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The CIDRZ Research Repository serves as an open-access archive for peer-reviewed publications, conference papers, and other scholarly outputs from CIDRZ researchers. Our goal is to promote the dissemination of knowledge and support evidence-based public health initiatives.
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Item Defining person-centred treatment support for multidrug-resistant TB: a discrete choice experiment.(2026-Jun) Kagujje, Mary; Mtumbi G; Sikandangwa M; Shatalimi J; Muyoyeta, Monde; Kerkhoff, Andrew D.BACKGROUND: Multidrug-resistant TB (MDR-TB) treatment remains challenging, with significant toxicity and associated hardships that undermine adherence and cure rates. Support packages may improve outcomes, but the features most valued by people with MDR-TB are unknown. METHODS: A discrete choice experiment was performed among adults receiving MDR-TB treatment in Lusaka, Zambia. Five features (3-4 levels each) comprising a support package were evaluated through 12 choice tasks comparing hypothetical packages. RESULTS: Among 99 participants (median age 36 years, 68.9% men, 42.4% HIV-positive), material support was the most valued feature (relative importance [RI] = 45.7%), with transport vouchers plus food assistance being the most preferred option. Visit frequency was also important (RI = 26.7%), with similar preferences for monthly and bimonthly visits. Participants preferred phone calls for visit reminders (RI = 11.8%), health care workers for emotional support (RI = 11.2%), and community-based health care workers or loved ones for treatment observation (RI = 4.7%). Three distinct preference groups were identified - all highly valued material support but varied in their preferences for other support features and their delivery. CONCLUSION: Among people with MDR-TB in Zambia, material support mechanisms and less frequent clinic visits were highly valued. Incorporating patient preferences into treatment programmes could optimise MDR-TB care and improve treatment adherence and outcomes.Item Prospective multicentre accuracy evaluation of the FUJIFILM SILVAMP TB LAM test for the diagnosis of tuberculosis in people living with HIV demonstrates lot-to-lot variability.(2024) Székely, Rita; Sossen, Bianca; Mukoka, Madalo; Muyoyeta, Monde; Nakabugo, Elizabeth; Hella, Jerry; Nguyen, Hung V.; Ubolyam, Sasiwimol; Chikamatsu, Kinuyo; Macé, Aurelien; Vermeulen, Marcia; Centner, Chad M.; Nyangu, Sarah; Sanjase, Nsala; Sasamalo, Mohamed; Dinh, Huong T.; Ngo, The A.; Manosuthi, Weerawat; Jirajariyavej, Supennee; Mitarai, Satoshi; Nguyen, Nhung V.; Avihingsanon, Anchalee; Reither, Klaus; Nakiyingi, Lydia; Kerkhoff, Andrew D.; MacPherson, Peter; Meintjes, Graeme; Denkinger, Claudia M.; Ruhwald, MortenThere is an urgent need for rapid, non-sputum point-of-care diagnostics to detect tuberculosis. This prospective trial in seven high tuberculosis burden countries evaluated the diagnostic accuracy of the point-of-care urine-based lipoarabinomannan assay FUJIFILM SILVAMP TB LAM (FujiLAM) among inpatients and outpatients living with HIV. Diagnostic performance of FujiLAM was assessed against a mycobacterial reference standard (sputum culture, blood culture, and Xpert Ultra from urine and sputum at enrollment, and additional sputum culture ≤7 days from enrollment), an extended mycobacterial reference standard (eMRS), and a composite reference standard including clinical evaluation. Of 1637 participants considered for the analysis, 296 (18%) were tuberculosis positive by eMRS. Median age was 40 years, median CD4 cell count was 369 cells/ul, and 52% were female. Overall FujiLAM sensitivity was 54·4% (95% CI: 48·7-60·0), overall specificity was 85·2% (83·2-87·0) against eMRS. Sensitivity and specificity estimates varied between sites, ranging from 26·5% (95% CI: 17·4%-38·0%) to 73·2% (60·4%-83·0%), and 75·0 (65·0%-82·9%) to 96·5 (92·1%-98·5%), respectively. Post-hoc exploratory analysis identified significant variability in the performance of the six FujiLAM lots used in this study. Lot variability limited interpretation of FujiLAM test performance. Although results with the current version of FujiLAM are too variable for clinical decision-making, the lipoarabinomannan biomarker still holds promise for tuberculosis diagnostics. The trial is registered at clinicaltrials.gov (NCT04089423).Item Diagnostic yield as an important metric for the evaluation of novel tuberculosis tests: rationale and guidance for future research.(2024-Jul) Broger, Tobias; Marx, Florian M. ; Theron, Grant ; Marais, Ben J ; Nicol, Mark P.; Kerkhoff, Andrew D.; Nathavitharana, Ruvandhi; Huerga, Helena; Gupta-Wright, Ankur; Kohli, Mikashmi ; Nichols, Brooke E. ; Muyoyeta, Monde; Meintjes, Graeme; Ruhwald, Morten; Peeling, Rosanna W. ; Pai, Nitika P. ; Pollock, Nira R.; Pai, Madhukar; Cattamanchi, Adithya; Dowdy, David W.; Dewan, Puneet; Denkinger, Claudia M.Better access to tuberculosis testing is a key priority for fighting tuberculosis, the leading cause of infectious disease deaths in people. Despite the roll-out of molecular WHO-recommended rapid diagnostics to replace sputum smear microscopy over the past decade, a large diagnostic gap remains. Of the estimated 10·6 million people who developed tuberculosis globally in 2022, more than 3·1 million were not diagnosed. An exclusive focus on improving tuberculosis test accuracy alone will not be sufficient to close the diagnostic gap for tuberculosis. Diagnostic yield, which we define as the proportion of people in whom a diagnostic test identifies tuberculosis among all people we attempt to test for tuberculosis, is an important metric not adequately explored. Diagnostic yield is particularly relevant for subpopulations unable to produce sputum such as young children, people living with HIV, and people with subclinical tuberculosis. As more accessible non-sputum specimens (eg, urine, oral swabs, saliva, capillary blood, and breath) are being explored for point-of-care tuberculosis testing, the concept of yield will be of growing importance. Using the example of urine lipoarabinomannan testing, we illustrate how even tests with limited sensitivity can diagnose more people with tuberculosis if they enable increased diagnostic yield. Using tongue swab-based molecular tuberculosis testing as another example, we provide definitions and guidance for the design and conduct of pragmatic studies that assess diagnostic yield. Lastly, we show how diagnostic yield and other important test characteristics, such as cost and implementation feasibility, are essential for increased effective population coverage, which is required for optimal clinical care and transmission impact. We are calling for diagnostic yield to be incorporated into tuberculosis test evaluation processes, including the WHO Grading of Recommendations, Assessment, Development, and Evaluations process, providing a crucial real-life implementation metric that complements traditional accuracy measures.Item Reaching for 90:90:90 in Correctional Facilities in South Africa and Zambia: Virtual Cross-Section of Coverage of HIV Testing and Antiretroviral Therapy During Universal Test and Treat Implementation.(2024-Aug-15) Hoffmann, Christopher J.; Herce, Michael E.; Chimoyi, Lucy; Smith, Helene J.; Tlali, Mpho; Olivier, Cobus J. ; Topp, Stephanie M.; Muyoyeta, Monde; Reid, Stewart E.; Hausler, Harry; Charalambous, Salome; Fielding, KatherineBACKGROUND: People in correctional settings are a key population for HIV epidemic control. We sought to demonstrate scale-up of universal test and treat in correctional facilities in South Africa and Zambia through a virtual cross-sectional analysis. METHODS: We used routine data on 2 dates: At the start of universal test and treat implementation (time 1, T1) and 1 year later (time 2, T2). We obtained correctional facility census lists for the selected dates and matched HIV testing and treatment data to generate virtual cross-sections of HIV care continuum indicators. RESULTS: In the South African site, there were 4193 and 3868 people in the facility at times T1 and T2; 43% and 36% were matched with HIV testing or treatment data, respectively. At T1 and T2, respectively, 1803 (43%) and 1386 (36%) had known HIV status, 804 (19%) and 845 (21%) were known to be living with HIV, and 60% and 56% of those with known HIV were receiving antiretroviral therapy (ART). In the Zambian site, there were 1467 and 1366 people in the facility at times T1 and T2; 58% and 92% were matched with HIV testing or treatment data, respectively. At T1 and T2, respectively, 857 (59%) and 1263 (92%) had known HIV status, 277 (19%) and 647 (47%) were known to be living with HIV, and 68% and 68% of those with known HIV were receiving ART. CONCLUSIONS: This virtual cross-sectional analysis identified gaps in HIV testing coverage, and ART initiation that was not clearly demonstrated by prior cohort-based studies.Item A Prospective Evaluation of the Diagnostic Accuracy of the Point-of-Care VISITECT CD4 Advanced Disease Test in 7 Countries.(2025-Feb-04) Gils, Tinne; Hella, Jerry; Jacobs, Bart K.M.; Sossen, Bianca; Mukoka, Madalo; Muyoyeta, Monde; Nakabugo, Elizabeth; Nguyen, Hung Van; Ubolyam, Sasiwimol; Macé, Aurélien; Vermeulen, Marcia; Nyangu, Sarah; Sanjase, Nsala; Sasamalo, Mohamed; Dinh, Huong T.; Ngo, The A.; Manosuthi, Weerawat; Jirajariyavej, Supunnee; Denkinger, Claudia M. ; Nguyen, Nhung V.; Avihingsanon, Anchalee; Nakiyingi, Lydia; Székely, Rita; Kerkhoff, Andrew D.; MacPherson, Peter; Meintjes, Graeme; Reither, Klaus; Ruhwald, MortenBACKGROUND: CD4 measurement is pivotal in the management of advanced human immunodeficiency virus (HIV) disease. VISITECT CD4 Advanced Disease (VISITECT; AccuBio, Ltd) is an instrument-free, point-of-care, semiquantitative test allowing visual identification of CD4 ≤ 200 cells/µL or >200 cells/ µL from finger-prick or venous blood. METHODS: As part of a diagnostic accuracy study of FUJIFILM SILVAMP TB LAM, people with HIV ≥18 years old were prospectively recruited in 7 countries from outpatient departments if a tuberculosis symptom was present, and from inpatient departments. Participants provided venous blood for CD4 measurement using flow cytometry (reference standard) and finger-prick blood for VISITECT (index text), performed at point-of-care. Sensitivity, specificity, and positive and negative predictive values of VISITECT to determine CD4 ≤ 200 cells/ µL were evaluated. RESULTS: Among 1604 participants, the median flow cytometry CD4 was 367 cells/µL (interquartile range, 128-626 cells/µL) and 521 (32.5%) had CD4 ≤ 200 cells/µL. VISITECT sensitivity was 92.7% (483/521; 95% confidence interval [CI], 90.1%-94.7%) and specificity was 61.4% (665/1083; 95% CI, 58.4%-64.3%). For participants with CD4 0-100, 101-200, 201-300, 301-500, and >500 cells/µL, VISITECT misclassified 4.5% (95% CI, 2.5%-7.2%), 12.5 (95% CI, 8.0%-18.2%), 74.1% (95% CI, 67.0%-80.5%), 48.0% (95% CI, 42.5%-53.6%), and 22.6% (95% CI, 19.3%-26.3%), respectively. CONCLUSIONS: VISITECT's sensitivity, but not specificity, met the World Health Organization's minimal sensitivity and specificity threshold of 80% for point-of-care CD4 tests. VISITECT's quality needs to be assessed and its accuracy optimized. VISITECT's utility as CD4 triage test should be investigated. Clinical Trials Registration. NCT04089423.Item Expanding molecular diagnostic coverage for tuberculosis by combining computer-aided chest radiography and sputum specimen pooling: a modeling study from four high-burden countries.(2024) Codlin, Andrew J.; Vo, Luan N. Q.; Garg, Tushar; Banu, Sayera; Ahmed, Shahriar; John, Stephen; Abdulkarim, Suraj; Muyoyeta, Monde; Sanjase, Nsala; Wingfield, Tom; Iem, Vibol; Squire, Bertie; Creswell, JacobBACKGROUND: In 2022, fewer than half of persons with tuberculosis (TB) had access to molecular diagnostic tests for TB due to their high costs. Studies have found that the use of artificial intelligence (AI) software for chest X-ray (CXR) interpretation and sputum specimen pooling can each reduce the cost of testing. We modeled the combination of both strategies to estimate potential savings in consumables that could be used to expand access to molecular diagnostics. METHODS: We obtained Xpert testing and positivity data segmented into deciles by AI probability scores for TB from the community- and healthcare facility-based active case finding conducted in Bangladesh, Nigeria, Viet Nam, and Zambia. AI scores in the model were based on CAD4TB version 7 (Zambia) and qXR (all other countries). We modeled four ordinal screening and testing approaches involving AI-aided CXR interpretation to indicate individual and pooled testing. Setting a false negative rate of 5%, for each approach we calculated additional and cumulative savings over the baseline of universal Xpert testing, as well as the theoretical expansion in diagnostic coverage. RESULTS: In each country, the optimal screening and testing approach was to use AI to rule out testing in deciles with low AI scores and to guide pooled vs individual testing in persons with moderate and high AI scores, respectively. This approach yielded cumulative savings in Xpert tests over baseline ranging from 50.8% in Zambia to 57.5% in Nigeria and 61.5% in Bangladesh and Viet Nam. Using these savings, diagnostic coverage theoretically could be expanded by 34% to 160% across the different approaches and countries. CONCLUSIONS: Using AI software data generated during CXR interpretation to inform a differentiated pooled testing strategy may optimize TB diagnostic test use, and could extend molecular tests to more people who need them. The optimal AI thresholds and pooled testing strategy varied across countries, which suggests that bespoke screening and testing approaches may be needed for differing populations and settings. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s44263-024-00081-2.Item The accuracy of point-of-care C-Reactive Protein as a screening test for tuberculosis in children.(2024) Kagujje, Mary; Nyangu, Sarah; Maimbolwa, Minyoi M.; Shuma, Brian; Sanjase, Nsala; Chungu, Chalilwe ; Kerkhoff, Andrew D.; Creswell, Jacob; Muyoyeta, MondeSystematic screening for TB in children, especially among those at high risk of TB, can promote early diagnosis and treatment of TB. The World Health Organization (WHO) recently recommended C-Reactive Protein as a TB screening tool in adults and adolescents living with HIV (PLHIV). Thus, we aimed to assess the performance of point-of-care (POC) CRP as a screening tool for TB in children. A cross-sectional study was conducted at 2 primary health care facilities in Lusaka, Zambia between September 2020 -August 2021. Consecutive children (aged 5-14 years) presenting for TB services were enrolled irrespective of TB symptoms. All participants were screened for the presence of TB symptoms and signs, asked about TB contact history, and undertook a POC CRP test, chest X-ray, and sputum Xpert MTB/RIF Ultra test. The accuracy of CRP (≥10 mg/L cutoff) was determined using a microbiological reference standard (MRS) and a composite reference standard (CRS). Of 280 children enrolled and with complete results available, the median age was 10 years (IQR 7-12), 56 (20.0%) were HIV positive, 228 (81.4%) had a positive WHO symptom screen for TB, 62 (22.1%) had a close TB contact, and 79 (28.2%) had a positive CRP POC test. Five (1.8%) participants had confirmed TB, 71 (25.4%) had unconfirmed TB, and 204 (72.3%) had unlikely TB. When the MRS was used, the sensitivity of CRP was 80.0% (95%CI: 28.4-99.5%) and the specificity was 72.7% (95%CI: 67.1-77.9%). When the CRS was used, the sensitivity of CRP was 32.0% (95%CI: 23.3% - 42.5%), while the specificity was 74.0% (95%CI: 67.0% - 80.3%). Using the CRS, there were no statistically significant differences in sensitivity and specificity of CRP in the HIV positive and HIV negative individuals. Among children in Zambia, POC CRP had limited utility as a screening tool for TB. There remains a continued urgent need for better tools and strategies to improve TB detection in children.Item Urine-Xpert Ultra for the diagnosis of tuberculosis in people living with HIV: a prospective, multicentre, diagnostic accuracy study.(2024-Dec) Sossen, Bianca; Székely, Rita; Mukoka, Madalo; Muyoyeta, Monde; Nakabugo, Elizabeth; Hella, Jerry; Van Nguyen, Hung; Ubolyam, Sasiwimol; Erkosar, Berra; Vermeulen, Marcia; Centner, Chad M.; Nyangu, Sarah; Sanjase, Nsala; Sasamalo, Mohamed; Dinh, Huong T.; Ngo, The A.; Manosuthi, Weerawat; Jirajariyavej, Supunnee; Nguyen, Nhung V.; Avihingsanon, Anchalee; Kerkhoff, Andrew D.; Denkinger, Claudia M.; Reither, Klaus; Nakiyingi, Lydia; MacPherson, Peter; Meintjes, Graeme; Ruhwald, MortenBACKGROUND: Diagnostic delays for tuberculosis are common, with high resultant mortality. Urine-Xpert Ultra (Cepheid) could improve time to diagnosis of tuberculosis disease and rifampicin resistance. We previously reported on lot-to-lot variation of the Fujifilm SILVAMP TB LAM. In this prespecified secondary analysis of the same cohort, we aimed to determine the diagnostic yield and accuracy of Urine-Xpert Ultra for tuberculosis in people with HIV, compared with an extended microbiological reference standard (eMRS) and composite reference standard (CRS) and also compared with Determine TB LAM Ag (AlereLAM, Abbott). METHODS: In this prospective, multicentre, diagnostic accuracy study, we recruited consecutive inpatients and outpatients (aged ≥18 years) with HIV from 13 hospitals and clinics in seven countries (Malawi, South Africa, Tanzania, Thailand, Uganda, Viet Nam, and Zambia). Patients with no isoniazid preventive therapy in the past 6 months and fewer than three doses of tuberculosis treatment in the past 60 days were included. Reference and index testing was performed in real time. The primary outcome of this secondary analysis was the diagnostic yield and accuracy of Urine-Xpert Ultra compared with the eMRS and CRS. Diagnostic accuracy was compared with AlereLAM and diagnostic yield was compared with both AlereLAM and Sputum-Xpert Ultra. This study was registered with ClinicalTrials.gov, NCT04089423, and is complete. FINDINGS: Between Dec 13, 2019, and Aug 5, 2021, 3528 potentially eligible individuals were screened and 1731 were enrolled, of whom 1602 (92·5%) were classifiable by the eMRS (median age 40 years [IQR 33-48], 838 [52·3%] of 1602 were female, 764 [47·7%] were male, 937 [58·5%] were outpatients, 665 [41·5%] were inpatients, median CD4 count was 374 cells per μL [IQR 138-630], and 254 [15·9%] had microbiologically confirmed tuberculosis). Against eMRS as reference, sensitivities of Urine-Xpert Ultra and AlereLAM were 32·7% (95% CI 27·2-38·7) and 30·7% (25·4-36·6) and specificities were 98·0% (97·1-98·6) and 90·4% (88·7-91·8), respectively. Against CRS as reference, sensitivities of Urine-Xpert Ultra and AlereLAM were 21·1% (95% CI 17·6-25·1), and 30·5% (26·4-34·9), and specificities were 99·1% (98·3-99·6) and 95·1% (93·5-96·3), respectively. The combination of Sputum-Xpert Ultra with AlereLAM or Urine-Xpert Ultra diagnosed 202 (77·1%) and 204 (77·9%) of 262 eMRS-positive participants, respectively, in incompletely overlapping groups; combining all three tests diagnosed 214 (81·7%) of 262 eMRS-positive participants INTERPRETATION: Urine-Xpert Ultra could offer promising clinical utility in addition to AlereLAM and Sputum-Xpert Ultra. In inpatient settings where both AlereLAM and Urine-Xpert Ultra are possible, both should be offered to support rapid diagnosis and treatment. FUNDING: Global Health Innovative Technology Fund, KfW Development Bank, Commonwealth of Australia represented by the Department of Foreign Affairs and Trade, and the Netherlands Enterprise Agency.Item Early user perspectives on using computer-aided detection software for interpreting chest X-ray images to enhance access and quality of care for persons with tuberculosis.(2023-Dec-21) Creswell, Jacob; Vo, Luan N. Q.; Qin, Zhi Z.; Muyoyeta, Monde; Tovar, Marco; Wong, Emily B.; Ahmed, Shahriar; Vijayan, Shibu; John, Stephen ; Maniar, Rabia; Rahman, Toufiq; MacPherson, Peter; Banu, Sayera; Codlin, Andrew J.Despite 30 years as a public health emergency, tuberculosis (TB) remains one of the world's deadliest diseases. Most deaths are among persons with TB who are not reached with diagnosis and treatment. Thus, timely screening and accurate detection of TB, particularly using sensitive tools such as chest radiography, is crucial for reducing the global burden of this disease. However, lack of qualified human resources represents a common limiting factor in many high TB-burden countries. Artificial intelligence (AI) has emerged as a powerful complement in many facets of life, including for the interpretation of chest X-ray images. However, while AI may serve as a viable alternative to human radiographers and radiologists, there is a high likelihood that those suffering from TB will not reap the benefits of this technological advance without appropriate, clinically effective use and cost-conscious deployment. The World Health Organization recommended the use of AI for TB screening in 2021, and early adopters of the technology have been using the technology in many ways. In this manuscript, we present a compilation of early user experiences from nine high TB-burden countries focused on practical considerations and best practices related to deployment, threshold and use case selection, and scale-up. While we offer technical and operational guidance on the use of AI for interpreting chest X-ray images for TB detection, our aim remains to maximize the benefit that programs, implementers, and ultimately TB-affected individuals can derive from this innovative technology.Item Prospective Multi-Site Validation of AI to Detect Tuberculosis and Chest X-Ray Abnormalities.(2024-Oct) Kazemzadeh, Sahar; Kiraly, Atilla P.; Nabulsi, Zaid; Sanjase, Nsala; Maimbolwa, Minyoi ; Shuma, Brian; Jamshy, Shahar; Chen, Christina; Agharwal, Arnav; Lau, Charles T.; Sellergren, Andrew; Golden, Daniel; Yu, Jin; Wu, Eric; Matias, Yossi; Chou, Katherine ; Corrado, Greg S.; Shetty, Shravya ; Tse, Daniel; Eswaran, Krish; Liu, Yun; Pilgrim, Rory; Muyoyeta, Monde; Prabhakara, ShruthiBACKGROUND: Using artificial intelligence (AI) to interpret chest X-rays (CXRs) could support accessible triage tests for active pulmonary tuberculosis (TB) in resource-constrained settings. METHODS: The performance of two cloud-based CXR AI systems - one to detect TB and the other to detect CXR abnormalities - in a population with a high TB and human immunodeficiency virus (HIV) burden was evaluated. We recruited 1978 adults who had TB symptoms, were close contacts of known TB patients, or were newly diagnosed with HIV at three clinical sites. The TB-detecting AI (TB AI) scores were converted to binary using two thresholds: a high-sensitivity threshold and an exploratory threshold designed to resemble radiologist performance. Ten radiologists reviewed images for signs of TB, blinded to the reference standard. Primary analysis measured AI detection noninferiority to radiologist performance. Secondary analysis evaluated AI detection as compared with the World Health Organization (WHO) targets (90% sensitivity, 70% specificity). Both used an absolute margin of 5%. The abnormality-detecting AI (abnormality AI) was evaluated for noninferiority to a high-sensitivity target suitable for triaging (90% sensitivity, 50% specificity). RESULTS: Of the 1910 patients analyzed, 1827 (96%) had conclusive TB status, of which 649 (36%) were HIV positive and 192 (11%) were TB positive. The TB AI's sensitivity and specificity were 87% and 70%, respectively, at the high-sensitivity threshold and 78% and 82%, respectively, at the balanced threshold. Radiologists' mean sensitivity was 76% and mean specificity was 82%. At the high-sensitivity threshold, the TB AI was noninferior to average radiologist sensitivity (P<0.001) but not to average radiologist specificity (P=0.99) and was higher than the WHO target for specificity but not sensitivity. At the balanced threshold, the TB AI was comparable to radiologists. The abnormality AI's sensitivity and specificity were 97% and 79%, respectively, with both meeting the prespecified targets. CONCLUSIONS: The CXR TB AI was noninferior to radiologists for active pulmonary TB triaging in a population with a high TB and HIV burden. Neither the TB AI nor the radiologists met WHO recommendations for sensitivity in the study population. AI can also be used to detect other CXR abnormalities in the same population.