Speaking the Same Language: How a New Global Consensus is Redefining High-Risk Myeloma image

Speaking the Same Language: How a New Global Consensus is Redefining High-Risk Myeloma

Posted on: Oct 06, 2025

The global myeloma community has come together to create a single, unified definition for high-risk disease, a landmark achievement presented by Dr. Anais Schavgoulidze at the IMS 2025 conference. This new Consensus Genomic Staging (CGS) model is not just an academic exercise; it's about breaking down a major barrier to research, allowing scientists and doctors worldwide to "speak the same language" and work together more effectively to improve outcomes for the most vulnerable patients.

Why a Unified Definition Was Urgently Needed

This global consensus was born out of a pressing need to solve two major problems that were holding back progress for high-risk patients:

Outdated Risk Factors: With the arrival of powerful new triplet and quadruplet therapies, the traditional ways of predicting a patient's prognosis were no longer reliable. The disease course had changed, and the old rulebook was obsolete.

A Lack of Uniformity: Different clinical trials and research groups all used their own slightly different definitions of "high-risk myeloma." This made it nearly impossible to compare results between studies, creating a fundamental "break to knowledge" that slowed the pace of discovery.

A workshop in Barcelona brought cooperative groups together to share data and create one harmonized definition, allowing the entire field to move forward in unison.

A clear definition of high risk

The CGS model provides a clear, structured framework based on a cancer cell's specific genetic markers. A patient is classified as high-risk if they have certain "major red flags" or a specific combination of "warning signs."

A patient is considered high-risk if they have at least one of the following:

  • Loss of a key protective gene, del(17p), or a mutation in the TP53 gene. Think of TP53 as the cell's emergency brake; losing it is a major problem.

  • An aggressive cancer-driving gene rearrangement involving the MYC oncogene.

  • A combination of at least two "intermediate-risk factors" (see below).

The intermediate-risk "warning signs"

These genetic markers are significant, but a patient must have at least two of them to be classified as high-risk. Having only one of these places a patient in the standard-risk category.

  • Specific chromosomal swaps: t(4;14), t(14;16), or t(14;20).

  • Extra copies of a part of chromosome 1 (gain of 1q).

  • Loss of a part of chromosome 1 (deletion of 1p).

The model also includes a "functional high-risk" category for patients whose cancer cells are dividing very rapidly, even if they don't have any of the specific genetic markers listed above.

A foundation built on decades of research

This new consensus stands on the shoulders of decades of scientific discovery. The journey began in 1985 with the simple observation that any chromosomal abnormality was a bad sign. It advanced in 1995 with the identification of specific markers like the deletion of chromosome 13. The development of technology like FISH, which allowed scientists to "light up" and see specific genetic changes, paved the way for the sophisticated, unified model we have today. The CGS model, while not perfect, is a vital foundation for future research.

The new Consensus Genomic Staging model is a landmark achievement born from decades of research and a pressing need for collaboration. By providing the global myeloma community with a single, clear language to define high-risk disease, this model overcomes a major obstacle to progress. While it's a starting point that will evolve as our knowledge grows, this unified framework is essential for designing better clinical trials, comparing research findings, and ultimately accelerating the development of more effective therapies for patients with the most aggressive forms of multiple myeloma.

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Healthtree contact Valeria Escobedo

Valeria Escobedo

Valeria Escobedo is an International Medical Graduate who joined HealthTree in May 2024 as a Clinical Data Manager and Research Associate. She supports myeloma patients by transforming medical records into clear, accurate profiles that drive research and care. Outside of work, she enjoys romance novels, traveling, listening to music while she works, and finding beauty in everyday moments.