Data from: The interest of inflammatory biomarkers in the diagnostic approach

Background: The role of inflammatory biomarkers in the etiological
orientation is increasingly under study, and their potential significance
is recognized. Methods: Procalcitonin (PCT), neutrophil-lymphocyte ratio
(NLR), C-reactive-protein (CRP), fibrinogen, ferritinaemia and lactate
were measured on admission in all patients. The optimal cut-off values for
the sensitivities and specificities to the infectious diseases were
determined using the receiver operating curve(ROC) analysis and
Youden's index. The diagnostic accuracy of biomarkers and their
combinations for predicting infectious etiologies was calculated by area
under the curve(AUC). Results: A total of 164 patients were included in
the study. The mean age was 50.7 ± 18 years [18 – 92 years]. Fifty-three
patients (32.3%) were over 65 years old. Patients were split into four
groups: 53 patients (32.3%) with infectious diseases of which 45 patients
(84.9%) presented bacterial infections, 62 patients (37.8%) with
inflammatory diseases, 14 patients (8.5%) with neoplasms and 35 patients
(21.3%) with other diagnosis. The high mean levels of Leukocytes (12047
cells/mm3, Neutrophils (9015 cells/mm3), Neutrophils to lymphocytes ratio
(NLR) (9.7), C reactive protein (CRP) (152.5 mg/L), Procalcitonin
(PCT)(3.28 ng/ml)and fibrinogen (5.37g/L) were associated to infectious
etiologies with statistically significant differences. Thus, we identified
cut-offs of NLR(6.1), CRP (123 mg/L),PCT(0.24 ng/mL) and fibrinogen (4.9
g/L) to discriminate infectious etiologies in our population. For
diagnosing infectious diseases, the CRP showed higher AUC( Area under the
curve) (Sp: 89.7%, Se: 64.3%, AUC=0.9, CI: 0.83-0.96, p<10-3) than
PCT (Sp: 86.1%,Se: 62.3%, AUC=0,87, CI:0.80-0.93, p<10-3), NLR (Sp:
87.1%, Se: 61%, AUC=0.81, CI: 0.731- 0.902, p <10-3) and Fibrinogen
(Sp: 84.7%, Se:68.3%, AUC=0.77, CI: 0.65 – 0.98, p<10-3).The
combination of CRP and NLR levels improved the diagnostic accuracy (AUC
0.93, 95% CI 0.84–0.96; p< 10-3) for distinguishing between
infectious and non-infectious diseases. Conclusions: Our study is
characterized by the variety of included disease categories. It showed the
usefulness of inflammatory biomarkers, particularly the NLR and its
combination with CRP, which are low cost and easy to assess, in promoting
the diagnostic accuracy to distinguish infections among inflammatory,
neoplasia and other diagnoses.

背景：炎症生物标志物（inflammatory biomarkers）在病因学研究方向的作用正受到越来越多的关注，其潜在临床价值已获得学界认可。方法：所有患者均于入院时检测降钙素原（Procalcitonin, PCT）、中性粒细胞淋巴细胞比值（neutrophil-lymphocyte ratio, NLR）、C反应蛋白（C-reactive-protein, CRP）、纤维蛋白原、血清铁蛋白及乳酸水平。采用受试者工作特征曲线（receiver operating curve, ROC）分析和约登指数（Youden's index）确定感染性疾病诊断的最佳临界值（对应灵敏度与特异度的最优截断点）。通过曲线下面积（area under the curve, AUC）计算各生物标志物及其联合应用预测感染性病因的诊断效能。结果：本研究共纳入164例患者，平均年龄为50.7±18岁[18~92岁]，其中53例（32.3%）患者年龄超过65岁。将患者分为四组：53例（32.3%）为感染性疾病组，其中45例（84.9%）为细菌感染；62例（37.8%）为炎症性疾病组；14例（8.5%）为肿瘤性疾病组；35例（21.3%）为其他诊断组。白细胞计数平均水平（12047个/mm³）、中性粒细胞计数平均水平（9015个/mm³）、中性粒细胞淋巴细胞比值（NLR，9.7）、C反应蛋白（CRP，152.5mg/L）、降钙素原（PCT，3.28ng/ml）及纤维蛋白原（5.37g/L）的升高与感染性病因显著相关，且差异具有统计学意义。据此，本研究确定了可区分人群中感染性病因的临界值：NLR为6.1、CRP为123mg/L、PCT为0.24ng/ml、纤维蛋白原为4.9g/L。在感染性疾病诊断中，CRP的曲线下面积（AUC）高于PCT、NLR及纤维蛋白原：CRP的灵敏度（Sensitivity, Se）为64.3%、特异度（Specificity, Sp）为89.7%，AUC=0.9，置信区间（Confidence Interval, CI）为0.83~0.96，p<10⁻³；PCT的灵敏度为62.3%、特异度为86.1%，AUC=0.87，置信区间为0.80~0.93，p<10⁻³；NLR的灵敏度为61%、特异度为87.1%，AUC=0.81，置信区间为0.731~0.902，p<10⁻³；纤维蛋白原的灵敏度为68.3%、特异度为84.7%，AUC=0.77，置信区间为0.65~0.98，p<10⁻³。CRP与NLR联合检测可提升感染性与非感染性疾病的鉴别诊断效能，其AUC为0.93，95%置信区间为0.84~0.96，p<10⁻³。结论：本研究的特点在于纳入了多种疾病类别。研究证实，炎症生物标志物尤其是成本低廉、易于检测的NLR及其与CRP的联合应用，可有效提升感染性疾病与炎症性疾病、肿瘤性疾病及其他疾病的鉴别诊断准确性。