Cargando…
Harnessing Big Data to Optimize an Algorithm for Rapid Diagnosis of Pulmonary Tuberculosis in a Real-World Setting
BACKGROUND: The prompt diagnosis of pulmonary tuberculosis (PTB) remains a challenge in clinical practice. The present study aimed to optimize an algorithm for rapid diagnosis of PTB in a real-world setting. METHODS: 28,171 adult inpatients suspected of having PTB in China were retrospectively analy...
Autores principales: | , , , , , , , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012509/ https://www.ncbi.nlm.nih.gov/pubmed/33816355 http://dx.doi.org/10.3389/fcimb.2021.650163 |
_version_ | 1783673377267908608 |
---|---|
author | Peng, Jing Song, Juan Wang, Feng Zuo, Peng Lu, Yanjun Liu, Weiyong Tian, Lei Chen, Zhongju Zhu, Yaowu Wang, Xiong Shen, Na Wang, Xu Wu, Shiji Yu, Qin Vallance, Bruce A. Jacobson, Kevan Sun, Ziyong Yu, Hong Bing |
author_facet | Peng, Jing Song, Juan Wang, Feng Zuo, Peng Lu, Yanjun Liu, Weiyong Tian, Lei Chen, Zhongju Zhu, Yaowu Wang, Xiong Shen, Na Wang, Xu Wu, Shiji Yu, Qin Vallance, Bruce A. Jacobson, Kevan Sun, Ziyong Yu, Hong Bing |
author_sort | Peng, Jing |
collection | PubMed |
description | BACKGROUND: The prompt diagnosis of pulmonary tuberculosis (PTB) remains a challenge in clinical practice. The present study aimed to optimize an algorithm for rapid diagnosis of PTB in a real-world setting. METHODS: 28,171 adult inpatients suspected of having PTB in China were retrospectively analyzed. Bronchoalveolar lavage fluid (BALF) and/or sputum were used for acid-fast bacilli (AFB) smear, Xpert MTB/RIF (Xpert), and culture. A positive mycobacterial culture was used as the reference standard. Peripheral blood mononuclear cells (PBMC) were used for T-SPOT.TB. We analyzed specimen types’ effect on these assays’ performance, determined the number of smears for diagnosing PTB, and evaluated the ability of these assays performed alone, or in combination, to diagnose PTB and nontuberculous mycobacteria (NTM) infections. RESULTS: Sputum and BALF showed moderate to substantial consistency when they were used for AFB smear or Xpert, with a higher positive detection rate by BALF. 3-4 smears had a higher sensitivity than 1-2 smears. Moreover, simultaneous combination of AFB and Xpert correctly identified 44/51 of AFB(+)/Xpert(+) and 6/7 of AFB(+)/Xpert(-) cases as PTB and NTM, respectively. Lastly, when combined with AFB/Xpert sequentially, T-SPOT showed limited roles in patients that were either AFB(+) or Xpert(+). However, T-SPOT(MDC) (manufacturer-defined cut-off) showed a high negative predicative value (99.1%) and suboptimal sensitivity (74.4%), and TBAg/PHA (ratio of Mycobacterium tuberculosis-specific antigens to phytohaemagglutinin spot-forming cells, which is a modified method calculating T-SPOT.TB assay results) ≥0.3 demonstrated a high specificity (95.7%) and a relatively low sensitivity (16.3%) in AFB(-)/Xpert(-) patients. CONCLUSIONS: Concurrently performing AFB smear (at least 3 smears) and Xpert on sputum and/or BALF could aid in rapid diagnosis of PTB and NTM infections in a real-world high-burden setting. If available, BALF is preferred for both AFB smear and Xpert. Expanding this algorithm, PBMC T-SPOT(MDC) and TBAg/PHA ratios have a supplementary role for PTB diagnosis in AFB(-)/Xpert(-) patients (moderately ruling out PTB and ruling in PTB, respectively). Our findings may also inform policy makers’ decisions regarding prevention and control of TB in a high burden setting. |
format | Online Article Text |
id | pubmed-8012509 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-80125092021-04-02 Harnessing Big Data to Optimize an Algorithm for Rapid Diagnosis of Pulmonary Tuberculosis in a Real-World Setting Peng, Jing Song, Juan Wang, Feng Zuo, Peng Lu, Yanjun Liu, Weiyong Tian, Lei Chen, Zhongju Zhu, Yaowu Wang, Xiong Shen, Na Wang, Xu Wu, Shiji Yu, Qin Vallance, Bruce A. Jacobson, Kevan Sun, Ziyong Yu, Hong Bing Front Cell Infect Microbiol Cellular and Infection Microbiology BACKGROUND: The prompt diagnosis of pulmonary tuberculosis (PTB) remains a challenge in clinical practice. The present study aimed to optimize an algorithm for rapid diagnosis of PTB in a real-world setting. METHODS: 28,171 adult inpatients suspected of having PTB in China were retrospectively analyzed. Bronchoalveolar lavage fluid (BALF) and/or sputum were used for acid-fast bacilli (AFB) smear, Xpert MTB/RIF (Xpert), and culture. A positive mycobacterial culture was used as the reference standard. Peripheral blood mononuclear cells (PBMC) were used for T-SPOT.TB. We analyzed specimen types’ effect on these assays’ performance, determined the number of smears for diagnosing PTB, and evaluated the ability of these assays performed alone, or in combination, to diagnose PTB and nontuberculous mycobacteria (NTM) infections. RESULTS: Sputum and BALF showed moderate to substantial consistency when they were used for AFB smear or Xpert, with a higher positive detection rate by BALF. 3-4 smears had a higher sensitivity than 1-2 smears. Moreover, simultaneous combination of AFB and Xpert correctly identified 44/51 of AFB(+)/Xpert(+) and 6/7 of AFB(+)/Xpert(-) cases as PTB and NTM, respectively. Lastly, when combined with AFB/Xpert sequentially, T-SPOT showed limited roles in patients that were either AFB(+) or Xpert(+). However, T-SPOT(MDC) (manufacturer-defined cut-off) showed a high negative predicative value (99.1%) and suboptimal sensitivity (74.4%), and TBAg/PHA (ratio of Mycobacterium tuberculosis-specific antigens to phytohaemagglutinin spot-forming cells, which is a modified method calculating T-SPOT.TB assay results) ≥0.3 demonstrated a high specificity (95.7%) and a relatively low sensitivity (16.3%) in AFB(-)/Xpert(-) patients. CONCLUSIONS: Concurrently performing AFB smear (at least 3 smears) and Xpert on sputum and/or BALF could aid in rapid diagnosis of PTB and NTM infections in a real-world high-burden setting. If available, BALF is preferred for both AFB smear and Xpert. Expanding this algorithm, PBMC T-SPOT(MDC) and TBAg/PHA ratios have a supplementary role for PTB diagnosis in AFB(-)/Xpert(-) patients (moderately ruling out PTB and ruling in PTB, respectively). Our findings may also inform policy makers’ decisions regarding prevention and control of TB in a high burden setting. Frontiers Media S.A. 2021-03-18 /pmc/articles/PMC8012509/ /pubmed/33816355 http://dx.doi.org/10.3389/fcimb.2021.650163 Text en Copyright © 2021 Peng, Song, Wang, Zuo, Lu, Liu, Tian, Chen, Zhu, Wang, Shen, Wang, Wu, Yu, Vallance, Jacobson, Sun and Yu http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Cellular and Infection Microbiology Peng, Jing Song, Juan Wang, Feng Zuo, Peng Lu, Yanjun Liu, Weiyong Tian, Lei Chen, Zhongju Zhu, Yaowu Wang, Xiong Shen, Na Wang, Xu Wu, Shiji Yu, Qin Vallance, Bruce A. Jacobson, Kevan Sun, Ziyong Yu, Hong Bing Harnessing Big Data to Optimize an Algorithm for Rapid Diagnosis of Pulmonary Tuberculosis in a Real-World Setting |
title | Harnessing Big Data to Optimize an Algorithm for Rapid Diagnosis of Pulmonary Tuberculosis in a Real-World Setting |
title_full | Harnessing Big Data to Optimize an Algorithm for Rapid Diagnosis of Pulmonary Tuberculosis in a Real-World Setting |
title_fullStr | Harnessing Big Data to Optimize an Algorithm for Rapid Diagnosis of Pulmonary Tuberculosis in a Real-World Setting |
title_full_unstemmed | Harnessing Big Data to Optimize an Algorithm for Rapid Diagnosis of Pulmonary Tuberculosis in a Real-World Setting |
title_short | Harnessing Big Data to Optimize an Algorithm for Rapid Diagnosis of Pulmonary Tuberculosis in a Real-World Setting |
title_sort | harnessing big data to optimize an algorithm for rapid diagnosis of pulmonary tuberculosis in a real-world setting |
topic | Cellular and Infection Microbiology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8012509/ https://www.ncbi.nlm.nih.gov/pubmed/33816355 http://dx.doi.org/10.3389/fcimb.2021.650163 |
work_keys_str_mv | AT pengjing harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT songjuan harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT wangfeng harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT zuopeng harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT luyanjun harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT liuweiyong harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT tianlei harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT chenzhongju harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT zhuyaowu harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT wangxiong harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT shenna harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT wangxu harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT wushiji harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT yuqin harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT vallancebrucea harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT jacobsonkevan harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT sunziyong harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting AT yuhongbing harnessingbigdatatooptimizeanalgorithmforrapiddiagnosisofpulmonarytuberculosisinarealworldsetting |