Jean Claude Semuto Ngabonziza1, Tom Decroo2, Patrick Migambi3, Yves Mucyo Habimana3, Armand Van Deun4, Conor J Meehan5, Gabriela Torrea6, Faridath Massou7, Willem Bram de Rijk6, Bertin Ushizimpumu8, Esdras Belamo Niyigena8, Emil Ivan8, Jules Mugabo Semahore9, Jean Baptiste Mazarati10, Corinne Simone Merle11, Philip Supply12, Dissou Affolabi7, Leen Rigouts13, Bouke Catherine de Jong6. 1. National Reference Laboratory Division, Department of Biomedical Services, Rwanda Biomedical Centre, Kigali, Rwanda; Mycobacteriology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium; Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium. Electronic address: jclaude.ngabonziza@rbc.gov.rw. 2. Department of Clinical Sciences, Institute of Tropical Medicine, Antwerp, Belgium; Research Foundation Flanders, Brussels, Belgium. 3. Tuberculosis and Other Respiratory Diseases Division, Institute of HIV/AIDS Disease Prevention and Control, Rwanda Biomedical Centre, Kigali, Rwanda. 4. Damian Foundation, Brussels, Belgium. 5. Mycobacteriology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium; School of Chemistry and Biosciences, University of Bradford, UK. 6. Mycobacteriology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium. 7. Laboratoire de Référence des Mycobactéries, Cotonou, Benin. 8. National Reference Laboratory Division, Department of Biomedical Services, Rwanda Biomedical Centre, Kigali, Rwanda. 9. HIV, STIs, Hepatitis and Tuberculosis Programmes, WHO Country Office, Kigali, Rwanda. 10. Department of Biomedical Services, Rwanda Biomedical Centre, Kigali, Rwanda. 11. UNICEF/UNDP/World Bank/WHO Special Programme on Research and Training in Tropical Diseases, Geneva, Switzerland; London School of Hygiene & Tropical Medicine, London, UK. 12. University of Lille, CNRS, INSERM, CHU Lille, Institut Pasteur de Lille, U1019 - UMR 9017 - CIIL - Center for Infection and Immunity of Lille, F-59000 Lille, France. 13. Mycobacteriology Unit, Department of Biomedical Sciences, Institute of Tropical Medicine, Antwerp, Belgium; Department of Biomedical Sciences, University of Antwerp, Antwerp, Belgium.
Abstract
BACKGROUND: The Xpert MTB/RIF (Xpert) assay is used globally to rapidly diagnose tuberculosis and resistance to rifampicin. We investigated the frequency and predictors of false-positive findings of rifampicin resistance with Xpert. METHODS: We did a prospective, observational study of individuals who were enrolled in a Rwandan nationwide diagnostic cohort study (DIAMA trial; NCT03303963). We included patients identified to have rifampicin resistance on initial Xpert testing. We did a repeat Xpert assay and used rpoB Sanger and deep sequencing alongside phenotypic drug susceptibility testing (pDST) to ascertain final rifampicin susceptibility status, with any (hetero)resistant result overriding. We used multivariable logistic regression to assess predictors of false rifampicin resistance on initial Xpert testing, adjusted for HIV status, tuberculosis treatment history, initial Xpert semi-quantitative bacillary load, and initial Xpert probe. FINDINGS: Between May 4, 2017, and April 30, 2019, 175 people were identified with rifampicin resistance at initial Xpert testing, of whom 154 (88%) underwent repeat Xpert assay. 54 (35%) patients were confirmed as rifampicin resistant on repeat testing and 100 (65%) were not confirmed with resistance. After further testing and sequencing, 121 (79%) of 154 patients had a final confirmed status for rifampicin susceptibility. 57 (47%) of 121 patients were confirmed to have a false rifampicin resistance result and 64 (53%) had true rifampicin resistance. A high pretest probability of rifampicin resistance did not decrease the odds of false rifampicin resistance (adjusted odds ratio [aOR] 6·0, 95% CI 1·0-35·0, for new tuberculosis patients vs patients who needed retreatment). Ten (16%) of the 64 patients with true rifampicin resistance did not have confirmed rifampicin resistance on repeat Xpert testing, of whom four had heteroresistance. Of 63 patients with a very low bacillary load on Xpert testing, 54 (86%) were falsely diagnosed with rifampicin-resistant tuberculosis. Having a very low bacillary load on Xpert testing was strongly associated with false rifampicin resistance at the initial Xpert assay (aOR 63·6, 95% CI 9·9-410·4). INTERPRETATION: The Xpert testing algorithm should include an assessment of bacillary load and retesting in case rifampicin resistance is detected on a paucibacillary sputum sample. Only when rifampicin resistance has been confirmed on repeat testing should multidrug-resistant tuberculosis treatment be started. When rifampicin resistance has not been confirmed on repeat testing, we propose that patients should be given first-line anti-tuberculosis drugs and monitored closely during treatment, including by baseline culture, pDST, and further Xpert testing. FUNDING: The European & Developing Countries Clinical Trials Partnership 2 programme, and Belgian Directorate General for Development Cooperation.
BACKGROUND: The Xpert MTB/RIF (Xpert) assay is used globally to rapidly diagnose tuberculosis and resistance to rifampicin. We investigated the frequency and predictors of false-positive findings of rifampicin resistance with Xpert. METHODS: We did a prospective, observational study of individuals who were enrolled in a Rwandan nationwide diagnostic cohort study (DIAMA trial; NCT03303963). We included patients identified to have rifampicin resistance on initial Xpert testing. We did a repeat Xpert assay and used rpoB Sanger and deep sequencing alongside phenotypic drug susceptibility testing (pDST) to ascertain final rifampicin susceptibility status, with any (hetero)resistant result overriding. We used multivariable logistic regression to assess predictors of false rifampicin resistance on initial Xpert testing, adjusted for HIV status, tuberculosis treatment history, initial Xpert semi-quantitative bacillary load, and initial Xpert probe. FINDINGS: Between May 4, 2017, and April 30, 2019, 175 people were identified with rifampicin resistance at initial Xpert testing, of whom 154 (88%) underwent repeat Xpert assay. 54 (35%) patients were confirmed as rifampicin resistant on repeat testing and 100 (65%) were not confirmed with resistance. After further testing and sequencing, 121 (79%) of 154 patients had a final confirmed status for rifampicin susceptibility. 57 (47%) of 121 patients were confirmed to have a false rifampicin resistance result and 64 (53%) had true rifampicin resistance. A high pretest probability of rifampicin resistance did not decrease the odds of false rifampicin resistance (adjusted odds ratio [aOR] 6·0, 95% CI 1·0-35·0, for new tuberculosis patients vs patients who needed retreatment). Ten (16%) of the 64 patients with true rifampicin resistance did not have confirmed rifampicin resistance on repeat Xpert testing, of whom four had heteroresistance. Of 63 patients with a very low bacillary load on Xpert testing, 54 (86%) were falsely diagnosed with rifampicin-resistant tuberculosis. Having a very low bacillary load on Xpert testing was strongly associated with false rifampicin resistance at the initial Xpert assay (aOR 63·6, 95% CI 9·9-410·4). INTERPRETATION: The Xpert testing algorithm should include an assessment of bacillary load and retesting in case rifampicin resistance is detected on a paucibacillary sputum sample. Only when rifampicin resistance has been confirmed on repeat testing should multidrug-resistant tuberculosis treatment be started. When rifampicin resistance has not been confirmed on repeat testing, we propose that patients should be given first-line anti-tuberculosis drugs and monitored closely during treatment, including by baseline culture, pDST, and further Xpert testing. FUNDING: The European & Developing Countries Clinical Trials Partnership 2 programme, and Belgian Directorate General for Development Cooperation.
Authors: P M Mbelele; W Sabiiti; S K Heysell; E Sauli; E A Mpolya; S Mfinanga; S H Gillespie; K K Addo; G Kibiki; D J Sloan; S G Mpagama Journal: Int J Tuberc Lung Dis Date: 2022-03-01 Impact factor: 3.427
Authors: Peter M Mbelele; Christian Utpatel; Elingarami Sauli; Emmanuel A Mpolya; Beatrice K Mutayoba; Ivan Barilar; Viola Dreyer; Matthias Merker; Margaretha L Sariko; Buliga M Swema; Blandina T Mmbaga; Jean Gratz; Kennedy K Addo; Michel Pletschette; Stefan Niemann; Eric R Houpt; Stellah G Mpagama; Scott K Heysell Journal: JAC Antimicrob Resist Date: 2022-04-21
Authors: Peter M Mbelele; Elingarami Sauli; Emmanuel A Mpolya; Sagal Y Mohamed; Kennedy K Addo; Sayoki G Mfinanga; Scott K Heysell; Stellah Mpagama Journal: Trop Med Int Health Date: 2021-06-24 Impact factor: 3.918