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Background Perturbed iron homeostasis is a risk factor for tuberculosis (TB) progression and an indicator of TB treatment failure and mortality. Few studies have evaluated iron homeostasis as a TB diagnostic biomarker. Methods We recruited participants with TB, latent TB infection (LTBI), cured TB (RxTB), pneumonia (PN) and healthy controls (HCs). We measured serum levels of three iron biomarkers including serum iron, ferritin and transferrin, then established and validated our prediction model. Results We observed and verified that the three iron biomarker levels correlated with patient status (TB, HC, LTBI, RxTB or PN) and with the degree of lung damage and bacillary load in patients with TB. We then built a TB prediction model, neural network (NNET), incorporating the data of the three iron biomarkers. The model showed good performance for diagnosis of TB, with 83% (95% CI 77 to 87) sensitivity and 86% (95% CI 83 to 89) specificity in the training data set (n=663) and 70% (95% CI 58 to 79) sensitivity and 92% (95% CI 86 to 96) specificity in the test data set (n=220). The area under the curves (AUCs) of the NNET model to discriminate TB from HC, LTBI, RxTB and PN were all >0.83. Independent validation of the NNET model in a separate cohort (n=967) produced an AUC of 0.88 (95% CI 0.85 to 0.91) with 74% (95% CI 71 to 77) sensitivity and 92% (95% CI 87 to 96) specificity. Conclusions The established NNET TB prediction model discriminated TB from HC, LTBI, RxTB and PN in a large cohort of patients. This diagnostic assay may augment current TB diagnostics.

During China’s urbanization process, rural labor migrants have been suggested to be one important bridge population to change urban-rural distribution on tuberculosis (TB) burden. Aiming to estimate the prevalence of TB infection and to track the active disease development in rural labor migrants, a prospective study was conducted in Shenzhen city, southern China. TB infection was detected using interferon-γ release assay (IGRA). Here we mainly report the characteristics of TB infection in the study population based on the baseline survey. A total of 4,422 eligible participants completed baseline survey in July 2013. QuantiFERON (QFT) positivity rates 17.87% (790/4,422) and was found to be consistent with the local TB epidemic of the areas where the participants immigrated from. Age, smoking, residence registered place, and present of BCG scars were found to be independently associated with QFT positivity. Additionally, evidence for interaction between smoking and age was observed (p for likelihood ratio test