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<p>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 (<i>n</i> = 231) and low-risk (<i>n</i> = 472) groups. The low-risk group exhibited significantly longer median OS (64.5 months vs. 32.2 months; <i>p</i> &lt; 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.</p>

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

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年2月6日

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  • Yue Wang,
  • Tianwei Lan,
  • Shiyang Gu,
  • Yian Zhang,
  • Peng Liu

摘要

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.