COVID-19 infection or SARS-CoV-2 vaccination on patient experience. These deficits underscore an urgent need to advance therapies and supportive care to mitigate symptom burden and improve PROs for individuals living with MM.

Collectively, rapid enrollment, high retention, ascertainment of infections and vaccinations, and detailed QOL and symptom data demonstrated important proof of concept for COSMIC as a study conducted within the ASH RC Data Hub, a CRN, in generating real-world evidence on the impact of the pandemic and boosters on the experience of patients with MM. It may be that given the significant symptom burden, at least a proportion of these patients would not be offered clinical trials, highlighting the ability to collect meaningful data on a population essentially invisible to traditional research efforts. Future analyses integrating EHR data for patients who consented to linkage will add clinical context and end points such as hospitalization and death. These linkages are consistent with national real-world evidence infrastructures that combine EHR, PRO, and other data streams at scale. 21 , 22

We acknowledge several limitations in our approach. Because we did not enroll consecutive patients or undertake more formal analyses of representativeness, we are limited in our ability to claim true generalizability of our findings. We did not have Spanish language patient-facing materials, and our use of a patient portal implied the need for some level of internet connectivity, ability to read, and digital literacy; these elements can contribute to disparities unless specifically addressed. 23 Although we provided PRO data to clinicians, we did not formally study the utility of these data in guiding clinical insight or decision-making. Prior randomized studies have shown that electronic PRO monitoring can reduce unplanned acute care events and improve survival; however, this effect is dependent on the implementation of carefully designed pathways. 24 , 25 , 26 , 27

Nonetheless, the decentralized research approach developed within the ASH RC Data Hub, which leveraged engaged sites and a provider network, may prove useful for addressing rapid evidence development needs. With additional modifications and enhancements, the platform can be repurposed for many additional uses. For example, provider-facing tools can be developed to promote provider engagement, facilitate identification of patients meeting more sophisticated inclusion/exclusion criteria, and encourage referrals to the study enrollment portal. 28 With consent, patient data in the portal can be linked to patient data in the ASH RC Data Hub, a site-based continuous data repository of EHR and electronic case report form data for patients seen in usual care at each site. In this type of decentralized design, in which there is an external sponsor, supportive care, navigation, or decision-support interventions can be developed and administered either externally or through communication with local providers at the site. The design of this study, in obtaining PRO data from patients, aggregating at the Data Hub level, and feeding the PRO data back to site providers, illustrates how this type of closed-loop intervention can proceed.

Limitations

Although COSMIC demonstrates the feasibility of decentralized, patient-facing research in MM, the study population may not be fully representative of the broader MM community. Participation required English proficiency, internet access, and comfort with digital tools, which likely excluded some patients who are older, socioeconomically disadvantaged, or from racial and ethnic minority groups. These populations have borne a disproportionate burden of COVID-19–related morbidity and mortality, and thus, findings from this study should be interpreted primarily as a proof of concept for decentralized data collection rather than as broadly generalizable estimates. Although vaccination status and COVID-19–related hospitalizations were collected, the study was not designed or powered to assess associations between vaccination receipt and severity of COVID-19 outcomes.

As with many longitudinal PRO studies, follow-up completion was not random. Participants with worse health status or more severe COVID-19 illness may have been less likely to complete follow-up surveys, potentially biasing observed PRO stability over time. Furthermore, COVID-19 infection status was primarily self-reported, and EHR confirmation was not uniformly available, introducing potential misclassification. This reflects a common challenge in decentralized studies conducted during rapidly evolving public health emergencies. Analyses of prior COVID-19 infection history may be subject to immortal time bias, particularly among older participants, because individuals with severe infections early in the pandemic may not have survived to enrollment.

Although COSMIC demonstrates the potential of decentralized platforms, limited EHR linkage constrained the granularity of treatment-specific and immunosuppression-related analyses. Future iterations of this infrastructure will prioritize broader EHR integration to enable more detailed risk stratification.

Conclusion

In conclusion, observed stability in PRO scores over follow-up should be interpreted cautiously. The baseline symptom burden was high in the study population, follow-up duration was limited, and data missingness may also be nonrandom. Therefore, the findings from the COSMIC study should not be interpreted as evidence that COVID-19 infection had limited or no impact on QOL in patients with MM. Although acknowledging this, the COSMIC study demonstrated that rapid, real-world evidence generation was feasible for patients with MM confronting the COVID-19 endemic. The platform, developed as a proof of concept with COSMIC, will help create research-ready networks that can respond to pandemics or other future urgent evidence generation needs in hematology.

Conflict-of-interest disclosure: S.Z.U. is the Chair of the American Society of Hematology (ASH) Research Collaborative Multiple Myeloma Research Network; a member of the ASH Research Collaborative Multiple Myeloma Scientific Research Project Team; a member of the ASH Research Collaborative Data Quality Project Team; reports research funding from AbbVie, Amgen, Bristol Myers Squibb (BMS)/Celgene, Gracell, Gilead, GSK, Janssen, Merck, Pharmacyclics, Takeda, Seattle Genetics, Sanofi, and SkylineDx; and serves as a consultant for AbbVie, Amgen, BMS/Celgene, GSK, Genentech/Roche, Merck, Janssen, Regeneron, and Sanofi. E.A.S., S.J., and K.T. are employees of the ASH Research Collaborative. W.A.W. reports leadership positions with oversight groups and committees within the ASH Research Collaborative; reports research funding from Genentech; equity ownership in Koneksa Health; and consultancy fees from Lantern Health, Teladoc Health, and Quantum Health. D.S.N. has held an advisory position with the ASH Research Collaborative. R.V. serves on advisory boards for Janssen, Sanofi, BMS, Pfizer, and GSK. S. Richard reports honoraria from Janssen, BMS, Genentech, Karyopharm Therapeutics, MJH Life Sciences, Haymarket, and OncLive; serves on BMS’s Steering Committee; reports research support from Janssen, BMS, C4 Therapeutics, AstraZeneca, and Heidelberg Pharma; sits on the advisory boards of Genentech, Janssen, BMS, Karyopharm Therapeutics, and AstraZeneca; and is a member of the ASH Research Collaborative Multiple Myeloma Research Network Council and the ASH Research Collaborative Multiple Myeloma Scientific Research Project Team. S. Rubinstein serves as a consultant for Johnson & Johnson, Sanofi, and BMS; and is a cochair of the ASH Research Collaborative Multiple Myeloma Data Quality Project Team. A. D’Souza is a member of the ASH Research Collaborative Multiple Myeloma Research Network Council and the ASH Research Collaborative Multiple Myeloma Scientific Research Project Team. M.A.S. is a member of the ASH Research Collaborative Multiple Myeloma Research Network Council. D.J.C. is a member of the ASH Research Collaborative Multiple Myeloma Research Network Council. B.M.W. is an employee of and reports stock ownership in Moderna. S.K.K. reports consulting with no personal payment for AbbVie, Amgen, Arcellx, BeiGene, BMS, CARsgen, GSK, Janssen, K36, Moderna, Pfizer, Regeneron, Roche-Genentech, Sanofi, and Takeda and with personal payment for CVS Caremark and BD Biosciences; and reports clinical trial support to institution from AbbVie, Amgen, AstraZeneca, BMS, CARsgen, GSK, Gracell Bio, Janssen, Oricell, Roche-Genentech, Sanofi, Takeda, and TeloGenomics. A.K.N. has served on advisory boards and received honorarium from AstraZeneca, Cellectar Biosciences, GlaxoSmithKline, Janssen, Kite Therapeutics, ONK Therapeutics, Opna, Pfizer, Perceptive Informatics LLC, Premier Research, and Sebia. The remaining authors declare no competing financial interests.

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Supplementary Material

Supplemental Tables and Figures

Acknowledgments

The authors thank the participating sites and investigators for their valuable contributions to this study. They are especially grateful to the patients and their families, whose participation made this research possible. Biostatistical support was provided by Susan Geyer and Levi Pederson at 10.13039/100000871 Mayo Clinic . The following sites successfully recruited patients into the study: 10.13039/100007052 Memorial Sloan Kettering Cancer Center , the 10.13039/100007890 University of North Carolina at Chapel Hill , 10.13039/100011912 Washington University School of Medicine in St. Louis , 10.13039/100005595 University of California , Davis, Karmanos Cancer Institute , 10.13039/100008980 Medical College of Wisconsin , 10.13039/100007277 Icahn School of Medicine at Mount Sinai , and 10.13039/100007886 Dana-Farber Cancer Institute .

This study was sponsored by the American Society of Hematology (ASH) Research Collaborative and funding was provided by 10.13039/100019533 Moderna, Inc .

The views expressed in this publication are solely of the authors and do not represent the opinion of the ASH Research Collaborative, 10.13039/100001422 ASH , or 10.13039/100019533 Moderna, Inc . The ASH Research Collaborative holds exclusive ownership of the cross-institutional data.

Authorship

Contribution: W.A.W. contributed to the study design, drafting of the manuscript, interpretation of analysis, and final review; E.A.S. and S.J. contributed to the study design, study execution, and drafting of the manuscript; D.S.N. contributed to the study design and read and commented on the final draft of the manuscript; S. Rubinstein, A. D'Souza, S. Richard, M.A.S., D.J.C., A.R., J.Z., T.M., A.C., R.V., and K.C.A. contributed to patient enrollment and provided critical review of the manuscript; B.M.W. and S.K.K. contributed to the study design and provided critical review of the manuscript; A.K.N. provided critical review of the manuscript; S.Z.U. contributed to the study design, drafting of the manuscript, interpretation of analysis, and final review of the manuscript; L.P., A. Derkach, and S.G. contributed to the data analysis and critical review of the manuscript; and K.T. contributed to the study design and study execution and provided critical review of the manuscript.

The deidentified data used in this study may be available for additional research inquiries through our formal research proposal application process. For more information, please contact info@ashrc.org .

The full-text version of this article contains a data supplement.