Notice bibliographique
Résumé
To the Editor—I thank Amélie Menard and colleagues for their interest in my article and for pointing out that the data I reviewed came from clinical trials rather than “real-life” treatment cohorts [1]. Participants in clinical trials are often highly motivated patients with few comorbidities and concomitant medications, and they are usually seen at a higher frequency than patients treated outside clinical trials. Several studies have reported lower hepatitis C virus (HCV) sustained virological response (SVR) rates in real-world cohorts compared with results obtained with the same direct-acting antiviral (DAA)-containing regimens in clinical trials [2–4], especially with interferon-containing therapy [2, 3]. However, recent data suggest that SVR rates in real-world patients treated with current the American Association for the Study of Liver Diseases and the Infectious Diseases Society of America recommended interferon-free therapy for genotype 1 do not have lower SVR rates than observed in clinical trials [5]. The principal thrust of my article was that human immunodeficiency virus (HIV)-coinfected patients have the same SVR rates as do HCV monoinfected patients treated with the same anti-HCV regimen, at least in clinical trials. Thus, the issue is not so much whether there is a reduced SVR rate in real world patients, but rather whether there is a differential in SVR rates between HCV monoinfected patients and HIV-HCV coinfected patients in the real world. Menard and colleagues report on 55 HIV-HCV coinfected patients treated for HCV with sofosbuvir-containing therapy, of whom 2 received interferon, and observed an SVR rate of 94.5% (52/55), similar to that observed in clinical trials [1]. Schaerer and colleagues similarly observed that the SVR rate in HCV genotype 1-HIV coinfected patients treated with an HCV protease inhibitor in combination with pegylated interferon plus ribavirin in the Swiss Cohort Study was similar to that observed in clinical trials [6]. Two groups of investigators have reported similar SVR rates in HCV genotype 1 monoinfected patients and HCV genotype 1-HIV coinfected patients treated with telaprevir plus pegylated interferon and ribavirin in the very same clinic [7, 8], thereby showing no differential in SVR rate between the HCV monoinfected and the HIV-HCV coinfected in a real-world setting. The report by Menard and colleagues is consistent with data from Switzerland [6], the United States [7], and Canada [8] in demonstrating that HIV-HCV coinfected patients have similar SVR rates as HCV monoinfected patients in real-world practice using DAA-containing therapy and, therefore, taking a different approach to treating HCV in the HIV-coinfected compared with the HCV monoinfected (“HIV exceptionalism”) is unjustifiable. Potential conflict of interest. Author certifies no potential conflicts of interest. The author has submitted the ICMJE Form for Disclosure of Potential Conflicts of Interest. Conflicts that the editors consider relevant to the content of the manuscript have been disclosed.
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 machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,059 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,002 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,007 | 0,005 |
| Communication savante | 0,008 | 0,005 |
| Science ouverte | 0,003 | 0,004 |
| Intégrité de la recherche | 0,135 | 0,062 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,011 |
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 source (Gemma direct ou Codex distillé), 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 ».