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Enregistrement W2735129180 · doi:10.1016/s2214-109x(17)30247-4

Use of the GeneXpert tuberculosis system for HIV viral load testing in India

2017· letter· en· W2735129180 sur OpenAlexaffabout
Madlen Nash, John Ramapuram, Ramya Kaiya, Sophie Huddart, Madhukar Pai, Shrikala Baliga

Notice bibliographique

RevueThe Lancet Global Health · 2017
Typeletter
Langueen
DomaineMedicine
ThématiqueHIV/AIDS drug development and treatment
Établissements canadiensMcGill University
Organismes subventionnairesnon disponible
Mots-clésGeneXpert MTB/RIFTuberculosisMedicineViral loadVirologyPrivate sectorTuberculosis diagnosisHuman immunodeficiency virus (HIV)Public healthEconomic growthMycobacterium tuberculosisPathology

Résumé

récupéré en direct d'OpenAlex

The Xpert MTB/RIF assay (Cepheid; Sunnyvale, CA, USA) on the GeneXpert molecular system, which was endorsed by WHO in 2010, is the biggest advance in tuberculosis diagnosis and the most scaled-up new tuberculosis technology. Between 2010 and 2016, more than 6500 GeneXpert machines and 23 million Xpert assay cartridges were procured in the public sector in 130 of the 145 countries eligible for concessional pricing.1WHOWHO monitoring of Xpert MTB/RIF roll-out.http://www.who.int/tb/areas-of-work/laboratory/mtb-rif-rollout/en/Date: 2017Google Scholar India alone has acquired more than 750 GeneXpert systems in the public sector and more than 100 systems in the private sector. However, GeneXpert systems are often underused because of high cost, restrictive algorithms, inadequate decentralisation, exclusion of the private sector from concessional pricing, and weak implementation of policies.2Pai M Furin J Tuberculosis innovations mean little if they cannot save lives.eLife. 2017; 6: e25956Crossref PubMed Scopus (1) Google Scholar One potential solution is to expand access to tuberculosis testing, while simultaneously using the GeneXpert platform to test for other diseases of global health importance. Given the high co-prevalence of tuberculosis and HIV in many settings, and the need for greater integration of tuberculosis and HIV services, it makes sense to use the GeneXpert technology for HIV viral load testing. The new global 90-90-90 targets for HIV/AIDS require scaled-up HIV-1 viral load testing,3Sidibe M Loures L Samb B The UNAIDS 90-90-90 target: a clear choice for ending AIDS and for sustainable health and development.J Int AIDS Soc. 2016; 19: 21133Crossref PubMed Scopus (70) Google Scholar which is the preferred antiretroviral therapy monitoring approach to assess treatment efficacy and confirm suspected treatment failure.4WHOConsolidated guidelines on the use of antiretroviral drugs for treating and preventive HIV infection: recommendations of a public health approach. WHO, Geneva2016Google Scholar The use of viral load testing to assess treatment failure can reduce delays in switching to second-line drugs and limit unnecessary switching, thus reducing accumulation of drug-resistance mutations and improving clinical outcomes.4WHOConsolidated guidelines on the use of antiretroviral drugs for treating and preventive HIV infection: recommendations of a public health approach. WHO, Geneva2016Google Scholar High viral loads can also indicate non-adherence and identify patients who could benefit from adherence support. Although viral load testing is critical for antiretroviral therapy rollout, access to such testing remains a problem in many countries.5Roberts T Cohn J Bonner K Hargreaves S Scale-up of routine viral load testing in resource-poor settings: current and future implementation challenges.Clin Infect Dis. 2016; 62: 1043-1048Crossref PubMed Scopus (150) Google Scholar, 6Drain P Point-of-care viral load testing to enable streamlined care and task shifting for chronic HIV care. Bethesda.Clinicaltrials.govDate: 2017Google Scholar Current assays require sophisticated facilities, expensive equipment, and skilled technicians, making them impractical for widespread use in resource-constrained settings.5Roberts T Cohn J Bonner K Hargreaves S Scale-up of routine viral load testing in resource-poor settings: current and future implementation challenges.Clin Infect Dis. 2016; 62: 1043-1048Crossref PubMed Scopus (150) Google Scholar As such, patients in low-income and middle-income countries are mostly managed by CD4 cell counts and clinical staging. In India, serious concerns have been expressed over the scarcity of adequate access to HIV viral load testing; according to one estimate, more than 800 000 tests are needed annually, whereas only about 7000 are being done.7Isaakidis P Gupta S Das M et al.HIV viral load messages should go viral in India.Lancet HIV. 2015; 2: e414-e415Summary Full Text Full Text PDF PubMed Scopus (2) Google Scholar In this context, the Xpert HIV-1 Viral Load (Cepheid) cartridge was launched in 2014, as a potential point-of-care, rapid viral load assay. However, before the Xpert HIV-1 Viral Load cartridge can be clinically used in India, validation is essential. In March, 2017, Xpert HIV-1 Viral Load cartridges were approved by the Indian regulatory agency, but there are no published data on test performance in India. We validated a research use only version of this new HIV-1 viral load assay in India, in a hospital setting where GeneXpert was already used for tuberculosis testing. We recruited 246 known HIV-1-positive adults receiving care at Kasturba Medical College, Attavar Hospital in Mangalore, India, between July, 2016, and September, 2016, irrespective of antiretroviral therapy status. 146 (60%) were male and 172 (70%) were receiving antiretroviral therapy. The median age of participants was 41 years. We assessed the correlation between the viral loads obtained from Xpert and from a current reference standard—the COBAS TaqMan HIV-1 assay (Roche Molecular Diagnostics, CA, USA). This assay was performed in an accredited, centralised, national chain laboratory. Ethics approval was obtained and all participants provided written informed consent. Clinical decisions were made using the TaqMan assay. Of the 246 blood samples collected, 21 (9%) were precluded from testing because of insufficient blood volume or breaks in the cold chain. These events were unlikely to be related to the viral loads of the patients. Of the 225 (91%) patient samples remaining, 22 tests generated Xpert error results and 17 tests were invalid, resulting in an Xpert error and invalid rate of 17%. 10 samples were retested and their results were included in subsequent analyses. Ultimately, 196 samples had valid Xpert results. Of these, 89 (45%) patients had viral load values above the lower limit of detection for Xpert and the reference. The turnaround time from specimen collection to receipt of results was less than 1 day for Xpert assays, compared with 7–10 days for TaqMan assays (including sample transportation time). We compared the Xpert viral load results with the reference standard and the Pearson correlation coefficient was 0·96 (95% Cl 0·94–0·97; figure). Bland-Altman analysis showed close quantification of the samples with a mean bias of 0·133 (95% CI 0·073–0·192), and 96·6% of viral load pairs fell within the threshold of statistical acceptability. Our results are consistent with similar validation studies in other countries.8Ceffa S Luhanga R Andreotti M et al.Comparison of the Cepheid GeneXpert and Abbott M2000 HIV-1 real time molecular assays for monitoring HIV-1 viral load and detecting HIV-1 infection.J Virol Methods. 2016; 229: 35-39Crossref PubMed Scopus (48) Google Scholar, 9Garrett NJ Drain PK Werner L Samsunder N Abdool Karim SS Diagnostic accuracy of the point-of-care xpert HIV-1 viral load assay in a South African HIV clinic.J Acquir Immune Defic Syndr. 2016; 72: e45-e48Crossref PubMed Scopus (31) Google Scholar, 10Gueudin M Baron A Alessandri-Gradt E et al.Performance evaluation of the new HIV-1 quantification assay, Xpert HIV-1 viral load, on a wide panel of HIV-1 variants.J Acquir Immune Defic Syndr. 2016; 72: 521-526PubMed Google Scholar, 11Jordan JA Plantier JC Templeton K Wu AHB Multi-site clinical evaluation of the Xpert® HIV-1 viral load assay.J Clin Virol. 2016; 80: 27-32Summary Full Text Full Text PDF PubMed Scopus (13) Google Scholar, 12Mor O Gozlan Y Wax M et al.Evaluation of the RealTime HIV-1, Xpert HIV-1, and Aptima HIV-1 Quant Dx assays in comparison to the NucliSens EasyQ HIV-1 v2.0 assay for quantification of HIV-1 viral load.J Clin Microbiol. 2015; 53: 3458-3465Crossref PubMed Scopus (46) Google Scholar, 13Moyo S Mohammed T Wirth KE et al.Point-of-care Cepheid Xpert HIV-1 viral load test in rural African communities is feasible and reliable.J Clin Microbiol. 2016; 54: 12Crossref Scopus (49) Google Scholar, 14Gous N Scott L Berrie L Stevens W Options to expand HIV viral load testing in South Africa: evaluation of the GeneXpert® HIV-1 viral load assay.PLoS One. 2016; 11: e0168244Crossref PubMed Scopus (33) Google Scholar After a detailed investigation by the company, the high invalid and error rate was primarily attributed to a suboptimal cartridge lot. We also identified supply chain issues, such as broken cartridges during shipping and a defect that caused plasma sample leakage within the cartridge. In summary, our data show that the results of the Xpert HIV-1 Viral Load assay correlated highly with the current reference standard and therefore could be considered for wider use in India by using the large installed base of GeneXpert systems in the tuberculosis programme. However, the supply chain and quality issues we identified will need to be adequately investigated and addressed. In addition, subsidised pricing, similar to that of the Xpert tuberculosis cartridge, will be essential for scaled-up use in India. We declare no competing interests. This project was supported by a Dr TMA Pai Endowment Chair in Translational Epidemiology & Implementation Research held by MP at Manipal University, India. MN received a Cavazzoni Family Undergraduate Award for Global Health, as part of McGill Global Health Scholars program. JR holds a Dr TMA Pai Endowment Chair in HIV and opportunistic infections at Manipal University. MP holds a Canada Research Chair by the Canadian Institutes of Health Research. The funding sources were not involved in this project or the manuscript. We are grateful to Cepheid India for their engagement and support, and for addressing the supply chain issues identified during the project.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction distillée sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,163
Score d'incertitude au seuil0,669

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,001
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,069
Tête enseignante GPT0,337
Écart entre enseignants0,268 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations24
Publié2017
Routes d'admission2
Résumé présentoui

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