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Multiple myeloma current treatment algorithms

The treatment of multiple myeloma (MM) continues to evolve rapidly with arrival of multiple new drugs, and emerging data from randomized trials to guide therapy. Along the disease course, the choice of specific therapy is affected by many variables including age, performance status, comorbidities, a...

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Autores principales: Rajkumar, S. Vincent, Kumar, Shaji
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523011/
https://www.ncbi.nlm.nih.gov/pubmed/32989217
http://dx.doi.org/10.1038/s41408-020-00359-2
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author Rajkumar, S. Vincent
Kumar, Shaji
author_facet Rajkumar, S. Vincent
Kumar, Shaji
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description The treatment of multiple myeloma (MM) continues to evolve rapidly with arrival of multiple new drugs, and emerging data from randomized trials to guide therapy. Along the disease course, the choice of specific therapy is affected by many variables including age, performance status, comorbidities, and eligibility for stem cell transplantation. In addition, another key variable that affects treatment strategy is risk stratification of patients into standard and high-risk MM. High-risk MM is defined by the presence of t(4;14), t(14;16), t(14;20), gain 1q, del(17p), or p53 mutation. In this paper, we provide algorithms for the treatment of newly diagnosed and relapsed MM based on the best available evidence. We have relied on data from randomized controlled trials whenever possible, and when appropriate trials to guide therapy are not available, our recommendations reflect best practices based on non-randomized data, and expert opinion. Each algorithm has been designed to facilitate easy decision-making for practicing clinicians. In all patients, clinical trials should be considered first, prior to resorting to the standard of care algorithms we outline.
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spelling pubmed-75230112020-10-19 Multiple myeloma current treatment algorithms Rajkumar, S. Vincent Kumar, Shaji Blood Cancer J Current Treatment Algorithm The treatment of multiple myeloma (MM) continues to evolve rapidly with arrival of multiple new drugs, and emerging data from randomized trials to guide therapy. Along the disease course, the choice of specific therapy is affected by many variables including age, performance status, comorbidities, and eligibility for stem cell transplantation. In addition, another key variable that affects treatment strategy is risk stratification of patients into standard and high-risk MM. High-risk MM is defined by the presence of t(4;14), t(14;16), t(14;20), gain 1q, del(17p), or p53 mutation. In this paper, we provide algorithms for the treatment of newly diagnosed and relapsed MM based on the best available evidence. We have relied on data from randomized controlled trials whenever possible, and when appropriate trials to guide therapy are not available, our recommendations reflect best practices based on non-randomized data, and expert opinion. Each algorithm has been designed to facilitate easy decision-making for practicing clinicians. In all patients, clinical trials should be considered first, prior to resorting to the standard of care algorithms we outline. Nature Publishing Group UK 2020-09-28 /pmc/articles/PMC7523011/ /pubmed/32989217 http://dx.doi.org/10.1038/s41408-020-00359-2 Text en © The Author(s) 2020 Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Current Treatment Algorithm
Rajkumar, S. Vincent
Kumar, Shaji
Multiple myeloma current treatment algorithms
title Multiple myeloma current treatment algorithms
title_full Multiple myeloma current treatment algorithms
title_fullStr Multiple myeloma current treatment algorithms
title_full_unstemmed Multiple myeloma current treatment algorithms
title_short Multiple myeloma current treatment algorithms
title_sort multiple myeloma current treatment algorithms
topic Current Treatment Algorithm
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7523011/
https://www.ncbi.nlm.nih.gov/pubmed/32989217
http://dx.doi.org/10.1038/s41408-020-00359-2
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