Browsing by Author "Reither K"

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A Prospective Evaluation of the Diagnostic Accuracy of the Point-of-Care VISITECT CD4 Advanced Disease Test in 7 Countries.
(2025-Feb-04) Gils T; Hella J; Jacobs BKM; Sossen B; Mukoka M; Muyoyeta M; Nakabugo E; Van Nguyen H; Ubolyam S; Macé A; Vermeulen M; Nyangu S; Sanjase N; Sasamalo M; Dinh HT; Ngo TA; Manosuthi W; Jirajariyavej S; Denkinger CM; Nguyen NV; Avihingsanon A; Nakiyingi L; Székely R; Kerkhoff AD; MacPherson P; Meintjes G; Reither K; Ruhwald M; School of Health and Wellbeing, University of Glasgow, Glasgow, United Kingdom.; German Centre for Infection Research, Heidelberg University Hospital, Heidelberg, Germany.; Viet Tiep Hospital, Hai Phong, Viet Nam.; Bamrasnaradura Infectious Diseases Institute, Nonthaburi, Thailand.; National Lung Hospital, Ha Noi, Viet Nam.; Taksin Hospital, Bangkok, Thailand.; Global Health Institute, University of Antwerp, Wilrijk, Belgium.; Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium.; Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.; University of Basel, Basel, Switzerland.; Public Health Group, Malawi-Liverpool-Wellcome Programme, Blantyre, Malawi.; Ifakara Health Institute, Dar es Salaam, Tanzania.; Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.; Division of HIV, Infectious Diseases and Global Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California, San Francisco, San Francisco, California, USA.; Clinical Research Unit, Swiss Tropical and Public Health Institute, Allschwil, Switzerland.; Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi.; HIV Netherlands Australia Thailand Research Collaboration, Thai Red Cross AIDS Research Centre and Center of Excellence in Tuberculosis, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.; Foundation for Innovative New Diagnostics, the Global Alliance for Diagnostics, Geneva, Switzerland.; Clinical Research Department, London School of Hygiene and Tropical Medicine, London, United Kingdom.; Division of Infectious Disease and Tropical Medicine, Heidelberg University Hospital and Faculty of Medicine, Heidelberg University, Heidelberg, Germany.; Infectious Diseases Institute, Makerere University, Kampala, Uganda.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
BACKGROUND: 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.
Breaking the threshold: Developing multivariable models using computer-aided chest X-ray analysis for tuberculosis triage.
(2024-Oct) Geric C; Tavaziva G; Breuninger M; Dheda K; Esmail A; Scott A; Kagujje M; Muyoyeta M; Reither K; Khan AJ; Benedetti A; Ahmad Khan F; Tuberculosis Department, Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; IRD Global, Singapore.; Tuberculosis Department, Centre for Infectious Disease Research in Zambia, Lusaka, Zambia; Zambart, Lusaka, Zambia.; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada; Department of Medicine, McGill University, Montreal, Canada; Respiratory Epidemiology and Clinical Research Unit, Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Canada. Electronic address: faiz.ahmadkhan@mcgill.ca.; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada; Respiratory Epidemiology and Clinical Research Unit, Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Canada.; Centre for Lung Infection and Immunity Unit, Division of Pulmonology and UCT Lung Institute, University of Cape Town, Cape Town, South Africa.; Centre for Lung Infection and Immunity Unit, Division of Pulmonology and UCT Lung Institute, University of Cape Town, Cape Town, South Africa; Faculty of Infectious and Tropical Diseases, Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.; Division of Infectious Diseases, Department I of Internal Medicine, University of Cologne, Cologne, Germany.; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada; Department of Medicine, McGill University, Montreal, Canada; Department of Epidemiology, Biostatistics & Occupational Health, McGill University, Montreal, Canada.; Swiss Tropical and Public Health Institute, Allschwill, Switzerland; University of Basel, Basel, Switzerland.; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada; Department of Medicine, McGill University, Montreal, Canada; Respiratory Epidemiology and Clinical Research Unit, Centre for Outcomes Research and Evaluation, Research Institute of the McGill University Health Centre, Montreal, Canada.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
OBJECTIVES: Computer-aided detection (CAD) software packages quantify tuberculosis (TB)-compatible chest X-ray (CXR) abnormality as continuous scores. In practice, a threshold value is selected for binary CXR classification. We assessed the diagnostic accuracy of an alternative approach to applying CAD for TB triage: incorporating CAD scores in multivariable modeling. METHODS: We pooled individual patient data from four studies. Separately, for two commercial CAD, we used logistic regression to model microbiologically confirmed TB. Models included CAD score, study site, age, sex, human immunodeficiency virus status, and prior TB. We compared specificity at target sensitivities ≥90% between the multivariable model and the current threshold-based approach for CAD use. RESULTS: We included 4,733/5,640 (84%) participants with complete covariate data (median age 36 years; 45% female; 22% with prior TB; 22% people living with human immunodeficiency virus). A total of 805 (17%) had TB. Multivariable models demonstrated excellent performance (areas under the receiver operating characteristic curve [95% confidence interval]: software A, 0.91 [0.90-0.93]; software B, 0.92 [0.91-0.93]). Compared with threshold scores, multivariable models increased specificity (e.g., at 90% sensitivity, threshold vs model specificity [95% confidence interval]: software A, 71% [68-74%] vs 75% [74-77%]; software B, 69% [63-75%] vs 75% [74-77%]). CONCLUSION: Using CAD scores in multivariable models outperformed the current practice of CAD-threshold-based CXR classification for TB diagnosis.
Chest X-ray Analysis With Deep Learning-Based Software as a Triage Test for Pulmonary Tuberculosis: An Individual Patient Data Meta-Analysis of Diagnostic Accuracy.
(2022-Apr-28) Tavaziva G; Harris M; Abidi SK; Geric C; Breuninger M; Dheda K; Esmail A; Muyoyeta M; Reither K; Majidulla A; Khan AJ; Campbell JR; David PM; Denkinger C; Miller C; Nathavitharana R; Pai M; Benedetti A; Ahmad Khan F; Swiss Tropical and Public Health Institute, Basel, Switzerland.; IRD Global, Singapore.; World Health Organization, Geneva, Switzerland.; Département des Médicaments et Santé des Populations, Faculty of Pharmacy, Université de Montréal, Montreal, Canada.; Centre for Lung Infection and Immunity Unit, Division of Pulmonology and UCT Lung Institute, University of Cape Town, Cape Town, South Africa.; Clinical Addiction Research and Education Unit, Section of General Internal Medicine, Department of Medicine, Boston University School of Medicine and Boston Medical Center, Boston, Massachusetts, USA.; McGill International TB Centre, Research Institute of the McGill University Health Centre, Montreal, Canada.; Division of Infectious Diseases, Department I of Internal Medicine, University of Cologne, Cologne, Germany.; Interactive Research & Development (IRD) Pakistan, Karachi, Pakistan.; Division of Tropical Medicine, Center of Infectious Diseases, University Hospital Heidelberg, Heidelberg, Germany.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; University of Basel, Basel, Switzerland.; Division of Infectious Diseases, Beth Israel Deaconess Medical Center, Harvard Medical School, Boston, Massachusetts, USA.; Faculty of Infectious and Tropical Diseases, Department of Infection Biology, London School of Hygiene and Tropical Medicine, London, United Kingdom.; Departments of Medicine & Epidemiology, Biostatistics & Occupational Health, McGill University, Montreal, Canada.; Zambart, Lusaka, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
BACKGROUND: Automated radiologic analysis using computer-aided detection software (CAD) could facilitate chest X-ray (CXR) use in tuberculosis diagnosis. There is little to no evidence on the accuracy of commercially available deep learning-based CAD in different populations, including patients with smear-negative tuberculosis and people living with human immunodeficiency virus (HIV, PLWH). METHODS: We collected CXRs and individual patient data (IPD) from studies evaluating CAD in patients self-referring for tuberculosis symptoms with culture or nucleic acid amplification testing as the reference. We reanalyzed CXRs with three CAD programs (CAD4TB version (v) 6, Lunit v3.1.0.0, and qXR v2). We estimated sensitivity and specificity within each study and pooled using IPD meta-analysis. We used multivariable meta-regression to identify characteristics modifying accuracy. RESULTS: We included CXRs and IPD of 3727/3967 participants from 4/7 eligible studies. 17% (621/3727) were PLWH. 17% (645/3727) had microbiologically confirmed tuberculosis. Despite using the same threshold score for classifying CXR in every study, sensitivity and specificity varied from study to study. The software had similar unadjusted accuracy (at 90% pooled sensitivity, pooled specificities were: CAD4TBv6, 56.9% [95% confidence interval {CI}: 51.7-61.9]; Lunit, 54.1% [95% CI: 44.6-63.3]; qXRv2, 60.5% [95% CI: 51.7-68.6]). Adjusted absolute differences in pooled sensitivity between PLWH and HIV-uninfected participants were: CAD4TBv6, -13.4% [-21.1, -6.9]; Lunit, +2.2% [-3.6, +6.3]; qXRv2: -13.4% [-21.5, -6.6]; between smear-negative and smear-positive tuberculosis was: were CAD4TBv6, -12.3% [-19.5, -6.1]; Lunit, -17.2% [-24.6, -10.5]; qXRv2, -16.6% [-24.4, -9.9]. Accuracy was similar to human readers. CONCLUSIONS: For CAD CXR analysis to be implemented as a high-sensitivity tuberculosis rule-out test, users will need threshold scores identified from their own patient populations and stratified by HIV and smear status.
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 R; Sossen B; Mukoka M; Muyoyeta M; Nakabugo E; Hella J; Nguyen HV; Ubolyam S; Chikamatsu K; Macé A; Vermeulen M; Centner CM; Nyangu S; Sanjase N; Sasamalo M; Dinh HT; Ngo TA; Manosuthi W; Jirajariyavej S; Mitarai S; Nguyen NV; Avihingsanon A; Reither K; Nakiyingi L; Kerkhoff AD; MacPherson P; Meintjes G; Denkinger CM; Ruhwald M; Clinical Research Department, London School of Hygiene & Tropical Medicine, London, United Kingdom.; HIV-NAT, Thai Red Cross AIDS Research Centre and Centre of Excellence in Tuberculosis, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.; Viet Tiep Hospital, Hai Phong, Viet Nam.; Bamrasnaradura Infectious Diseases Institute, Nonthaburi, Thailand.; National Lung Hospital, Ha Noi, Viet Nam.; Taksin Hospital, Bangkok, Thailand.; Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.; University of Basel, Basel, Switzerland.; Department of Mycobacterium Reference and Research, Research Institute of Tuberculosis, Japan Anti-Tuberculosis Association, Tokyo, Japan.; Public Health Group, Malawi-Liverpool-Wellcome Programme, Blantyre, Malawi.; Wellcome Centre for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.; Ifakara Health Institute, Dar es Salaam, Tanzania.; FIND, The Global Alliance for Diagnostics, Geneva, Switzerland.; Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi.; Department of Clinical Sciences, Liverpool School of Tropical Medicine, Liverpool, United Kingdom.; Division of HIV, Infectious Diseases and Global Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California San Francisco, San Francisco, CA, United States of America.; Division of Infectious Disease and Tropical Medicine, Heidelberg University Hospital and Faculty of Medicine, Heidelberg University, Heidelberg, Germany.; Infectious Diseases Institute, Makerere University, Kampala, Uganda.; Swiss Tropical and Public Health Institute, Allschwil, Switzerland.; German Centre for Infection Research (DZIF), Partner site Heidelberg University Hospital, Heidelberg, Germany.; Division of Medical Microbiology, University of Cape Town and National Health Laboratory Service, Groote Schuur Hospital, Cape Town, South Africa.; Centre for Infectious Disease Research in Zambia, Lusaka, Zambia.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
There 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).
Urine-Xpert Ultra for the diagnosis of tuberculosis in people living with HIV: a prospective, multicentre, diagnostic accuracy study.
(2024-Dec) Sossen B; Székely R; Mukoka M; Muyoyeta M; Nakabugo E; Hella J; Van Nguyen H; Ubolyam S; Erkosar B; Vermeulen M; Centner CM; Nyangu S; Sanjase N; Sasamalo M; Dinh HT; Ngo TA; Manosuthi W; Jirajariyavej S; Nguyen NV; Avihingsanon A; Kerkhoff AD; Denkinger CM; Reither K; Nakiyingi L; MacPherson P; Meintjes G; Ruhwald M; Division of Medical Microbiology, University of Cape Town, Cape Town, South Africa; National Health Laboratory Service, Groote Schuur Hospital, Cape Town, South Africa.; Centre for Infectious Diseases Research in Zambia, Lusaka, Zambia.; Viet Tiep Hospital, Hai Phong, Viet Nam.; Bamrasnaradura Infectious Diseases Institute, Nonthaburi, Thailand.; National Lung Hospital, Ha Noi, Viet Nam.; Taksin Hospital, Bangkok, Thailand.; Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa; Wellcome Center for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.; Public Health Group, Malawi-Liverpool-Wellcome Programme, Blantyre, Malawi; Department of Pathology, Kamuzu University of Health Sciences, Blantyre, Malawi.; Wellcome Center for Infectious Diseases Research in Africa, Institute of Infectious Disease and Molecular Medicine, University of Cape Town, Cape Town, South Africa.; Department of Medicine, Faculty of Health Sciences, University of Cape Town, Cape Town, South Africa.; Ifakara Health Institute, Dar es Salaam, Tanzania.; Public Health Group, Malawi-Liverpool-Wellcome Programme, Blantyre, Malawi; School of Health and Wellbeing, University of Glasgow, Glasgow, UK; Clinical Research Department, London School of Hygiene & Tropical Medicine, London, UK.; Swiss Tropical and Public Health Institute, Allschwil, Switzerland; University of Basel, Basel, Switzerland.; HIV-NAT, Thai Red Cross AIDS Research Centre, Bangkok, Thailand; Center of Excellence in Tuberculosis, Faculty of Medicine, Chulalongkorn University, Bangkok, Thailand.; FIND, Geneva, Switzerland; Division of Infectious Disease and Tropical Medicine, Heidelberg University Hospital, Heidelberg, Germany; Faculty of Medicine, Heidelberg University, Heidelberg, Germany; German Centre for infection Research (DZIF), partner site Heidelberg University Hospital, Heidelberg, Germany.; Division of HIV, Infectious Diseases, and Global Medicine, Zuckerberg San Francisco General Hospital and Trauma Center, University of California San Francisco, San Francisco, CA, USA.; FIND, Geneva, Switzerland.; FIND, Geneva, Switzerland. Electronic address: morten.ruhwald@finddx.org.; Infectious Diseases Institute, Makerere University, Kampala, Uganda.; CIDRZ; Centre for Infectious Disease Research in Zambia (CIDRZ)
BACKGROUND: 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.