降钙素原与中性粒细胞和淋巴细胞计数比值对肿瘤患者细菌感染预测价值

Diagnostic value of procalcitonin and neutrophil-lymphocyte ratio for detecting tumor patients with bacterial infection

目的恶性肿瘤破坏人体正常免疫屏障,使机体免疫力下降,加之手术和化疗等治疗对机体的损伤,增加了细菌感染可能,使癌症患者死亡率增加,严重影响患者预后。本研究探讨降钙素原(procalcitonin,PCT)和中性粒细胞/淋巴细胞比值(neutrophil-to-lymphocyte ratio,NLR)对肿瘤患者细菌感染的预测价值。方法选取山东省肿瘤医院2017-03-01-2017-11-01收治的330例肿瘤患者作为研究对象,其中感染组173例,非感染组157例。采用电化学发光免疫分析法测定患者血清PCT水平,同时采用sysmex XN9000血细胞分析仪进行血细胞分类计数检查,计算NLR,以受试者工作特征(ROC)曲线评价PCT和NLR以及两者联合对肿瘤患者细菌感染的诊断价值。结果感染组NLR和PCT水平显著高于非感染组(P<0.001),ROC曲线分析结果显示,NLR、PCT和两者联合诊断肿瘤感染的曲线下面积(AUC)分别为0.731、0.736和0.801,检测灵敏度分别为61.3%、88.4%和94.2%,特异度分别为77.7%、51.0%和43.3%。结论 PCT和NLR在肿瘤患者细菌感染中具有较好诊断价值,PCT和NLR联合检测价值优于单项指标诊断价值,可显著提高其诊断灵敏度,有望成为预测肿瘤患者细菌感染的生物标志物。

OBJECTIVE This study aimed to investigate the predictive value of proealcitonin（PCT） and neutrophi/ lymphocyte ratio（NLR） on tumor infection. METHODS Totally 330 cancer patients were enrolled,including 173 cancer patients with infection and 157 cancer patients with non-infection. The serum procalcitonin levels were determined by elec- trochemiluminescenee immunoassay. Blood cells were classified and counted by sysmex XNg000 analyzer. PCT, NLR and the combination of the two biomarkers in the diagnosis of tumor infection were evaluated by receiver operating characteris- tic curve（ROC）. Results based on the bacterial culture acted as the gold standard. RESULTS The NLR and PCT levels in tumor patients were significantly higher than those in non-infected patients（P〈0. 001）. The ROC curve showed that the area under the curve（AUC） of NLR,PCT and the combination of the two biomarkers in the diagnosis of tumor infection were 0. 731,0. 736 and 0. 801 ,respectively. The sensitivity of them were 61.3%,88.4% and 94.2% and specificity were 77.7% ,51.0% and 43.3%, respectively. CONCLUSIONS PCT and NLR may be helpful in the diagnosis of tumor pa tients with bacterial infection. The diagnostic value of PCT combined with NLR is superior to the single, which can signifi-cantly improve the diagnostic sensitivity and be expected to become a biomarker to predict bacterial infection in tumor patients.