IL-1R2-based biomarker models predict melioidosis mortality independent of clinical data.
IL-1R2-based biomarker models predict melioidosis mortality independent of clinical data.
复制标题
基于IL-1R2的生物标志物模型可预测与临床数据无关的黑胶病死亡率。
DOI：
10.3389/fmed.2023.1211265
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发表时间：
2023
影响因子：
3.9
通讯作者：
中科院分区：
文献类型：
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作者：
类鼻疽病是一种由革兰氏阴性杆菌伪伯克霍尔德菌引起的致命热带传染病，但很少有研究确定有希望的生物标志物候选物来预测预后。在78名前瞻性纳入的类鼻窦病住院患者中，从文献中鉴定出的6种候选蛋白质生物标志物在入组时在血浆中进行了测量。采用最小绝对收缩和选择算子（LASSO）回归建立了多生物标志物模型，并通过受试者工作特征曲线分析将死亡率判别与临床变量模型进行比较。在191名前瞻性入组的类鼻疽住院患者的外部验证组中，死亡率预测得到了证实。LASSO回归选择IL-1R2和骨髓细胞可溶性触发受体1 （sTREM-1）纳入候选生物标志物模型。IL-1R2 + sTREM-1模型（AUC 0.81, 95% CI 0.72-0.91）和仅IL-1R2模型（AUC 0.78, 95% CI 0.68-0.88）的受试者工作特征曲线（AUC 0.69, 95% CI 0.56-0.81, p < 0.01, p = 0.03）下的死亡率判别面积均高于基于修改的顺序器官衰竭评估（SOFA）评分的模型（AUC 0.69, 95% CI 0.56-0.81, p < 0.01, p = 0.03）。在外部验证集中，IL-1R2 + sTREM-1模型（AUC 0.86, 95% CI 0.81-0.92）与改进的SOFA模型（AUC 0.80, 95% CI 0.74-0.86, p < 0.01）相比具有更好的28天死亡率判别性，与单独含有IL-1R2的模型相似（AUC 0.82, 95% CI 0.76-0.88, p = 0.33）。与类鼻疽病的临床变量模型相比，含有IL-1R2的生物标志物模型具有更好的28天死亡率预测，可能是未来快速测试开发的目标。
Melioidosis is an often-fatal tropical infectious disease caused by the Gram-negative bacillus Burkholderia pseudomallei, but few studies have identified promising biomarker candidates to predict outcome. In 78 prospectively enrolled patients hospitalized with melioidosis, six candidate protein biomarkers, identified from the literature, were measured in plasma at enrollment. A multi-biomarker model was developed using least absolute shrinkage and selection operator (LASSO) regression, and mortality discrimination was compared to a clinical variable model by receiver operating characteristic curve analysis. Mortality prediction was confirmed in an external validation set of 191 prospectively enrolled patients hospitalized with melioidosis. LASSO regression selected IL-1R2 and soluble triggering receptor on myeloid cells 1 (sTREM-1) for inclusion in the candidate biomarker model. The areas under the receiver operating characteristic curve (AUC) for mortality discrimination for the IL-1R2 + sTREM-1 model (AUC 0.81, 95% CI 0.72–0.91) as well as for an IL-1R2-only model (AUC 0.78, 95% CI 0.68–0.88) were higher than for a model based on a modified Sequential Organ Failure Assessment (SOFA) score (AUC 0.69, 95% CI 0.56–0.81, p < 0.01, p = 0.03, respectively). In the external validation set, the IL-1R2 + sTREM-1 model (AUC 0.86, 95% CI 0.81–0.92) had superior 28-day mortality discrimination compared to a modified SOFA model (AUC 0.80, 95% CI 0.74–0.86, p < 0.01) and was similar to a model containing IL-1R2 alone (AUC 0.82, 95% CI 0.76–0.88, p = 0.33). Biomarker models containing IL-1R2 had improved 28-day mortality prediction compared to clinical variable models in melioidosis and may be targets for future, rapid test development.