Combination of Blood Routine Examination and T-SPOT.TB Assay for Distinguishing Between Active Tuberculosis and Latent Tuberculosis Infection
BackgroundDistinguishing between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging.MethodsBetween 2013 and 2019, 2,059 (1,097 ATB and 962 LTBI) and another 883 (372 ATB and 511 LTBI) participants were recruited based on positive T-SPOT.TB (T-SPOT) results from Qi...
Main Authors: | , , , , , , , , , , , |
---|---|
Format: | Article |
Language: | English |
Published: |
Frontiers Media S.A.
2021-06-01
|
Series: | Frontiers in Cellular and Infection Microbiology |
Subjects: | |
Online Access: | https://www.frontiersin.org/articles/10.3389/fcimb.2021.575650/full |
id |
doaj-5e71f4d04cea4eb78fc519fe5d4023df |
---|---|
record_format |
Article |
collection |
DOAJ |
language |
English |
format |
Article |
sources |
DOAJ |
author |
Ying Luo Guoxing Tang Xu Yuan Qun Lin Liyan Mao Huijuan Song Ying Xue Ying Xue Shiji Wu Renren Ouyang Hongyan Hou Feng Wang Ziyong Sun |
spellingShingle |
Ying Luo Guoxing Tang Xu Yuan Qun Lin Liyan Mao Huijuan Song Ying Xue Ying Xue Shiji Wu Renren Ouyang Hongyan Hou Feng Wang Ziyong Sun Combination of Blood Routine Examination and T-SPOT.TB Assay for Distinguishing Between Active Tuberculosis and Latent Tuberculosis Infection Frontiers in Cellular and Infection Microbiology active tuberculosis latent tuberculosis infection differential diagnosis diagnostic model blood routine examination T-SPOT.TB |
author_facet |
Ying Luo Guoxing Tang Xu Yuan Qun Lin Liyan Mao Huijuan Song Ying Xue Ying Xue Shiji Wu Renren Ouyang Hongyan Hou Feng Wang Ziyong Sun |
author_sort |
Ying Luo |
title |
Combination of Blood Routine Examination and T-SPOT.TB Assay for Distinguishing Between Active Tuberculosis and Latent Tuberculosis Infection |
title_short |
Combination of Blood Routine Examination and T-SPOT.TB Assay for Distinguishing Between Active Tuberculosis and Latent Tuberculosis Infection |
title_full |
Combination of Blood Routine Examination and T-SPOT.TB Assay for Distinguishing Between Active Tuberculosis and Latent Tuberculosis Infection |
title_fullStr |
Combination of Blood Routine Examination and T-SPOT.TB Assay for Distinguishing Between Active Tuberculosis and Latent Tuberculosis Infection |
title_full_unstemmed |
Combination of Blood Routine Examination and T-SPOT.TB Assay for Distinguishing Between Active Tuberculosis and Latent Tuberculosis Infection |
title_sort |
combination of blood routine examination and t-spot.tb assay for distinguishing between active tuberculosis and latent tuberculosis infection |
publisher |
Frontiers Media S.A. |
series |
Frontiers in Cellular and Infection Microbiology |
issn |
2235-2988 |
publishDate |
2021-06-01 |
description |
BackgroundDistinguishing between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging.MethodsBetween 2013 and 2019, 2,059 (1,097 ATB and 962 LTBI) and another 883 (372 ATB and 511 LTBI) participants were recruited based on positive T-SPOT.TB (T-SPOT) results from Qiaokou (training) and Caidian (validation) cohorts, respectively. Blood routine examination (BRE) was performed simultaneously. Diagnostic model was established according to multivariate logistic regression.ResultsSignificant differences were observed in all indicators of BRE and T-SPOT assay between ATB and LTBI. Diagnostic model built on BRE showed area under the curve (AUC) of 0.846 and 0.850 for discriminating ATB from LTBI in the training and validation cohorts, respectively. Meanwhile, TB-specific antigens spot-forming cells (SFC) (the larger of early secreted antigenic target 6 and culture filtrate protein 10 SFC in T-SPOT assay) produced lower AUC of 0.775 and 0.800 in the training and validation cohorts, respectively. The diagnostic model based on combination of BRE and T-SPOT showed an AUC of 0.909 for differentiating ATB from LTBI, with 78.03% sensitivity and 90.23% specificity when a cutoff value of 0.587 was used in the training cohort. Application of the model to the validation cohort showed similar performance. The AUC, sensitivity, and specificity were 0.910, 78.23%, and 90.02%, respectively. Furthermore, we also assessed the performance of our model in differentiating ATB from LTBI with lung lesions. Receiver operating characteristic analysis showed that the AUC of established model was 0.885, while a threshold of 0.587 yield a sensitivity of 78.03% and a specificity of 85.69%, respectively.ConclusionsThe diagnostic model based on combination of BRE and T-SPOT could provide a reliable differentiation between ATB and LTBI. |
topic |
active tuberculosis latent tuberculosis infection differential diagnosis diagnostic model blood routine examination T-SPOT.TB |
url |
https://www.frontiersin.org/articles/10.3389/fcimb.2021.575650/full |
work_keys_str_mv |
AT yingluo combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection AT guoxingtang combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection AT xuyuan combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection AT qunlin combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection AT liyanmao combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection AT huijuansong combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection AT yingxue combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection AT yingxue combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection AT shijiwu combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection AT renrenouyang combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection AT hongyanhou combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection AT fengwang combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection AT ziyongsun combinationofbloodroutineexaminationandtspottbassayfordistinguishingbetweenactivetuberculosisandlatenttuberculosisinfection |
_version_ |
1721352892286238720 |
spelling |
doaj-5e71f4d04cea4eb78fc519fe5d4023df2021-06-30T14:51:42ZengFrontiers Media S.A.Frontiers in Cellular and Infection Microbiology2235-29882021-06-011110.3389/fcimb.2021.575650575650Combination of Blood Routine Examination and T-SPOT.TB Assay for Distinguishing Between Active Tuberculosis and Latent Tuberculosis InfectionYing Luo0Guoxing Tang1Xu Yuan2Qun Lin3Liyan Mao4Huijuan Song5Ying Xue6Ying Xue7Shiji Wu8Renren Ouyang9Hongyan Hou10Feng Wang11Ziyong Sun12Department of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Immunology, School of Basic Medicine, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Clinical Immunology, Tongji Hospital, Tongji Medical College, Huazhong University of Sciences and Technology, Wuhan, ChinaDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaDepartment of Laboratory Medicine, Tongji Hospital, Tongji Medical College, Huazhong University of Science and Technology, Wuhan, ChinaBackgroundDistinguishing between active tuberculosis (ATB) and latent tuberculosis infection (LTBI) remains challenging.MethodsBetween 2013 and 2019, 2,059 (1,097 ATB and 962 LTBI) and another 883 (372 ATB and 511 LTBI) participants were recruited based on positive T-SPOT.TB (T-SPOT) results from Qiaokou (training) and Caidian (validation) cohorts, respectively. Blood routine examination (BRE) was performed simultaneously. Diagnostic model was established according to multivariate logistic regression.ResultsSignificant differences were observed in all indicators of BRE and T-SPOT assay between ATB and LTBI. Diagnostic model built on BRE showed area under the curve (AUC) of 0.846 and 0.850 for discriminating ATB from LTBI in the training and validation cohorts, respectively. Meanwhile, TB-specific antigens spot-forming cells (SFC) (the larger of early secreted antigenic target 6 and culture filtrate protein 10 SFC in T-SPOT assay) produced lower AUC of 0.775 and 0.800 in the training and validation cohorts, respectively. The diagnostic model based on combination of BRE and T-SPOT showed an AUC of 0.909 for differentiating ATB from LTBI, with 78.03% sensitivity and 90.23% specificity when a cutoff value of 0.587 was used in the training cohort. Application of the model to the validation cohort showed similar performance. The AUC, sensitivity, and specificity were 0.910, 78.23%, and 90.02%, respectively. Furthermore, we also assessed the performance of our model in differentiating ATB from LTBI with lung lesions. Receiver operating characteristic analysis showed that the AUC of established model was 0.885, while a threshold of 0.587 yield a sensitivity of 78.03% and a specificity of 85.69%, respectively.ConclusionsThe diagnostic model based on combination of BRE and T-SPOT could provide a reliable differentiation between ATB and LTBI.https://www.frontiersin.org/articles/10.3389/fcimb.2021.575650/fullactive tuberculosislatent tuberculosis infectiondifferential diagnosisdiagnostic modelblood routine examinationT-SPOT.TB |