# Advanced disease and CD8+ TEMRA cells predict severe infections in multiple myeloma

## TL;DR

This study identifies risk factors for severe infections in multiple myeloma patients, including advanced disease and specific immune cell levels, to help doctors predict and prevent infections.

## Contribution

A novel risk score incorporating immune parameters and clinical factors to predict severe infections in MGUS and NDMM patients.

## Key findings

- 45% of patients developed infections, with 26% experiencing severe infections within 12 months.
- Four key risk factors for severe infections were identified, including elevated CD8+ TEMRA cells and advanced disease stage.
- The developed risk score achieved 92.9% sensitivity and 80% specificity in stratifying patients by infection risk.

## Abstract

Infections are a major cause of early morbidity and mortality in patients with multiple myeloma (MM) who are characterized by immunodeficiency secondary to disease. However, prospectively collected data on infection risk in this population are scarce. We aimed at identifying parameters in monoclonal gammopathy of undetermined significance (MGUS) and newly diagnosed MM (NDMM) patients with predictive power for early severe infections (SI).

We conducted a prospective study with newly diagnosed MGUS and NDMM patients. Besides clinical and laboratory data, immune parameters were collected at initial diagnosis before therapy initiation. Primary endpoint was the occurrence of SI within 12 months after diagnosis.

45% of patients developed infection, 26% with SI. Four main risk factors for SI were identified: ECOG ≥ 2 (p < 0.001), ISS stage II/III (p = 0.002), therapeutic intervention (p < 0.001), and elevated CD8+ TEMRA cells (p = 0.027). A risk score was compiled, enabling the stratification of patients with low or high risk for SI with a sensitivity of 92.9% and a specificity of 80%.

We developed a straightforward risk score that considers the relevance of T cell fitness in MGUS and NDMM patients and can help physicians to identify patients at risk of infection, thus enabling the implementation of timely and individualized prevention strategies.