Risk Factors For False-negative T-SPOT Assay Results In Etiology-confirmed Tuberculosis Patients

ObjectivesAimed to explore the risk factors of false-negative T-SPOT assay results of etiology-confirmed tuberculosis patients,and to provide scientific references for correct interpretation of T-SPOT assay results.MethodsWe enrolled 1021 etiology-positive tuberculosis patients as research subjects who admitted to the First Affiliated Hospital of Zhejiang University between March 2012 and November 2017.We collected basic clinical characteristics and laboratory results of patients.All patients were divided into two groups based on T-SPOT results,the risk factors of false-negative T-SPOT results were identified by single variate analysis and multivariate logistic regression analysis.Taking tuberculosis patients as training samples,the machine learning support vector machines(SVM)algorithm was used to establish the prediction model of results of the T-SPOT assay of active tuberculosis patients.The validity of the SVM model is judged by the area under the curve,accuracy,specificity,sensitivity.ResultsTotally,833 patients confirmed M.tuberculosis infection were included,of which 674 patients had positive T-SPOT results,159 patients had negative T-SPOT results,and the false-negative rate of T-SPOT assay was 19.1%.Multivariate logistic regression analysis showed that older age,female,acid-fast bacilli smear-negative result,chronic lung disease and HIV co-infection were independent risk factors for false-negative T-SPOT results.The lowest synthetic false-negative rate of SVM prediction model combined with T-SPOT assay is 4.44%,which is 76.75%lower than that of independent T-SPOT assayConclusionsOlder age,female,acid-fast bacilli smear-negative result,chronic lung disease,and HIV co-infection patients are independent risk factors for false-negative T-SPOT results.The results of T-SPOT assay should be interpreted with caution in such patients with highly suspected TB infection.SVM prediction model combined with T-SPOT assay can improve the accuracy of interpretation of T-SPOT results,which contribute to early diagnosis of tuberculosis.