Ronner Lukas, Giannini Heather M, Miano Todd A, Ittner Caroline A G, Turner Alexandra P, Dunn Thomas G, Agyekum Roseline S, Dasgupta Anushka, West Kirstin, Jones Tiffanie K, Shashaty Michael G S, Reilly John P, Meyer Nuala J
Division of Hematology and Oncology, Hospital of the University of Pennsylvania, Philadelphia, PA.
Division of Pulmonary and Critical Care Medicine and Center for Translational Lung Biology, University of Pennsylvania Perelman School of Medicine, Philadelphia, PA.
Crit Care Med. 2025 Jul 10. doi: 10.1097/CCM.0000000000006774.
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.
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.
None.
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 severe neutropenia and the subphenotype/mortality association. Hematologic malignancy uniquely appeared to attenuate the associated mortality of the IL-6-assigned hyperinflammatory subphenotype (interaction; p = 0.037), but not the IL-8-assigned hyperinflammatory subphenotype (interaction; p = 0.260), which retained an independent association with mortality in hematologic malignancy subjects (hazard ratio, 1.50; 95% CI, 1.08-2.07; p = 0.014).
As subphenotyping algorithms are being tested as point-of-care prognostic tools, it is important to understand their generalizability to patients with comorbid malignancy, which constitute an increasing proportion of ICU patients. The differential behavior of these algorithms in patients with hematologic malignancy suggests a need for independent derivation and validation in this specific population.
基于潜在类别分配的亚表型分析算法可能识别出脓毒症和急性呼吸窘迫综合征重症患者中对治疗有反应的亚组。目前尚不清楚这些算法是否可推广应用于合并恶性肿瘤的患者，这种情况可能会干扰有影响力的炎症生物标志物。本研究旨在测试恶性肿瘤或中性粒细胞减少症是否会改变两种算法进行亚表型分配的效果，这两种算法应用于一个前瞻性队列，该队列富集了患有活动性恶性肿瘤的ICU患者。
在美国一家单一的四级转诊中心进行的前瞻性队列研究。
设置/患者：入住ICU且主要入院指征为脓毒症的18岁以上ICU患者。
无。
我们将两种已发表的亚表型分析算法应用于我们的930例脓毒症患者队列，其中396例（42%）患有活动性恶性肿瘤。与基于白细胞介素（IL）-6的算法相比，基于IL-8（除可溶性肿瘤坏死因子受体1和碳酸氢盐外）的算法将更高比例的血液系统恶性肿瘤患者分配为“高炎症”亚表型（58%对32%）。在被IL-8算法分类为高炎症的患者中，白血病和中性粒细胞减少症患者的比例过高。我们构建了Cox比例风险模型，以评估实体恶性肿瘤、血液系统恶性肿瘤和严重中性粒细胞减少症的存在与亚表型/死亡率关联之间的相互作用。血液系统恶性肿瘤似乎独特地减弱了基于IL-6分配的高炎症亚表型的相关死亡率（相互作用；p = 0.037），但没有减弱基于IL-8分配的高炎症亚表型的相关死亡率（相互作用；p = 0.260），后者在血液系统恶性肿瘤患者中与死亡率保持独立关联（风险比，1.50；95%CI，1.08 - 2.07；p = 0.014）。
由于亚表型分析算法正在作为床旁预后工具进行测试，了解它们对合并恶性肿瘤患者（在ICU患者中所占比例日益增加）的可推广性很重要。这些算法在血液系统恶性肿瘤患者中的不同表现表明需要在这一特定人群中进行独立推导和验证。
