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New Risk Model Aims to Better Predict When Smoldering Myeloma Will Turn Aggressive

An international effort spanning seven medical centers and more than 2,300 patients has produced a dynamic tool that tracks changing biomarkers over time to predict progression to active multiple myeloma.

New Risk Model Aims to Better Predict When Smoldering Myeloma Will Turn Aggressive
New Risk Model Aims to Better Predict When Smolde…      Multiple Myeloma    Steven Fruitsmaak / Wikimedia Commons (CC BY-SA 3.0)
By Free News Press Editorial Team
Published April 17, 2026 at 8:15 PM PDT

Predicting when a precancerous blood condition will become full-blown cancer is one of the thorniest challenges in oncology. A new study published in Nature Medicine takes a significant step forward for patients with smoldering multiple myeloma, a precursor state that sometimes progresses to active multiple myeloma requiring treatment — and sometimes doesn't.

The research assembled data from 2,344 patients across seven international centers to build and validate a new risk stratification framework. The key innovation is that the model doesn't rely on a single snapshot of a patient's lab results. Instead, it incorporates evolving biomarker trajectories over time, capturing changes that static models miss.

Current tools for assessing smoldering myeloma risk are limited precisely because they treat the disease as frozen in time. A patient classified as low-risk at diagnosis might show worrying shifts in their bloodwork months later, but traditional models have no way to incorporate that new information. The new system, developed through the Precursor Asymptomatic Neoplasms by Group Effort initiative, is designed to update risk assessments dynamically as new clinical and biological data come in.

Getting this prediction right carries real consequences. Intervening too early means exposing patients to the side effects of cancer treatment they may never have needed. Waiting too long risks allowing the disease to progress to a stage where it causes serious organ damage. A more precise, continuously updated risk model could help doctors and patients navigate that difficult middle ground with greater confidence, though the tool will need further validation before widespread clinical adoption.

Multiple Myeloma    Steven Fruitsmaak, Armenian translation by user:GgGevorg / Wikimedia Commons (CC BY-SA 3.0)