Parsimonious Subphenotyping Algorithms Perform Differently in Patients With Sepsis and Hematologic Malignancy
Abstract
Objectives: Latent class assignment-derived subphenotyping algorithms may identify treatment-responsive subgroups of critically ill patients with sepsis and acute respiratory distress syndrome. It is unclear if these algorithms are generalizable to patients with comorbid malignancy, a state which may perturb influential inflammatory biomarkers. This study aimed to test whether malignancy or neutropenia modified the effect of subphenotype assignment by two algorithms as applied to a prospective cohort enriched for ICU patients with active malignancy.
Design: Prospective cohort study at a single U.S. quaternary referral center.
Setting/patients: ICU patients older than 18 admitted to an ICU with a primary admission indication of sepsis.
Interventions: None.
Measurements and main results: We applied two published subphenotyping algorithms utilizing either interleukin (IL)-6 or IL-8 (in addition to soluble tumor necrosis factor receptor 1 and bicarbonate) to our cohort of 930 patients with sepsis, 396 (42%) of whom had active malignancy. A greater proportion of hematologic malignancy patients were assigned the "hyperinflammatory" subphenotype by the IL-8-utilizing algorithm than the IL-6 algorithm (58% vs. 32%). Patients with leukemia and neutropenia were overrepresented among those classified as hyperinflammatory by IL-8 algorithm. We constructed Cox proportional hazards models to assess for interaction between the presence of solid malignancy, hematologic malignancy, and…
How strong is the evidence?
Evidence Hub reads this as a cohort study, done in people. Its evidence level is 3 of 5 (Moderate · trial / cohort / secondary analysis). Trials without a large randomized design, cohorts and secondary analyses give moderate evidence. Reported size: 930 participants or records.
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