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Abstract：
Most patients with active pulmonary tuberculosis (TB) are difficult to be differentiated from pneumonia (PN), especially those with acid-fast bacillus smear-negative (AFB-) and interferon-γ release assay-positive (IGRA+) results. Thus, the aim of the present study was to develop a risk model of low-cost and rapid test for the diagnosis of AFB- IGRA+ TB from PN. A total of 41 laboratory variables of 204 AFB- IGRA+ TB and 156 PN participants were retrospectively analyzed. Candidate variables were identified by t-statistic test and univariate logistic model. The logistic regression analysis was used to construct the multivariate risk model and nomogram with internal and external validation. A total of 13 statistically differential variables were compared between AFB- IGRA+ TB and PN by false discovery rate (FDR) and odds ratio (OR). By integrating five variables, including age, uric acid (UA), albumin (ALB), hemoglobin (Hb) and white blood cell counts (WBC), a multivariate risk model with a concordance index (C-index) of 0.7 (95% CI: 0.61, 0.8) was constructed. The nomogram showed that UA and Hb acted as protective factors with an OR <1, while age, WBC and ALB were risk factors for TB occurrence. Internal and external validation revealed that nomogram prediction was consistent with the actual observations. Collectively, it was revealed that an integration of five biomarkers (age, UA, ALB, Hb and WBC) may be used to quickly predict TB in AFB- IGRA+ clinical samples from PN.
摘要：
大多数活动性肺结核（TB）患者很难与肺炎（PN）区分，尤其是那些抗酸杆菌涂片阴性（AFB-）和干扰素-γ释放试验阳性（IGRA）结果。因此，本研究的目的是建立一种低成本快速检测的风险模型,用于诊断来自PN的AFB-IGRA+TB.回顾性分析了204名AFB-IGRA+TB和156名PN参与者的41个实验室变量。通过t统计量检验和单变量Logistic模型确定候选变量。采用logistic回归分析构建多变量风险模型和列线图,并进行内部和外部验证。通过错误发现率（FDR）和比值比（OR），在AFB-IGRATB和PN之间比较了13个统计学差异变量。通过整合五个变量，包括年龄,尿酸（UA），白蛋白（ALB），血红蛋白（Hb）和白细胞计数（WBC），构建了一致性指数(C指数)为0.7(95%CI:0.61,0.8)的多变量风险模型.列线图显示，UA和Hb作为保护因子，OR<1，而年龄，WBC和ALB是结核病发生的危险因素。内部和外部验证表明，列线图预测与实际观察结果一致。总的来说，据透露，五个生物标志物的整合(年龄，UA,ALB,Hb和WBC）可用于快速预测来自PN的AFB-IGRA临床样品中的TB。
