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      Daratumumab combined with dexamethasone and lenalidomide or bortezomib in relapsed/refractory multiple myeloma (RRMM) patients: Report from the multiple myeloma GIMEMA Lazio group

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          Abstract

          The multiple myeloma (MM) treatment has changed over the last years due to the introduction of novel drugs. Despite improvements in the MM outcome, MM remains an incurable disease. Daratumumab is a human IgGK monoclonal antibody targeting CD38 with tumor activity associated with immunomodulatory mechanism. In combination with standard of care regimens, including bortezomib (Vd) or lenalidomide (Rd), daratumumab prolonged progression‐free survival (PFS) in patients (pts) with relapsed/refractory multiple myeloma (RRMM) and in new diagnosis MM. We report the data of the MM GIMEMA Lazio group in 171 heavily treated pts who received daratumumab, lenalidomide and dexamethasone (DRd) or daratumumab, velcade and dexamethasone (DVd). The overall response rate was 80%, and the overall survival (OS) and PFS were 84% and 77%, respectively. In addition, pts treated with DRd showed a better median PFS compared to pts treated with DVd, at 12 and 24 months, respectively. The most common hematologic treatment‐emergent adverse events (TAEs) were neutropenia, thrombocytopenia, and anemia. The most common nonhematologic TAEs were peripheral sensory neuropathy and infections. Our data confirmed that DRd or DVd therapy is effective and safe in RRMM pts, and our real‐life analysis could support the physicians regarding the choice of optimal therapy in this setting of pts.

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          Research electronic data capture (REDCap)--a metadata-driven methodology and workflow process for providing translational research informatics support.

          Paul A. Harris, Robert Taylor, Robert Thielke … (2009)
          Research electronic data capture (REDCap) is a novel workflow methodology and software solution designed for rapid development and deployment of electronic data capture tools to support clinical and translational research. We present: (1) a brief description of the REDCap metadata-driven software toolset; (2) detail concerning the capture and use of study-related metadata from scientific research teams; (3) measures of impact for REDCap; (4) details concerning a consortium network of domestic and international institutions collaborating on the project; and (5) strengths and limitations of the REDCap system. REDCap is currently supporting 286 translational research projects in a growing collaborative network including 27 active partner institutions.
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            The REDCap consortium: Building an international community of software platform partners

            Paul Harris, Robert Taylor, Brenda Minor … (2019)
            The Research Electronic Data Capture (REDCap) data management platform was developed in 2004 to address an institutional need at Vanderbilt University, then shared with a limited number of adopting sites beginning in 2006. Given bi-directional benefit in early sharing experiments, we created a broader consortium sharing and support model for any academic, non-profit, or government partner wishing to adopt the software. Our sharing framework and consortium-based support model have evolved over time along with the size of the consortium (currently more than 3200 REDCap partners across 128 countries). While the "REDCap Consortium" model represents only one example of how to build and disseminate a software platform, lessons learned from our approach may assist other research institutions seeking to build and disseminate innovative technologies.
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              International Myeloma Working Group consensus criteria for response and minimal residual disease assessment in multiple myeloma.

              Shaji Kumar, Bruno Paiva, Kenneth Anderson … (2016)
              Treatment of multiple myeloma has substantially changed over the past decade with the introduction of several classes of new effective drugs that have greatly improved the rates and depth of response. Response criteria in multiple myeloma were developed to use serum and urine assessment of monoclonal proteins and bone marrow assessment (which is relatively insensitive). Given the high rates of complete response seen in patients with multiple myeloma with new treatment approaches, new response categories need to be defined that can identify responses that are deeper than those conventionally defined as complete response. Recent attempts have focused on the identification of residual tumour cells in the bone marrow using flow cytometry or gene sequencing. Furthermore, sensitive imaging techniques can be used to detect the presence of residual disease outside of the bone marrow. Combining these new methods, the International Myeloma Working Group has defined new response categories of minimal residual disease negativity, with or without imaging-based absence of extramedullary disease, to allow uniform reporting within and outside clinical trials. In this Review, we clarify several aspects of disease response assessment, along with endpoints for clinical trials, and highlight future directions for disease response assessments.
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                Author and article information

                Contributors
                Francesca Fazio: fazio@bce.uniroma1.it
                Journal
                Journal ID (nlm-ta): EJHaem
                Journal ID (iso-abbrev): EJHaem
                Journal ID (doi): 10.1002/(ISSN)2688-6146
                Journal ID (publisher-id): JHA2
                Title: EJHaem
                Publisher: John Wiley and Sons Inc. (Hoboken )
                ISSN (Electronic): 2688-6146
                Publication date (Electronic): 15 January 2022
                Publication date Collection: February 2022
                Volume: 3
                Issue: 1 ( doiID: 10.1002/jha2.v3.1 )
                Pages: 121-128
                Affiliations
                [ 1 ] Department of Translational and Precision Medicine, Hematology Azienda Policlinico Umberto I Sapienza University of RomeSapienza Università di Roma
                [ 2 ] Transplant Network, Hematology‐Stem Cell Transplant Unit Rome Italy
                [ 3 ] Department of Haematology, University Campus Biomedico Rome Italy
                [ 4 ] ASL RM/A UOSD Ematologia Asl Roma 1 Rome Italy
                [ 5 ] Department of Hematology, Hematology San Camillo Forlanini Hospital Rome Italy
                [ 6 ] Department of Hematology, Hematology Ospedale Sant'Eugenio Rome Italy
                [ 7 ] Department of Hematology San Giovanni‐Addolorata Hospital Rome Italy
                [ 8 ] Department of Hematology Ospedale Fabrizio Spaziani Rome Italy
                [ 9 ] Haematology and Stem Cell Transplant Regina Elena National Cancer Institute Rome Italy
                [ 10 ] Azienda Ospedaliera Sant'Andrea Rome Italy
                [ 11 ] S. Eugenio Hospital Institute of Haematology Rome Italy
                [ 12 ] Data Center, Italian Group for Adult Hematologic Diseases, (GIMEMA) Rome Italy
                [ 13 ] Department of Haematology Ospedale Sant'Eugenio Rome Italy
                [ 14 ] Hematology and Bone Marrow Transplantation Unit Azienda Ospedaliera San Camillo‐Forlanini Rome Italy
                [ 15 ] Department of Hematology, ASL Roma 1 Rome Italy
                [ 16 ] Department of Haematology Campus Bio‐Medico University of Rome Rome Italy
                [ 17 ] Chair of Hematology, Universita Tor Vergata Rome Italy
                Author notes
                [*] [* ] Correspondence

                Francesca Fazio, Department of Translational and Precision Medicine, Sapienza University of Rome, Via Benevento 6, 00161 Rome, Italy.

                Email: fazio@ 123456bce.uniroma1.it

                Article
                Publisher ID: JHA2359
                DOI: 10.1002/jha2.359
                PMC ID: 9175681
                PubMed ID: 35846211
                SO-VID: 78631a4a-241d-42a1-b3e7-3de6948fdc03
                Copyright © © 2022 The Authors. eJHaem published by British Society for Haematology and John Wiley & Sons Ltd.
                License:

                This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

                History
                Date revision received : 14 November 2021
                Date received : 04 October 2021
                Date accepted : 18 November 2021
                Page count
                Figures: 2, Tables: 2, Pages: 8, Words: 5010
                Categories
                Subject: Research Article
                Subject: Haematologic Malignancy ‐ Plasma Cell
                Subject: Research Articles
                Custom metadata
                source-schema-version-number 2.0
                cover-date February 2022
                details-of-publishers-convertor Converter:WILEY_ML3GV2_TO_JATSPMC version:6.1.6 mode:remove_FC converted:23.05.2022

                Keywords: immunotherapy,multiple myeloma,relapsed refractory
                Data availability:
                Keywords: immunotherapy, multiple myeloma, relapsed refractory

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