A prognostic model incorporating inflammatory cells and cytokines for newly diagnosed multiple myeloma patients.

Abstract

Peripheral blood cell counts and cytokines can be used as predictors of multiple myeloma (MM) patients' outcomes. 313 newly diagnosed MM patients treated with novel agents were divided into training and validation cohorts. We selected the common peripheral blood cell counts, including the lymphocyte/monocyte ratio (LMR), neutrophil/lymphocyte ratio (NLR), and platelet/lymphocyte ratio (PLR), systemic inflammation response index (SIRI), and serum cytokines which contained tumor necrosis factor-α (TNF-α), interleukin-1β (IL-1β), interleukin-2 receptor (IL-2R), interleukin-8 (IL-8), interleukin-6 (IL-6), and interleukin-10 (IL-10) as related variables. The least absolute shrinkage and selection operator (LASSO) regression was conducted to sort the predictor variables in the training cohort, and then the developed nomogram was assessed in the training and validation cohort. Our study showed that SIRI, PLR, and IL-8 were independent prognostic factors for the survival of MM patients. Patients with lower SIRI (≤ 0.87) had superior survival than patients with higher SIRI (> 0.87). Further, according to the LASSO regression, a nomogram embracing LMR (> 3.78), SIRI (> 0.87), PLR (≤ 106.44), and IL-8 was established. The nomogram demonstrated a better correlation with the outcomes of MM patients in the training cohort than International Staging System (ISS) and Revised-International Staging System (R-ISS). The same results were verified in the validation cohort. The nomogram incorporating inflammatory cells and cytokines could be a helpful tool to stratify MM patients in the era of novel agents.