Association of Reduced-Intensity Conditioning Regimens With Overall Survival Among Patients With Non-Hodgkin Lymphoma Undergoing Allogeneic Transplant | Stem Cell Transplantation | JAMA Oncology | JAMA Network
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Figure.  Adjusted Outcomes of Patients With Non-Hodgkin Lymphoma Undergoing Reduced-Intensity Conditioning Allogeneic Transplant
Adjusted Outcomes of Patients With Non-Hodgkin Lymphoma Undergoing Reduced-Intensity Conditioning Allogeneic Transplant

Bu indicates busulfan; Cy, cyclophosphamide; Flu, fludarabine; Mel, melphalan; and TBI, total body irradiation.

Table.  Engraftment, GVHD, and Adjusted Transplant Outcomes
Engraftment, GVHD, and Adjusted Transplant Outcomes
1.
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Klyuchnikov  E, Bacher  U, Kröger  NM,  et al.  Reduced-intensity allografting as first transplantation approach in relapsed/refractory grades one and two follicular lymphoma provides improved outcomes in long-term survivors.   Biol Blood Marrow Transplant. 2015;21(12):2091-2099. doi:10.1016/j.bbmt.2015.07.028PubMedGoogle ScholarCrossref
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Shah  NN, Ahn  KW, Litovich  C,  et al.  Outcomes of Medicare-age eligible NHL patients receiving RIC allogeneic transplantation: a CIBMTR analysis.   Blood Adv. 2018;2(8):933-940. doi:10.1182/bloodadvances.2018018531 PubMedGoogle ScholarCrossref
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Hamadani  M, Saber  W, Ahn  KW,  et al.  Allogeneic hematopoietic cell transplantation for chemotherapy-unresponsive mantle cell lymphoma: a cohort analysis from the Center for International Blood and Marrow Transplant Research.   Biol Blood Marrow Transplant. 2013;19(4):625-631. doi:10.1016/j.bbmt.2013.01.009PubMedGoogle ScholarCrossref
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Hamadani  M, Saber  W, Ahn  KW,  et al.  Impact of pretransplantation conditioning regimens on outcomes of allogeneic transplantation for chemotherapy-unresponsive diffuse large B cell lymphoma and grade III follicular lymphoma.   Biol Blood Marrow Transplant. 2013;19(5):746-753. doi:10.1016/j.bbmt.2013.01.024PubMedGoogle ScholarCrossref
7.
Avivi  I, Canals  C, Vernant  J-P,  et al; EBMT Lymphoma Working Party.  Matched unrelated donor allogeneic transplantation provides comparable long-term outcome to HLA-identical sibling transplantation in relapsed diffuse large B-cell lymphoma.   Bone Marrow Transplant. 2014;49(5):671-678. doi:10.1038/bmt.2014.4 PubMedGoogle ScholarCrossref
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Dreger  P, Sureda  A, Ahn  KW,  et al.  PTCy-based haploidentical vs matched related or unrelated donor reduced-intensity conditioning transplant for DLBCL.   Blood Adv. 2019;3(3):360-369. doi:10.1182/bloodadvances.2018027748 PubMedGoogle ScholarCrossref
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Epperla  N, Ahn  KW, Litovich  C,  et al.  Allogeneic hematopoietic cell transplantation provides effective salvage despite refractory disease or failed prior autologous transplant in angioimmunoblastic T-cell lymphoma: a CIBMTR analysis.   J Hematol Oncol. 2019;12(1):6. doi:10.1186/s13045-018-0696-z PubMedGoogle ScholarCrossref
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Hong  S, Le-Rademacher  J, Artz  A, McCarthy  PL, Logan  BR, Pasquini  MC.  Comparison of non-myeloablative conditioning regimens for lymphoproliferative disorders.   Bone Marrow Transplant. 2015;50(3):367-374. doi:10.1038/bmt.2014.269 PubMedGoogle ScholarCrossref
11.
Kekre  N, Marquez-Malaver  FJ, Cabrero  M,  et al.  Fludarabine/busulfan versus fludarabine/melphalan conditioning in patients undergoing reduced-intensity conditioning hematopoietic stem cell transplantation for lymphoma.   Biol Blood Marrow Transplant. 2016;22(10):1808-1815. doi:10.1016/j.bbmt.2016.07.006PubMedGoogle ScholarCrossref
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Bacigalupo  A, Ballen  K, Rizzo  D,  et al.  Defining the intensity of conditioning regimens: working definitions.   Biol Blood Marrow Transplant. 2009;15(12):1628-1633. doi:10.1016/j.bbmt.2009.07.004 PubMedGoogle ScholarCrossref
13.
Cheson  BD, Pfistner  B, Juweid  ME,  et al; International Harmonization Project on Lymphoma.  Revised response criteria for malignant lymphoma.   J Clin Oncol. 2007;25(5):579-586. doi:10.1200/JCO.2006.09.2403 PubMedGoogle ScholarCrossref
14.
Przepiorka  D, Weisdorf  D, Martin  P,  et al.  1994 Consensus Conference on Acute GVHD Grading.   Bone Marrow Transplant. 1995;15(6):825-828.PubMedGoogle Scholar
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Shulman  HM, Sullivan  KM, Weiden  PL,  et al.  Chronic graft-versus-host syndrome in man. a long-term clinicopathologic study of 20 Seattle patients.   Am J Med. 1980;69(2):204-217. doi:10.1016/0002-9343(80)90380-0 PubMedGoogle ScholarCrossref
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Clark  TG, Altman  DG, De Stavola  BL.  Quantification of the completeness of follow-up.   Lancet. 2002;359(9314):1309-1310. doi:10.1016/S0140-6736(02)08272-7 PubMedGoogle ScholarCrossref
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Zhang  X, Loberiza  FR, Klein  JP, Zhang  M-J.  A SAS macro for estimation of direct adjusted survival curves based on a stratified Cox regression model.   Comput Methods Programs Biomed. 2007;88(2):95-101. doi:10.1016/j.cmpb.2007.07.010 PubMedGoogle ScholarCrossref
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Zhang  X, Zhang  M-J.  SAS macros for estimation of direct adjusted cumulative incidence curves under proportional subdistribution hazards models.   Comput Methods Programs Biomed. 2011;101(1):87-93. doi:10.1016/j.cmpb.2010.07.005 PubMedGoogle ScholarCrossref
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Bartlett  JW, Seaman  SR, White  IR, Carpenter  JR; Alzheimer’s Disease Neuroimaging Initiative*.  Multiple imputation of covariates by fully conditional specification: accommodating the substantive model.   Stat Methods Med Res. 2015;24(4):462-487. doi:10.1177/0962280214521348 PubMedGoogle ScholarCrossref
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Rubin  DB.  Multiple Imputation for Nonresponse in Surveys. John Wiley & Sons; 2004.
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Liu  Y, Nickleach  D, Lipscomb  J. Propensity score matching for multiple treatment comparisons in observational studies. In: Proceedings of the 59th ISI World Statistics Congress; August 25-30, 2013; Hong Kong. Session CPS108.
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Lee  EW, Wei  LJ, Amato  DA, Leurgans  S. Cox-type regression analysis for large numbers of small groups of correlated failure time observations. In: Klein  JP, Goel  PK, eds.  Survival Analysis. State of the Art. NATO Science. Series E: Applied Sciences. Vol 211. Springer; 1992. doi:10.1007/978-94-015-7983-4_14
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Benjamini  Y, Yekutieli  D.  The control of the false discovery rate in multiple testing under dependency.   Ann Stat. 2001;29(4):1165-1188.Google ScholarCrossref
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Bacher  U, Klyuchnikov  E, Le-Rademacher  J,  et al; Lymphoma Working Committee of the CIBMTR.  Conditioning regimens for allotransplants for diffuse large B-cell lymphoma: myeloablative or reduced intensity?   Blood. 2012;120(20):4256-4262. doi:10.1182/blood-2012-06-436725 PubMedGoogle ScholarCrossref
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Yerushalmi  R, Shem-Tov  N, Danylesko  I, Avigdor  A, Nagler  A, Shimoni  A.  Fludarabine and treosulfan compared with other reduced-intensity conditioning regimens for allogeneic stem cell transplantation in patients with lymphoid malignancies.   Bone Marrow Transplant. 2015;50(12):1526-1535. doi:10.1038/bmt.2015.174 PubMedGoogle ScholarCrossref
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Baron  F, Labopin  M, Peniket  A,  et al.  Reduced-intensity conditioning with fludarabine and busulfan versus fludarabine and melphalan for patients with acute myeloid leukemia: a report from the Acute Leukemia Working Party of the European Group for Blood and Marrow Transplantation.   Cancer. 2015;121(7):1048-1055. doi:10.1002/cncr.29163 PubMedGoogle ScholarCrossref
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Shimoni  A, Hardan  I, Shem-Tov  N,  et al.  Comparison between two fludarabine-based reduced-intensity conditioning regimens before allogeneic hematopoietic stem-cell transplantation: fludarabine/melphalan is associated with higher incidence of acute graft-versus-host disease and non-relapse mortality and lower incidence of relapse than fludarabine/busulfan.   Leukemia. 2007;21(10):2109-2116. doi:10.1038/sj.leu.2404886 PubMedGoogle ScholarCrossref
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Ahmed  S, Kanakry  JA, Ahn  KW,  et al.  Lower graft-versus-host disease and relapse risk in post-transplant cyclophosphamide-based haploidentical versus matched sibling donor reduced-intensity conditioning transplant for Hodgkin lymphoma.   Biol Blood Marrow Transplant. 2019;25(9):1859-1868. doi:10.1016/j.bbmt.2019.05.025PubMedGoogle ScholarCrossref
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Le Bourgeois  A, Labopin  M, Blaise  D,  et al; Société Francophone de Greffe de Moelle et de Thérapie Cellulaire.  Reduced-intensity versus reduced-toxicity myeloablative fludarabine/busulfan-based conditioning regimens for allografted non-Hodgkin lymphoma adult patients: a retrospective study on behalf of the Société Francophone de Greffe de Moelle et de Thérapie Cellulaire.   Ann Oncol. 2017;28(9):2191-2198. doi:10.1093/annonc/mdx274PubMedGoogle ScholarCrossref
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Saini  NY, Saliba  RM, Rondon  G,  et al.  Impact of donor type and melphalan dose on allogeneic transplantation outcomes for patients with lymphoma.   Biol Blood Marrow Transplant. 2019;25(7):1340-1346. doi:10.1016/j.bbmt.2019.02.002PubMedGoogle ScholarCrossref
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Ghosh  N, Karmali  R, Rocha  V,  et al.  Reduced-intensity transplantation for lymphomas using haploidentical related donors versus HLA-matched sibling donors: a Center for International Blood and Marrow Transplant Research analysis.   J Clin Oncol. 2016;34(26):3141-3149. doi:10.1200/JCO.2015.66.3476 PubMedGoogle ScholarCrossref
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Kanate  AS, Mussetti  A, Kharfan-Dabaja  MA,  et al.  Reduced-intensity transplantation for lymphomas using haploidentical related donors vs HLA-matched unrelated donors.   Blood. 2016;127(7):938-947. doi:10.1182/blood-2015-09-671834 PubMedGoogle ScholarCrossref
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    Original Investigation
    June 4, 2020

    Association of Reduced-Intensity Conditioning Regimens With Overall Survival Among Patients With Non-Hodgkin Lymphoma Undergoing Allogeneic Transplant

    Author Affiliations
    • 1Department of Hematologic Oncology and Blood Disorders, Levine Cancer Institute, Atrium Health, Charlotte, North Carolina
    • 2Department of Myeloma and Lymphoma, University of Texas, MD Anderson Cancer Center, Houston
    • 3Department of Medicine, Center for International Blood and Marrow Transplant Research, Medical College of Wisconsin, Milwaukee
    • 4Division of Biostatistics, Institute for Health and Equity, Medical College of Wisconsin, Milwaukee
    • 5Department of Oncology, King Faisal Specialist Hospital Center and Research, Riyadh, Saudi Arabia
    • 6Department of Hematology, Inselspital, Bern University Hospital, University of Bern, Switzerland
    • 7The Ottawa Hospital Blood and Marrow Transplant Program, The Ottawa Hospital Research Institute, Ottawa, Ontario, Canada
    • 8Division of Hematology, Department of Medicine, The James Cancer Hospital and Solove Research Institute, The Ohio State University, Columbus
    • 9Division of Hematology and Oncology, University of Florida College of Medicine, Gainesville
    • 10Texas Transplant Institute, San Antonio, Texas
    • 11Division of Hematological Malignancy and Cellular Therapeutics, University of Kansas Health System, Kansas City
    • 12Department of Medicine, University of Colorado Hospital, Aurora, Colorado
    • 13Division of Hematology, Mayo Clinic, Rochester, Minnesota
    • 14Division of Hematology and Oncology, Center for Cell and Gene Therapy, Baylor College of Medicine, Houston, Texas
    • 15Department of Hematology and Oncology, University Hospitals Cleveland Medical Center, Case Western Reserve University, Cleveland, Ohio
    • 16Department of Medicine, University of Miami, Miami, Florida
    • 17Division of Hematology–Oncology, Blood and Marrow Transplantation Program, Mayo Clinic Florida, Jacksonville
    • 18Department of Blood and Marrow Transplant and Cellular Immunotherapy, Moffitt Cancer Center, Tampa, Florida
    • 19Lymphoma, Bone Marrow Transplant and Cellular Therapy Program, UT Southwestern Medical Center, Dallas, Texas
    • 20Division of Hematologic Malignancies and Cellular Therapy, Duke University, Durham, North Carolina
    • 21Division of Hematology and Oncology, Department of Medicine, Greenebaum Comprehensive Cancer Center, Blood and Marrow Transplantation Program, University of Maryland, Baltimore
    • 22Institut Català d'Oncologia–Hospitalet, Hematology Department, University of Barcelona, Barcelona, Spain
    JAMA Oncol. 2020;6(7):1011-1018. doi:10.1001/jamaoncol.2020.1278
    Key Points

    Question  Are reduced-intensity conditioning and nonmyeloablative conditioning (RIC-NMAC) regimens at a higher spectrum of intensity associated with higher nonrelapse mortality and inferior overall survival compared with RIC-NMAC regimens at a lower spectrum of intensity in patients with non-Hodgkin lymphoma undergoing allogeneic transplant?

    Findings  In this cohort study of registry data from 1823 adult patients with non-Hodgkin lymphoma, the most commonly used RIC-NMAC regimen, fludarabine-melphalan 140, was associated with the highest nonrelapse mortality risk and inferior overall survival compared with the other regimens.

    Meaning  The findings suggest that use of a more intense RIC-NMAC regimen, such as fludarabine-melphalan 140, for allogeneic transplant in patients with non-Hodgkin lymphoma should be considered with caution.

    Abstract

    Importance  Reduced-intensity conditioning and nonmyeloablative conditioning (RIC-NMAC) regimens are frequently used in allogeneic hematopoietic cell transplant (HCT) for non-Hodgkin lymphoma. However, the optimal RIC-NMAC regimen in allogeneic HCT for non-Hodgkin lymphoma is not known.

    Objective  To investigate whether RIC-NMAC regimens at a higher end of the intensity spectrum are associated with increased nonrelapse mortality and lower overall survival compared with RIC-NMAC regimens at the lower end of the intensity spectrum in patients with non-Hodgkin lymphoma undergoing allogeneic HCT.

    Design, Setting, and Participants  This cohort study used data from 1823 adult patients with non-Hodgkin lymphoma in the Center for International Blood and Marrow Transplant Research registry. Included patients underwent allogeneic HCT using matched related or unrelated donors between January 2008 and December 2016. Statistical analysis was performed from June 1, 2019, to February 10, 2020.

    Interventions  Patients received 1 of 4 RIC-NMAC regimens: fludarabine-intravenous busulfan (Flu-Bu), approximately 6.4 mg/kg (n = 458); fludarabine-melphalan (Flu-Mel140), 140 mg/m2 (n = 885); fludarabine-cyclophosphamide (Flu-Cy) (n = 391); or Flu-Cy with 2 Gy total body irradiation (Flu-Cy-2GyTBI) (n = 89).

    Main Outcomes and Measures  The primary outcome was overall survival. Secondary outcomes were nonrelapse mortality, incidence of relapse, progression-free survival, and the incidence of acute and chronic graft-vs-host disease (GVHD).

    Results  Of 1823 patients, 1186 (65%) were male, with a mean (SD) age of 54.8 (9.9) years. The 4-year adjusted OS was 58% in the Flu-Bu cohort, 67% in the Flu-Cy-2GyTBI cohort, 49% in the Flu-Mel140 cohort, and 63% in the Flu-Cy cohort (P < .001). After adjustment for age, Karnofsky performance score, HCT comorbidity index, NHL subtype, remission status at HCT, and the use of antithymocyte globulin or alemtuzumab, the regression analysis showed a significantly higher mortality risk associated with Flu-Mel140 compared with Flu-Bu (hazard ratio [HR], 1.34; 95% CI, 1.13-1.59; P < .001). Compared with the Flu-Cy cohort, the Flu-Mel140 cohort had a higher risk of chronic GVHD (HR, 1.38; 95% CI, 1.15-1.65; P < .001). The Flu-Mel140 regimen was associated with a higher nonrelapse mortality risk (HR, 1.78; 95% CI, 1.37-2.31; P < .001) compared with the Flu-Bu regimen.

    Conclusions and Relevance  The findings suggest that use of the more intense RIC-NMAC regimen, Flu-Mel140, may have a negative association with overall survival and may be associated with higher nonrelapse mortality. The Flu-Bu and Flu-Cy regimens with or without 2GyTBI regimens appeared to provide comparable overall survival.

    Introduction

    Reduced-intensity conditioning and nonmyeloablative conditioning (RIC-NMAC) regimens have significantly expanded the access to allogeneic hematopoietic cell transplant (HCT) in the treatment of hematologic malignant neoplasms.1-4 Although RIC-NMAC regimens generally are associated with lower nonrelapse mortality compared with myeloablative conditioning regimens,5,6 disease relapse remains the most common cause of treatment failure among patients with non-Hodgkin lymphoma (NHL) undergoing allogeneic HCT with such lower-intensity platforms.7-9 The various RIC-NMAC regimens commonly used in practice differ in their immunosuppressive and cytoreductive effects, but to our knowledge, no prospective randomized trials are available to define an optimal regimen among patients with NHL.

    A Center for International Blood and Marrow Transplant Research (CIBMTR) analysis compared HCT outcomes among patients with lymphoma who underwent either a total body irradiation (TBI)–based regimen or a non–TBI-containing NMAC regimen allogeneic HCT.10 The study found a higher risk of graft-vs-host disease (GVHD) associated with TBI-based approaches but no difference in survival. A retrospective North American and Spanish study (n = 136) showed inferior overall survival (OS) associated with use of fludarabine-melphalan, 140 mg/m2 (Flu-Mel140) compared with fludarabine-busulfan (Flu-Bu).11 This survival difference was largely attributed to a higher risk of acute grade 2 to 4 GVHD associated with Flu-Mel140. That study was, however, limited because of its small sample size, inclusion of Hodgkin lymphoma with NHL histologic findings, and the absence of comparison with other commonly used RIC-NMAC regimens (eg, fludarabine-cyclophosphamide [Flu-Cy]–based approaches).

    We hypothesized that within the RIC-NMAC spectrum, patients with NHL receiving a higher-intensity regimen, such as Flu-Mel140, would have higher nonrelapse mortality and inferior OS compared with those receiving lower-intensity regimens, such as Flu-Bu, Flu-Cy, or Flu-Cy with 2 Gy total body irradiation (Flu-Cy-2GyTBI).

    Methods
    Data Source

    This cohort study used data from the CIBMTR, a working group of more than 500 transplantation centers worldwide that contributed detailed data on HCT to a statistical center at the Medical College of Wisconsin, Milwaukee. Participating centers were required to report all transplants consecutively, and compliance was monitored by onsite audits. Computerized checks for discrepancies, physicians' review of submitted data, and onsite audits of participating centers ensured data quality. Observational studies conducted by the CIBMTR are performed in compliance with all applicable federal regulations pertaining to the protection of human research participants. Patients provided written informed consent for research. The institutional review boards of the Medical College of Wisconsin and the National Marrow Donor Program approved this study.

    The CIBMTR collects data at 2 levels: Transplant Essential Data and Comprehensive Report Form data. Transplant Essential Data include disease type, age, sex, pre-HCT disease stage and chemotherapy responsiveness, date of diagnosis, graft type, conditioning regimen, posttransplant disease progression and survival, development of a new malignant neoplasm, and cause of death. All CIBMTR centers contribute Transplant Essential Data.

    The CIBMTR uses a weighted randomization scheme to select a subset of patients for Comprehensive Report Form reporting with more details about disease and pretransplant and posttransplant clinical information. Both Transplant Essential Data– and Comprehensive Report Form–level data are collected before HCT, 100 days after HCT, 6 months after HCT, and annually thereafter or until death. Data for the current analysis were retrieved from CIBMTR Transplant Essential Data and Comprehensive Report Form (eTable 7 in the Supplement).

    Patients

    This analysis included adults (aged ≥18 years) with NHL who underwent their first RIC-NMAC regimen allogeneic HCT between January 2008 and December 2016. Eligible donors included either HLA-identical sibling donors or unrelated donors matched at the allele-level at HLA-A, HLA-B, HLA-C, and HLA-DRB1. Graft source was limited to peripheral blood. GVHD prophylaxis was limited to calcineurin inhibitor–based approaches. The study cohort was divided into 4 RIC-NMAC regimens (Flu-Bu, Flu-Cy-2GyTBI, Flu-Mel140, and Flu-Cy). Patients in the Flu-Bu cohort received a uniform intravenous busulfan dose of approximately 6.4 mg/m2. The Flu-Mel140 cohort was limited to a melphalan dose of 140 mg/m2. Allogeneic HCT recipients could have received in vivo T-cell depletion with antithymocyte globulin or alemtuzumab. Patients receiving ex vivo graft manipulation were not included.

    Definitions and End Points

    The intensity of allogeneic HCT conditioning regimens was assessed using consensus criteria.12 Disease response at the time of HCT was assessed using the International Working Group criteria in use during the era of this analysis.13 The primary end point was OS; death from any cause was considered an event, and surviving patients were censored at the last follow-up. Secondary outcomes included nonrelapse mortality, progression or relapse, GVHD, progression-free survival (PFS), and time to neutrophil and platelet recovery. Nonrelapse mortality was defined as death without evidence of lymphoma progression or relapse; relapse was considered a competing risk.

    Progression or relapse was defined as progressive lymphoma after HCT or lymphoma recurrence after a complete remission; nonrelapse mortality was considered a competing risk. For PFS, a patient was considered to experience treatment failure at time of progression or relapse or death from any cause. Patients alive without evidence of disease relapse or progression were censored at the last follow-up. Acute GVHD and chronic GVHD were graded using established clinical criteria.14,15 Probabilities of PFS and OS were calculated using the Kaplan-Meier estimates.

    Neutrophil recovery was defined as the first of 3 successive days with an absolute neutrophil count of 500/μL after posttransplant nadir. Platelet recovery was considered to have occurred on the first of 3 consecutive days with a platelet count of 20 000/μL or higher in the absence of platelet transfusion for 7 consecutive days. For neutrophil and platelet recovery, death without the event was considered a competing risk.

    Statistical Analysis

    The study compared 4 RIC-NMAC regimens: Flu-Bu vs Flu-Cy-2GyTBI vs Flu-Mel140 vs Flu-Cy. The χ2 test for categorical variables and Kruskal-Wallis test for continuous variables were used to compare baseline characteristics. Completeness of follow-up was assessed as described previously16 and was at least 90% in all groups at 4 years, consistent with low rates of loss to follow-up. Statistical analysis was performed from June 1, 2019, to February 10, 2020.

    Cumulative incidences of hematopoietic recovery, GVHD, relapse, and nonrelapse mortality were calculated to accommodate for competing risks. Associations among patient-, disease-, and transplant-associated variables (eTable 1 in the Supplement) and outcomes of interest were evaluated using Cox proportional hazards regression for PFS and OS; a cause-specific hazard model for chronic GVHD, relapse, and nonrelapse mortality to account for competing risks; and logistic regression for acute GVHD. Forward stepwise selection was used to identify covariates associated with outcomes. Covariates with 2-sided P < .01 were considered to be statistically significant. The proportional hazards assumption for Cox regression and the cause-specific hazards function were tested by adding a time-dependent covariate for each risk factor and each outcome. Center effect was examined by the score test for chronic GVHD, relapse, nonrelapse mortality, PFS, and OS and testing a random association from the generalized linear mixed model for acute GVHD.17 No center effect was seen for any outcomes. Interactions between the main effect and significant covariates were examined. Unadjusted probabilities were calculated for neutrophil recovery, platelet recovery, and GVHDs. Adjusted probabilities were calculated based on the final model for relapse, nonrelapse mortality, PFS, and OS.18,19

    We also confirmed the final model for relapse, nonrelapse mortality, PFS, and OS by comparing it with the model from multiple imputation and propensity score matching. We imputed missing covariates using multiple imputation and obtained 10 imputed data sets.20 Then, multinomial logistic regression was used to obtain propensity scores for each person using Rubin rules.21 Persons were matched using estimated propensity scores with nearest neighbor caliper matching.22 We fitted the marginal Cox proportional hazards regression model for PFS and OS, the marginal cause-specific hazards model for relapse, and nonrelapse mortality23 for each imputed data set to account for matched pairs. The final model for each outcome was summarized using Rubin rules. To account for multiple pairwise tests, the false discovery rate24 was used with a 0.05 cutoff, and Q values (adjusted P values from the false discovery rate) were reported. We further confirmed the analysis results by conducting a subset analysis for Flu-Bu vs Flu-Mel140 with multiple imputation and propensity score matching.

    Results
    Baseline Characteristics

    The patient population (N = 1823) was divided into 4 cohorts: Flu-Bu (n = 458), Flu-Cy-2GyTBI (n = 89), Flu-Mel140 (n = 885), and Flu-Cy (n = 391). The baseline patient-, disease-, and transplant-associated characteristics are shown in eTable 2 in the Supplement. Of the 1823 patients, 1186 (65%) were male, with a mean (SD) age of 54.8 (9.9) years. There were no significant differences between the 4 cohorts in terms of patient sex, remission status at HCT, and history of autologous HCT. Significantly more patients in the Flu-Bu (187 of 458 [41%]) and Flu-Cy-2GyTBI (34 of 89 [38%]) cohorts were older than 60 years compared with the Flu-Mel140 (282 of 885 [32%]) and Flu-Cy (123 of 391 [32%]) cohorts (P < .001). Significantly more patients in the Flu-Bu cohort had a Karnofsky performance score of less than 90, HCT comorbidity index of at least 3, and self-identified white race (eTable 2 in the Supplement) compared with the other cohorts. Aggressive lymphomas (diffuse large B-cell lymphoma and T-cell NHL) were more frequent in the Flu-Bu (262 [57%]) and Flu-Mel140 (557 [63%]) cohorts (P < .001).

    Overall Survival

    The 4-year adjusted OS was 58% in the Flu-Bu cohort, 67% in the Flu-Cy-2GyTBI cohort, 49% in the Flu-Mel140 cohort, and 63% in the Flu-Cy cohort (P < .001) (Table and Figure). After adjustment for age, Karnofsky performance score, HCT comorbidity index, NHL subtype, remission status at HCT, and the use of antithymocyte globulin or alemtuzumab, the regression analysis showed a significantly higher mortality risk associated with Flu-Mel140 compared with Flu-Bu (hazard ratio [HR], 1.34; 95% CI, 1.13-1.59; Q < .001), Flu-Cy-2GyTBI (HR, 1.82; 95% CI, 1.23-2.69; Q = .01), and Flu-Cy (HR, 1.59; 95% CI, 1.29-1.95; Q < .001) (eTable 3 in the Supplement). There was no significant difference in OS among Flu-Bu, Flu-Cy-2GyTBI, and Flu-Cy. The inferior OS associated with Flu-Mel140 was also found with propensity score matching (HR, 1.43; 95% CI, 1.20-1.71; Q < .001) (eTable 4 in the Supplement).

    Nonrelapse Mortality

    The 4-year adjusted cumulative incidence of nonrelapse mortality was 16% in the Flu-Bu cohort, 17% in the Flu-Cy-2GyTBI cohort, 26% in the Flu-Mel140 cohort, and 17% in the Flu-Cy cohort (P < .001) (Table and Figure). After adjustment for age, Karnofsky performance score, HCT comorbidity index, history of autologous HCT, and use of antithymocyte globulin or alemtuzumab in the regression analysis, the use of the Flu-Mel140 regimen was associated with a significantly higher risk of nonrelapse mortality compared with the Flu-Bu regimen (HR, 1.78; 95% CI, 1.37-2.31; Q < .001) (eTable 3 in the Supplement). Compared with the Flu-Bu regimen, the Flu-Cy and Flu-Cy-2GyTBI regimens were not associated with a higher risk of nonrelapse mortality (eTable 3 in the Supplement). The higher nonrelapse mortality associated with Flu-Mel140 was also found with propensity score matching (HR, 1.91; 95% CI, 1.48-2.46; Q < .001) (eTable 4 in the Supplement).

    Relapse and PFS

    The adjusted cumulative incidence of relapse or progression at 4 years was 47% in the Flu-Bu cohort, 33% in the Flu-Cy-2GyTBI cohort, 37% in the Flu-Mel140 cohort, and 50% in the Flu-Cy cohort (P < .001) (Table and Figure). After adjustment for remission status at HCT, NHL subtype, donor type, and the use of antithymocyte globulin or alemtuzumab, the regression analysis showed that the Flu-Mel140 cohort did not have significantly lower risk of relapse or progression compared with the Flu-Bu cohort (HR, 0.79; 95% CI, 0.66-0.94; Q= .07) (eTable 3 in the Supplement). Compared with the Flu-Bu regimen, the Flu-Cy and the Flu-Cy-2GyTBI regimens were not associated with a significantly lower risk of relapse or progression (eTable 3 in the Supplement). The lower relapse risk associated with the Flu-Mel140 compared with the Flu-Cy regimens was also found with propensity score matching (HR, 0.75; 95% CI, 0.62-0.91; Q= .04) (eTable 4 in the Supplement).

    The 4-year adjusted PFS was 38% in the Flu-Bu cohort, 51% in the Flu-Cy-2GyTBI cohort, 39% in the Flu-Mel140 cohort, and 35% in the Flu-Cy cohort was (P = .07) (Table and Figure). After adjustment for Karnofsky performance score, remission status at HCT, NHL subtype, and the use of antithymocyte globulin or alemtuzumab, the regression analysis did not show a significantly improved PFS associated with the Flu-Mel140 (HR, 1.03; 95% CI, 0.89-1.19), the Flu-Cy-2GyTBI (HR, 0.70; 95% CI, 0.51-0.98) or the Flu-Cy (HR, 1.07; 95% CI, 0.89-1.29) regimen compared with the Flu-Bu regimen (overall P = .09) (eTable 3 in the Supplement). Propensity score matching validated these findings (eTable 4 in the Supplement).

    Hematopoietic Recovery

    The cumulative incidence of neutrophil recovery at day 30 was significantly lower in the Flu-Mel140 cohort (96%) compared with the Flu-Bu (99%), the Flu-Cy-2GyTBI (99%), and the Flu-Cy (98%) cohorts (P < .001) (Table). The day 100 cumulative incidence of platelet recovery was also significantly lower in the Flu-Mel140 cohort (90%) compared with the Flu-Bu (97%), the Flu-Cy-2GyTBI (97%), and the Flu-Cy (99%) cohorts (P < .001) (Table).

    Acute and Chronic GVHD

    The univariate cumulative incidence rates of grade 2 to 4 and 3 to 4 acute GVHD across 4 cohorts are shown in the Table. After adjustment for GVHD prophylaxis, the multivariate analysis (eTable 3 in the Supplement) showed no statistically significant difference in the risk of grade 3 to 4 acute GVHD in patients who received the Flu-Cy-2GyTBI (HR, 0.81; 95% CI, 0.37-1.77), the Flu-Mel140 (HR, 1.42; 95% CI, 0.99-2.02), and the Flu-Cy (HR, 1.34; 95% CI, 0.9-2.02) regimens compared with the Flu-Bu regimens.

    On univariate analysis, the cumulative incidence of chronic GVHD at 1 year was 41% in the Flu-Bu cohort, 32% in the Flu-Cy-2GyTBI cohort, 43% in the Flu-Mel140 cohort, and 42% in the Flu-Cy cohort (Table). After adjusting for donor type, GVHD prophylaxis, and antithymocyte globulin or alemtuzumab use in conditioning, the multivariate analysis (eTable 3 in the Supplement) showed no significant difference in risk of chronic GVHD in patients who received Flu-Cy-2GyTBI (HR, 0.96; 95% CI, 0.68-1.34), Flu-Mel140 (HR, 1.12; 95% CI, 0.94-1.33), and Flu-Cy (HR, 0.81; 95% CI, 0.67-0.99) compared with Flu-Bu. However, the Flu-Mel140 cohort had a significantly higher risk of chronic GVHD when compared with the Flu-Cy cohort (HR, 1.38; 95% CI, 1.15-1.65; P < .001; Q = .006).

    Subset Analysis

    A subset analysis comparing Flu-Bu vs Flu-Mel140 also showed inferior outcomes associated with Flu-Mel140 (eTable 5 in the Supplement). No interaction between NHL histologic findings and the main effect (ie, conditioning regimen type) was seen for any of the following outcomes at a significance level of 0.01: acute grade 3 to 4 GVHD, chronic GVHD, nonrelapse mortality, relapse or progression, PFS, and OS.

    Causes of death

    The most common cause of death in all the cohorts was recurrent or progressive lymphoma (53% [103 of 194] in the Flu-Bu cohort, 37% [11 of 30] in the Flu-Cy-2GyTBI cohort, 38% [164 of 428] in the Flu-Mel140 cohort, and 42% [60 of 143] in the Flu-Cy cohort). GVHD and infectious complications were the other common causes of death (eTable 6 in the Supplement).

    Discussion

    We report the findings of, to our knowledge, the largest registry analysis comparing the outcomes of patients with NHL undergoing allogeneic HCT after RIC-NMAC regimens with Flu-Bu, Flu-Cy-2GyTBI, Flu-Mel140, or Flu-Cy and made several important observations: (1) hematopoietic recovery was slower after the Flu-Mel140 regimen; (2) there were no significant differences in grade 3 to 4 acute GVHD; (3) compared with Flu-Mel140, Flu-Cy was associated with a lower risk of chronic GVHD; and (4) Flu-Mel140 was associated with a significantly higher risk of nonrelapse mortality and with inferior OS compared with the other regimens.

    The importance of conditioning regimen intensity for patients with NHL undergoing allogeneic HCT has been debated. A CIBMTR analysis for patients with chemosensitive diffuse large B-cell lymphoma showed no difference in 5-year PFS and OS between the myeloablative conditioning regimen and the RIC-NMAC regimens.25 Similarly, even among patients with refractory NHL, intensity of conditioning regimens (myeloablative conditioning vs RIC-NMAC) was not associated with survival outcomes.5,6 Although previous CIBMTR studies5,6 have questioned the use of myeloablative conditioning regimens among patients with lymphoma, there are limited comparative data published on the relative efficacy and toxic effects of the individual RIC-NMAC regimens commonly used in NHL.

    A few reports11,26 have compared the outcomes associated with Flu-Mel and Flu-Bu in patients with lymphoma, albeit with limited sample size. Kekre et al11 examined the outcomes in 136 patients with lymphoma, and Yerushalmi et al26 studied 144 patients; in both of these studies,11,26 Flu-Mel was associated with a higher risk of acute GVHD, nonrelapse mortality, and inferior OS. Unlike with NHL, for myeloid malignancies, several studies27,28 have reported that Flu-Mel was associated with a lower relapse rate, higher nonrelapse mortality, and equivalent or inferior survival compared with Flu-Bu.

    There are several important differences between our study and previously published reports.11,26 First, the large number of patients in our study improved on the limited power of smaller studies by allowing us to match propensity scores. Second, Flu-Cy and Flu-Cy-2GyTBI regimens were not included in previous comparisons.11,26

    In addition, previous studies11,26-28 were either limited to myeloid disorders or pooled patients with Hodgkin lymphoma and NHL, but these patients had different demographic characteristics. Patients who underwent allogeneic HCT for a diagnosis of Hodgkin lymphoma were younger29 (median age, 35 years), more likely to have received a previous autologous transplant, and often had fewer comorbid conditions and thus may have been able to tolerate higher-intensity regimens (eg, Flu-Mel140), unlike the significantly older cohort with NHL in this analysis.

    Limitations

    We acknowledge the limitation that our study included a variety of NHL subtypes (which had varying degrees of relapse risk). However, we found the association of conditioning regimen did not vary according to NHL histologic findings, and this justified inclusion of different NHL subtypes in this analysis.

    Busulfan dose intensity in the Flu-Bu regimen ranges from RIC dosage (Flu-Bu2, 2 days of busulfan at 4 mg/kg per day orally or 3.2 mg/kg per day intravenously) to myeloablative conditioning (Flu-Bu3/Flu-Bu4, 3 or 4 days of busulfan at 4 mg/kg per day orally or 3.2 mg/kg per day intravenously) dosage. Previous reports30 on NHL have shown no advantage of using a myeloablative conditioning Flu-Bu regimen vs an RIC Flu-Bu regimen.

    Similarly, melphalan dose varied from 100mg/m2 to 140mg/m2 across Flu-Mel regimens, and no differences in outcomes have been noted between the 2 doses.31 To reduce the heterogeneity of the regimens, we used the most common RIC Flu-Bu dose (total busulfan dose of approximately 6.4 mg/kg intravenous) and Flu-Mel140 dose (melphalan dose of 140 mg/m2) for our analysis.

    Our study included patients who received grafts from only matched and related or matched and unrelated donors, and GVHD prophylaxis was limited to calcineurin inhibitor–based approaches. Patients who underwent haploidentical HCT with posttransplant cyclophosphamide had similar survival compared with patients receiving grafts from HLA-matched donors.32,33 Haploidentical HCT recipients were excluded from our study because this donor source is associated with the Flu-Cy-2GyTBI regimen.

    Similar to other registry-based analyses, there are important caveats to be considered. Unlike a randomized clinical trial, this was a cohort comparison based on registry data. We therefore used propensity score matching to balance the distributions of significant covariates between the groups and to reduce the association of confounding variables. Transplant center practices can be associated with survival outcomes. Therefore, we examined center effect and found none in this analysis.

    Patients in this study had various NHL subtypes. However, a lack of interaction between the main effect and NHL subtypes argues against a differential effect of RIC-NMAC regimens across different NHL subtypes.

    Conclusions

    In this cohort study, we found that the high-intensity RIC-NMAC regimen Flu-Mel140 was associated with significantly higher nonrelapse mortality risk and inferior OS compared with other regimens despite patients who received this regimen having fewer comorbidities at baseline. The other regimens evaluated provided comparable survival outcomes. The results of our study are potentially practice changing and caution against the use of more intense conditioning regimens in the treatment of NHL.

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    Article Information

    Accepted for Publication: March 17, 2020.

    Published Online: June 4, 2020. doi:10.1001/jamaoncol.2020.1278

    Correction: This article was corrected on October 15, 2020, and on May 27, 2021, to fix errors in the Funding/Support section.

    Corresponding Author: Mehdi Hamadani, MD, Department of Medicine, Center for International Blood and Marrow Transplant Research, Medical College of Wisconsin, 9200 W Wisconsin Ave, Ste C5500, Milwaukee, WI 53226 (mhamadani@mcw.edu).

    Author Contributions: Dr Hamadani had full access to all of the data in the study and takes responsibility for the integrity of the data and the accuracy of the data analysis.

    Concept and design: Ghosh, Ahmed, Litovich, Aljurf, Haverkos, Kamble, Ramakrishnan, Rizzieri, Yared, Sureda, Hamadani.

    Acquisition, analysis, or interpretation of data: Ghosh, Ahmed, Ahn, Khanal, Litovich, Aljurf, Bacher, Bredeson, Epperla, Farhadfar, Freytes, Ganguly, Haverkos, Inwards, Kamble, Lazarus, Lekakis, Murthy, Nishihori, Ramakrishnan, Yared, Kharfan-Dabaja, Sureda, Hamadani.

    Drafting of the manuscript: Ghosh, Ahmed, Khanal, Litovich, Aljurf, Haverkos, Kamble, Lazarus, Ramakrishnan, Yared, Kharfan-Dabaja, Sureda, Hamadani.

    Critical revision of the manuscript for important intellectual content: Ghosh, Ahmed, Ahn, Khanal, Aljurf, Bacher, Bredeson, Epperla, Farhadfar, Freytes, Ganguly, Haverkos, Inwards, Kamble, Lazarus, Lekakis, Murthy, Nishihori, Ramakrishnan, Rizzieri, Yared, Kharfan-Dabaja, Sureda, Hamadani.

    Statistical analysis: Ghosh, Ahmed, Ahn, Khanal, Litovich, Aljurf, Bacher, Kamble, Lekakis, Hamadani.

    Obtained funding: Hamadani.

    Administrative, technical, or material support: Litovich, Haverkos, Kamble, Rizzieri.

    Supervision: Ghosh, Farhadfar, Freytes, Ganguly, Haverkos, Kamble, Lekakis, Kharfan-Dabaja, Sureda.

    Conflict of Interest Disclosures: Dr Ghosh reported receiving grants and personal fees from Celgene Corporation, Janssen/Pharmacyclics, Seattle Genetics, and TG Therapeutics; receiving grants from Genentech and Forty Seven Inc; receiving personal fees from AbbVie, AstraZeneca, BMS, and Gilead/Kite outside the submitted work; participating in speakers bureaus for AbbVie, AstraZeneca, BMS, Celgene Corporation, Gilead, Janssen/Pharmacyclics, and Seattle Genetics; and consulting for Celgene Corporation, Gilead, Janssen/Pharmacyclics, Seattle Genetics, and TG Therapeutics. Dr Epperla reported receiving other compensation from AstraZeneca, Pharmacyclics, and Verastem Oncology outside the submitted work. Dr Ganguly reported receiving personal fees from Seattle Genetics outside the submitted work. Dr Lazarus reported receiving other compensation from Pharmacyclics, AstraZeneca, Seattle Genetics, and Genentech. Dr Nishihori reported receiving other compensation from Novartis AG and receiving other compensation from Karyopharm outside the submitted work. Dr Rizzieri reported receiving other compensation from the Center for International Blood & Marrow Transplant Research (CIBMTR) during the conduct of the study. Dr Kharfan-Dabaja reported receiving other compensation from Pharmacyclics and receiving other compensation from Daiichi Sankyo outside the submitted work. Dr Sureda reported receiving personal fees and nonfinancial support from Takeda; receiving personal fees from BMS, Celgene Corporation, Janssen, and Novartis AG; receiving grants and personal fees from Gilead Kite; receiving personal fees and nonfinancial support from Sanofi outside the submitted work; and receiving compensation from BMS, Celgene Corporation, Gilead, Incyte, Janssen, MSD, Novartis AG, Roche, Sanofi, Takeda, and the Lymphoma Working Party of the European Society for Blood and Marrow Transplantation. Dr Hamadani reported receiving grants from Astellas, Spectrum, and Takeda outside the submitted work; receiving research funding to their institution from Celgene Corporation, Janssen R&D, MedImmune, Merck, Millennium Pharmaceuticals, and Seattle Genetics; receiving consultancy fees from AbGenomics, ADC Therapeutics, AstraZeneca, Celgene Corporation, Cellerant Therapeutics, Incyte Corporation, Janssen R&D, Magenta Therapeutics, MedImmune LLC, Omeros, and Pharmacyclics; participating on the speakers bureaus for Sanofi Genzyme, TeneoBio, and Verastem; and receiving research support and funding from Astellas Pharma and Spectrum Pharmaceuticals. No other disclosures were reported.

    Funding/Support: The CIBMTR is supported primarily by grant/cooperative agreement U24CA076518 from the Public Health Service and the National Cancer Institute (NCI), the National Heart, Lung, and Blood Institute (NHLBI), and the National Institute of Allergy and Infectious Diseases; grant/cooperative agreement U24HL138660 from the NHLBI and the NCI; grants R21HL140314 and U01HL128568 from the NHLBI; contract HHSH250201700006C from the Health Resources and Services Administration (HRSA); grants N00014-18-1-2888 and N00014-17-1-2850 from the Office of Naval Research; subaward from prime contract award SC1MC31881-01-00 from the HRSA; subawards from prime grant awards R01HL131731 and R01HL126589 from the NHLBI; subawards from prime grant awards 5P01CA111412, 5R01HL129472, R01CA152108, 1R01HL131731, 1U01AI126612, and 1R01CA231141 from the NIH; and commercial funds from Actinium Pharmaceuticals Inc; Adaptive Biotechnologies; Allovir Inc; Amgen Inc; anonymous donation to the Medical College of Wisconsin; Anthem Inc; Astellas Pharma US; Atara Biotherapeutics Inc; Biomedical Advanced Research and Development Authority; Be the Match Foundation; bluebird bio Inc; Boston Children’s Hospital; Bristol-Myers Squibb Company; Celgene Corporation; Children’s Hospital of Los Angeles; Chimerix Inc; City of Hope Medical Center; CSL Behring; CytoSen Therapeutics Inc; Daiichi Sankyo Company Ltd; Dana Farber Cancer Institute; Enterprise Science and Computing Inc; Fred Hutchinson Cancer Research Center; Gamida-Cell Ltd; Genzyme; Gilead Sciences Inc; GlaxoSmithKline; HistoGenetics Inc; Immucor; Incyte Corporation; Janssen Biotech Inc; Janssen Pharmaceuticals Inc; Janssen Research and Development LLC; Janssen Scientific Affairs LLC; Japan Hematopoietic Cell Transplantation Data Center; Jazz Pharmaceuticals Inc; Karius Inc; Karyopharm Therapeutics Inc; Kite, a Gilead Company; Kyowa Kirin; Magenta Therapeutics; Mayo Clinic and Foundation Rochester; Medac GmbH; Mediware; Memorial Sloan Kettering Cancer Center; Merck and Company Inc; Mesoblast; MesoScale Diagnostics Inc; Millennium, the Takeda Oncology Company; Miltenyi Biotec Inc; Mundipharma EDO; National Marrow Donor Program; Novartis Oncology; Novartis Pharmaceuticals Corporation; Omeros Corporation; Oncoimmune Inc; OptumHealth; Orca Biosystems Inc; the Patient-Centered Outcomes Research Institute; Pfizer Inc; Phamacyclics LLC; PIRCHE AG; Regeneron Pharmaceuticals Inc; REGiMMUNE Corporation; Sanofi Genzyme; Seattle Genetics; Shire; Sobi Inc; Spectrum Pharmaceuticals Inc; St Baldrick's Foundation; Swedish Orphan Biovitrum Inc; Takeda Oncology Company; The Medical College of Wisconsin; University of Minnesota; University of Pittsburgh; University of Texas–M. D. Anderson; University of Wisconsin–Madison; Viracor Eurofins; and Xenikos BV.

    Role of the Funder/Sponsor: The funding organizations had no role in the design and conduct of the study; collection, management, analysis, and interpretation of the data; preparation, review, or approval of the manuscript; and decision to submit the manuscript for publication.

    Disclaimer: The views expressed in this article do not reflect the official policy or position of the NIH, the Department of the Navy, the Department of Defense, the HRSA, or any other agency of the US Government.

    Additional Contributions: Jennifer Motl, BS (Medical College of Wisconsin), provided editorial support, which was funded by the Medical College of Wisconsin in accordance with Good Publication Practice guidelines.

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