Staging and Prognostication of Multiple Myeloma

Overview

Journal Expert Rev Hematol

Specialty Hematology

Date 2014 Feb 4

PMID 24483346

Citations 14

Authors

Rafael Fonseca

Jorge Monge

Meletios A Dimopoulos

Affiliations

Soon will be listed here.

Abstract

Multiple myeloma (MM) is a heterogeneous disease that, over the past 15 years, has seen an increased understanding of its biology and of novel therapeutic options. Distinctive subtypes of the disease have been described, each with different outcomes and clinic-pathological features. Even though a detailed classification of MM into at least seven or eight major subtypes is possible, a more practical clinical approach can classify the disease into high-risk and non-high-risk MM. Such classification has permitted a more personalized approach to the management of the disease. Additionally, risk stratification should be included in outcome discussions with patients, as survival differs significantly by high-risk status. Nowadays, test for risk stratification are widely available and can be routinely used in the clinic. A greater understanding of the genetic abnormalities underlying the biology of MM will allow for the development of novel targeted therapies and better prognostic markers of the disease.

Citing Articles

Predicting cytogenetic risk in multiple myeloma using conventional whole-body MRI, spinal dynamic contrast-enhanced MRI, and spinal diffusion-weighted imaging.

Den Berghe T, Verberckmoes B, Kint N, Wallaert S, De Vos N, Algoet C Insights Imaging. 2024; 15(1):106.

PMID: 38597979 PMC: 11006637. DOI: 10.1186/s13244-024-01672-1.

Predicting risk of progression in relapsed multiple myeloma using traditional risk models, focal lesion assessment with PET-CT and minimal residual disease status.

Baker D, Bimali M, Carrillo L, Sachedina A, Alapat D, Hoque M Haematologica. 2021; 106(12):3215-3218.

PMID: 34847659 PMC: 8634177. DOI: 10.3324/haematol.2021.278779.

Initial Therapeutic Approaches to Patients with Multiple Myeloma.

Berbari H, Kumar S Adv Ther. 2021; 38(7):3694-3711.

PMID: 34145483 DOI: 10.1007/s12325-021-01824-5.

CNV Radar: an improved method for somatic copy number alteration characterization in oncology.

Soong D, Stratford J, Avet-Loiseau H, Bahlis N, Davies F, Dispenzieri A BMC Bioinformatics. 2020; 21(1):98.

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Identification of the xenograft and its ascendant sphere-forming cell line as belonging to EBV-induced lymphoma, and characterization of the status of sphere-forming cells.

Dolgova E, Petrova D, Proskurina A, Ritter G, Kisaretova P, Potter E Cancer Cell Int. 2019; 19:120.

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