BACKGROUND: Active case finding (ACF) is an alternative strategy to accelerate the identification of TB cases among the migrant population.
OBJECTIVE: This study aimed to synthesize the evidence for the effectiveness of ACF TB in migrants.
METHODS: This study uses the PRISMA model as a method of searching for journal articles in the databases of Google Scholar, ProQuest, EBSCO, ScienceDirect, Elsevier, and PubMed, as well as other sources such as textbooks and reports from 2017 to 2021 with the keywords "tuberculosis" AND "active case finding" AND "migrant". The search revealed 371 articles, of which 26 met the criteria for further discussion.
RESULTS: Most studies show that the TB incidence among migrants is higher than in the local population. Factors leading to increased cases include lack of knowledge about the symptoms, high mobilization, social isolation, economic problems, and medication adherence that impact an advanced stage. Furthermore, it is also influenced by the low quality of health services, including accessibility, health facilities, health workers, and information. Therefore, Active Case Finding (ACF) is more effective in identifying cases of TB in the risk groups. This was conducted on migrants with increased notifications followed up with treatment.
CONCLUSION: ACF is effective approach in screening and diagnosing TB in the migrant group.
BACKGROUND: Community-based active case-finding interventions might identify and treat more people with tuberculosis disease than standard case detection. We aimed to assess whether active case-finding interventions can affect tuberculosis epidemiology in the wider community.
METHODS: We did a systematic review by searching PubMed, Embase, Scopus, and Cochrane Library for studies that compared tuberculosis case notification rates, tuberculosis disease prevalence, or tuberculosis infection prevalence or incidence in children, between populations exposed and unexposed to active case-finding interventions. We included studies published in English between Jan 1, 1980, and April 13, 2020. Studies of active case-finding in the general population, in populations perceived to be at high risk for tuberculosis, and in closed settings were included, whereas studies of tuberculosis screening at health-care facilities, among household contacts, or among children only, and studies that screened fewer than 1000 people were excluded. To estimate effectiveness, we extracted or calculated case notification rates, prevalence of tuberculosis disease, and incidence or prevalence of tuberculosis infection in children, and compared ratios of these outcomes between groups that were exposed or not exposed to active case-finding interventions.
RESULTS: 27 883 abstracts were screened and 988 articles underwent full text review. 28 studies contributed data for analysis of tuberculosis case notifications, nine for prevalence of tuberculosis disease, and two for incidence or prevalence of tuberculosis infection in children. In one cluster-randomised trial in South Africa and Zambia, an active case-finding intervention based on community mobilisation and sputum drop-off did not affect tuberculosis prevalence, whereas, in a cluster-randomised trial in Vietnam, an active case-finding intervention based on sputum tuberculosis tests for everyone reduced tuberculosis prevalence in the community. We found inconsistent, low-quality evidence that active case-finding might increase the number of cases of tuberculosis notified in populations with structural risk factors for tuberculosis.
INTERPRETATION: Community-based active case-finding for tuberculosis might be effective in changing tuberculosis epidemiology and thereby improving population health if delivered with high coverage and intensity. If possible, active case-finding projects should incorporate a well designed, robust evaluation to contribute to the evidence base and help elucidate which delivery methods and diagnostic strategies are most effective.
FUNDING: WHO Global TB Programme.
BACKGROUND: Xpert MTB/RIF Ultra (Xpert Ultra) and Xpert MTB/RIF are World Health Organization (WHO)-recommended rapid nucleic acid amplification tests (NAATs) widely used for simultaneous detection of Mycobacterium tuberculosis complex and rifampicin resistance in sputum. To extend our previous review on extrapulmonary tuberculosis (Kohli 2018), we performed this update to inform updated WHO policy (WHO Consolidated Guidelines (Module 3) 2020).
OBJECTIVES: To estimate diagnostic accuracy of Xpert Ultra and Xpert MTB/RIF for extrapulmonary tuberculosis and rifampicin resistance in adults with presumptive extrapulmonary tuberculosis.
SEARCH METHODS: Cochrane Infectious Diseases Group Specialized Register, MEDLINE, Embase, Science Citation Index, Web of Science, Latin American Caribbean Health Sciences Literature, Scopus, ClinicalTrials.gov, the WHO International Clinical Trials Registry Platform, the International Standard Randomized Controlled Trial Number Registry, and ProQuest, 2 August 2019 and 28 January 2020 (Xpert Ultra studies), without language restriction.
SELECTION CRITERIA: Cross-sectional and cohort studies using non-respiratory specimens. Forms of extrapulmonary tuberculosis: tuberculous meningitis and pleural, lymph node, bone or joint, genitourinary, peritoneal, pericardial, disseminated tuberculosis. Reference standards were culture and a study-defined composite reference standard (tuberculosis detection); phenotypic drug susceptibility testing and line probe assays (rifampicin resistance detection).
DATA COLLECTION AND ANALYSIS: Two review authors independently extracted data and assessed risk of bias and applicability using QUADAS-2. For tuberculosis detection, we performed separate analyses by specimen type and reference standard using the bivariate model to estimate pooled sensitivity and specificity with 95% credible intervals (CrIs). We applied a latent class meta-analysis model to three forms of extrapulmonary tuberculosis. We assessed certainty of evidence using GRADE.
MAIN RESULTS: 69 studies: 67 evaluated Xpert MTB/RIF and 11 evaluated Xpert Ultra, of which nine evaluated both tests. Most studies were conducted in China, India, South Africa, and Uganda. Overall, risk of bias was low for patient selection, index test, and flow and timing domains, and low (49%) or unclear (43%) for the reference standard domain. Applicability for the patient selection domain was unclear for most studies because we were unsure of the clinical settings. Cerebrospinal fluid Xpert Ultra (6 studies) Xpert Ultra pooled sensitivity and specificity (95% CrI) against culture were 89.4% (79.1 to 95.6) (89 participants; low-certainty evidence) and 91.2% (83.2 to 95.7) (386 participants; moderate-certainty evidence). Of 1000 people where 100 have tuberculous meningitis, 168 would be Xpert Ultra-positive: of these, 79 (47%) would not have tuberculosis (false-positives) and 832 would be Xpert Ultra-negative: of these, 11 (1%) would have tuberculosis (false-negatives). Xpert MTB/RIF (30 studies) Xpert MTB/RIF pooled sensitivity and specificity against culture were 71.1% (62.8 to 79.1) (571 participants; moderate-certainty evidence) and 96.9% (95.4 to 98.0) (2824 participants; high-certainty evidence). Of 1000 people where 100 have tuberculous meningitis, 99 would be Xpert MTB/RIF-positive: of these, 28 (28%) would not have tuberculosis; and 901 would be Xpert MTB/RIF-negative: of these, 29 (3%) would have tuberculosis. Pleural fluid Xpert Ultra (4 studies) Xpert Ultra pooled sensitivity and specificity against culture were 75.0% (58.0 to 86.4) (158 participants; very low-certainty evidence) and 87.0% (63.1 to 97.9) (240 participants; very low-certainty evidence). Of 1000 people where 100 have pleural tuberculosis, 192 would be Xpert Ultra-positive: of these, 117 (61%) would not have tuberculosis; and 808 would be Xpert Ultra-negative: of these, 25 (3%) would have tuberculosis. Xpert MTB/RIF (25 studies) Xpert MTB/RIF pooled sensitivity and specificity against culture were 49.5% (39.8 to 59.9) (644 participants; low-certainty evidence) and 98.9% (97.6 to 99.7) (2421 participants; high-certainty evidence). Of 1000 people where 100 have pleural tuberculosis, 60 would be Xpert MTB/RIF-positive: of these, 10 (17%) would not have tuberculosis; and 940 would be Xpert MTB/RIF-negative: of these, 50 (5%) would have tuberculosis. Lymph node aspirate Xpert Ultra (1 study) Xpert Ultra sensitivity and specificity (95% confidence interval) against composite reference standard were 70% (51 to 85) (30 participants; very low-certainty evidence) and 100% (92 to 100) (43 participants; low-certainty evidence). Of 1000 people where 100 have lymph node tuberculosis, 70 would be Xpert Ultra-positive and 0 (0%) would not have tuberculosis; 930 would be Xpert Ultra-negative and 30 (3%) would have tuberculosis. Xpert MTB/RIF (4 studies) Xpert MTB/RIF pooled sensitivity and specificity against composite reference standard were 81.6% (61.9 to 93.3) (377 participants; low-certainty evidence) and 96.4% (91.3 to 98.6) (302 participants; low-certainty evidence). Of 1000 people where 100 have lymph node tuberculosis, 118 would be Xpert MTB/RIF-positive and 37 (31%) would not have tuberculosis; 882 would be Xpert MTB/RIF-negative and 19 (2%) would have tuberculosis. In lymph node aspirate, Xpert MTB/RIF pooled specificity against culture was 86.2% (78.0 to 92.3), lower than that against a composite reference standard. Using the latent class model, Xpert MTB/RIF pooled specificity was 99.5% (99.1 to 99.7), similar to that observed with a composite reference standard. Rifampicin resistance Xpert Ultra (4 studies) Xpert Ultra pooled sensitivity and specificity were 100.0% (95.1 to 100.0), (24 participants; low-certainty evidence) and 100.0% (99.0 to 100.0) (105 participants; moderate-certainty evidence). Of 1000 people where 100 have rifampicin resistance, 100 would be Xpert Ultra-positive (resistant): of these, zero (0%) would not have rifampicin resistance; and 900 would be Xpert Ultra-negative (susceptible): of these, zero (0%) would have rifampicin resistance. Xpert MTB/RIF (19 studies) Xpert MTB/RIF pooled sensitivity and specificity were 96.5% (91.9 to 98.8) (148 participants; high-certainty evidence) and 99.1% (98.0 to 99.7) (822 participants; high-certainty evidence). Of 1000 people where 100 have rifampicin resistance, 105 would be Xpert MTB/RIF-positive (resistant): of these, 8 (8%) would not have rifampicin resistance; and 895 would be Xpert MTB/RIF-negative (susceptible): of these, 3 (0.3%) would have rifampicin resistance.
AUTHORS' CONCLUSIONS: Xpert Ultra and Xpert MTB/RIF may be helpful in diagnosing extrapulmonary tuberculosis. Sensitivity varies across different extrapulmonary specimens: while for most specimens specificity is high, the tests rarely yield a positive result for people without tuberculosis. For tuberculous meningitis, Xpert Ultra had higher sensitivity and lower specificity than Xpert MTB/RIF against culture. Xpert Ultra and Xpert MTB/RIF had similar sensitivity and specificity for rifampicin resistance. Future research should acknowledge the concern associated with culture as a reference standard in paucibacillary specimens and consider ways to address this limitation.
Active case finding (ACF) is an alternative strategy to accelerate the identification of TB cases among the migrant population.
OBJECTIVE:
This study aimed to synthesize the evidence for the effectiveness of ACF TB in migrants.
METHODS:
This study uses the PRISMA model as a method of searching for journal articles in the databases of Google Scholar, ProQuest, EBSCO, ScienceDirect, Elsevier, and PubMed, as well as other sources such as textbooks and reports from 2017 to 2021 with the keywords "tuberculosis" AND "active case finding" AND "migrant". The search revealed 371 articles, of which 26 met the criteria for further discussion.
RESULTS:
Most studies show that the TB incidence among migrants is higher than in the local population. Factors leading to increased cases include lack of knowledge about the symptoms, high mobilization, social isolation, economic problems, and medication adherence that impact an advanced stage. Furthermore, it is also influenced by the low quality of health services, including accessibility, health facilities, health workers, and information. Therefore, Active Case Finding (ACF) is more effective in identifying cases of TB in the risk groups. This was conducted on migrants with increased notifications followed up with treatment.
CONCLUSION:
ACF is effective approach in screening and diagnosing TB in the migrant group.
