Immune response in severe infection Towards personalized therapeutic targets and prognostic indicators

The aim of this thesis was to enhance our understanding of patient classification and personalized treatment strategies in patients suffering from severe infections. We summarized all clinical studies available on immunotherapy in sepsis in an extensive scoping review, highlighting personalized approaches. Furthermore, we introduce the ImmunoSep trial aimed at providing immunotherapy based on individual immunological profiles.
In the context of COVID-19, the thesis includes a nationwide retrospective analysis of hospitalized patients, identifying changes in epidemiology and treatment outcomes over four pandemic waves. Additionally, an analysis of immunosuppressive therapies in critically ill COVID-19 patients highlighted significant biomarker changes, suggesting potential for improved patient stratification. The exploration of treatment heterogeneity found consistent benefits of the C5a inhibitor vilobelimab across COVID-19 patient clusters, particularly in the most severe cases.
Furthermore, we analyzed clinical phenotypes and host responses in ICU patients, which underscored the association between severe phenotypes and increased mortality. Lastly, elevated IL-6 and IL-10 levels at hospital discharge in COVID-19 patients were found to predict adverse outcome.
Identifying patients with sepsis who are most at risk for adverse outcome and most responsive to treatment presents a complex challenge. The sepsis field has evolved considerably over the past decades in terms of insights into the pathogenesis of sepsis and novel trial design, and now focuses on prognostic and predictive enrichment strategies to improve patient outcomes. From the perspective of this author, the most promising way forward is using personalized approaches to determine therapeutic targets and prognostic indicators.