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Risk Stratification and Treatment in Smoldering Multiple Myeloma
Smoldering multiple myeloma is a heterogeneous asymptomatic precursor to multiple myeloma. Since its identification in 1980, risk stratification models have been developed using two main stratification methods: clinical measurement-based and genetics-based. Clinical measurement models can be subdivi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8750018/ https://www.ncbi.nlm.nih.gov/pubmed/35011692 http://dx.doi.org/10.3390/cells11010130 |
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author | Lussier, Tyler Schoebe, Natalie Mai, Sabine |
author_facet | Lussier, Tyler Schoebe, Natalie Mai, Sabine |
author_sort | Lussier, Tyler |
collection | PubMed |
description | Smoldering multiple myeloma is a heterogeneous asymptomatic precursor to multiple myeloma. Since its identification in 1980, risk stratification models have been developed using two main stratification methods: clinical measurement-based and genetics-based. Clinical measurement models can be subdivided in three types: baseline measurements (performed at diagnosis), evolving measurements (performed over time during follow-up appointments), and imaging (for example, magnetic resonance imaging). Genetic approaches include gene expression profiling, DNA/RNA sequencing, and cytogenetics. It is important to accurately distinguish patients with indolent disease from those with aggressive disease, as clinical trials have shown that patients designated as “high-risk of progression” have improved outcomes when treated early. The risk stratification models, and clinical trials are discussed in this review. |
format | Online Article Text |
id | pubmed-8750018 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-87500182022-01-12 Risk Stratification and Treatment in Smoldering Multiple Myeloma Lussier, Tyler Schoebe, Natalie Mai, Sabine Cells Review Smoldering multiple myeloma is a heterogeneous asymptomatic precursor to multiple myeloma. Since its identification in 1980, risk stratification models have been developed using two main stratification methods: clinical measurement-based and genetics-based. Clinical measurement models can be subdivided in three types: baseline measurements (performed at diagnosis), evolving measurements (performed over time during follow-up appointments), and imaging (for example, magnetic resonance imaging). Genetic approaches include gene expression profiling, DNA/RNA sequencing, and cytogenetics. It is important to accurately distinguish patients with indolent disease from those with aggressive disease, as clinical trials have shown that patients designated as “high-risk of progression” have improved outcomes when treated early. The risk stratification models, and clinical trials are discussed in this review. MDPI 2021-12-31 /pmc/articles/PMC8750018/ /pubmed/35011692 http://dx.doi.org/10.3390/cells11010130 Text en © 2021 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Review Lussier, Tyler Schoebe, Natalie Mai, Sabine Risk Stratification and Treatment in Smoldering Multiple Myeloma |
title | Risk Stratification and Treatment in Smoldering Multiple Myeloma |
title_full | Risk Stratification and Treatment in Smoldering Multiple Myeloma |
title_fullStr | Risk Stratification and Treatment in Smoldering Multiple Myeloma |
title_full_unstemmed | Risk Stratification and Treatment in Smoldering Multiple Myeloma |
title_short | Risk Stratification and Treatment in Smoldering Multiple Myeloma |
title_sort | risk stratification and treatment in smoldering multiple myeloma |
topic | Review |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8750018/ https://www.ncbi.nlm.nih.gov/pubmed/35011692 http://dx.doi.org/10.3390/cells11010130 |
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