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December 8, 2025BloodOpen Access

Feasibility of risk classification with newly proposed international myeloma working group (IMWG) high-risk definition: A single-center analysis using natural language processing

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Authors

MFMark A. FialaWashington University in St. LouisSKSarah Kelley

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Implication

Single-center analysis reveals missing data challenges in risk classification for multiple myeloma, suggesting the need for improved methods.

Key Points

  • To analyze the feasibility of a new high-risk classification for multiple myeloma using natural language processing.
  • Analyzed patients diagnosed with multiple myeloma from 2018 to 2024 at a single center.
  • Utilized natural language processing to convert unstructured texts into discrete data for classification.
  • Compared IMWG high-risk classification against traditional ISS, R-ISS, and R2-ISS systems.
  • 305 patients were included with 50.5% unclassified by IMWG due to missing data.
  • Cytogenetic data was often missing (e.g., del(17p): 10.8%).
  • There was a significant difference in unclassified risk across various risk systems.

Cite This Study

Fiala et al. (2025) studied this question.

synapsesocial.com/papers/69362f4b4fa91c937236d7e6https://doi.org/10.1182/blood-2025-2218
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Also Consider

Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context:

  1. 1Real-world validation of the 2025 IMWG high-risk criteria in multiple myeloma.2026
  2. 2Validation of the High-Risk Consensus Genomic Staging System in Newly Diagnosed Multiple Myeloma2025 · 1 citations
  3. 3Validation of the 2025 IMS / IMWG risk classification in patients with newly diagnosed multiple myeloma treated with quadruplets and autologous stem cell transplant2026 · 2 citations
  4. 4Validation of the new IMS/IMWG consensus genomic staging (CGS) of high‐risk multiple myeloma (HRMM) in a contemporary cohort of 1209 patients2025 · 2 citations
  5. 5Identifying high-risk cytogenetic subgroups in multiple myeloma using large language artificial intelligence models.2026