Introduction

Minimal residual disease (MRD) has emerged as a critical prognostic marker in multiple myeloma (MM). Traditional MRD assessment relies heavily on bone marrow–based methods such as multiparameter flow cytometry (MFC), next-generation flow cytometry (NGF), and next-generation sequencing (NGS). However, these are invasive, costly, and limited in their ability to capture disease heterogeneity over time.

In this study, the authors evaluated EasyM, a mass spectrometry (MS)-based assay for blood-based MRD monitoring, offering a non-invasive and ultrasensitive alternative for longitudinal tracking of disease status in multiple myeloma.

Study Summary

447 sequential serum samples from 56 newly diagnosed multiple myeloma (NDMM) patients were assessed by EasyM clonotypic peptides mass spectrometry and the results compared to IFE, MFC (10-4), NGF (10-5) using time matched samples.  Samples were obtained from a prospectively maintained institutional database of patients in China with multiple myeloma, the National Longitudinal Cohort of Hematological Diseases-Multiple Myeloma (NICHE-MM).

The objectives were to assess the sensitivity, specificity, and prognostic impact of EasyM in comparison to conventional MRD monitoring methods across a cohort of real-world patients with newly diagnosed multiple myeloma (NDMM).

Key takeaways:

  • EasyM showed 99.6% sensitivity vs IFE and 100% sensitivity vs both MFC and NGF.
  • When adjusted for an optimized cutoff (<1.86% residual M-protein), EasyM achieved specificity of 93.2% vs NGF, maintaining high sensitivity (93.2%).
  • MS-MRD negativity was independently predictive of significantly longer PFS and OS.
  • EasyM enabled earlier relapse detection than IFE and bone marrow–based methods in several patients.

Conclusions

EasyM offers a minimally invasive, highly sensitive, and practical approach to MRD monitoring in MM. Its integration into clinical workflows could reduce the frequency of bone marrow biopsies and support more timely and personalized treatment adjustments.

Read the Publication

Authors

Huishou Fan, Bing Wang, Lihui Shi, Ni Pan, Wenqiang Yan, Jingyu Xu, Lixin Gong, Lingna Li, Yuntong Liu, Chenxing Du, Jian Cui, Guoqing Zhu, Shuhui Deng, Weiwei Sui, Yan Xu, Shuhua Yi, Mu Hao, Dehui Zou, Xiequn Chen, Lugui Qiu, and Gang An

doi: 10.1158/1078-0432.CCR-23-2767

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