Comprehensive analysis and establishment of a prognostic model based on non-genetic predictors in multiple myeloma

Cancer Biomark. 2023;38(1):49-59. doi: 10.3233/CBM-220451.

Abstract

Background: Multiple myeloma (MM) is a systemic hematological malignancy usually incurable. The value of some important prognostic factors may gradually decrease.

Objective: We aimed to explore the non-genetic indexes, prognostic models, and significance of clinical staging systems of MM.

Methods: A retrospective analysis was conducted on clinical data from 110 patients with MM who first visit the First Affiliated Hospital of Guangzhou Medical University between September 2005 to December 2018.

Results: Bone marrow plasma cell percentage (BMPC%), cystatin C (CysC), and β2 microglobulin (β2-MG) were positively correlated with Durie-Salmon (D-S) and international staging system (ISS) stages, while red blood cell count (RBC) and hemoglobin volume (HGB) were negatively correlated (P< 0.05). Univariate analysis showed that ISS stage, treatment protocol, immunofixation electrophoresis (IFE), ratio of red cell distribution width to platelet count (RPR), monocyte count (MONO), lactate dehydrogenase, and immunoglobulin G were significantly associated with the three-year overall survival (OS). IFE, treatment protocol, and β2-MG significantly affected progression-free survival (P< 0.05). Multivariate analysis showed that the treatment protocol, ISS stage, RPR, MONO, and IFE were independent prognostic factors for three-year OS (P< 0.05).

Conclusions: BMPC%, CysC, and β2-MG were positively correlated with both clinical staging systems and RBC and HGB were negatively correlated. RPR and MONO affect MM prognosis and the established prognostic model can guide patient prognosis.

Keywords: Multiple myeloma; clinical staging; monocyte count; non-genetic predictors; prognostic model.

MeSH terms

  • Humans
  • Multiple Myeloma* / diagnosis
  • Multiple Myeloma* / drug therapy
  • Multiple Myeloma* / genetics
  • Multivariate Analysis
  • Neoplasm Staging
  • Prognosis
  • Retrospective Studies