Diagnostic accuracy of screening algorithms to identify persons with active pulmonary tuberculosis at prison entry: protocol of a systematic review and network meta-analysis

Prison inmates are a high-risk group for tuberculosis (TB) infection and disease due to the increasing number of vulnerable fringe groups, risk factors ( e.g ., alcohol and drug addictions), contagious diseases (HIV, hepatitis), and their high-risk behavior. Compared to the general population, TB in...

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Veröffentlicht in:	Journal of medicine and life Jg. 15; H. 12; S. 1464 - 1475
Hauptverfasser:	Pape, Stephanie, Gulma, Kabiru, Shivalli, Siddharudha, Kiev, Laurent Cleenewerck de
Format:	Journal Article
Sprache:	Englisch
Veröffentlicht:	Romania Carol Daila University Foundation 01.12.2022 Carol Davila University Press
Schlagworte:	Accuracy Algorithms Diagnostic tests Hepatitis HIV Human immunodeficiency virus Humans Infections Infectious diseases Latent Tuberculosis - diagnosis Latent Tuberculosis - epidemiology Medical screening Meta-analysis Microscopy Network Meta-Analysis as Topic Original Prisoners Prisons Radiography Sexually transmitted diseases STD Systematic review Systematic Reviews as Topic Tuberculosis Tuberculosis - diagnosis Tuberculosis, Pulmonary - diagnosis Tuberculosis, Pulmonary - epidemiology Tumor necrosis factor-TNF DOTS – Directly observed therapy strategy SROC – Sum ROC MDR TB – Multidrug-resistant tuberculosis IGRA – Interferon-gamma release assay DNA – Deoxyribonucleic acid ZN – Ziehl-Neelsen ECDC – European Centre for Disease Prevention and Control PTB – Pulmonary TB BAL – Bronchoalveolar lavage Sn – Sensitivity TST – Tuberculin skin test (Mendel-Mantoux-Test) prison active case finding SL LPA – Second-line line probe assay Sp – Specificity AUC – Area under the curve CT – Computed tomography tuberculosis TN – True-negative TNF – Tumor necrosis factor TPR – True-positive rate STD – Sexually transmitted diseases MMR – Mass miniature radiography FM – Fluorescence microscopy FP – False-positive 95% CI – 95% confidence intervals CD4 – Cluster of differentiation 4 ROC – Receiver Operating Characteristic HIV – Human immunodeficiency virus TB – Tuberculosis LTBI – Latent tuberculosis infection QUADAS-2 – Quality Assessment of Diagnostic Accuracy Studies (revised tool) FPR – False-positive rate HSROC – Hierarchical summary receiver operating characteristic NAAT – Nucleic acid amplification test FL LPA – First-line line probe assay BCG – Bacille Calmette Guerin HBC – High burden country MRI – Magnetic resonance imaging EPTB – Extrapulmonary tuberculosis PICOS – Population, Intervention, Comparison, Outcomes, Setting TB-LAMP – Loop-mediated isothermal amplification entry screening UV – Ultraviolet WHO – World Health Organization AFB – Acid-fast bacilli SD – Standard deviation NMA – Network meta-analysis MGIT – Mycobacterial growth inhibitor tubes CXR – Chest radiography FN – False-negative PRISMA – Preferred Reporting Items for Systematic Reviews and Meta-Analyses TP – True-positive LAM – Lipoarabinomannan PROSPERO – International Prospective Register of Systematic Reviews LJ – Löwenstein-Jensen SDGs – Sustainable Development Goals PCR – Polymerase chain reaction LPA – Line probe assay
ISSN:	1844-122X, 1844-3117, 1844-3117
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Zusammenfassung:	Prison inmates are a high-risk group for tuberculosis (TB) infection and disease due to the increasing number of vulnerable fringe groups, risk factors ( e.g ., alcohol and drug addictions), contagious diseases (HIV, hepatitis), and their high-risk behavior. Compared to the general population, TB incidence and prevalence rates are significantly higher among prison inmates. Early identification of potentially infectious pulmonary TB (PTB) and targeted care of sick inmates are essential to effectively control TB within the prison system. The WHO recommends combining active and passive case-finding in prisons. No study has been published comparing the broad spectrum of screening tools using a diagnostic accuracy network meta-analysis (NMA). We aim to identify the most accurate TB case-finding algorithm at prison entry that is feasible in resource-limited prisons of high-burden TB countries and ensures continuous comprehensive TB detection services in such settings. Evidence generated by this NMA can provide important decision support in selecting the most (cost-) effective algorithms for screening methods for resource-limited settings in the short, medium, and long terms.
Bibliographie:	ObjectType-Article-2 SourceType-Scholarly Journals-1 content type line 14 ObjectType-Feature-3 ObjectType-Evidence Based Healthcare-1 ObjectType-Article-1 ObjectType-Feature-2 content type line 23
ISSN:	1844-122X 1844-3117 1844-3117
DOI:	10.25122/jml-2022-0164