Multi-trajectory models of serum biomarkers among patients with monoclonal gammopathy of undetermined significance

Hematol Oncol. 2022 Aug;40(3):409-416. doi: 10.1002/hon.2992. Epub 2022 Apr 1.


Understanding the progression of monoclonal gammopathy of undetermined significance (MGUS) to multiple myeloma (MM) is needed to identify patients who would benefit from closer clinical surveillance. Given that two of the defining criteria of MM are renal failure and anemia, we described the trajectories of creatinine (Cr) and hemoglobin (Hgb) over time in patients with a diagnosis of MGUS. Patients diagnosed with MGUS (n = 424) were identified by a previously validated case-finding algorithm using health claims and electronic health record data (2007-2015) and followed through 2018. Group-based trajectory modeling identified patients with distinct laboratory value trajectories of Cr (mg/dl) and Hgb (g/dl). Most patients were non-Hispanic White (97.6%) with a mean age of 75 years at MGUS diagnosis. Three multi-trajectory groups were identified: (1) Normal Cr/Hgb (n = 225; 53.1%)-stable serum Cr levels and decreasing, normal Hgb levels; (2) Normal Cr/lower-normal Hgb group (n = 188; 44.3%)-stable, slightly elevated levels of Cr and decreasing levels of Hgb; and (3) High Cr/borderline Hgb group (n = 11; 2.6%)-increased Cr levels and stable low levels of Hgb. Patients with MGUS in Group 2 were older than patients in other groups, and patients in group 3 had more comorbidities than participants in all other groups. Few patients developed MM during the study period. We were able to identify distinct biomarker trajectories in patients with MGUS over time. Future research should investigate how these trajectories may be related to the risk of progression to MM, including M-protein levels.

Keywords: MGUS; biomarkers; creatinine; hemoglobin; multiple myeloma.

MeSH terms

  • Aged
  • Biomarkers
  • Comorbidity
  • Disease Progression
  • Humans
  • Monoclonal Gammopathy of Undetermined Significance*
  • Multiple Myeloma*
  • Paraproteinemias* / diagnosis
  • Paraproteinemias* / epidemiology


  • Biomarkers