Immune heterogeneity at diagnosis influences treatment response and survival in multiple myeloma.

The clinical heterogeneity of multiple myeloma (MM) remains incompletely captured by existing staging systems. To determine whether baseline immune profiles could refine prognostication, we conducted a large-scale analysis of 703 newly diagnosed MM patients. Peripheral blood immune subsets and serum cytokines were quantified before treatment via flow cytometry and multiplex immunoassays. Time-dependent ROC analysis identified optimal prognostic thresholds for each parameter. Univariate analysis associated inferior overall survival (OS) with low CD19⁺ B-cell counts, a low CD4⁺/CD8⁺ ratio, high NK cell percentage, elevated levels of IL-1β, sIL-2R, IL-6, IL-8, IL-10, and TNF, and low complement C3. A multivariate Cox model integrated the most robust predictors into an immune risk score (IM): IM = − 0.107 × (CD4⁺/CD8⁺) + 0.001 × sIL-2R + 0.003 × IL-6 + 0.006 × IL-8 − 1.238 × C3. Using the optimal cut-off (0.394), patients were stratified into high-risk (n = 231) and low-risk (n = 472) groups. The low-risk group exhibited significantly longer median OS (64.5 months vs. 32.2 months; p < 0.0001), and the IM score remained an independent prognostic factor after adjusting for clinical variables. Subgroup analysis confirmed its predictive value across treatment backgrounds. These results establish the pre-treatment systemic immune state as a powerful prognostic determinant and provide a clinically applicable immune-based scoring system for improved risk stratification in MM.