Low absolute CD4⁺ T cell counts in peripheral blood predict poor prognosis in patients with newly diagnosed multiple myeloma

Abstract

The T lymphocyte system plays an active role in tumor immunosurveillance in multiple myeloma (MM), and abnormal T lymphocyte populations are often observed in patients with MM. In the current study, we evaluated the prognostic impact of abnormal T lymphocyte subset distributions in patients with newly diagnosed MM (NDMM). Between December 2012 to October 2016, 110 NDMM patients were included in this study. Multiparameter flow cytometry was applied to quantitatively analysis the peripheral blood T lymphocyte subsets, including CD4⁺ T cell, CD8⁺ T cell, and CD4/CD8 ratio. Survival analyses were performed based on the patients’ clinical data and the quantity of T lymphocyte subsets. The median follow-up time was 27.0 months (range, 2.5–66). Baseline percentages and absolute CD4⁺ T cell counts and the CD4/CD8 ratio were positively correlated with both overall survival (OS) and progression-free survival (PFS) according to Kaplan–Meier curves (p < .05). In the multivariate COX analysis, lower CD4⁺ T cell count was an independent unfavorable factor in predicting both OS (p = .016) and PFS (p = .010). Furthermore, lower CD4/CD8 ratio was an independent adverse prognostic factor for shorter PFS (p = .017). These results suggested that T lymphocyte subsets were crucial indicators in correlation with MM patients’ prognosis. Low CD4⁺ T cell counts and CD4/CD8 ratio were independent unfavorable prognostic predictors for patients with MM at diagnosis.

Keywords:

• T lymphocyte subsets
• prognosis
• peripheral blood
• multiple myeloma

Disclosure statement

The author reports no conflicts of interest in this work.

Additional information

Funding

This work was supported by National Natural Science Foundation of China (81670199); Jiangsu Province’s Medical Elite Program (ZDRCA2016015); Project of National Key Clinical Specialty, National Science & Technology Pillar Program (2014BAI09B12), Jiangsu Provincial Special Program of Medical Science (BL2014086 and BE2017751) and National Science and Technology Major Project (2018ZX09734007).