P3-S5.03 Conflict of interest and point of care tests: an exploration of accuracy in Hepatitis C infection
Notice bibliographique
Résumé
Background The WHO estimates that 170 million people worldwide are infected with Hepatitis C. In the context of HIV co-infection, rapid point-of-care tests gain importance in both the developing and developed countries. Moreover, in the light of the Food and Drug Administration's approval of the Oraquick point-of-care test for Hepatitis C for use in the USA, the accuracy of these tests is relevant. Objective We conducted a systematic review and meta-analysis of the literature examining the sensitivity and specificity of all rapid point-of-care tests used to diagnose incident or prevalent Hepatitis C, with an attention to involvement of industry in reporting of results. Methods Two reviewers conducted independent searches of five databases between the years of 1995 and 2010. Bayesian meta-analysis was conducted accounting for the use of imperfect reference standards (sensitivity and specificity ranges of 90%–100% were assumed) in the assessment of index tests. The quality of all included full-text studies was assessed using the QUADAS and STARD checklists, with a focus on reporting of conflict of interest with industry. Results A total of seven studies were identified from the database searches, of which five were conducted in developing settings. Eight index tests were examined including Oraquick, HCV Tri-Dot, HCV Bidot, Therma Ricerca, SM-HCV, Onecheck, Goldspot and Accurate. Sensitivity of all index tests ranged from 45% to 100%, while specificity ranged from 93% to 100%. Oraquick reportedly had the highest accuracy, with sensitivity ranging from 99% to 100% and a specificity of 100%. However, the authors of the study reported a financial relationship with Orasure Technologies Inc., the makers of Oraquick. Although pooled sensitivity of all tests was high at 92.72% (95% CI 72.11% to 99.93%), when the Oraquick study was removed from analysis, the pooled sensitivity of all other tests dropped to 77.11% (95% CI 45.49% to 99.61%) see Abstract P3-S5.03 table 1. Pooled specificity remained high at almost 100% regardless of whether the Oraquick study was included or not. Abstract P3-S5.03 Table 1 Results of bayesian meta-analysis: diagnostic accuracy of index tests used to detect Hepatitis C Pooled results Sensitivity (95% CI) Specificity (95% CI) Including oraquick study 92.72% (72.11% to 99.93%) 99.88% (99.56% to 100%) Excluding oraquick study 77.11% (45.49% to 99.61%) 99.99% (99.82% to 100%) Conclusion Although Oraquick appears to be the most promising test, authors' ties with industry make these results less credible. More independent testing is required to be able to make policy recommendations for the most accurate index test to detect Hepatitis C infection.
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 enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».