Validation of diagnostic gene sets to identify critically ill patients with sepsis.

Purpose: Gene expression diagnostics have been proposed to identify critically ill patients with sepsis. Three expression-based scores have been developed, but have not been compared in a prospective validation. We sought to validate these scores using an independent dataset and analysis.

Methods: We generated gene expression profiles from 61 critically ill patients. We validated the performance of 3 expression-based sepsis scores including 1) the Sepsis MetaScore (SMS); 2) the SeptiCyte™ Lab; and 3) the FAIM3:PLAC8 ratio. Sepsis was identified as the presence of definite, probable, or possible infection in the setting of organ dysfunction (SOFA score ≥ 2).

Results: For all 3 models, scores were significantly different between patients with and without sepsis. Discrimination was highest for the SMS (area under the receiver operating characteristics curve [AUROC 0.80 [95% CI 0.67-0.92]), with greater confidence in the presence of infection resulting in better model performance (max AUROC 0.93 [0.87-1.0]).

Conclusions: All three scores distinguished septic from non-septic ICU patients, with the SMS showing the best performance overall in our cohort. Our results suggest that models developed from the co-analysis of multiple cohorts are more generalizable. Further work is needed to identify expression-based biomarkers of response to specific therapies.