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The RAG Model: a new paradigm for genetic risk stratification in multiple myeloma
journal contribution
posted on 2023-06-08, 20:01 authored by Steven M Prideaux, Emma Conway O'Brien, Timothy ChevassutTimothy ChevassutMolecular studies have shown that multiple myeloma is a highly genetically heterogonous disease which may manifest itself as any number of diverse subtypes each with variable clinicopathological features and outcomes. Given this genetic heterogeneity, a universal approach to treatment of myeloma is unlikely to be successful for all patients and instead we should strive for the goal of personalised therapy using rationally informed targeted strategies. Current DNA sequencing technologies allow for whole genome and exome analysis of patient myeloma samples that yield vast amounts of genetic data and provide a mutational overview of the disease. However, the clinical utility of this information currently lags far behind the sequencing technology which is increasingly being incorporated into clinical practice. This paper attempts to address this shortcoming by proposing a novel genetically based “traffic-light” risk stratification system for myeloma, termed the RAG (Red, Amber, Green) model, which represents a simplified concept of how complex genetic data may be compressed into an aggregate risk score. The model aims to incorporate all known clinically important trisomies, translocations, and mutations in myeloma and utilise these to produce a score between 1.0 and 3.0 that can be incorporated into diagnostic, prognostic, and treatment algorithms for the patient.
History
Publication status
- Published
File Version
- Published version
Journal
Bone Marrow ResearchISSN
2090-2999Publisher
Hindawi Publishing CorporationExternal DOI
Volume
2014Article number
a526568Department affiliated with
- Clinical and Experimental Medicine Publications
Research groups affiliated with
- Haematology Research Group Publications
Full text available
- Yes
Peer reviewed?
- Yes
Legacy Posted Date
2015-02-16First Open Access (FOA) Date
2015-02-16First Compliant Deposit (FCD) Date
2015-02-16Usage metrics
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